Systems and methods for bioproduction process monitoring and control via mid-infrared spectroscopy

Abstract

Presented herein are methods and systems for monitoring and / or control of production units used at various stages in development and manufacture of biological products. In particular, in certain embodiments, bio-production monitoring and control technologies described herein utilize mid-infrared (mid-IR) analyzers capable of obtaining mid-IR spectral data from aqueous samples in substantially real-time. Technologies described herein may leverage this mid-IR spectral data to measure sample quality metrics, such as protein content, titer, secondary structure, aggregation, etc. as well as viral and / or nucleic acid properties. Sample quality metrics may, accordingly, be measured in substantially real-time and / or on a continuous basis to assess production quality for, e.g., protein therapeutics and gene-therapy agents, and may be used by control systems for adjustment and / or control of process parameters, thereby improving, among other things, product quality.

Description

Attorney Docket No. 2017297-0013SYSTEMS AND METHODS FOR BIOPRODUCTION PROCESS MONITORING AND CONTROL VIA MID-INFRARED SPECTROSCOPY CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to and benefit of U.S. Provisional Application No.63 / 425,504, filed November 15, 2022, U.S. Provisional Application No.63 / 431,989, filed December 12, 2022, and U.S. Provisional Application No.63 / 438,969, filed January 13, 2023, the contents of each of which are hereby incorporated by reference herein in their entirety. BACKGROUND

[0002] Biologic products (also referred to as biologics) are a rapidly developing and increasingly important class of drug products obtained (e.g., isolated) from natural sources, such as humans, animals, or microorganisms. They may include a range of products, such as vaccines, blood and blood components, allergenics, somatic cells, gene therapy components, tissues, and proteins. For example, recently approved recombinant protein therapeutics have been developed to treat a wide variety of clinical indications, including cancers, autoimmunity / inflammation, exposure to infectious agents, and genetic disorders. Gene therapy has immense potential to transform lives of patients with genetic diseases.

[0003] Unlike conventional small-molecule drugs that are chemically synthesized and have known structures, biologics are manufactured via highly-complex biological processes, and are – either as end products or at various steps along the production line – complex mixtures that are challenging to identify and / or characterize. Multi-step purification processes are typically required to obtain a consistent, pure, and effective end product.

[0004] Difficulties associated with accurate identification and characterization of biological products and their ingredients along the manufacturing cycle thus present an obstacle to development and testing of manufacturing processes for new biologics, scaling up production capacity following approval and / or to address variations in demand, and refinement and control of existing procedures to ensure consistent product quality, avoid adverse events, and reduce downtime. Improved technologies for monitoring inputs and outputs of biological product processing steps and control of manufacturing are thus needed. - 1 - 11677372v1Attorney Docket No. 2017297-0013SUMMARY

[0005] Presented herein are methods and systems for monitoring and / or control of production units used at various stages in development and manufacture of biological products. In particular, in certain embodiments, bio-production monitoring and control technologies described herein utilize mid-infrared (mid-IR) analyzers capable of obtaining mid-IR spectral data from aqueous samples in substantially real-time. Technologies described herein may leverage this mid-IR spectral data to measure sample quality metrics, such as protein content, titer, secondary structure, aggregation, etc. as well as viral and / or nucleic acid properties such as empty / full capsid measures and other sample properties that may, in certain embodiments, serve as critical quality attributes (CQAs) in accordance with Food and Drug Administration (FDA) pharmaceutical development guidance. Sample quality metrics may, accordingly, be measured in substantially real-time and / or on a continuous basis to assess production quality for, e.g., protein therapeutics and gene-therapy agents on an ongoing basis.

[0006] Control systems and methods may, in turn, use this real-time data to control and / or adjust process parameters, such as collection windows for collecting target fractions during a chromatography elution process, flow rates, salt gradients, etc., to improve target recovery, sample purity, potency, stability, and the like.

[0007] In this manner, by facilitating control and refinement of downstream sample processing, technologies described herein allow for more efficient and robust processing, with improved results in terms of product quality (e.g., purity and potency) and reduced variations thereof. These translate to improved success rates in FDA trials, faster time-to- market, facilitate scaling, and reduce costs and, ultimately, more effective and accessible therapeutics for patients in need.

[0008] In one aspect, the present disclosure is directed to methods for obtaining a purified sample of a target protein species via real-time monitoring of protein heterogeneity and (e.g., automated; e.g., semi-automated) control of purification processing, the method comprising: (a) measuring, via one or more mid-infrared (MIR) analyzer(s), at each of one or more time points, a corresponding infrared (IR) absorbance signal from an aqueous sample exiting from a purification unit (e.g., a chromatography column), the aqueous sample comprising one or more protein species including the target protein species; (b) receiving, by - 2 - 11677372v1Attorney Docket No. 2017297-0013a processor of a computing device, IR absorbance data corresponding to the IR absorbance signal(s) at each of the one or more time points; (c) determining, by the processor, values of one or more sample quality metrics based on the IR absorbance data, the one or more sample quality metrics comprising a protein aggregation metric indicative of a level of protein aggregation within the aqueous sample; and (d) using the one or more sample quality metrics to control collection of a target fraction of the aqueous sample (e.g., during a particular collection window), thereby obtaining the purified sample of the target protein species.

[0009] In certain embodiments, a purification unit is or comprises a chromatography column. In certain embodiments, the chromatography column is a member selected from the group consisting of an affinity chromatography (AC) column, a hydrophobic interaction chromatography (HIC) column, an ion exchange chromatograph (IEX) column, a size exclusion chromatography (SEC) column, and a mixed-mode chromatography column [e.g., any combination of the foregoing (e.g., IEX and HIC; e.g., IEX and SEC)].

[0010] In certain embodiments, a target protein species is or comprises one or more members selected from the group consisting of a monoclonal antibody (mAb), a fusion protein, a viral capsid protein, an antibody-drug conjugate, a recombinant protein, and a plasmatic protein. In certain embodiments, the target protein species is or comprises a peptide chain and / or a protein fragment.

[0011] In certain embodiments, an aqueous sample comprises a plurality of different protein species. In certain embodiments, wherein the aqueous sample comprises a heterogeneous population of the target protein species, comprising a monomeric portion and an aggregated portion. In certain embodiments, wherein the target protein species is a sub- species of a particular protein species, the target protein species having a particular desired level and / or type of molecular conjugation (e.g. glycan, small-molecule drug, polyethylene glycol, etc.).

[0012] In certain embodiments, at least one of the one or more MIR analyzers is or comprises a MIR spectrometer comprising: a MIR source aligned and operable to emit a beam of MIR light [e.g., comprising a range of wavelengths substantially within the MIR spectral range (e.g., ranging from about 5000 cm-1to about 500 cm-1(e.g., about 2 to 20 microns))]; one or more sampling optics, aligned to direct and / or allow passage of the beam of MIR light, and / or at least a portion thereof, through and / or into contact with at least a portion of the aqueous sample [e.g., wherein the beam of MIR light contacts the portion of - 3 - 11677372v1Attorney Docket No. 2017297-0013the aqueous sample via reflection at an interface between a solid material (e.g., an ATR crystal and / or optical fiber) and the aqueous sample (e.g., wherein the beam of MIR light undergoes total internal reflection, and contacts / probes the portion of the aqueous sample via an evanescent wave extending into the aqueous sample)] and, following passage through or contact with the portion of the aqueous sample, towards one or more detectors; and the one or more detectors, aligned and operable to detect the beam of MIR light following its passage through and / or contact with the aqueous sample.

[0013] In certain embodiments, one or more sampling optics comprise a high- refractive index material (e.g., an ATR crystal; e.g., an optical fiber) aligned such that the beam of MIR light is directed towards, incident upon, and reflected internally (e.g., back within the high-refractive index material) by an interface between the high-refractive index material and the aqueous sample (e.g., such that the beam of MIR light is incident upon the interface at an angle above a critical angle for total internal reflection); and the one or more detectors are aligned and operable to detect the beam of MIR light exiting from, following its internal reflection by, the high-refractive index material. In certain embodiments, the high- refractive index material is an ATR crystal. In certain embodiments, the high-refractive index material is an optical fiber.

[0014] In certain embodiments, one or more sampling optics comprise a flow cell comprising a detection channel through which the aqueous sample flows; and the one or more detectors are aligned and operable to detect the beam of MIR light exiting from, following its transmission through, the detection channel. In certain embodiments, a path length (e.g., followed by the beam of MIR light upon transmission) through the detection channel is about 10 μm or greater (e.g., about or at least 15 μm or greater; e.g., about 25 μm or greater; e.g., about 30 μm or greater; e.g., about 40 μm or greater; e.g., about 50 μm or greater).

[0015] In certain embodiments, one or more MIR analyzer(s) is or comprise a quantum cascade laser (QCL)-based MIR spectrometer comprising a QCL source operable to emit a beam of MIR light [e.g., comprising a range of wavelengths substantially within the MIR spectral range (e.g., ranging from about 5000 cm-1to about 500 cm-1(e.g., about 2 to 20 microns))].

[0016] In certain embodiments, (e.g., the MIR source is a laser and) a beam of MIR light has spectral line width of about 4 cm-1or less (e.g., about 2 cm-1or less; e.g., about 1 cm-1or less; e.g., about 0.5 cm-1or less). - 4 - 11677372v1Attorney Docket No. 2017297-0013

[0017] In certain embodiments, a power of the beam of MIR light is about 1 mW or greater (e.g., about 10 mW; e.g., about 50 mW or greater; e.g., about 100 mW or greater; e.g., about 500 mW or greater; e.g., about 1000 mW or greater).

[0018] In certain embodiments, a spectral resolution of the MIR spectrometer is about 4 cm-1or better (e.g., less) [e.g., about 2 cm-1or better (e.g., less); e.g., about 1 cm-1or better (e.g., less); e.g., about 0.5 cm-1or better (e.g., less); e.g., about 0.25 cm-1or better (e.g., less); e.g., about 0.1 cm-1or better (e.g., less); e.g., about 0.05 cm-1or better (e.g., less)].

[0019] In certain embodiments, an (e.g., frequency / wavelength) accuracy of the MIR spectrometer is about 2 cm-1or better (e.g., less) [e.g.; about 1 cm-1or better (e.g., less); e.g., about 0.5 cm-1or better (e.g., less); e.g., about 0.25 cm-1or better (e.g., less); e.g., about 0.1 cm-1or better (e.g., less); e.g., about 0.01 cm-1or better (e.g., less)].

[0020] In certain embodiments, a (e.g., frequency / wavelength) repeatability of the MIR spectrometer is about 0.5 cm-1or better (e.g., less) [e.g., about 0.25 cm-1or better (e.g., less); e.g., about 0.1 cm-1or better (e.g., less); e.g., about 0.05 cm-1or better (e.g., less); e.g., about 0.001 cm-1or better (e.g., less)].

[0021] In certain embodiments, an MIR source is a tunable laser (e.g., a tunable QCL) (e.g., operable sweep an emission frequency of the beam of MIR light through a plurality of frequencies across a scan range), and the method comprises, at each of the one or more time points: sweeping an emission frequency of the beam MIR light across a scan range of the tunable laser, thereby illuminating the aqueous sample with a plurality of emission frequencies; and detecting, with the one or more detectors, the beam of MIR light (e.g., having been (i) internally reflected by an interface between the high-index material and the aqueous sample and / or (ii) transmitted through the detection channel through which the aqueous sample flows) at each of the plurality of emission frequencies, thereby measuring, as the corresponding infrared (IR) absorbance signal from the aqueous sample, a corresponding IR spectrum comprising a plurality of values, each associated with and representing and / or based on a detected power at a particular one of the plurality of emission frequencies.

[0022] In certain embodiments, a plurality of emission wavelengths comprises one or more wavelengths within a spectral band ranging from about 1800 to about 800 cm-1(e.g., from about 1725 to about 1025 cm-1; e.g., from about 1750 to about 1350 cm-1; e.g., from about 1725 to about 1375 cm-1; e.g., from about 1700 to about 1500 cm-1; e.g., from about 1700 to about 1600 cm-1; e.g., from about 1700 to about 1000 cm-1). In certain embodiments, - 5 - 11677372v1Attorney Docket No. 2017297-0013the plurality of emission wavelengths comprises one or more wavelengths within a spectral band ranging from about 1600 cm-1to about 1500 cm-1.

[0023] In certain embodiments, an MIR analyzer is an on-line sensor (e.g., as opposed to an off-line or at-line sensor) that measures the IR absorbance signal in substantially real- time as the aqueous solution exits from the purification unit.

[0024] In certain embodiments, IR absorbance data comprises, for each of the one or more time points, a corresponding Amide band spectrum [e.g., the Amide band spectrum comprising, for each particular wavelength of a plurality of sampled (e.g., emission) wavelengths within a range from about 1800 to about 800 cm-1, an associated absorption value representing a level of absorption, by a portion of the aqueous sample, at the particular wavelength].

[0025] In certain embodiments, step (d) comprises determining, for each particular time point of at least a portion of the one or more time points, a corresponding value of the protein aggregation metric.

[0026] In certain embodiments, for each particular time point, determining a corresponding value of the protein aggregation metric comprises: computing, from the Amide band spectrum corresponding to the particular time point, a value of an Amide II peak metric that quantifies one or more properties of an Amide II band (e.g., a frequency position, a linewidth, an intensity) at the particular time point; and using the Amide II peak metric value to determine the corresponding value of the protein aggregation metric (e.g., wherein the protein aggregation metric is or is a function of the Amide II peak metric).

[0027] In certain embodiments, an Amide II peak metric is a frequency position metric that quantifies a frequency about which the Amide II band is substantially centered at the particular time point [e.g., a center of mass frequency, a frequency of a maximal height of the Amide II band, a center frequency of a fitted peak function (e.g., a Gaussian, a Lorentz, etc.), etc.]. In certain embodiments, the frequency position metric is a center of mass frequency for the Amide II band.

[0028] In certain embodiments, for each particular time point, determining a corresponding value of the protein aggregation metric comprises: computing, from the Amide band spectrum corresponding to the particular time point, a value of an Amide I peak metric that quantifies one or more properties of an Amide I band (e.g., frequency position, a linewidth, an intensity) at the particular time point; and using both the Amide I peak metric - 6 - 11677372v1Attorney Docket No. 2017297-0013value and the Amide II peak metric value to determine the corresponding value of the protein aggregation metric (e.g., wherein the protein aggregation metric is a function of the Amide I peak metric and the Amide II peak metric).

[0029] In certain embodiments, an Amide I peak metric is a peak intensity metric that quantifies an intensity of the Amide I band at the particular time point (e.g., a peak height of the Amide I band, an area under the curve (AUC) for the Amide I band); an Amide II peak metric is a peak intensity metric that quantifies an intensity of the Amide II band at the particular time point (e.g., a peak height of the Amide I band, an area under the curve (AUC) for the Amide I band); and determining the value of the protein aggregation metric comprises computing (i) a ratio of the Amide I peak metric value to the Amide II peak metric value and / or (ii) a ratio of the Amide II peak metric value to the Amide I peak metric value.

[0030] In certain embodiments, one or more sample quality metrics further comprise a total protein content metric indicative of a level of protein content within the aqueous sample.

[0031] In certain embodiments, step (d) comprises causing, by the processor, transmission of one or more trigger signals (e.g., voltages) to a controller unit of the purification unit. In certain embodiments, the one or more trigger signals comprise an analog voltage signal having a time varying amplitude based on (e.g., substantially proportional to) a value of the protein aggregation metric. In certain embodiments, the one or more trigger signals comprise an analog voltage signal having a time varying amplitude based on (e.g., substantially proportional to) a value of a total protein content metric.

[0032] In certain embodiments, step (d) comprises one or both of: initiating, by the controller unit, based on the one or more trigger signals, collection of the target fraction of the aqueous sample [e.g., wherein a particular one of the one or more trigger signals is an analog signal and the controller unit initiates collection of the target fraction based on an amplitude of the analog signal (e.g., when it exceeds a particular threshold; e.g., when it drops below a particular threshold); e.g., wherein a particular one of the one or more trigger signals is a digital signal that triggers (e.g., by transitioning from a 0 voltage level to 1 voltage level or vice-a-versa) initiating collection of the target fraction] and stopping, by the controller unit, based the one or more trigger signals, collection of the target fraction of the aqueous sample [e.g., wherein a particular one of the one or more trigger signals is an analog signal and the controller unit stops collection of the target fraction based on an amplitude of - 7 - 11677372v1Attorney Docket No. 2017297-0013the analog signal (e.g., when it exceeds a particular threshold; e.g., when it drops below a particular threshold); e.g., wherein a particular one of the one or more trigger signals is a digital signal that triggers (e.g., by transitioning from a 0 voltage level to 1 voltage level or vice-a-versa) stopping collection of the target fraction].

[0033] In another aspect, the present disclosure is directed to methods for real-time monitoring of protein aggregation in a sample, the method comprising: (a) repeatedly receiving, by a processor of a computing device, infrared (IR) absorbance data corresponding to IR absorbance signals measured at each of a plurality of time points, the IR absorbance data comprising, for each particular time point of the plurality of time points, a corresponding IR absorbance spectrum measured from the sample at the particular time point and comprising a plurality of absorbance values, each associated with a particular wavenumber; (b) analyzing (e.g., automatically), by the processor, the IR absorbance data to obtain a real- time protein aggregation signal providing a measure of protein aggregation in the sample as a function of time, by, for each particular time point of the plurality of time points: determining, using the IR absorbance spectrum corresponding to the particular time point, values of one or more peak metrics for one or both of an Amide I band and an Amide II band; determining, using the values of the one or more peak metrics, a value of a protein aggregation metric indicative of a level of protein aggregation within the sample at the particular time point; and updating the real-time protein aggregation signal with the determined value of the protein aggregation metric for the particular time point; and (c) storing and / or providing, by the processor, the real-time protein aggregation signal for one or more of (i) further processing, (ii) display, and (iii) use as a control signal for adjusting one or more purification units (e.g., chromatography systems).

[0034] In certain embodiments, step (b) comprises, for each particular time point, determining, as the value of the protein aggregation metric indicative of the level of protein aggregation within the sample at the particular time point, a value of a frequency position metric that quantifies a frequency about which the Amide II band is substantially centered at the particular time point [e.g., a center of mass frequency, a frequency of a maximal height of the Amide II band, a center frequency of a fitted peak function (e.g., a Gaussian, a Lorentz, etc.), etc.]. In certain embodiments, the frequency position metric is a center of mass frequency for the Amide II band.

[0035] In certain embodiments, step (b) comprises, for each particular time point: determining a value of an Amide I peak intensity metric that quantifies an intensity of the - 8 - 11677372v1Attorney Docket No. 2017297-0013Amide I band at the particular time point (e.g., a peak height of the Amide I band, an area under the curve (AUC) for the Amide I band); determining a value of an Amide II peak intensity metric that quantifies an intensity of the Amide II band at the particular time point (e.g., a peak height of the Amide I band, an area under the curve (AUC) for the Amide I band); and determining, as the value of the protein aggregation metric, (i) a ratio of the Amide I peak metric value to the Amide II peak metric value and / or (ii) a ratio of the Amide II peak metric value to the Amide I peak metric value.

[0036] In another aspect, the present disclosure is directed to methods for mid-IR (MIR)-spectroscopy-based monitoring and control of a production unit for manufacture of a biological product (e.g., a protein; e.g., a nucleic acid; e.g., a virus) the method comprising: (a) measuring, via one or more (e.g., integrated) mid-infrared (MIR) analyzer(s) [e.g., MIR analyzer(s) as described in one or more aspects and / or embodiments herein (e.g., in paragraphs above)], at each of one or more time points, a corresponding infrared (IR) absorbance signal from an aqueous sample flowing to and / or from the production unit (e.g., and which comprises one or more inputs, output products, waste products, or in-progress products of the production unit); (b) receiving, by a processor of a computing device, IR absorbance data corresponding to the IR absorbance signal(s) at each of the one or more time points; and (c) using the received IR absorbance data to adjust one or more process parameters of: (i) the production unit and / or (ii) a second (e.g., upstream and / or downstream) production unit.

[0037] In certain embodiments, a production unit is or comprises a purification unit. In certain embodiments, the purification unit is a member selected from the group consisting of an alternating tangential flow filtration (ATF) system, tangential flow depth filtration (TFDF) system, tangential flow filtration (TFF) system, a chromatography column, a direct, or normal, flow filtration unit, an ultra-filtration unit, and a dia-filtration unit. In certain embodiments, the purification unit is a chromatography column {e.g., and wherein the chromatography column is a member selected from the group consisting of an affinity chromatography (AC) column, a hydrophobic interaction chromatography (HIC) column, an ion exchange chromatograph (IEX) column, a size exclusion chromatography (SEC) column, and a mixed-mode chromatography column [e.g., any combination of the foregoing (e.g., IEX and HIC; e.g., IEX and SEC)]}.

[0038] In certain embodiments, a production unit is or comprises a bioreactor (e.g., a seed bioreactor; e.g., a production bioreactor). - 9 - 11677372v1Attorney Docket No. 2017297-0013

[0039] In certain embodiments, an aqueous sample comprises one or more protein species selected from the group consisting of a monoclonal antibody (mAb), a fusion protein, a viral capsid protein, an antibody-drug conjugate, a recombinant protein, and a plasmatic protein. In certain embodiments, the aqueous sample comprises a peptide chain and / or a protein fragment.

[0040] In certain embodiments, an aqueous sample comprises a plurality of different protein species. In certain embodiments, the aqueous sample comprises a heterogeneous population of a target protein species, comprising a monomeric portion and an aggregated portion. In certain embodiments, the aqueous sample comprises one or more sub-species of a particular protein species, having a particular desired level and / or type of molecular conjugation (e.g. glycan, small-molecule drug, polyethylene glycol, etc.).

[0041] In certain embodiments, an aqueous sample comprises nucleic acid (e.g., DNA, RNA, mRNA, etc.).

[0042] In certain embodiments, an aqueous sample comprises one or more species of virus and / or virus-like particles [e.g., adeno-associated viral vectors (AAV); e.g., lentiviral vectors].

[0043] In certain embodiments, step (c) comprises using the IR absorbance data to determine values one or more sample quality metrics at each of the one or more time points (e.g., and adjusting the one or more process parameters based thereon).

[0044] In certain embodiments, one or more sample quality metrics comprise(s) a total protein content metric that quantifies a quantity and / or concentration of protein within the aqueous sample. In certain embodiments, the one or more sample quality metrics comprise(s) a protein aggregation metric indicative of a level of protein aggregation within the aqueous sample. In certain embodiments, the one or more sample quality metrics comprise(s) one or more protein species metrics that identify presence and / or quantify content (e.g., absolute content; e.g., relative content) of one or more particular protein species within the aqueous sample. In certain embodiments, the one or more sample quality metrics comprise a protein conjugation metric that quantifies a level and / or type of molecular conjugation (e.g. glycan, small-molecule drug, polyethylene glycol, etc.). In certain embodiments, the one or more sample quality metrics comprise one or more protein secondary structure metrics that quantify presence and or content of one or more protein - 10 - 11677372v1Attorney Docket No. 2017297-0013secondary structure motifs (e.g., alpha-helical content, beta-sheet content, turn content, disordered content).

[0045] In certain embodiments, one or more sample quality metrics comprise one or more nucleic acid content metrics that quantify a content of nucleic acid [e.g., a total content of nucleic acid (e.g., a concentration (e.g., titer), mass per volume (e.g., mg / mL, number of particles per volume, number of viral genome copies, etc.); e.g., a total and / or relative content of one or more particular types of nucleic acid (e.g., DNA, RNA, ssDNA, dsDNA), e.g., independent and / or distinguishable content metrics measuring viral nucleic acid and host cell nucleic acid; e.g., the total amount of particular nucleotide bases in a nucleic acid sample, for example, GC content] within the aqueous sample.

[0046] In certain embodiments, one or more sample quality metrics comprise one or more viral content metrics that quantify a content of viral and / or virus like particles within the aqueous sample [e.g., a concentration (e.g., titer), mass per volume (e.g. mg / mL), number of (viral) particles per volume, etc.]. In certain embodiments, the one or more sample quality metrics comprise one or more empty / full capsid ratios that quantify an content and / or relative fraction of empty and / or full viral vectors (e.g., percent, ratio, etc. of full viral vectors) within the aqueous sample. In certain embodiments, one or more sample quality metrics comprise a capsid aggregation metric indicative of a level of capsid aggregation within the viral vector sample. In certain embodiments, one or more sample quality metrics comprise a viral nucleic acid (e.g., viral DNA, RNA, etc.) content metric that differentiates the viral nucleic acid from the host cell proteins and host cell nucleic acid content.

[0047] In certain embodiments, at least a portion (e.g., one or more) of the sample quality metrics are computed based on one or more peak metrics that measure features of one or more absorption bands in IR spectral data {e.g., wherein each peak metric is associated with one or more particular spectral bands [e.g., a continuous range of wavelengths / wavenumbers (e.g., an Amide-I band, an Amide-II band, an Amide-III band, e.g.; an Amide region, spanning two or more of the Amide bands; e.g., an antisymmetric PO4 band; e.g.; a symmetric PO4 band)] and quantifies a particular structural feature [e.g., an intensity (e.g., a peak amplitude; e.g., an Area Under the Curve (AUC)); e.g., a linewidth; e.g., a frequency position (e.g., peak frequency; e.g., center of mass frequency)] of one or more absorption peaks within the particular spectral band}. - 11 - 11677372v1Attorney Docket No. 2017297-0013

[0048] In certain embodiments, IR absorbance data comprises: (i) one or more (e.g., a plurality of) Amide II absorbance value(s), associated with and measuring IR absorption (of the viral sample) at wavenumbers within an Amide II spectral band (e.g., ranging from about 1500 cm-1to about 1600 cm-1, e.g., ranging from about 1500 cm-1to about 1575 cm-1; e.g., ranging from about 1500 cm-1to about 1550 cm-1; e.g., ranging from about 1540 cm-1to about 1560 cm-1); and / or (ii) one or more (e.g., a plurality of) Amide III absorbance value(s), associated with and measuring IR absorption (of the viral sample) at wavenumbers within an Amide II spectral band (e.g., ranging from about 1250 cm-1to about 1350 cm-1, e.g., ranging from about 1250 cm-1to about 1325 cm-1; e.g., ranging from about 1275 cm-1to about 1325 cm-1; e.g., ranging from about 1280 cm-1to about 1300 cm-1).

[0049] In certain embodiments, determining one or more sample quality metrics comprises determining values of a protein content metric [e.g., concentration (e.g., titer)] that quantifies protein content within the sample based at least in part on the Amide II and / or Amide III absorbance value(s). In certain embodiment, methods comprise determining a value of an Amide II peak metric based on the Amide II absorbance values and / or a value of an Amide III peak metric based on the Amide III absorbance values; and using the Amide II peak metric value and / or the Amide III peak metric value to determine the protein content metric value. In certain embodiments, an Amide II peak metric and / or the Amide III peak metric is a peak intensity metric that quantifies an intensity of the Amide II band and / or Amide III band, respectively [e.g., a peak height, an area under the curve (AUC), etc.].

[0050] In certain embodiments, IR absorbance data comprises: (i) one or more (e.g., a plurality of) antisymmetric Phosphate Stretch (antisymmetric-PO4) absorbance value(s), associated with and measuring IR absorption (of the viral sample) at wavenumbers within an antisymmetric-PO4 spectral band (e.g., ranging from about 1150 cm-1to about 1250 cm-1, e.g., ranging from about 1175 cm-1to about 1250 cm-1; e.g., ranging from about 1200 cm-1to about 1250 cm-1; e.g., ranging from about 1210 cm-1to about 1230 cm-1); and / or (ii) one or more (e.g., a plurality of) symmetric Phosphate Stretch (symmetric-PO4) absorbance value(s), associated with and measuring IR absorption (of the viral sample) at wavenumbers within a symmetric-PO4spectral band (e.g., ranging from about 1000 cm-1to about 1100 cm-1, e.g., ranging from about 1050 cm-1to about 1100 cm-1; e.g., ranging from about 1075 cm-1to about 1100 cm-1; e.g., ranging from about 1075 cm-1to about 1085 cm-1).

[0051] In certain embodiments, determining one or more sample quality metric values comprises determining values of a nucleic acid (e.g., DNA, RNA, etc.) content metric that - 12 - 11677372v1Attorney Docket No. 2017297-0013quantifies nucleic acid content [e.g., concentration (e.g., titer)] within the sample based at least in part on the antisymmetric-PO4 and / or symmetric-PO4 absorbance value(s). In certain embodiments, methods comprise determining a value of an antisymmetric-PO4peak metric based on the antisymmetric-PO4 absorbance values and / or a value of an symmetric-PO4 peak metric based on the symmetric-PO4absorbance values; and using the antisymmetric-PO4peak metric value and / or the symmetric-PO4 peak metric value to determine the nucleic acid content metric value. In certain embodiments, an antisymmetric-PO4peak metric and / or the symmetric-PO4 peak metric is a peak intensity metric that quantifies an intensity of the antisymmetric-PO4band and / or symmetric-PO4band, respectively [e.g., a peak height, an area under the curve (AUC), etc.].

[0052] In certain embodiments, determining one or more sample quality metric values comprises determining (i) value(s) of a protein content metric [e.g., concentration (e.g., titer)] that quantifies protein content within the sample and (ii) values of a nucleic acid (e.g., DNA, RNA, etc.) content metric that quantifies nucleic acid content [e.g., concentration (e.g., titer)] within the sample, thereby independently quantifying total protein and nucleic acid content within the sample. In certain embodiments, determining one or more sample quality metric values comprises determining a total capsid content based at least in part on (e.g., as a function of) the value(s) of the protein content metric. In certain embodiments, determining one or more sample quality metric values comprises determining a full capsid fraction based at least in part on (e.g., as a function of) (i) the value(s) of the protein content metric and / or the total capsid content and (ii) the value(s) of the nucleic acid content metric.

[0053] In certain embodiments, IR absorbance data is or comprises one or more IR absorbance spectra, each IR absorbance spectra comprising, for each particular wavenumber of a plurality of wavenumber spanning a measured spectral band, a corresponding IR absorbance value representing a measure of absorption of IR light, by the aqueous sample, at the particular wavenumber.

[0054] In certain embodiments, measured spectral bands span one or more bands selected from the group consisting of an Amide II band, an Amide III band, an asymmetric- PO4 band, and a symmetric-PO4 band.

[0055] In certain embodiments, provided methods comprise determining values of the one or more sample quality metrics for each of the one or more time points, thereby monitoring the one or more sample quality metrics over time. In certain embodiments, - 13 - 11677372v1Attorney Docket No. 2017297-0013methods comprise determining values of one or more sample quality metrics in substantially real-time.

[0056] In certain embodiments, at least one particular sample quality metric of the one or more sample quality metrics is computed using a machine learning model that receives, as input, one or more IR spectra and generates the particular sample quality metric as output. In certain embodiments, computing a particular sample quality metric comprises de-convolving an amide spectral region into sub-bands and / or computing a second derivative spectra.

[0057] In certain embodiments, IR absorbance data comprises an IR absorbance spectrum and step (c) comprises: receiving (e.g., and / or accessing) one or more reference spectra, each measured from a corresponding (e.g., high-quality) reference sample [e.g., comprising a target viral vector species at high purity and / or concentration and / or one or more model constituents thereof (e.g., a model protein solution; e.g., a model ssDNA solution)]; and determining (e.g., automatically), values of at least a portion of one or more sample quality metrics using the IR absorbance spectrum and the one or more reference spectra [e.g., determining, as the values of the portion of the one or more viral vector sample quality metrics, one or more (e.g., a plurality) measure(s) of deviation between the reference spectra and the IR absorbance spectrum].

[0058] In certain embodiments, one or more reference spectra comprises a high- quality viral vector spectrum measured from a reference sample having a full capsid fraction (e.g., a-priori known; e.g., determined to be) at or above a particular threshold fraction. In certain embodiments, a threshold fraction is about 75% [e.g., about 80% (e.g., about 90%)].

[0059] In certain embodiments, step (c) comprises computing a difference spectrum based on at least one of the one or more reference spectra and the IR absorbance spectrum (e.g., by subtracting an IR absorbance spectrum, and / or a scaled or otherwise pre-processed version thereof, from a reference spectrum, and / or a scaled or otherwise pre-processed version thereof, or vice-versa). In certain embodiments, step (c) comprises computing one or more derivative spectra (e.g., a first derivative; e.g., a second derivative) of at least one of the one or more reference spectra and / or the IR absorbance spectrum. In certain embodiments, step (c) comprises computing (e.g., as values of one or more of the sample quality metrics) one or more members selected from the group consisting of: a correlation value based on a correlation of (i) a particular one of the one or more reference spectra and / or one or more - 14 - 11677372v1Attorney Docket No. 2017297-0013derivatives thereof, and (ii) the IR absorbance spectrum and / or one or more derivatives thereof; a covariance value based on a covariance of (i) a particular one of the one or more reference spectra and / or one or more derivatives thereof, and (ii) the IR absorbance spectrum and / or one or more derivatives thereof; a Pearson’s correlation value between (i) a particular one of the one or more reference spectra and / or one or more derivatives thereof, and (ii) the IR absorbance spectrum and / or one or more derivatives thereof; and an overlap integral value based on an overlap integral of (i) a particular one of the one or more reference spectra and / or one or more derivatives thereof, and (ii) the IR absorbance spectrum and / or one or more derivatives thereof.

[0060] In certain embodiments, step (c) comprises: determining values for a set of one or more particular peak metrics from the IR absorbance spectrum, thereby obtaining a set of sample peak metric values; and determining values of one or more of the sample quality metrics based the set of sample peak metric values and a set of reference peak metric values having been determined for the one or more particular peak metrics from the one or more reference spectra.

[0061] In certain embodiments, provided methods comprise determining (e.g., as one or more of the sample quality metric values) a similarity score that measures a similarity between the one or more reference spectra and the IR absorbance spectrum. In certain embodiments, methods comprise performing steps (a) – (c) repeatedly, in substantially real- time, thereby monitoring deviation from the one or more reference spectra in real-time.

[0062] In certain embodiments, one or more time points are a plurality of time points [e.g., step (a) comprises (e.g., repeatedly) measuring an IR absorption signal at each of a plurality of time points (e.g., continuously, in real time)].

[0063] In certain embodiments, provided methods comprise determining values of a first sample quality metric at each of the plurality of time points and determining a value of a second (e.g., time differential; e.g., time aggregated) sample quality metric using values of the first sample quality metric corresponding to two or more of the plurality of time points.

[0064] In certain embodiments, a second sample quality metric is a time differential metric that measure a temporal change in the first sample quality metric and is computed based on a difference between (i) value(s) of the first sample quality metric at a first set of time point(s) and (ii) value(s) of the first sample quality metric at a second set of time point(s) [e.g., a difference between a value of the first sample quality metric at a first (e.g., - 15 - 11677372v1Attorney Docket No. 2017297-0013current) time point and a value of the first sample quality metric at a second (e.g., prior) time point (e.g., a difference between values at consecutive time points)].

[0065] In certain embodiments, a second sample quality metric is a (e.g., real-time) time-aggregated signal that is a function of at least a portion [e.g., a cumulative, increasing portion, e.g., beginning at a particular time point and ending at a current time point; e.g., a temporal window of a particular size (e.g., a backward looking window)] of the plurality of time points (e.g., a running sum, mean, median, mode, variance, standard deviation, etc. over a particular time window).

[0066] In certain embodiments, step (c) comprises causing, by the processor, transmission of one or more trigger signals (e.g., voltages) to a controller unit of the production unit. In certain embodiments, the one or more trigger signals comprise an analog voltage signal having a time varying amplitude based on (e.g., substantially proportional to) values of at least a portion of the one or more sample quality metrics.

[0067] In certain embodiments, step (c) comprises using a machine learning model to adjust the one or more process parameters [e.g., wherein the machine learning model receives one or more sample quality metrics as input and generates an adjustment to and / or a target process parameter as output; e.g., wherein the machine learning model receives one or more IR spectra as input and generates an adjustment to and / or a target process parameter as output].

[0068] In certain embodiments, one or more process parameters comprise one or more members selected from the group consisting of a flow rate, a flow direction a pressure, a temperature, and a pH. In certain embodiments, the one or more process parameters comprise an amount (e.g., absolute and / or relative) of one or more raw materials (e.g., used as input to the production unit). In certain embodiments, the one or more process parameters comprise a time to initiate and / or halt a sub-process (e.g., heating, collection of an eluted fraction, growth, etc.).

[0069] In certain embodiments, one or more IR absorbance signal(s), to which the IR absorbance data received at step (b) corresponds, is / are measured from the aqueous sample, at each of one or more time points, as it (the aqueous sample) exits from a purification unit (e.g., a chromatography column); and methods comprise: using the IR absorption data to determine one or both of (i) a total capsid content and (ii) a full capsid fraction; and using the determined total capsid content and / or full capsid fraction to control collection of a target - 16 - 11677372v1Attorney Docket No. 2017297-0013fraction of the aqueous sample (e.g., during a particular collection window), thereby obtaining a purified sample of viral vector material.

[0070] In certain embodiments, one or more IR absorbance signal(s), to which the IR absorbance data received at step (b) corresponds, is / are measured from the aqueous sample, at each of one or more time points, as it (the aqueous sample) exits from a purification unit (e.g., a chromatography column); and the method comprises: using the IR absorption data to determine a capsid aggregation metric that measures a level of aggregation between capsids in the viral vector sample; and using the capsid aggregation metric to control collection of a target fraction of the aqueous sample (e.g., during a particular collection window), thereby obtaining a purified sample of viral vector material.

[0071] In another aspect, the present disclosure is directed to systems for obtaining a purified sample of a target protein species via real-time monitoring of protein heterogeneity and (e.g., automated; e.g., semi-automated) control of purification processing, the system comprising: (a) one or more mid-infrared (MIR) analyzer(s), aligned and operable to measure, at each of one or more time points, a corresponding infrared (IR) absorbance signal from an aqueous sample exiting from a purification unit (e.g., a chromatography column), the aqueous sample comprising one or more protein species including the target protein species; (b) a processor of a computing device; and (c) memory having instructions stored thereon, wherein the instructions, when executed by the processor cause the processor to: receive IR absorbance data corresponding to the IR absorbance signal(s) at each of the one or more time points; determine values of one or more sample quality metrics based on the IR absorbance data, the one or more sample quality metrics comprising a protein aggregation metric indicative of a level of protein aggregation within the aqueous sample; and provide (e.g., transmit to a controller unit of the purification unit) and / or use the one or more sample quality metrics for control collection of a target fraction of the aqueous sample (e.g., during a particular collection window), thereby causing the purified sample of the target protein species to be obtained.

[0072] In certain embodiments, provided systems further comprise the purification unit and / or a controller unit thereof.

[0073] In another aspect, the present disclosure is directed to systems for real-time monitoring of protein aggregation in a sample, the system comprising: a processor of a computing device; and memory having instructions stored thereon, wherein the instructions, - 17 - 11677372v1Attorney Docket No. 2017297-0013when executed by the processor, cause the processor to: (a) repeatedly receive infrared (IR) absorbance data corresponding to IR absorbance signals measured at each of a plurality of time points, the IR absorbance data comprising, for each particular time point of the plurality of time points, a corresponding IR absorbance spectrum measured from the sample at the particular time point and comprising a plurality of absorbance values, each associated with a particular wavenumber; (b) analyze (e.g., automatically) the IR absorbance data to obtain a real-time protein aggregation signal providing a measure of protein aggregation in the sample as a function of time, by, for each particular time point of the plurality of time points: determining, using the IR absorbance spectrum corresponding to the particular time point, values of one or more peak metrics for one or both of an Amide I band and an Amide II band; determining, using the values of the one or more peak metrics, a value of a protein aggregation metric indicative of a level of protein aggregation within the sample at the particular time point; and updating the real-time protein aggregation signal with the determined value of the protein aggregation metric for the particular time point; and (c) store and / or provide the real-time protein aggregation signal for one or more of (i) further processing, (ii) display, and (iii) use as a control signal for adjusting one or more purification units (e.g., chromatography systems).

[0074] In another aspect, the present disclosure is directed to systems for mid-IR (MIR)-spectroscopy-based monitoring and control of a production unit for manufacture of a biological product (e.g., a protein; e.g., a virus) the method comprising: (a) one or more (e.g., integrated) mid-infrared (MIR) analyzer(s) [e.g., MIR analyzer(s) as recited in one or more aspects and / or embodiments herein (e.g., in paragraphs above)] aligned and operable to measure, at each of one or more time points, a corresponding infrared (IR) absorbance signal from an aqueous sample flowing to and / or from the production unit (e.g., and which comprises one or more inputs, output products, waste products, or in-progress products of the production unit); (b) a processor of a computing device; and (c) memory having instructions stored thereon, wherein the instructions, when executed by the processor cause the processor to: receive IR absorbance data corresponding to the IR absorbance signal(s) at each of the one or more time points; and use the received IR absorbance data to cause adjustment to one or more process parameters of the production unit.

[0075] In certain embodiments, provided systems further comprise a production unit and / or a controller unit thereof. - 18 - 11677372v1Attorney Docket No. 2017297-0013

[0076] In another aspect, the present disclosure is directed to methods for quantifying and / or monitoring (e.g., in real-time) viral vector quality within an aqueous sample comprising one or more species of virus and / or virus-like particles, the methods comprising: (a) receiving (e.g., repeatedly), by a processor of a computing device, infrared (IR) absorbance data corresponding to one or more IR absorbance signal(s) measured from the sample; (b) determining (e.g., automatically), by the processor, using the IR absorbance data, values of one or more viral vector sample quality metrics; and (c) storing and / or providing for display and / or further processing, the one or more viral vector sample quality metric value(s).

[0077] In certain embodiments, one or more viral vector quality metrics comprise a total capsid content that quantifies a content of viral capsids within the sample [e.g., a concentration (e.g., titer), mass per volume (e.g. mg / mL), number of (viral) particles per volume, etc.]. In certain embodiments, one or more viral vector sample quality metrics comprise a full capsid fraction (e.g., percent, ratio, etc. of full viral vectors). In certain embodiments, one or more viral vector sample quality metrics comprise a capsid aggregation metric indicative of a level of capsid aggregation within the viral vector sample. In certain embodiments, one or more viral vector sample quality metrics comprise a protein content metric that quantifies protein content within the sample [e.g., a concentration (e.g., titer), mass per volume (e.g. mg / mL), number of particles per volume, etc.].

[0078] In certain embodiments, one or more viral vector sample quality metrics comprise a nucleic acid (e.g., DNA, RNA, etc.) content metric that quantifies nucleic acid content within the sample [e.g., a concentration (e.g., titer), mass per volume (e.g. mg / mL), number of particles per volume, number of viral genome copies, etc.].

[0079] In certain embodiments, one or more viral vector sample quality metrics comprise a viral nucleic acid (e.g., viral DNA, RNA, etc.) content metric that differentiates the viral nucleic acid from the host cell proteins and host cell nucleic acid content.

[0080] In certain embodiments, step (b) comprises: determining, by the processor, a value for each of one or more peak metrics for the IR absorption data, wherein each peak metric is associated with one or more particular spectral bands [e.g., a continuous range of wavelengths / wavenumbers (e.g., an Amide-I band, an Amide-II band, an Amide-III band, e.g.; an Amide region, spanning two or more of the Amide bands; e.g., an antisymmetric PO4 band; e.g.; a symmetric PO4 band)] and quantifies a particular structural feature [e.g., an - 19 - 11677372v1Attorney Docket No. 2017297-0013intensity (e.g., a peak amplitude; e.g., an Area Under the Curve (AUC)); e.g., a linewidth; e.g., a frequency position (e.g., peak frequency; e.g., center of mass frequency)] of one or more absorption peaks within the particular spectral band; and using the determined values of the one or more peak metrics to determine the values of at least a portion of the viral vector sample quality metrics.

[0081] In certain embodiments, IR absorbance data comprises: (i) one or more (e.g., a plurality of) Amide II absorbance value(s), associated with and measuring IR absorption (of the viral sample) at wavenumbers within an Amide II spectral band (e.g., ranging from about 1500 cm-1to about 1600 cm-1, e.g., ranging from about 1500 cm-1to about 1575 cm-1; e.g., ranging from about 1500 cm-1to about 1550 cm-1; e.g., ranging from about 1540 cm-1to about 1560 cm-1); and / or (ii) one or more (e.g., a plurality of) Amide III absorbance value(s), associated with and measuring IR absorption (of the viral sample) at wavenumbers within an Amide II spectral band (e.g., ranging from about 1250 cm-1to about 1350 cm-1, e.g., ranging from about 1250 cm-1to about 1325 cm-1; e.g., ranging from about 1275 cm-1to about 1325 cm-1; e.g., ranging from about 1280 cm-1to about 1300 cm-1).

[0082] In certain embodiments, step (b) comprises determining values of a protein content metric [e.g., concentration (e.g., titer)] that quantifies protein content within the sample based at least in part on the Amide II and / or Amide III absorbance value(s).

[0083] In certain embodiments, provided methods comprise: determining a value of an Amide II peak metric based on the Amide II absorbance values and / or a value of an Amide III peak metric based on the Amide III absorbance values; and using the Amide II peak metric value and / or the Amide III peak metric value to determine the protein content metric value. In certain embodiments, an Amide II peak metric and / or an Amide III peak metric is a peak intensity metric that quantifies an intensity of the Amide II band and / or Amide III band, respectively [e.g., a peak height, an area under the curve (AUC), etc.].

[0084] In certain embodiments, one or more viral vector sample quality metrics comprise one or more protein structure metrics (e.g., protein structure metrics; e.g., protein tertiary and / or quaternary structure metrics) indicative of presence and / or content (e.g., absolute content; e.g., relative content) of one or more particular protein structural forms (e.g., particular secondary structure motifs; e.g., particular tertiary and / or quaternary structure motifs / forms) within the sample (e.g., thereby providing for monitoring variation in capsid protein secondary / tertiary / quaternary structure). - 20 - 11677372v1Attorney Docket No. 2017297-0013

[0085] In certain embodiments, IR absorbance data comprises: (i) one or more (e.g., a plurality of) antisymmetric Phosphate Stretch (antisymmetric-PO4) absorbance value(s), associated with and measuring IR absorption (of the viral sample) at wavenumbers within an antisymmetric-PO4 spectral band (e.g., ranging from about 1150 cm-1to about 1250 cm-1, e.g., ranging from about 1175 cm-1to about 1250 cm-1; e.g., ranging from about 1200 cm-1to about 1250 cm-1; e.g., ranging from about 1210 cm-1to about 1230 cm-1); and / or (ii) one or more (e.g., a plurality of) symmetric Phosphate Stretch (symmetric-PO4) absorbance value(s), associated with and measuring IR absorption (of the viral sample) at wavenumbers within a symmetric-PO4spectral band (e.g., ranging from about 1000 cm-1to about 1100 cm-1, e.g., ranging from about 1050 cm-1to about 1100 cm-1; e.g., ranging from about 1075 cm-1to about 1100 cm-1; e.g., ranging from about 1075 cm-1to about 1085 cm-1).

[0086] In certain embodiments, step (b) comprises determining values of a nucleic acid (e.g., DNA, RNA, etc.) content metric that quantifies nucleic acid content [e.g., concentration (e.g., titer)] within the sample based at least in part on the antisymmetric-PO4and / or symmetric-PO4 absorbance value(s). In certain embodiments, provided methods comprise determining a value of an antisymmetric-PO4peak metric based on the antisymmetric-PO4 absorbance values and / or a value of an symmetric-PO4 peak metric based on the symmetric-PO4absorbance values; and using the antisymmetric-PO4peak metric value and / or the symmetric-PO4 peak metric value to determine the nucleic acid content metric value.

[0087] In certain embodiments, an antisymmetric-PO4peak metric and / or the symmetric-PO4 peak metric is a peak intensity metric that quantifies an intensity of the antisymmetric-PO4band and / or symmetric-PO4band, respectively [e.g., a peak height, an area under the curve (AUC), etc.].

[0088] In certain embodiments, step (b) comprises determining (i) value(s) of a protein content metric [e.g., concentration (e.g., titer)] that quantifies protein content within the sample and (ii) values of a nucleic acid (e.g., DNA, RNA, etc.) content metric that quantifies nucleic acid content [e.g., concentration (e.g., titer)] within the sample, thereby independently quantifying total protein and nucleic acid content within the sample. In certain embodiments, step (b) comprises: determining as one of the viral vector sample quality metrics, a total capsid content based at least in part on (e.g., as a function of) the value(s) of the protein content metric. In certain embodiments, step (b) comprises determining, as one of the viral vector sample quality metrics, a full capsid fraction based at least in part on (e.g., as - 21 - 11677372v1Attorney Docket No. 2017297-0013a function of) (i) the value(s) of the protein content metric and / or the total capsid content and (ii) the value(s) of the nucleic acid content metric.

[0089] In certain embodiments, IR absorbance data is or comprises one or more IR absorbance spectra, each IR absorbance spectra comprising, for each particular wavenumber of a plurality of wavenumber spanning a measured spectral band, a corresponding IR absorbance value representing a measure of absorption of IR light, by the aqueous sample, at the particular wavenumber. In certain embodiments, measured spectral band spans one or more bands selected from the group consisting of an Amide II band, an Amide III band, an asymmetric-PO4 band, and a symmetric-PO4 band.

[0090] In certain embodiments, step (a) comprises repeatedly receiving the IR absorbance data at a plurality of time points, thereby obtaining, for each of the plurality of time points, a corresponding set of IR absorbance data; and provided methods comprise performing steps (b) through (c) for each set of IR absorbance data, thereby monitoring the total capsid content and / or full capsid fraction over time.

[0091] In certain embodiments, provided methods comprise performing steps (a) through (c) in substantially real-time to obtain (i) a real-time capsid content signal providing a measure of capsid content in the sample as a function of time and / or full capsid fraction signal providing a measure of a fraction of capsids within the sample that are full, as a function of time.

[0092] In certain embodiments, provided methods comprise measuring, via one or more (e.g., integrated) mid-infrared (MIR) analyzer(s) [e.g., MIR analyzer(s) as described in various aspects and embodiments herein (e.g., in paragraphs above)], the one or more IR absorbance signal(s).

[0093] In certain embodiments, provided methods comprise measuring, at each of one or more time points, a corresponding one of the one or more infrared (IR) absorbance signal.

[0094] In certain embodiments, provided methods comprise measuring the one or more IR absorbance signal(s) from the aqueous sample as it (the aqueous sample) flows to (e.g., into) and / or from a production unit (e.g., the aqueous sample comprising one or more inputs, output products, waste products, or in-progress products of the production unit).

[0095] In certain embodiments, one or more species of virus and / or virus-like particles comprise one or more species of adeno-associated virus (AAV). In certain embodiments, one or more species of virus comprises adeno viruses and / or retroviruses (e.g., - 22 - 11677372v1Attorney Docket No. 2017297-0013lentiviruses). In certain embodiments, one or more species of virus comprises plant-based viruses (e.g., tobacco mosaic viruses).

[0096] In certain embodiments, one or more IR absorbance signal(s), to which the IR absorbance data correspond, is / are measured from the aqueous sample as it (the aqueous sample) flows to (e.g., into) and / or from a production unit (e.g., the aqueous sample comprising one or more inputs, output products, waste products, or in-progress products of the production unit).

[0097] In certain embodiments, a production unit is a purification unit. In certain embodiments, a purification unit is a member selected from the group consisting of an alternating tangential flow filtration (ATF) system, tangential flow depth filtration (TFDF) system, tangential flow filtration (TFF) system, a chromatography column, a direct, or normal, flow filtration unit, an ultra-filtration unit, and a dia-filtration unit. In certain embodiments, a purification unit is a chromatography column {e.g., and wherein the chromatography column is a member selected from the group consisting of an affinity chromatography (AC) column, a hydrophobic interaction chromatography (HIC) column, an ion exchange chromatograph (IEX) column, a size exclusion chromatography (SEC) column, and a mixed-mode chromatography column [e.g., any combination of the foregoing (e.g., IEX and HIC; e.g., IEX and SEC)]}.

[0098] In certain embodiments, a production unit is or comprises a bioreactor (e.g., a seed bioreactor; e.g., a production bioreactor).

[0099] In certain embodiments, step (c) comprises causing, by the processor, generation and / or transmission of one or more trigger signals (e.g., voltages) to a controller unit of the production unit based at least in part on (e.g., a value of) one or more of the determined viral vector sample quality metrics [e.g., a value of a determined capsid content and / or (e.g., a value of) a determined full capsid fraction]. In certain embodiments, step (c) comprises causing, by the processor, generation of a trigger signal (e.g., an analog signal) having a value based at least in part on a determined viral vector quality metric [e.g., a capsid content; e.g., a full capsid fraction; e.g., a capsid aggregation metric].

[0100] In certain embodiments, one or more IR absorbance signal(s), to which the IR absorbance data received at step (a) corresponds, is / are measured from the aqueous sample, at each of one or more time points, as it (the aqueous sample) exits from a purification unit (e.g., a chromatography column); and provided methods comprise: using the IR absorption - 23 - 11677372v1Attorney Docket No. 2017297-0013data to determine one or both of (i) a total capsid content and (ii) a full capsid fraction; and using the determined total capsid content and / or full capsid fraction to control collection of a target fraction of the aqueous sample (e.g., during a particular collection window), thereby obtaining a purified sample of viral vector material.

[0101] In certain embodiments, one or more IR absorbance signal(s), to which the IR absorbance data received at step (a) corresponds, is / are measured from the aqueous sample, at each of one or more time points, as it (the aqueous sample) exits from a purification unit (e.g., a chromatography column); and provided methods comprise: using the IR absorption data to determine a capsid aggregation metric that measures a level of aggregation between capsids in the viral vector sample; and using the capsid aggregation metric to control collection of a target fraction of the aqueous sample (e.g., during a particular collection window), thereby obtaining a purified sample of viral vector material.

[0102] In certain embodiments, IR absorbance data comprises an IR absorbance spectrum and wherein step (b) comprises: receiving (e.g., and / or accessing) one or more reference spectra, each measured from a corresponding (e.g., high-quality) reference sample comprising the target viral vector species at high purity and / or concentration and / or one or more model constituents thereof (e.g., a model protein solution; e.g., a model ssDNA solution); and determining (e.g., automatically), the values of at least a portion of the one or more viral vector sample quality metrics using the IR absorbance spectrum and the one or more reference spectra [e.g., determining, as the values of the portion of the one or more viral vector sample quality metrics, one or more (e.g., a plurality) measure(s) of deviation between the reference spectra and the IR absorbance spectrum].

[0103] In certain embodiments, one or more reference spectra comprises a high- quality viral vector spectrum measured from a reference sample having a full capsid fraction (e.g., a-priori known; e.g., determined to be) at or above a particular threshold fraction. In certain embodiments, a threshold fraction is about 75% [e.g., about 80% (e.g., about 90%)].

[0104] In certain embodiments, step (b) comprises computing a difference spectrum based on at least one of the one or more reference spectra and the IR absorbance spectrum (e.g., by subtracting an IR absorbance spectrum, and / or a scaled or otherwise pre-processed version thereof, from a reference spectrum, and / or a scaled or otherwise pre-processed version thereof, or vice-versa). - 24 - 11677372v1Attorney Docket No. 2017297-0013

[0105] In certain embodiments, step (b) comprises computing one or more derivative spectra (e.g., a first derivative; e.g., a second derivative) of at least one of the one or more reference spectra and / or the IR absorbance spectrum.

[0106] In certain embodiments, step (b) comprises computing (e.g., as the measure of deviation) one or more members selected from the group consisting of: a correlation value based on a correlation of (i) a particular one of the one or more reference spectra and / or one or more derivatives thereof, and (ii) the IR absorbance spectrum and / or one or more derivatives thereof; a covariance value based on a covariance of (i) a particular one of the one or more reference spectra and / or one or more derivatives thereof, and (ii) the IR absorbance spectrum and / or one or more derivatives thereof; a Pearson’s correlation value between (i) a particular one of the one or more reference spectra and / or one or more derivatives thereof, and (ii) the IR absorbance spectrum and / or one or more derivatives thereof; and an overlap integral value based on an overlap integral of (i) a particular one of the one or more reference spectra and / or one or more derivatives thereof, and (ii) the IR absorbance spectrum and / or one or more derivatives thereof.

[0107] In certain embodiments, step (b) comprises: determining values for a set of one or more particular peak metrics from the IR absorbance spectrum, thereby obtaining a set of sample peak metric values; and determining the measure of deviation based the set of sample peak metric values and a set of reference peak metric values having been determined for the one or more particular peak metrics from the one or more reference spectra.

[0108] In certain embodiments, provided methods comprise determining, as the measure of deviation, a similarity score that measures a similarity between the one or more reference spectra and the IR absorbance spectrum.

[0109] In certain embodiments, provided methods comprise performing steps (a) – (c) repeatedly, in substantially real-time, thereby monitoring deviation from the one or more reference spectra in real-time.

[0110] In another aspect, the present disclosure is directed to certain methods for evaluating and / or monitoring (e.g., in real-time) quality of viral vector content within an aqueous sample comprising a target viral vector species, the method comprising: (a) receiving (e.g., repeatedly), by a processor of a computing device, infrared (IR) absorbance data corresponding to one or more IR absorbance signal(s) measured from the sample, the IR absorbance data comprising an (e.g., at least one) IR absorbance spectrum measured from the - 25 - 11677372v1Attorney Docket No. 2017297-0013sample and comprising a plurality of absorbance values, each associated with a particular wavenumber; (b) receiving (e.g., and / or accessing), by the processor, one or more reference spectra, each measured from a corresponding (e.g., high-quality) reference sample comprising the target viral vector species at high purity and / or concentration and / or one or more model constituents thereof (e.g., a model protein solution; e.g., a model ssDNA solution); (c) determining (e.g., automatically), by the processor, one or more (e.g., a plurality) measure(s) of deviation using the IR absorbance spectrum and the one or more reference spectra; (d) storing and / or providing for display and / or further processing, the measure(s) of deviation.

[0111] In another aspect, the present disclosure is directed to systems for quantifying and / or monitoring (e.g., in real-time) viral vector quality within an aqueous sample comprising one or more species of virus and / or virus-like particles, the systems comprising: a processor of a computing device; and memory having instructions stored thereon, wherein the instructions, when executed by the processor, cause the processor to perform provided methods as described in certain aspects and embodiments herein (e.g., in paragraphs above).

[0112] In another aspect, the present disclosure is directed to methods for (e.g., real- time) monitoring of compositional changes of a sample via infrared (IR) absorption spectroscopy, the methods comprising: (a) repeatedly receiving, by a processor of a computing device, infrared (IR) absorbance data corresponding to IR absorbance signals measured at each of a plurality of time points, the IR absorbance data comprising, for each particular time point of the plurality of time points, a corresponding IR absorbance spectrum measured from the sample at the particular time point and comprising a plurality of absorbance values, each associated with a particular wavenumber; (b) analyzing (e.g., automatically), by the processor, the IR absorbance data to obtain a (e.g., real-time) normalized spectral difference signal that measures a change normalized spectral absorbance between consecutive time points, by, for each particular time point of the plurality of time points: normalizing a current IR absorbance spectrum that corresponds to the particular time point using a reference absorbance value determined from values of the current IR absorbance spectrum at one or more reference wavenumbers, thereby obtaining a current normalized spectrum; determining a current value of the spectral difference metric based on (e.g., computed as) a difference between the current normalized spectrum and a prior normalized spectrum, wherein the prior normalized spectrum is based on one or more previously obtained IR absorption spectra (e.g., is a particular previously obtained IR - 26 - 11677372v1Attorney Docket No. 2017297-0013absorption spectrum; e.g., is an average of a plurality of previously obtained IR absorption spectra), each corresponding to and having been measured at a particular previous time point (e.g., preceding the current particular time point by a particular time interval and / or multiples thereof) and each particular previously obtained IR absorption spectrum having been normalized using a reference value determined from values of the that particular previously obtained IR absorbance spectrum at the one or more reference wavenumbers; and updating the real-time normalized spectral difference signal according to the current value of the normalized spectral difference metric; and (c) storing and / or providing, by the processor, the real-time normalized spectral difference signal for one or more of (i) further processing, (ii) display, and (iii) use as a control signal for adjustment of one or more process parameters of a production unit (e.g., a chromatography unit; e.g., a filtration unit).

[0113] In certain embodiments, provided methods comprise identifying (e.g., by the processor) a change in composition of the sample (e.g., at a particular time) based on the real- time normalized spectral difference signal.

[0114] In certain embodiments, provided methods comprise detecting a changepoint [e.g., a change statistical properties (e.g., mean, median, mode, variance, etc.); e.g., a step- change] in the real-time normalized spectral difference signal and identifying the change in composition of the sample based on the detected changepoint.

[0115] In certain embodiments, provided methods comprise determining (e.g., as a sample quality metric) (e.g., at each time point, e.g., in real-time) values of one or more statistical parameter(s) of the real-time normalized spectral difference signal.

[0116] In certain embodiments, one or more statistical parameter(s) comprise one or more members selected from the group consisting of: a mean [e.g., running (e.g., backward looking) mean, e.g., computed as a mean of the real-time normalized spectral difference signal over a time window comprising (e.g., ending at) the current time point and one or more previous time point(s)]; a variance [e.g., running (e.g., backward looking) variance, e.g., computed as a variance of the real-time normalized spectral difference signal over a time window comprising (e.g., ending at) the current time point and one or more previous time point(s)]; a mode; and a standard deviation.

[0117] In certain embodiments, provided methods comprise identifying the change in composition based on a value of at least one of the one or more statistical parameter(s) (i) exceeding one or more threshold values and / or (ii) varying outside a particular range [e.g., - 27 - 11677372v1Attorney Docket No. 2017297-0013predetermined threshold values and / or ranges; e.g., threshold values and / or ranges that are determined on-the-fly, e.g., during an initial phase of a process run (e.g., during an initial time-window of a chromatography run, e.g., during an initial ramp-up of a salt gradient, e.g., before protein elutes)].

[0118] In certain embodiments, a sample is or comprises an aqueous sample. In certain embodiments, sample comprises one or more protein species [e.g., a target protein species, such as a monoclonal antibody; e.g., as recited in certain embodiments herein].

[0119] In certain embodiments, provided methods comprise identifying (e.g., by the processor) a change in composition of the sample (e.g., at a particular time) corresponding to a change in purity [e.g., presence of protein species other than the target; e.g., presence of undesired forms (e.g., non-monomeric) of the target protein species] and / or properties (e.g., secondary structure composition) of a target protein species.

[0120] In certain embodiments, an identified change in composition is or comprises (e.g., is indicative of) a change in level and / or presence of protein aggregation within the aqueous sample. In certain embodiments, an identified change in composition is or comprises (e.g., is indicative of) a one or more members selected from the group consisting of: a change in content (e.g., relative content) of one or more particular protein species within the (e.g., aqueous) sample; a change in a level and / or type of molecular conjugation (e.g. glycan, small-molecule drug, polyethylene glycol, etc.); and a change in content of one or more protein secondary structure motifs (e.g., alpha-helical content, beta-sheet content, turn content, disordered content).

[0121] In certain embodiments, a sample comprises nucleic acid (e.g., DNA, RNA, mRNA, etc.). In certain embodiments, provided methods comprise identifying (e.g., by the processor) a change in composition of the sample (e.g., at a particular time) corresponding to a change in purity and / or properties of the nucleic acid within the sample (e.g., a change in relative content of one or more particular types of nucleic acid (e.g., DNA, RNA, ssDNA, dsDNA)] within the (e.g., aqueous) sample.

[0122] In certain embodiments, an aqueous sample comprises one or more species of virus and / or virus-like particles [e.g., adeno-associated viral vectors (AAV); e.g., lentiviral vectors]. In certain embodiments, provided methods comprise identifying (e.g., by the processor) a change in composition of the sample (e.g., at a particular time) corresponding to a change in purity and / or properties of the virus and / or virus like particles within the sample. - 28 - 11677372v1Attorney Docket No. 2017297-0013

[0123] In certain embodiments, a change in composition corresponds to (e.g., is indicative of) a change in a relative fraction of empty and / or full viral vectors within the aqueous sample (e.g., percent, ratio, etc. of full viral vectors).

[0124] In certain embodiments, change in composition corresponds to (e.g., is indicative of) a level of capsid aggregation within the sample.

[0125] In certain embodiments, a change in composition corresponds to (e.g., is indicative of) a change in a relative content between viral nucleic acid from host cell proteins and host cell nucleic acid content.

[0126] In certain embodiments, provided methods comprise causing (e.g., triggering) adjustment of one or more process parameters of a production unit based on (e.g., triggered upon) the identification of the change in composition of the sample (e.g., detection of a changepoint; e.g., based on values of one or more statistical parameter(s) of the real-time normalized spectral difference signal).

[0127] In certain embodiments, a production unit is or comprises a purification unit.

[0128] In certain embodiments, a purification unit is or comprises a chromatography column.

[0129] In certain embodiments, a production unit is or comprises one or more members selected from the group consisting of a flow controller, a valve controller (e.g. for adjustment of a buffer composition (e.g., via valve switching), a temperature controller (e.g., for adjustment of one or more temperature set points and / or (e.g., temporal) profiles.

[0130] In certain embodiments, provided methods comprise triggering a response of a production unit (e.g., any of the parameters discussed herein) [e.g., wherein the production unit is a first production unit and the sample is associated with (e.g., is an input, an output, or component processed by) a second (e.g., upstream or downstream) production unit].

[0131] In certain embodiments, a sample is an aqueous sample and the method comprises causing adjustment a collection window to control collection of a target fraction of the aqueous sample (e.g., a monomeric species of protein), thereby obtaining a purified sample.

[0132] In certain embodiments, a production unit is or comprises a filtration unit (e.g., an ultrafiltration and / or diafiltration unit) (e.g., and wherein the method comprises causing - 29 - 11677372v1Attorney Docket No. 2017297-0013adjustment to a flow rates, transmembrane pressure, processing time, etc., to control a composition of retentate and / or permeate).

[0133] In certain embodiments, a method comprises monitoring progress of a chemical reaction [e.g., within the production unit (e.g., a bioreactor, a transfection unit, a pegylation unit, an antibody drug conjugation unit]based on (e.g., identification of a compositional change using) the real-time normalized spectral difference signal.

[0134] In certain embodiments, a method comprises causing adjustment to one or more members selected from the group consisting of an inline buffer preparation, a mixing process (e.g., in mixing tanks), a temperature controller.

[0135] In certain embodiments, a reference absorbance value is determined from a value of the current IR absorbance spectrum at a single reference wavenumber and the prior reference value is determined from a value of the prior IR absorbance spectrum at the single reference wavenumber.

[0136] In certain embodiments, determining a current value of the spectral difference metric comprises computing, for each of the current normalized spectrum and the prior normalized spectrum, an integrated absorbance over one or more particular spectral bands (e.g., and subtracting the integrated absorbance values).

[0137] In certain embodiments, one or more particular spectral bands comprise one or more members selected from the group consisting of: an Amide I spectral band (e.g., ranging from about 1600 cm-1to about 1700 cm-1or about 1800 cm-1(e.g., ranging from about 1600 cm-1to about 1725 cm-1; e.g., ranging from about 1625cm-1to about 1725 cm-1; e.g., ranging from about 1630 cm-1to about 1650 cm-1), and / or an Amide II region, ranging from about 1500 to about 1600 cm-1(e.g., ranging from about 1500 cm-1to about 1575 cm-1; e.g., ranging from about 1500 cm-1to about 1550 cm-1; e.g., ranging from about 1540 cm-1to about 1560 cm-1)); an Amide II spectral band (e.g., ranging from about 1500 cm-1to about 1600 cm-1, e.g., ranging from about 1500 cm-1to about 1575 cm-1; e.g., ranging from about 1500 cm-1to about 1550 cm-1; e.g., ranging from about 1540 cm-1to about 1560 cm-1); and an Amide III spectral band (e.g., ranging from about 1250 cm-1to about 1350 cm-1, e.g., ranging from about 1250 cm-1to about 1325 cm-1; e.g., ranging from about 1275 cm-1to about 1325 cm-1; e.g., ranging from about 1280 cm-1to about 1300 cm-1).

[0138] In certain embodiments, one or more particular spectral bands comprise one or more members selected from the group consisting of: an antisymmetric-PO4spectral band - 30 - 11677372v1Attorney Docket No. 2017297-0013(e.g., ranging from about 1150 cm-1to about 1250 cm-1, e.g., ranging from about 1175 cm-1to about 1250 cm-1; e.g., ranging from about 1200 cm-1to about 1250 cm-1; e.g., ranging from about 1210 cm-1to about 1230 cm-1); and a symmetric-PO4spectral band (e.g., ranging from about 1000 cm-1to about 1100 cm-1, e.g., ranging from about 1050 cm-1to about 1100 cm-1; e.g., ranging from about 1075 cm-1to about 1100 cm-1; e.g., ranging from about 1075 cm-1to about 1085 cm-1).

[0139] In certain embodiments, comprising measuring the IR absorbance signals using one or more MIR analyzer(s) (e.g., as recited in any one of claims 9 to 24).

[0140] In another aspect, the present disclosure provides for methods for (e.g., real- time) monitoring of temporal changes of a sample via infrared (IR) absorption spectroscopy, the method comprising: (a) repeatedly receiving, by a processor of a computing device, infrared (IR) absorbance data corresponding to IR absorbance signals measured at each of a plurality of time points, the IR absorbance data comprising, for each particular time point of the plurality of time points, a corresponding IR absorbance spectrum measured from the sample at the particular time point and comprising a plurality of absorbance values, each associated with a particular wavenumber; (b) analyzing (e.g., automatically), by the processor, the IR absorbance data to obtain one or both of: a (e.g., real-time) a time differential signal that measure a temporal change between values one or more features (e.g., sample quality metrics) determined using (i) a first set of one or more IR absorbance spectra that correspond to a first set of particular time point(s) and (ii) a second set of one or more IR absorbance spectra that correspond to a first set of particular time point(s); and a (e.g., real- time) time-aggregated signal that is a function of at least a portion [e.g., a cumulative, increasing portion, e.g., beginning at a particular time point and ending at a current time point; e.g., a temporal window of a particular size (e.g., a backward looking window)] of the plurality of time points (e.g., a running sum, mean, median, mode, variance, standard deviation, etc. over a particular time window); and (c) storing and / or providing, by the processor, the a time differential signal and / or the time-aggregated signal for one or more of (i) further processing, (ii) display, and (iii) use as a control signal for adjustment of one or more process parameters of a production unit (e.g., a chromatography unit; e.g., a filtration unit).

[0141] In another aspect, the present disclosure provides systems for (e.g., real-time) monitoring of temporal (e.g., compositional) changes of a sample via infrared (IR) absorption spectroscopy, the system comprising: a processor of a computing device; and memory having - 31 - 11677372v1Attorney Docket No. 2017297-0013instructions stored thereon, wherein the instructions, when executed by the processor, cause the processor to perform various methods described herein (e.g., in paragraphs above).

[0142] In certain embodiments, provided systems further comprise one or more MIR analyzer(s) (e.g., as described in paragraphs above).

[0143] In some aspects, the present disclosure provides methods for obtaining a purified sample of a target protein species via mid-infrared (IR) spectroscopy-based bioprocess monitoring and control, said provided methods comprising: (a) measuring, via one or more mid-infrared (MIR) analyzer(s), at each of a plurality of time points, a corresponding mid-IR absorbance spectrum from an aqueous sample exiting from a purification unit, the aqueous sample comprising one or more protein species including the target protein species, thereby measuring a plurality of mid-IR absorbance spectra over time; (b) receiving, by a processor of a computing device, spectral data corresponding to the plurality of measured mid-IR absorbance spectra; (c) determining, by the processor, for each of at least a portion of the plurality of time points, corresponding values of one or more sample quality metrics based on the spectral data, the one or more sample quality metrics comprising a measure of concentration and / or purity of the target protein species in the aqueous sample; and (d) using the determined values of the one or more sample quality metrics to control collection of a target fraction of the aqueous sample (e.g., during a particular collection window), thereby obtaining the purified sample of the target protein species.

[0144] In certain embodiments, a purification unit is or comprises a chromatography column {e.g., wherein the chromatography column is a member selected from the group consisting of an affinity chromatography (AC) column, a hydrophobic interaction chromatography (HIC) column, an ion exchange chromatograph (IEX) column, a size exclusion chromatography (SEC) column, and a mixed-mode chromatography column [e.g., any combination of the foregoing (e.g., IEX and HIC; e.g., IEX and SEC)]}. In certain embodiments, a purification unit is or comprises an ultrafiltration and diafiltration system (UF / DF) [e.g., a tangential flow filtration (TFF) system].

[0145] In certain embodiments, a target protein species is selected from the group consisting of a monoclonal antibody (mAb), a fusion protein, a viral capsid protein, an antibody-drug conjugate, a recombinant protein, and a plasmatic protein.

[0146] In certain embodiments, an aqueous sample comprises a plurality of different molecular forms of a particular protein [e.g., a therapeutic protein (e.g., a mAb)], including a - 32 - 11677372v1Attorney Docket No. 2017297-0013monomeric form and one or more aggregated forms (e.g., dimer and / or other multimers) and wherein the target protein species is the monomeric form of the particular protein.

[0147] In certain embodiments, an aqueous sample comprises one or more sub- species of a particular protein, each having a particular desired level and / or type of molecular conjugation (e.g., glycan, small-molecule drug, polyethylene glycol, etc.), and wherein the target protein species is a particular one of the one or more sub-species.

[0148] In certain embodiments, one or more MIR analyzer(s) comprise a quantum- cascade laser (QCL)-based mid-IR spectrometer comprising: a QCL-based source, aligned and operable to emit a beam of MIR light [e.g., comprising one or more wavelengths substantially within the MIR spectral range (e.g., ranging from about 5000 cm-1 to about 500 cm-1 (e.g., about 2 to 20 microns))]; one or more sampling optics, aligned to direct and / or allow passage of the beam of MIR light, and / or at least a portion thereof, through and / or into contact with at least a portion of the aqueous sample [e.g., wherein the beam of MIR light contacts the portion of the aqueous sample via reflection at an interface between a solid material (e.g., an ATR crystal and / or optical fiber) and the aqueous sample (e.g., wherein the beam of MIR light undergoes total internal reflection, and contacts / probes the portion of the aqueous sample via an evanescent wave extending into the aqueous sample)] and, following passage through or contact with the portion of the aqueous sample, towards one or more detectors; and the one or more detectors, aligned and operable to detect the beam of MIR light following its passage through and / or contact with the aqueous sample.

[0149] In certain embodiments, one or more sampling optics comprise a flow cell comprising a detection channel through which the aqueous sample flows; and one or more detectors are aligned and operable to detect the beam of MIR light exiting from, following its transmission through, the detection channel.

[0150] In certain embodiments, a QCL-based source is a tunable QCL operable sweep an emission frequency of the beam of MIR light through a plurality of frequencies across a scan range (e.g., wherein the scan range comprises a range from about 1700 cm-1 to 1400 cm-1; e.g., wherein the scan range comprises a range from 1300 cm-1 to 1050 cm-1; e.g., wherein the scan range comprises a range from at least 1200 cm-1 to 1000 cm-1) and the method comprises, at each of the one or more time points: sweeping the emission frequency of the beam MIR light across the scan range of the tunable laser, thereby illuminating the aqueous sample with a plurality of emission frequencies; and detecting, with the one or more - 33 - 11677372v1Attorney Docket No. 2017297-0013detectors, the beam of MIR light (e.g., having been (i) internally reflected by an interface between the high-index material and the aqueous sample and / or (ii) transmitted through the detection channel through which the aqueous sample flows) at each of the plurality of emission frequencies, thereby measuring, as the corresponding infrared (IR) absorbance signal from the aqueous sample, a corresponding IR spectrum comprising a plurality of values, each associated with and representing and / or based on a detected power at a particular one of the plurality of emission frequencies.

[0151] In certain embodiments, a MIR analyzer is an on-line sensor (e.g., as opposed to an off-line or at-line sensor) and wherein step (a) comprises repeatedly measuring IR absorbance spectra over time {e.g., every 20s or less [e.g., every 10s or less (e.g., every 5s or less; (e.g., every second or less))]}, as the aqueous solution exits from the purification unit (e.g., thereby measuring IR absorbance spectra from the aqueous sample in substantially real time).

[0152] In certain embodiments, spectral data comprises, for each of the one or more time points, a corresponding Amide band spectrum [e.g., the Amide band spectrum comprising, for each particular wavelength of a plurality of sampled (e.g., emission) wavelengths within a range from about 1800 to about 800 cm-1 (e.g., with a range from about 1700 to 1400 cm-1), an associated absorption value representing a level of absorption, by a portion of the aqueous sample, at the particular wavelength].

[0153] In certain embodiments, step (c) comprises: receiving (e.g., and or accessing), by the processor, a reference spectrum for the target protein species, said reference having been measured from a particular corresponding reference sample comprising the target protein species substantially in isolation and / or at high purity [e.g., 75% purity or better (e.g., 90% purity or better (e.g., 95% purity or better))]; and repeatedly, at each of the plurality of time points, using the reference spectrum to determine a concentration of the target protein species within the aqueous sample at each time point, thereby tracking a concentration of the target protein species over time.

[0154] In certain embodiments, step (c) comprises: receiving (e.g., and or accessing), by the processor, one or more impurity reference spectra, each associated with a particular impurity of interest and having been measured from a particular corresponding reference sample comprising the impurity of interest substantially in isolation and / or at high purity [e.g., 75% purity or better (e.g., 90% purity or better (e.g., 95% purity or better))]; and - 34 - 11677372v1Attorney Docket No. 2017297-0013repeatedly, at each of the plurality of time points, using the one or more impurity reference spectra reference spectrum to determine a concentration of each of the impurities of interest within the aqueous sample.

[0155] In certain embodiments, spectral data comprises, for each of the one or more time points, a corresponding Amide band spectrum and wherein step (c) comprises determining, as the measure of sample purity, a ratio of absorbance at at least two wavenumbers within the Amide band spectrum.

[0156] In certain embodiments, step (d) comprises causing, by the processor, transmission of one or more trigger signals (e.g., voltages) to a controller unit of the purification unit and / or a downstream (from the purification unit) valve.

[0157] In certain embodiments, step (d) comprises one or both of: initiating, by the controller unit, based on the one or more trigger signals, collection of the target fraction of the aqueous sample [e.g., wherein a particular one of the one or more trigger signals is an analog signal and the controller unit initiates collection of the target fraction based on an amplitude of the analog signal (e.g., when it exceeds a particular threshold; e.g., when it drops below a particular threshold); e.g., wherein a particular one of the one or more trigger signals is a digital signal that triggers (e.g., by transitioning from a 0 voltage level to 1 voltage level or vice-a-versa) initiating collection of the target fraction]; and stopping, by the controller unit, based the one or more trigger signals, collection of the target fraction of the aqueous sample [e.g., wherein a particular one of the one or more trigger signals is an analog signal and the controller unit stops collection of the target fraction based on an amplitude of the analog signal (e.g., when it exceeds a particular threshold; e.g., when it drops below a particular threshold); e.g., wherein a particular one of the one or more trigger signals is a digital signal that triggers (e.g., by transitioning from a 0 voltage level to 1 voltage level or vice-a-versa) stopping collection of the target fraction].

[0158] In certain embodiments, a target protein species is a monomeric form of a particular protein (e.g., a monoclonal antibody) and the method comprises: at step (c), determining, over time, values of (i) a concentration of the monomeric form of the particular protein and / or (ii) a cumulative purity [e.g., a relative fraction (e.g., mass) of the monomeric form of the particular protein collected relative to total protein collected] of the monomeric form of the particular protein within a total collected volume of sample exiting from the purification unit; and at step (d), stopping collection of aqueous sample exiting from the - 35 - 11677372v1Attorney Docket No. 2017297-0013purification unit at a particular stop time based at least in part on the values of the concentration and / or cumulative purity of the monomeric form of the particular protein.

[0159] In certain embodiments, an aqueous sample comprises (i) one or more high aggregated forms of the particular protein and / or (ii) one or more fragmented species of the particular protein and wherein step (c) comprises determining concentrations of the one or more aggregated forms and / or concentrations of the one or more fragmented species of the particular protein over time.

[0160] In certain embodiments, an aqueous sample comprises one or more excipients and the method comprises, at step (c): determining, based on the spectral data, values of concentrations and / or quantities of the one or more excipients within the aqueous sample exiting the purification unit at one or more time points; and at step (d), using the determined values of excipient concentrations and / or quantities to control collection of the target fraction of the aqueous sample.

[0161] In some aspects, the present disclosure provides methods for preparing a biologic drug formulation comprising one or more excipients, said provided methods comprising: (a) receiving a solution comprising a purified drug substance comprising a protein species (e.g., a monoclonal antibody); (b) injecting and / or mixing, into the solution of the purified drug substance, one or more excipients, over a period of time, thereby creating an in-process drug substance solution comprising the purified drug substance and the one or more excipients at relative concentrations that vary over the period of time, as the one or more excipients are injected and / or mixed; (c) measuring, via one or more mid-infrared (MIR) analyzer(s), at each of one or more of time points, one or both of: (i) a corresponding mid-IR absorbance spectrum from the in-process drug substance solution; and (ii) a corresponding mid-IR absorbance spectrum from a stock solution comprising at least one of the one or more excipients, thereby measuring one or more mid-IR absorbance spectra; (d) receiving, by a processor of a computing device, spectral data corresponding to the one or more measured mid-IR absorbance spectra; (e) determining, by the processor, for each of at least a portion of the one or more time points, corresponding values of one or more sample quality metrics based on the spectral data, the one or more sample quality metrics comprising a measure / measures of concentration and / or purity of (i) the protein species and / or (ii) at a subset of the one or more excipients; and (f) using the determined values of the one or more sample quality metrics to control the injection and / or mixing of the one or more excipients, - 36 - 11677372v1Attorney Docket No. 2017297-0013thereby obtaining a final drug substance having desired protein and / or excipient content and / or purity.

[0162] In certain embodiments, step (b) comprises using an ultra- filtration / diafiltration (UF / DF) system (e.g., to perform buffer exchange).

[0163] In certain embodiments, a protein species is or comprises a monoclonal antibody.

[0164] In certain embodiments, one or more excipients are or comprise one or more surfactants {e.g., detergents; e.g., wetting and / or solubilizing agents [e.g., Polysorbate 20 (Tween 20), Polysorbate 80 (Tween 80), Poloxamer (Pluronic F68 and F127), Triton X-100, Brij 30, Brij 35, etc.]}.

[0165] In certain embodiments, one or more excipients are or comprise one or more bulking agents {e.g., sugars and / or polyols [e.g., Sucrose, Trehalose, Glucose, Lactose, Sorbitol, Mannitol, Glycerol, etc.]; e.g., amino acids [e.g., Arginine, Aspartic Acid, Glutamic acid, Lysine, Proline, Glycine, Histidine, Methionine, Alanine, etc.]; e.g., polymers and proteins [e.g., Gelatin, PVP, PLGA, PEG, dextran, cyclodextrin and derivatives, starch derivatives, HSA, BSA]}.

[0166] In certain embodiments, one or more MIR analyzer(s) comprise a quantum- cascade laser (QCL)-based mid-IR spectrometer comprising: a QCL-based source, aligned and operable to emit a beam of MIR light [e.g., comprising one or more wavelengths substantially within the MIR spectral range (e.g., ranging from about 5000 cm-1 to about 500 cm-1 (e.g., about 2 to 20 microns))]; one or more sampling optics, aligned to direct and / or allow passage of the beam of MIR light, and / or at least a portion thereof, through and / or into contact with at least a portion of the stock solution and / or a portion of the in-process drug substance solution [e.g., wherein the beam of MIR light contacts the portion of the stock solution and / or the portion of the in-process drug substance solution via reflection at an interface between a solid material (e.g., an ATR crystal and / or optical fiber) and the portion of the stock solution and / or the portion of the in-process drug substance solution (e.g., wherein the beam of MIR light undergoes total internal reflection, and contacts / probes the portion of the stock solution and / or the portion of the in-process drug substance solution via an evanescent wave extending into the aqueous sample)] and, following passage through or contact with the portion of the stock solution and / or the portion of the in-process drug substance solution, towards one or more detectors; and the one or more detectors, aligned and - 37 - 11677372v1Attorney Docket No. 2017297-0013operable to detect the beam of MIR light following its passage through and / or contact with the portion of the stock solution and / or the portion of the in-process drug substance solution.

[0167] In certain embodiments, one or more sampling optics comprise a flow cell comprising a detection channel through which the portion of the stock solution and / or the portion of the in-process drug substance solution flow; and one or more detectors are aligned and operable to detect the beam of MIR light exiting from, following its transmission through, the detection channel.

[0168] In certain embodiments, a QCL-based source is a tunable QCL operable sweep an emission frequency of the beam of MIR light through a plurality of frequencies across a scan range (e.g., wherein the scan range comprises a range from about 1700 cm-1 to 1400 cm-1; e.g., wherein the scan range comprises a range from 1300 cm-1 to 1050 cm-1; e.g., wherein the scan range comprises a range from at least 1200 cm-1 to 1000 cm-1) and the method comprises, at each of the one or more time points: sweeping the emission frequency of the beam MIR light across the scan range of the tunable laser, thereby illuminating the portion of the stock solution and / or the portion of the in-process drug substance solution with a plurality of emission frequencies; and detecting, with the one or more detectors, the beam of MIR light (e.g., having been (i) internally reflected by an interface between the high-index material and the portion of the stock solution and / or the portion of the in-process drug substance solution and / or (ii) transmitted through the detection channel through which the portion of the stock solution and / or the portion of the in-process drug substance solution flows) at each of the plurality of emission frequencies, thereby measuring, as the corresponding infrared (IR) absorbance signal from the portion of the stock solution and / or the portion of the in-process drug substance solution, a corresponding IR spectrum comprising a plurality of values, each associated with and representing and / or based on a detected power at a particular one of the plurality of emission frequencies.

[0169] In certain embodiments, a MIR analyzer is an on-line sensor (e.g., as opposed to an off-line or at-line sensor) and wherein step (c) comprises repeatedly measuring IR absorbance spectra over time {e.g., every 20s or less [e.g., every 10s or less (e.g., every 5s or less; (e.g., every second or less))]}, as one or more excipients are injected and / or mixed (e.g., thereby measuring IR absorbance spectra from the in-process drug substance solution in substantially real time). - 38 - 11677372v1Attorney Docket No. 2017297-0013

[0170] In certain embodiments, spectral data comprises, for each of the one or more time points, a corresponding Amide band spectrum [e.g., the Amide band spectrum comprising, for each particular wavelength of a plurality of sampled (e.g., emission) wavelengths within a range from about 1800 to about 800 cm-1 (e.g., with a range from about 1700 to 1400 cm-1), an associated absorption value representing a level of absorption, by a portion of the aqueous sample, at the particular wavelength]. In certain embodiments, spectral data comprises, for each of the one or more time points, a corresponding sugar band spectrum [e.g., the sugar band spectrum comprising, for each particular wavelength of a plurality of sampled (e.g., emission) wavelengths within a range from about 1400 to about 800 cm-1 (e.g., with a range from about 1200 to 1000 cm-1), an associated absorption value representing a level of absorption, by a portion of the aqueous sample, at the particular wavelength].

[0171] In certain embodiments, step (e) comprises: receiving (e.g., and or accessing), by the processor, a reference spectrum for the protein species, said reference having been measured from a particular corresponding reference sample comprising the protein species substantially in isolation and / or at high purity [e.g., 75% purity or better (e.g., 90% purity or better (e.g., 95% purity or better))]; and repeatedly, at each of the plurality of time points, using the reference spectrum to determine a concentration of the protein species within the in- process drug substance solution at each time point, thereby tracking a concentration of the protein species over time.

[0172] In certain embodiments, step (e) comprises: receiving (e.g., and or accessing), by the processor, one or more excipient reference spectra, each associated with a particular excipient of interest (of the one or more excipients) and having been measured from particular corresponding reference sample comprising the particular excipient of interest substantially in isolation and / or at high purity [e.g., 75% purity or better (e.g., 90% purity or better (e.g., 95% purity or better))]; and repeatedly, at each of the plurality of time points, using the one or more excipient reference spectra reference spectrum to determine a concentration of each of the one or more excipients of interest within the stock solution and / or in-process drug substance solution.

[0173] In certain embodiments, step (f) comprises causing, by the processor, transmission of one or more trigger signals (e.g., voltages) to a controller unit (e.g., of a UF / DF system; e.g., of one or more valves). - 39 - 11677372v1Attorney Docket No. 2017297-0013

[0174] In certain embodiments, step (f) comprises one or both of: initiating, by the controller unit, injection and / or mixing of the one or more excipients [e.g., wherein a particular one of the one or more trigger signals is an analog signal and the controller unit initiates the injection and / or mixing based on an amplitude of the analog signal (e.g., when it exceeds a particular threshold; e.g., when it drops below a particular threshold); e.g., wherein a particular one of the one or more trigger signals is a digital signal that triggers (e.g., by transitioning from a 0 voltage level to 1 voltage level or vice-a-versa) initiating the injection and / or mixing] and stopping, by the controller unit, based the one or more trigger signals, injection and / or mixing of the one or more excipients [e.g., wherein a particular one of the one or more trigger signals is an analog signal and the controller unit stops injection and / or mixing of the one or more excipients based on an amplitude of the analog signal (e.g., when it exceeds a particular threshold; e.g., when it drops below a particular threshold); e.g., wherein a particular one of the one or more trigger signals is a digital signal that triggers (e.g., by transitioning from a 0 voltage level to 1 voltage level or vice-a-versa) stopping injection and / or mixing of the one or more excipients].

[0175] In some aspects, the present disclosure provides systems for obtaining a purified sample of a target protein species via mid-infrared (IR) spectroscopy-based bioprocess monitoring and control, said provided systems comprising: one or more mid- infrared (MIR) analyzer(s) [e.g., each operable to (e.g., based on one or more signals / communication with a processor) measure, at each of a plurality of time points, a corresponding mid-IR absorbance spectrum from an aqueous sample exiting from a purification unit, the aqueous sample comprising one or more protein species including the target protein species, thereby measuring a plurality of mid-IR absorbance spectra over time]; a processor of a computing device; and memory having instructions stored thereon, wherein the instructions, when executed by the processor, cause the processor to: (a) receive spectral data corresponding to a plurality of measured mid-IR absorbance spectra, each having been measured, by the one or more MIR analyzers at a corresponding one of a plurality of time points, from an aqueous sample exiting from a purification unit, the aqueous sample comprising one or more protein species including the target protein species; (b) determine for each of at least a portion of the plurality of time points, corresponding values of one or more sample quality metrics based on the spectral data, the one or more sample quality metrics comprising a measure of concentration and / or purity of the target protein species in the aqueous sample; and (c) use the determined values of the one or more sample quality metrics - 40 - 11677372v1Attorney Docket No. 2017297-0013to control collection of a target fraction of the aqueous sample (e.g., during a particular collection window), thereby obtaining the purified sample of the target protein species.

[0176] In some embodiments, the present disclosure provides systems for preparing a biologic drug formulation comprising one or more excipients, said provided systems comprising: one or more mid-infrared (MIR) analyzer(s); a processor of a computing device; and memory having instructions stored thereon, wherein the instructions, when executed by the processor, cause the processor to: (a) receiving spectral data corresponding to one or more mid-IR absorbance spectra having been measured, via the one or more MIR analyzer(s) at each of one or more time points, from one or both of: (i) an in-process drug substance solution comprising a purified drug substance and one or more excipients being injected and / or mixed therein / therewith, over time; and (ii) a stock solution comprising at least one of the one or more excipients; (b) determine for each of at least a portion of the one or more time points, corresponding values of one or more sample quality metrics based on the spectral data, the one or more sample quality metrics comprising a measure / measures of concentration and / or purity of (i) the protein species and / or (ii) at a subset of the one or more excipients; and (c) use the determined values of the one or more sample quality metrics to control the injection and / or mixing of the one or more excipients, thereby obtaining a final drug substance having desired protein and / or excipient content and / or purity.

[0177] Features of embodiments described with respect to one aspect of the present disclosure may be applied with respect to another aspect of the present disclosure. BRIEF DESCRIPTION OF THE DRAWING

[0178] The foregoing and other objects, aspects, features, and advantages of the present disclosure will become more apparent and better understood by referring to the following description taken in conjunction with the accompanying drawings, in which:

[0179] FIG.1A is a graph showing an absorption spectrum of biological material, according to an illustrative embodiment.

[0180] FIG.1B is a schematic illustrating certain vibrational modes, according to an illustrative embodiment.

[0181] FIG.2 is a graph and a schematic showing nucleic acid absorption in the mid- IR, according to an illustrative embodiment. - 41 - 11677372v1Attorney Docket No. 2017297-0013

[0182] FIG.3 is a schematic showing protein amide-band vibrations and relation to secondary structure conformation, according to an illustrative embodiment.

[0183] FIG.4 is a diagram comparing mid-IR absorption spectroscopy with UV absorption, according to an illustrative embodiment.

[0184] FIG.5 shows two graphs of UV absorption, according to an illustrative embodiment.

[0185] FIG.6A is a schematic of an FT-IR spectrometer, according to an illustrative embodiment.

[0186] FIG.6B is a schematic of a tunable QCL-based spectrometer, according to an illustrative embodiment.

[0187] FIG.6C is a schematic illustrating operation of a FT-IR spectrometer and a tunable-QCL spectrometer, according to an illustrative embodiment.

[0188] FIG.6D is a schematic illustrating operation of a FT-IR spectrometer and a tunable-QCL spectrometer, according to an illustrative embodiment.

[0189] FIG.6E is a schematic illustrating operation of a FT-IR spectrometer and a tunable-QCL spectrometer, according to an illustrative embodiment.

[0190] FIG.6F is a schematic illustrating operation of a FT-IR spectrometer and a tunable-QCL spectrometer, according to an illustrative embodiment.

[0191] FIG.7 is a graph showing spectral brightness of certain mid-IR sources, according to an illustrative embodiment.

[0192] FIG.8 is a graph showing water absorption in the mid-IR, according to an illustrative embodiment.

[0193] FIG.9A is a schematic of a tunable QCL-based spectrometer, according to an illustrative embodiment.

[0194] FIG.9B is a schematic illustrating tuning ranges of two QCL-based spectrometers, according to an illustrative embodiment.

[0195] FIG.10A is a schematic illustrating certain steps and mathematical treatments used to obtain absorbance spectra of analytes present in a mobile phase, according to one or more illustrative embodiments. - 42 - 11677372v1Attorney Docket No. 2017297-0013

[0196] FIG.10B is a schematic illustrating certain steps and mathematical treatments used to obtain absorbance spectra of analytes present in a mobile phase, according to one or more illustrative embodiments.

[0197] FIG.10C is a schematic illustrating certain steps and mathematical treatments used to obtain absorbance spectra of analytes present in a mobile phase, according to one or more illustrative embodiments.

[0198] FIG.10D is a schematic illustrating certain steps and mathematical treatments used to obtain absorbance spectra of analytes present in a mobile phase, according to one or more illustrative embodiments.

[0199] FIG.10E is a schematic illustrating certain steps and mathematical treatments used to obtain absorbance spectra of analytes present in a mobile phase, according to one or more illustrative embodiments.

[0200] FIG.10F is a schematic illustrating certain steps and mathematical treatments used to obtain absorbance spectra of analytes present in a mobile phase, according to one or more illustrative embodiments.

[0201] FIG.10G is a schematic illustrating certain steps and mathematical treatments used to obtain absorbance spectra of analytes present in a mobile phase, according to one or more illustrative embodiments.

[0202] FIG.10H is a schematic illustrating certain steps and mathematical treatments used to obtain absorbance spectra of analytes present in a mobile phase, according to one or more illustrative embodiments.

[0203] FIG.11 is an illustrative graph of three IR absorbance spectra showing absorbance of a protein-nucleic acid mixture, along with individual protein and nucleic acid component spectra, according to an illustrative embodiment.

[0204] FIG.12 is a plot of a IR absorbance spectra measured from a high-quality viral vector sample (e.g., having a high fraction of full capsids) and lower quality viral vector sample (e.g., comprising a large fraction of empty capsids), shown along with a difference spectrum, according to an illustrative embodiment.

[0205] FIG.13 is a schematic showing use of an example mid-IR spectrometer for measurements at various stages and with various production units in a biologic manufacturing process, according to an illustrative embodiment. - 43 - 11677372v1Attorney Docket No. 2017297-0013

[0206] FIG.14 is a schematic showing an empty adeno-associated virus (AAV) capsid along with one (AAV capsid) loaded with a genetic cassette, according to an illustrative embodiment.

[0207] FIG.15 is a block flow diagram of an example process for using IR absorption data measured from a viral vector sample to determine sample quality metrics and / or control bioproduction processes, according to an illustrative embodiment.

[0208] FIG.16A is a diagram showing steps in an AAV vector manufacturing process, according to an illustrative embodiment.

[0209] FIG.16B is a diagram showing steps in a lentiviral vector manufacturing process, according to an illustrative embodiment.

[0210] FIG.17 is a block flow diagram of an example process for using a reference spectrum to determine sample quality metrics and / or control bioproduction processes, according to an illustrative embodiment.

[0211] FIG.18 is a block diagram of an exemplary cloud computing environment, used in certain embodiments.

[0212] FIG.19 is a block diagram of an example computing device and an example mobile computing device, used in certain embodiments.

[0213] FIG.20A is a graph showing measurement of bovine serum albumin (BSA) with mid-IR spectroscopy, according to an illustrative embodiment.

[0214] FIG.20B is a graph showing measurement of bovine serum albumin (BSA) with mid-IR spectroscopy, according to an illustrative embodiment.

[0215] FIG.20C is a graph showing measurement of bovine serum albumin (BSA) with mid-IR spectroscopy, according to an illustrative embodiment.

[0216] FIG.20D is a graph showing measurement of bovine serum albumin (BSA) with mid-IR spectroscopy, according to an illustrative embodiment.

[0217] FIG.21 is a graph showing use of absorption spectroscopy for chromatography process monitoring, according to an illustrative embodiment.

[0218] FIG.22A is a graph showing use of absorption spectroscopy for chromatography process monitoring, according to an illustrative embodiment. - 44 - 11677372v1Attorney Docket No. 2017297-0013

[0219] FIG.22B is a graph showing use of absorption spectroscopy for chromatography process monitoring, according to an illustrative embodiment.

[0220] FIG.23A is a graph demonstrating use of mid-IR spectroscopy to measure protein secondary structure content, according to an illustrative embodiment.

[0221] FIG.23B is a graph demonstrating use of mid-IR spectroscopy to measure protein secondary structure content, according to an illustrative embodiment.

[0222] FIG.23C is a graph demonstrating use of mid-IR spectroscopy to measure protein secondary structure content, according to an illustrative embodiment.

[0223] FIG.23D is a graph demonstrating use of mid-IR spectroscopy to measure protein secondary structure content, according to an illustrative embodiment.

[0224] FIG.24 is a set of graphs demonstrating use of mid-IR spectroscopy to measure protein secondary structure content, according to an illustrative embodiment.

[0225] FIG.25 illustrates use of mid-IR absorption spectroscopy to compute protein relative density, according to an illustrative embodiment.

[0226] FIG.26A is a graph showing variation in mid-IR baseline with conductivity during elution, according to an illustrative embodiment.

[0227] FIG.26B is a graph showing variation in mid-IR baseline with conductivity during elution, according to an illustrative embodiment.

[0228] FIG.27 is a graph illustrating calculation of certain sample quality metrics described herein, according to certain illustrative embodiments.

[0229] FIG.28A is a graph illustrating calculation of certain sample quality metrics described herein, according to certain illustrative embodiments.

[0230] FIG.28B is a graph illustrating calculation of certain sample quality metrics described herein, according to certain illustrative embodiments.

[0231] FIG.29A is a graph illustrating calculation of certain sample quality metrics described herein, according to certain illustrative embodiments.

[0232] FIG.29B is a graph illustrating calculation of certain sample quality metrics described herein, according to certain illustrative embodiments. - 45 - 11677372v1Attorney Docket No. 2017297-0013

[0233] FIG.30A is a graph illustrating calculation of certain sample quality metrics described herein, according to certain illustrative embodiments.

[0234] FIG.30B is a graph illustrating calculation of certain sample quality metrics described herein, according to certain illustrative embodiments.

[0235] FIG.31 is a graph illustrating calculation of certain sample quality metrics described herein, according to certain illustrative embodiments.

[0236] FIG.32A is a block flow diagraph for a process for control of a production process based on IR absorption spectroscopy, according to an illustrative embodiment.

[0237] FIG.32B is an illustrative sketch showing anticipated (hypothetical) variation in sample quality metrics that measure total protein content and protein aggregation, as described herein, over time, during elution from an IEX chromatography column, according to an illustrative embodiment.

[0238] FIG.33A is a diagram illustrating certain workflows and data processing approaches for performing mid-IR spectroscopic measurements in accordance with various illustrative embodiments.

[0239] FIG.33B is a diagram illustrating certain workflows and data processing approaches for performing mid-IR spectroscopic measurements in accordance with various illustrative embodiments.

[0240] FIG.33C is a diagram illustrating certain workflows and data processing approaches for performing mid-IR spectroscopic measurements in accordance with various illustrative embodiments.

[0241] FIG.34A is a schematic illustrating control of elution, according to an illustrative embodiment.

[0242] FIG.34B is a schematic illustrating control of elution, according to an illustrative embodiment.

[0243] FIG.35 is a set of graphs demonstrating protein secondary structure monitoring during TFF injections, according to an illustrative embodiment.

[0244] FIG.36 is a graph showing spectral coverage of a QCL system, according to an illustrative embodiment. - 46 - 11677372v1Attorney Docket No. 2017297-0013

[0245] FIG.37 is a graph demonstrating sensitivity improvements in a mid-IR QCL system.

[0246] FIG.38A is a graph showing measurement of multiple analytes, according to an illustrative embodiment.

[0247] FIG.38B is a graph showing measurement of multiple analytes, according to an illustrative embodiment.

[0248] FIG.39A is a graph showing measurement of multiple analytes, according to an illustrative embodiment.

[0249] FIG.39B is a graph showing measurement of multiple analytes, according to an illustrative embodiment.

[0250] FIG.40A is a graph showing measurement of multiple analytes, according to an illustrative embodiment.

[0251] FIG.40B is a graph showing measurement of multiple analytes, according to an illustrative embodiment.

[0252] FIG.41A is a graph showing protein secondary structure measurements, according to an illustrative embodiment.

[0253] FIG.41B is a graph showing protein secondary structure measurements, according to an illustrative embodiment.

[0254] FIG.41C is a graph showing protein secondary structure measurements, according to an illustrative embodiment.

[0255] FIG.42 is a graph showing protein secondary structure measurements, according to an illustrative embodiment.

[0256] FIG.43A is a graph showing protein secondary structure measurements, according to an illustrative embodiment.

[0257] FIG.43B is a graph showing protein secondary structure measurements, according to an illustrative embodiment.

[0258] FIG.44 is a schematic of an example system comprising multiple mid-IR analyzers and an external computer, according to an illustrative embodiment. - 47 - 11677372v1Attorney Docket No. 2017297-0013

[0259] FIG.45A is a graph plotting results of certain tests of reproducibility, according to an illustrative embodiment.

[0260] FIG.45B is a graph plotting results of certain tests of reproducibility, according to an illustrative embodiment.

[0261] FIG.45C is a graph plotting results of certain tests of reproducibility, according to an illustrative embodiment.

[0262] FIG.45D is a graph plotting results of certain tests of reproducibility, according to an illustrative embodiment.

[0263] FIG.45E is a graph plotting results of certain tests of reproducibility, according to an illustrative embodiment.

[0264] FIG.46A is a graph showing IR absorbance spectra for a DNA and a protein (BSA) solution, according to an illustrative embodiment.

[0265] FIG.46B is a graph showing IR absorbance spectra for various DNA-protein mixtures, according to an illustrative embodiment.

[0266] FIG.46C is a diagram showing molecular structure of nucleotide bases.

[0267] FIG.46D is a plot of three IR absorbance spectra showing absorbance of a protein-nucleic acid mixture, along with individual protein and nucleic acid component spectra, according to an illustrative embodiment

[0268] FIG.47A is a graph of IR absorbance spectra measured for a sample comprising a monoclonal antibody at various concentrations, according to an illustrative embodiment.

[0269] FIG.47B is a graph of IR absorbance spectra measured for a sample comprising a monoclonal antibody at various concentrations, according to an illustrative embodiment.

[0270] FIG.48 is a graph showing an absorbance-based chromatogram along with variation in a normalized spectral difference signal over time, according to an illustrative embodiment.

[0271] FIG.49 shows a set of graphs showing an absorbance-based chromatogram along with variation in different versions of normalized spectral difference signal over time, according to an illustrative embodiment. - 48 - 11677372v1Attorney Docket No. 2017297-0013

[0272] FIG.50A is a schematic illustrating a system for protein purification, according to an illustrative embodiment.

[0273] FIG.50B is a block flow diagram of a process for monitoring protein purification via mid-IR spectroscopy, according to an illustrative embodiment.

[0274] FIG.50C is a block flow diagram of a process for determining component concentrations and / or sample quality metrics from measured IR spectra, according to an illustrative embodiment.

[0275] FIG.51A is a graph of three reference spectra, according to an illustrative embodiment.

[0276] FIG.51B is a graph of simulated variation in integrated absorbance over time over the course of an ion exchange column run, according to an illustrative embodiment.

[0277] FIG.51C is a graph showing extracted protein components from a simulated experiment, according to an illustrative embodiment.

[0278] FIG.51D is a graph showing variation in purity and yield determined from a simulated chromatography run, according to an illustrative embodiment.

[0279] FIG.51E is a set of three graphs showing (i) extracted protein components, (ii) integrated absorbance, and (iii) purity and yield as determined for a simulated chromatography run, according to an illustrative embodiment.

[0280] FIG.51F is a set of three graphs showing (i) extracted protein components, (ii) integrated absorbance, and (iii) purity and yield as determined for a simulated chromatography run, according to an illustrative embodiment.

[0281] FIG.51G is a set of three graphs showing (i) extracted protein components, (ii) integrated absorbance, and (iii) purity and yield as determined for a simulated chromatography run, according to an illustrative embodiment.

[0282] FIG.51H is a set of three graphs showing (i) extracted protein components, (ii) integrated absorbance, and (iii) purity and yield as determined for a simulated chromatography run, according to an illustrative embodiment.

[0283] FIG.51I is a graph showing integrated absorbance measured over the course of a size exclusion chromatography run, according to an illustrative embodiment. - 49 - 11677372v1Attorney Docket No. 2017297-0013

[0284] FIG.51J is a graph showing extracted dimer, monomer, and mixed dimer / monomer spectra, according to an illustrative embodiment.

[0285] FIG.51K is a graph showing a fragment reference spectrum, according to an illustrative embodiment.

[0286] FIG.52A is a graph showing mid-IR spectra of certain buffers.

[0287] FIG.52B is a graph showing mid-IR spectra of certain sugars.

[0288] FIG.53 is a schematic illustrating UF / DF process monitoring via an inline mid-IR analyzer and an inline UV spectrometer, according to an illustrative embodiment.

[0289] FIG.54A is a graph showing measured BSA concentration over time as determined via mid-IR spectroscopy and UV absorbance.

[0290] FIG.54B is a graph showing sucrose concentration over time as measured via mid-IR spectroscopy and a Cedex assay.

[0291] FIG.55A is a graph showing mid-IR spectra of polysorbate 80 (PS80) in water at various concentrations.

[0292] FIG.55B is a graph showing mid-IR spectra of PS80 spiked into a formulation buffer at various concentrations.

[0293] FIG.56A is a graph showing mid-IR spectra of two sugars.

[0294] FIG.56B is a graph showing mid-IR spectra of two proteins within a sugar absorption band.

[0295] FIG.57A is a graph showing mid-IR spectra of a high molecular weight form of a monoclonal antibody spiked into a pure monomer solution at varying concentrations.

[0296] FIG.57B is a graph showing detail around the amide band region for the spectra shown in FIG.57A.

[0297] FIG.57C is a graph comparing an IR peak metric correlation with monomer purity as measured by size exclusion chromatograph.

[0298] Features and advantages of the present disclosure will become more apparent from the detailed description of certain embodiments that is set forth below, particularly when taken in conjunction with the figures, in which like reference characters identify - 50 - 11677372v1Attorney Docket No. 2017297-0013corresponding elements throughout. In the figures, like reference numbers generally indicate identical, functionally similar, and / or structurally similar elements. CERTAIN DEFINITIONS

[0299] In order for the present disclosure to be more readily understood, certain terms are first defined below. Additional definitions for the following terms and other terms are set forth throughout the specification.

[0300] A, an: As used herein, “a” or “an” with reference to a claim feature means “one or more,” or “at least one.”

[0301] Absorption data, absorption spectra, absorbance data, absorbance spectra: As used herein, the terms “absorption data”, “absorption spectra”, “absorbance data”, “absorbance spectra” as in, e.g., “IR absorption data”, “IR absorption spectra”, “IR absorbance data”, “IR absorbance spectra”, etc., are used to refer to data, such as spectral data, that represents signal produced by and / or indicative of optical absorption by a sample, whether the data and / or underlying signal is obtained via a transmission measurement, an attenuated total internal (ATR) measurement, a reflection measurement, or other measurement. The use of the terms “absorption” and “absorbance” are not intended to be limiting with respect to a particular sampling / measurement geometry, manner of display and / or representation, or unit system. For example, an absorption spectrum may be represented as a transmission spectrum, in which absorption bands appear as negative peaks, or as an absorption spectrum, in which absorption peaks are positive, pointing upwards. An absorption spectrum may be represented in linear units or logarithmic units. While the term “absorbance” is, in certain cases, used in IR spectroscopy to refer to a unit that is directly proportional to concentration and path length (e.g., a logarithm of transmittance), its use herein is not intended to limit any method, system, processing approach, computation, etc. to being performed in any particular unit system.

[0302] Administration: As used herein, the term “administration” typically refers to the administration of a composition to a subject or system. Those of ordinary skill in the art will be aware of a variety of routes that may, in appropriate circumstances, be utilized for administration to a subject, for example a human. For example, in some embodiments, administration may be ocular, oral, parenteral, topical, etc. In some particular embodiments, administration may be bronchial (e.g., by bronchial instillation), buccal, dermal (which may - 51 - 11677372v1Attorney Docket No. 2017297-0013be or comprise, for example, one or more of topical to the dermis, intradermal, interdermal, transdermal, etc.), enteral, intra-arterial, intradermal, intragastric, intramedullary, intramuscular, intranasal, intraperitoneal, intrathecal, intravenous, intraventricular, within a specific organ (e.g., intrahepatic), mucosal, nasal, oral, rectal, subcutaneous, sublingual, topical, tracheal (e.g., by intratracheal instillation), vaginal, vitreal, etc. In some embodiments, administration may involve dosing that is intermittent (e.g., a plurality of doses separated in time) and / or periodic (e.g., individual doses separated by a common period of time) dosing. In some embodiments, administration may involve continuous dosing (e.g., perfusion) for at least a selected period of time.

[0303] Affinity: As is known in the art, “affinity” is a measure of the tightness with which two or more binding partners associate with one another. Those skilled in the art are aware of a variety of assays that can be used to assess affinity, and will furthermore be aware of appropriate controls for such assays. In some embodiments, affinity is assessed in a quantitative assay. In some embodiments, affinity is assessed over a plurality of concentrations (e.g., of one binding partner at a time). In some embodiments, affinity is assessed in the presence of one or more potential competitor entities (e.g., that might be present in a relevant – e.g., physiological – setting). In some embodiments, affinity is assessed relative to a reference (e.g., that has a known affinity above a particular threshold [a “positive control” reference] or that has a known affinity below a particular threshold [ a “negative control” reference”]. In some embodiments, affinity may be assessed relative to a contemporaneous reference; in some embodiments, affinity may be assessed relative to a historical reference. Typically, when affinity is assessed relative to a reference, it is assessed under comparable conditions.

[0304] Amino acid: in its broadest sense, as used herein, refers to any compound and / or substance that can be incorporated into a polypeptide chain, e.g., through formation of one or more peptide bonds. In some embodiments, an amino acid has the general structure H2N–C(H)(R)–COOH. In some embodiments, an amino acid is a naturally-occurring amino acid. In some embodiments, an amino acid is a non-natural amino acid; in some embodiments, an amino acid is a D-amino acid; in some embodiments, an amino acid is an L- amino acid. “Standard amino acid” refers to any of the twenty standard L-amino acids commonly found in naturally occurring peptides. “Nonstandard amino acid” refers to any amino acid, other than the standard amino acids, regardless of whether it is prepared synthetically or obtained from a natural source. In some embodiments, an amino acid, - 52 - 11677372v1Attorney Docket No. 2017297-0013including a carboxy- and / or amino-terminal amino acid in a polypeptide, can contain a structural modification as compared with the general structure above. For example, in some embodiments, an amino acid may be modified by methylation, amidation, acetylation, pegylation, glycosylation, phosphorylation, and / or substitution (e.g., of the amino group, the carboxylic acid group, one or more protons, and / or the hydroxyl group) as compared with the general structure. In some embodiments, such modification may, for example, alter the circulating half-life of a polypeptide containing the modified amino acid as compared with one containing an otherwise identical unmodified amino acid. In some embodiments, such modification does not significantly alter a relevant activity of a polypeptide containing the modified amino acid, as compared with one containing an otherwise identical unmodified amino acid. As will be clear from context, in some embodiments, the term “amino acid” may be used to refer to a free amino acid; in some embodiments it may be used to refer to an amino acid residue of a polypeptide.

[0305] Antibody, Antibody polypeptide: As used herein, the terms “antibody polypeptide” or “antibody”, or “antigen-binding fragment thereof”, which may be used interchangeably, refer to polypeptide(s) capable of binding to an epitope. In some embodiments, an antibody polypeptide is a full-length antibody, and in some embodiments, is less than full length but includes at least one binding site (comprising at least one, and preferably at least two sequences with structure of antibody “variable regions”). In some embodiments, the term “antibody polypeptide” encompasses any protein having a binding domain which is homologous or largely homologous to an immunoglobulin-binding domain. In particular embodiments, “antibody polypeptides” encompasses polypeptides having a binding domain that shows at least 99% identity with an immunoglobulin binding domain. In some embodiments, “antibody polypeptide” is any protein having a binding domain that shows at least 70%, 80%, 85%, 90%, or 95% identity with an immuglobulin binding domain, for example a reference immunoglobulin binding domain. An included “antibody polypeptide” may have an amino acid sequence identical to that of an antibody that is found in a natural source. Antibody polypeptides in accordance with the present invention may be prepared by any available means including, for example, isolation from a natural source or antibody library, recombinant production in or with a host system, chemical synthesis, etc., or combinations thereof. An antibody polypeptide may be monoclonal or polyclonal. An antibody polypeptide may be a member of any immunoglobulin class, including any of the human classes: IgG, IgM, IgA, IgD, and IgE. In certain embodiments, an antibody may be a - 53 - 11677372v1Attorney Docket No. 2017297-0013member of the IgG immunoglobulin class. As used herein, the terms “antibody polypeptide” or “characteristic portion of an antibody” are used interchangeably and refer to any derivative of an antibody that possesses the ability to bind to an epitope of interest. In certain embodiments, the “antibody polypeptide” is an antibody fragment that retains at least a significant portion of the full-length antibody’s specific binding ability. Examples of antibody fragments include, but are not limited to, Fab, Fab’, F(ab’)2, scFv, Fv, dsFv diabody, and Fd fragments. Alternatively or additionally, an antibody fragment may comprise multiple chains that are linked together, for example, by disulfide linkages. In some embodiments, an antibody polypeptide may be a human antibody. In some embodiments, the antibody polypeptides may be a humanized. Humanized antibody polypeptides include may be chimeric immunoglobulins, immunoglobulin chains or antibody polypeptides (such as Fv, Fab, Fab', F(ab')2 or other antigen-binding subsequences of antibodies) that contain minimal sequence derived from non-human immunoglobulin. In general, humanized antibodies are human immunoglobulins (recipient antibody) in which residues from a complementary-determining region (CDR) of the recipient are replaced by residues from a CDR of a non-human species (donor antibody) such as mouse, rat or rabbit having the desired specificity, affinity, and capacity.

[0306] Approximately: As used herein, the term “approximately” or “about,” as applied to one or more values of interest, refers to a value that is similar to a stated reference value. In certain embodiments, the term “approximately” or “about” refers to a range of values that fall within 25%, 20%, 19%, 18%, 17%, 16%, 15%, 14%, 13%, 12%, 11%, 10%, 9%, 8%, 7%, 6%, 5%, 4%, 3%, 2%, 1%, or less in either direction (greater than or less than) of the stated reference value unless otherwise stated or otherwise evident from the context (except where such number would exceed 100% of a possible value).

[0307] Backbone, peptide backbone: As used herein, the term “backbone,” for example, as in a backbone or a peptide or polypeptide, refers to the portion of the peptide or polypeptide chain that comprises the links between amino acids of the chain but excludes side chains. In other words, a backbone refers to the part of a peptide or polypeptide that would remain if side chains were removed. In certain embodiments, the backbone is a chain comprising a carboxyl group of one amino acid bound via a peptide bond to an amino group of a next amino acid, and so on. Backbone may also be referred to as “peptide backbone”. It should be understood that, where the term “peptide backbone” is used, it is used for clarity, - 54 - 11677372v1Attorney Docket No. 2017297-0013and is not intended to limit a length of a particular backbone. That is, the term “peptide backbone” may be used to describe a peptide backbone of a peptide and / or a protein.

[0308] Biologic: As used herein, the term “biologic” refers to a composition that is or may be produced by recombinant DNA technologies, chemical synthesis, peptide synthesis, or purified and / or isolated from natural sources (such as human, animal, or microorganisms) and that has a desired biological activity. A biologic can be, for example, a protein, peptide, glycoprotein, polysaccharide, nucleic acid, phospholipids, a mixture of proteins or peptides, a mixture of glycoproteins, a mixture of polysaccharides, a mixture of nucleic acids, a mixture of one or more of a protein, peptide, glycoprotein, polysaccharide or nucleic acid, or a derivatized form and / or an assembly of any of the foregoing entities. In certain embodiments, biologics may be or comprise living entities, such as cells or tissues. Molecular weight of biologics can vary widely, from about 1000 Da for small peptides such as peptide hormones to one thousand kDa or more for complex polysaccharides, mucins, and other heavily glycosylated proteins. Examples of biologics include, without limitation vaccines, blood and blood components, allergenics, somatic cells, gene therapy, tissues, and recombinant therapeutic proteins. In certain embodiments, a biologic is a drug used for treatment of diseases and / or medical conditions. Examples of biologic drugs include, without limitation, native or engineered antibodies or antigen binding fragments thereof, and antibody-drug conjugates, which comprise an antibody or antigen binding fragments thereof conjugated directly or indirectly (e.g., via a linker) to a drug of interest, such as a cytotoxic drug or toxin. In certain embodiments, biologic drugs, such as gene therapy drugs, comprise vectors, such as adeno-associated viral (AAV), adenoviral, lentiviral, and retroviral vectors, together with (e.g., loaded with) nucleic acid, such as DNA or RNA. In certain embodiments, a biologic is a diagnostic, used to diagnose diseases and / or medical conditions. For example, allergen patch tests utilize biologics (e.g., biologics manufactured from natural substances) that are known to cause contact dermatitis. Diagnostic biologics may also include medical imaging agents, such as proteins that are labelled with agents that provide a detectable signal that facilitates imaging such as fluorescent markers, dyes, radionuclides, and the like.

[0309] In vitro: The term “in vitro” as used herein refers to events that occur in an artificial environment, e.g., in a test tube or reaction vessel, in cell culture, etc., rather than within a multi-cellular organism. - 55 - 11677372v1Attorney Docket No. 2017297-0013

[0310] In vivo: As used herein, the term “in vivo” refers to events that occur within a multi-cellular organism, such as a human and a non-human animal. In the context of cell- based systems, the term may be used to refer to events that occur within a living cell (as opposed to, for example, in vitro systems).

[0311] Peptide: The term “peptide” as used herein refers to a polypeptide that is typically relatively short, for example having a length of less than about 100 amino acids, less than about 50 amino acids, less than about 40 amino acids less than about 30 amino acids, less than about 25 amino acids, less than about 20 amino acids, less than about 15 amino acids, or less than 10 amino acids.

[0312] Polypeptide: As used herein refers to a polymeric chain of amino acids. In some embodiments, a polypeptide has an amino acid sequence that occurs in nature. In some embodiments, a polypeptide has an amino acid sequence that does not occur in nature. In some embodiments, a polypeptide has an amino acid sequence that is engineered in that it is designed and / or produced through action of the hand of man. In some embodiments, a polypeptide may comprise or consist of natural amino acids, non-natural amino acids, or both. In some embodiments, a polypeptide may comprise or consist of only natural amino acids or only non-natural amino acids. In some embodiments, a polypeptide may comprise D-amino acids, L-amino acids, or both. In some embodiments, a polypeptide may comprise only D-amino acids. In some embodiments, a polypeptide may comprise only L-amino acids. In some embodiments, a polypeptide may include one or more pendant groups or other modifications, e.g., modifying or attached to one or more amino acid side chains, at the polypeptide’s N-terminus, at the polypeptide’s C-terminus, or any combination thereof. In some embodiments, such pendant groups or modifications may be selected from the group consisting of acetylation, amidation, lipidation, methylation, pegylation, etc., including combinations thereof. In some embodiments, a polypeptide may be cyclic, and / or may comprise a cyclic portion. In some embodiments, a polypeptide is not cyclic and / or does not comprise any cyclic portion. In some embodiments, a polypeptide is linear. In some embodiments, a polypeptide may be or comprise a stapled polypeptide. In some embodiments, the term “polypeptide” may be appended to a name of a reference polypeptide, activity, or structure; in such instances it is used herein to refer to polypeptides that share the relevant activity or structure and thus can be considered to be members of the same class or family of polypeptides. For each such class, the present specification provides and / or those skilled in the art will be aware of exemplary polypeptides within the class whose amino acid - 56 - 11677372v1Attorney Docket No. 2017297-0013sequences and / or functions are known; in some embodiments, such exemplary polypeptides are reference polypeptides for the polypeptide class or family. In some embodiments, a member of a polypeptide class or family shows significant sequence homology or identity with, shares a common sequence motif (e.g., a characteristic sequence element) with, and / or shares a common activity (in some embodiments at a comparable level or within a designated range) with a reference polypeptide of the class; in some embodiments with all polypeptides within the class). For example, in some embodiments, a member polypeptide shows an overall degree of sequence homology or identity with a reference polypeptide that is at least about 30-40%, and is often greater than about 50%, 60%, 70%, 80%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99% or more and / or includes at least one region (e.g., a conserved region that may in some embodiments be or comprise a characteristic sequence element) that shows very high sequence identity, often greater than 90% or even 95%, 96%, 97%, 98%, or 99%. Such a conserved region usually encompasses at least 3-4 and often up to 20 or more amino acids; in some embodiments, a conserved region encompasses at least one stretch of at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or more contiguous amino acids. In some embodiments, a relevant polypeptide may comprise or consist of a fragment of a parent polypeptide. In some embodiments, a useful polypeptide as may comprise or consist of a plurality of fragments, each of which is found in the same parent polypeptide in a different spatial arrangement relative to one another than is found in the polypeptide of interest (e.g., fragments that are directly linked in the parent may be spatially separated in the polypeptide of interest or vice versa, and / or fragments may be present in a different order in the polypeptide of interest than in the parent), so that the polypeptide of interest is a derivative of its parent polypeptide.

[0313] Protein: As used herein, the term “protein” refers to a polypeptide (i.e., a string of at least two amino acids linked to one another by peptide bonds). Proteins may include moieties other than amino acids (e.g., may be glycoproteins, proteoglycans, etc.) and / or may be otherwise processed or modified. Those of ordinary skill in the art will appreciate that a “protein” can be a complete polypeptide chain as produced by a cell (with or without a signal sequence), or can be a characteristic portion thereof. Those of ordinary skill will appreciate that a protein can sometimes include more than one polypeptide chain, for example linked by one or more disulfide bonds or associated by other means. Polypeptides may contain L-amino acids, D-amino acids, or both and may contain any of a variety of amino acid modifications or analogs known in the art. Useful modifications include, e.g., - 57 - 11677372v1Attorney Docket No. 2017297-0013terminal acetylation, amidation, methylation, etc. In some embodiments, proteins may comprise natural amino acids, non-natural amino acids, synthetic amino acids, and combinations thereof. The term “peptide” is generally used to refer to a polypeptide having a length of less than about 100 amino acids, less than about 50 amino acids, less than 20 amino acids, or less than 10 amino acids. In some embodiments, proteins are antibodies, antibody fragments, biologically active portions thereof, and / or characteristic portions thereof.

[0314] Machine learning module, machine learning model: As used herein, the terms “machine learning module” and “machine learning model” are used interchangeably and refer to a computer implemented process (e.g., a software function) that implements one or more particular machine learning algorithms, such as an artificial neural networks (ANN), convolutional neural networks (CNNs), random forest, decision trees, support vector machines, and the like, in order to determine, for a given input, one or more output values. In some embodiments, machine learning modules implementing machine learning techniques are trained, for example using curated and / or manually annotated datasets. Such training may be used to determine various parameters of machine learning algorithms implemented by a machine learning module, such as weights associated with layers in neural networks. In some embodiments, once a machine learning module is trained, e.g., to accomplish a specific task such as determining various metrics as described herein, values of determined parameters are fixed and the (e.g., unchanging, static) machine learning module is used to process new data (e.g., different from the training data) and accomplish its trained task without further updates to its parameters (e.g., the machine learning module does not receive feedback and / or updates). In some embodiments, machine learning modules may receive feedback, e.g., based on user review of accuracy, and such feedback may be used as additional training data, for example to dynamically update the machine learning module. In some embodiments, a trained machine learning module is a classification algorithm with adjustable and / or fixed (e.g., locked) parameters, e.g., a random forest classifier. In some embodiments, two or more machine learning modules may be combined and implemented as a single module and / or a single software application. In some embodiments, two or more machine learning modules may also be implemented separately, e.g., as separate software applications. A machine learning module may be software and / or hardware. For example, a machine learning module may be implemented entirely as software, or certain functions of a ANN module may be carried out via specialized hardware (e.g., via an application specific integrated circuit (ASIC), field programmable gate arrays (FPGAs), and the like). - 58 - 11677372v1Attorney Docket No. 2017297-0013

[0315] Mid-Infrared, Mid-IR, MIR: As used herein, the terms mid-infrared, mid-IR, and MIR are used interchangeably to refer to the portion of the electromagnetic spectrum ranging from about 5000 cm-1to about 500 cm-1(corresponding to a wavelength range from about 2 μm to about 20 μm) and / or, in certain embodiments, from about 3,000 cm-1to about 800 cm-1(corresponding to wavelengths ranging from about 3 μm to about 12 μm).

[0316] Substantially: As used herein, the term “substantially” refers to the qualitative condition of exhibiting total or near-total extent or degree of a characteristic or property of interest. DETAILED DESCRIPTION

[0317] It is contemplated that systems, architectures, devices, methods, and processes of the present disclosure encompass variations and adaptations developed using information from the embodiments described herein. Adaptation and / or modification of the systems, architectures, devices, methods, and processes described herein may be performed, as contemplated by this description.

[0318] Throughout the description, where architectures, articles, devices, methods, processes, and systems are described as having, including, or comprising specific components, or where processes and methods are described as having, including, or comprising specific steps, it is contemplated that, additionally, there are architectures, articles, devices, and systems of the present invention that consist essentially of, or consist of, the recited components, and that there are processes and methods according to the present invention that consist essentially of, or consist of, the recited processing steps.

[0319] It should be understood that the order of steps or order for performing certain action is immaterial so long as the invention remains operable. Moreover, two or more steps or actions may be conducted simultaneously.

[0320] The mention herein of any publication, for example, in the Background section, is not an admission that the publication serves as prior art with respect to any of the claims presented herein. The Background section is presented for purposes of clarity and is not meant as a description of prior art with respect to any claim. - 59 - 11677372v1Attorney Docket No. 2017297-0013

[0321] Documents are incorporated herein by reference as noted. Where there is any discrepancy in the meaning of a particular term, the meaning provided in the Definition section above is controlling.

[0322] Headers are provided for the convenience of the reader – the presence and / or placement of a header is not intended to limit the scope of the subject matter described herein.

[0323] Described herein are methods and systems for monitoring and controlling performance and operation of production units at various stages during biologic manufacturing processes. In certain embodiments, biologic production monitoring and / or control technologies described herein utilize mid-infrared (MIR) analyzers to measure infrared (IR) absorption signals from liquid samples and generate IR absorption data, such as IR spectra, in substantially real-time. Liquid samples measured in this manner may serve as inputs to and / or outputs of one or more production units used in manufacture of biologics.

[0324] As described in further detail herein, mid-IR spectroscopy provides a powerful non-destructive and label-free analytical technique that facilitates rapid and accurate identification and characterization of liquid samples comprising biological material. In certain embodiments, IR spectral data is used by biologic production monitoring and control technologies described herein to determine sample quality metrics that provide, among other things, measures of sample characteristics such as content of one or more desired target molecules, presence of impurities, molecular structural information, and the like. One or more sample quality attributes (e.g., critical quality attributes) may be monitored in real-time, and used, individually and / or in combination with each other and / or data from other sensors, to control and / or refine operation of one or more production units, thereby facilitating compliance with demanding quality tolerances, which may be required by regulation and / or produce increasingly effective and / or safe product, scaling up production capacity, improving efficiency, and the like. A. Mid-Infrared (MIR) Spectroscopy

[0325] Turning to FIG.1A, mid-IR spectroscopy can be used to obtain detailed information about vibrational transitions of biological molecules, such as carbohydrates, lipids, nucleic acids, proteins, and the like. As illustrated in FIG.1B, mid-IR spectroscopy - 60 - 11677372v1Attorney Docket No. 2017297-0013measures IR absorption signals resulting from vibrational modes of molecules. When a molecule is illuminated with mid-IR light (comprising a range of MIR frequencies / wavelengths), it may absorb that light to varying degrees at various frequencies / wavelengths. Molecules have characteristic sets of vibrational modes, which are dependent, among other things, on their molecular structure as well as local environment. Accordingly, as shown in FIG.1A, various molecules, such as lipids, proteins, nucleic acids, carbohydrates, and the like, absorb light within (one or more) characteristic bands. Absorption at these characteristic bands may be observed, for example, as a series of peaks in an IR absorption spectrum. As described in further detail herein, features of these peaks, such as their amplitude, linewidth, center frequenc(ies), area, etc., can be used to determine metrics that measure sample properties such as total protein content, molecular identity and / or heterogeneity, etc. A.i Mid-IR Spectral Bands

[0326] In certain embodiments, one or more mid-IR spectral bands are associated with nucleic acid molecules. For example, as shown in FIG.2, one or more peaks in a mid- IR spectrum may be associated with a antisymmetric PO4 stretch and / or an symmetric PO4 stretch bands, which, for the sample shown in FIG.2, present at around 1220 - 1250 cm-1and 1075 – 1100 cm-1, respectively and, accordingly, used to detect presence of and / or characterize nucleic acid, such as DNA and / or RNA, within a sample. As described in further detail herein, an IR absorption band associated with an antisymmetric PO4 stretch vibrational mode may occur / range from about 1150 cm-1to about 1250 cm-1(e.g., ranging from about 1175 cm-1to about 1250 cm-1; e.g., ranging from about 1200 cm-1to about 1250 cm-1; e.g., ranging from about 1210 cm-1to about 1230 cm-1). IR absorption associated with a symmetric PO4 stretch vibrational mode may occur / range from about 1000 cm-1to about 1100 cm-1(e.g., ranging from about 1050 cm-1to about 1100 cm-1; e.g., ranging from about 1075 cm-1to about 1100 cm-1; e.g., ranging from about 1075 cm-1to about 1085 cm-1). As shown in FIG.2, in certain embodiments, features such as central frequencies, shapes, individual and / or relative amplitudes, of peaks associated with these two (symmetric and antisymmetric) PO4stretch bands may be used to characterize a type and / or particular conformation of nucleic acid molecules. FIG.2, for example, shows variations in these spectral peaks for several nucleic acid molecules, including single-stranded and double stranded DNA and RNA. - 61 - 11677372v1Attorney Docket No. 2017297-0013

[0327] In certain embodiments, one or more mid-IR spectral bands may be associated with, and used to evaluate properties of, proteins. For example, as illustrated in FIG.1A, Amide I and Amide II bands may be associated with spectral peaks within a range from about 1500 to about 1700 cm-1and may be used to detect and / or characterize protein content and / or structure within a sample. For example, without wishing to be bound to any particular theory, Amide-I and Amide-II bands are believed to correspond to vibrational modes associated with protein peptide backbone atoms. Accordingly, in certain embodiments, presence and strength of these (Amide-I and Amide-II) bands can be used to determine presence and / or content of protein in a sample. In certain embodiments, additionally or alternatively, other bands associated with protein (e.g., backbone) vibrations, such as an Amide-III band, which ranges from about 1250 cm-1to about 1350 cm-1, may be used to determine presence and / or content of protein in a sample.

[0328] Additionally or alternatively, in certain embodiments, Amide-I band measurements may be used to characterize secondary structure and / or changes therein of one or more proteins in a sample. For example, without wishing to be bound to any particular theory, it is believed that an Amide I band originates from molecular vibrations in a protein peptide backbone (C=O stretching vibration) and is sensitive to protein secondary structure (e.g., conformation). For example, as shown in FIG.3, protein secondary structure motifs such as a random coil, alpha-helix, and beta-sheet each produce characteristic Amide-I absorption peaks, with characteristic center frequencies, linewidths, and splitting.

[0329] With respect to protein measurements, in certain embodiments, mid-IR spectroscopy techniques offer several advantages over ultraviolet (UV) absorption measurements. Turning to FIGs.4 and 5, among other things, UV absorption measures absorption at or near 280 nm, which originates from three particular amino acids – Tyrosine (Tyr), Tryptophan (Trp), and Phenylalanine (Phe). Accordingly, not all amino acids of a protein produce measurable UV absorption signal. In contrast, all amino acids (side chains and / or peptide bonds linking them) may contribute to detectable absorption in the IR, that can be measured via mid-IR spectroscopy. For example, Amide-I, Amide-II, and Amide-III absorption features are associated with vibrational modes of protein backbone atoms and, accordingly, are produced by all proteins and scale (in strength – i.e., level of absorption) roughly with amino acid count. Without wishing to be bound to any particular theory, the Amide-I band is believed to result (primarily) from C=O bond vibrations, and the Amide-II and III are believed to result from (out of phase and in phase combinations, respectively, of) - 62 - 11677372v1Attorney Docket No. 2017297-0013NH and CN bond vibrations. Accordingly, mid-IR-based measurements are not restricted to particular molecular weights and / or types of proteins. Moreover, UV absorption suffers from poor linearity and cannot be used to assess (e.g., de-convolve) heterogeneity of a protein mixture. As described and demonstrated herein, mid-IR absorption spectroscopy can, among other things, be used to measure total protein concentration as well as, additionally or alternatively, to quantify heterogeneity of protein mixtures, thereby offering functionality and insight into protein samples that is not achievable with UV absorption measurements. A.ii Mid-IR Analyzers

[0330] In certain embodiments, production monitoring and / or control technologies described herein utilize one or more MIR analyzer(s) to measure infrared (IR) absorbance signal from a sample mixture and produce IR absorbance data that can, for example, be analyzed to identify and / or characterize spectral peaks and / or peak features thereof that are associated with characteristic molecular absorption bands. Mid-IR analyzers may be or comprise systems that comprise one or more components such as mid-IR light sources, detectors, and associated optics, such as (but not limited to) sampling optics to direct light to and / or from a sample in a particular fashion, in order to interrogate it via a particular sampling geometry. MIR Light Sources

[0331] In certain embodiments, a MIR analyzer comprises one or more MIR light sources, operable to emit MIR light. For example, in certain embodiments, a MIR light source is or comprises a thermal source that emits light comprising a broad range of wavelengths, having a spectral profile corresponding approximately to a blackbody spectrum at a particular temperature, selected, for example, to place a substantial fraction of its emitted power within the MIR.

[0332] In certain embodiments, one or more light sources of a MIR analyzer comprise one or more lasers, which emit light at substantially a single frequency (e.g., within a narrow frequency band about a central wavelength) within the MIR. A MIR laser may be a tunable laser, such that its emission frequency can be tuned over a particular spectral range. Examples of tunable MIR lasers include, but are not limited to, quantum cascade lasers (QCLs). Other laser-based sources may include, without limitation, Interband Cascade - 63 - 11677372v1Attorney Docket No. 2017297-0013Lasers (ICLs), difference-frequency generation-based sources, frequency combs (e.g., dual comb sources), etc. As described in further detail herein, tunable QCL-based sources offer various advantageous features such as high spectral brightness and flexible tuning ranges within key spectral windows in the mid-IR. Spectral Measurements

[0333] In certain embodiments, a MIR analyzer may measure IR absorption signals at a plurality of wavelengths and / or times in order to create IR spectral data, which provides a measure of detected signal and / or absorbance at a plurality of wavelengths within a particular spectral range. FIGs.6A-F illustrate and compare two approaches for performing IR spectral measurements. One approach is an interferometric technique, referred to as Fourier Transform Infrared (FT-IR) spectroscopy. As shown in FIG.6A, FT-IR spectroscopy uses a split-beam interferometer with a moving mirror to record an interference pattern as a function of temporal delay between two beams. An interference pattern obtained in this manner may then be Fourier Transformed to obtain an IR spectrum. As shown in FIGs.6C and 6E, FT-IR spectroscopy simultaneously illuminates a sample at a plurality of frequencies and, accordingly, is typically used with broadband incoherent sources, such as thermal sources described herein.

[0334] In certain embodiments, a MIR analyzer uses a spectral scanning technique to record an IR spectrum. As illustrated in FIG.6B, a spectral scanning approach may be implemented using a tunable IR laser, such as a tunable QCL. Turning to FIGs.6D and 6F, a tunable laser emits light within a narrow frequency band, at a substantially single particular emission frequency / wavelength. The emission frequency of a tunable laser may be scanned, to illuminate a sample at plurality of wavelengths, one at a time, within a tuning range of the tunable laser. Signal may then be detected at each of the plurality of wavelengths scanned, to build up an IR spectrum, one wavelength at a time. Certain Advantages of QCL-Based Mid-IR Spectroscopy

[0335] MIR laser sources may offer advantages over thermal sources. Among other things, as shown in FIG. 7, laser sources such as QCLs emit intense beams of MIR light, with spectral brightness (units W×sr-1×m-2×μm-1, e.g., Watts per square-meter per steradian per - 64 - 11677372v1Attorney Docket No. 2017297-0013unit wavelength) several orders of magnitude (about 104– 106- fold) greater than that of a thermal source. FIG.7 shows three QCLs, each having a tuning range of about 2-3 um.

[0336] Turning to FIG.8, in certain embodiments, high spectral brightness provided by laser sources such as QCLs obviates several significant shortcomings that historically have limited application of conventional IR spectroscopy instruments, such as FTIRs, which relied on thermal sources, for measurement of biological samples and processes, particularly in aqueous environments.

[0337] First, as shown in FIG.8, liquid water has two strong and wide absorption bands in the MIR, one of which – a H-O-H bending mode centered at approximately 1638 cm-1– overlaps substantially with Amide-I and Amide II bands used to measure protein content and to characterize structure. As a result, IR measurements in water were limited to extremely short path length flow cells, which are incompatible with in-line monitoring of bioprocess workflows. Second, due to their low brightness, thermal sources typically are used with cryogenically cooled (e.g., with liquid nitrogen) detectors (e.g., MCT detectors) in order to obtain adequate sensitivity. Such cryogenically cooled detectors, however, are cumbersome to operate, have poor linearity, long-term stability, and reproducibility. Third, low spectral brightness thermal sources require long data acquisition times, in order to achieve adequate sensitivity. These (long acquisition times) are incompatible to PAT needs.

[0338] The high spectral brightness offered by MIR laser sources, such as QCLs, overcomes these historical limitations of IR spectroscopy, permitting much longer path- length measurements in water, use of electronically cooled detectors, and rapid acquisition times. Mid-IR Detectors

[0339] In certain embodiments, a MIR analyzer comprises one or more detectors. A variety of detectors, operable to detect light within a MIR range, may be used to detect MIR light, for example as part of a MIR analyzer. A detector may be a single element detector or a multi-element detector, such as a linear array or a focal plane array (FPA). In certain embodiments, a MIR detector is cryogenically cooled, for example via liquid nitrogen. In certain embodiments, a MIR detector is thermoelectrically cooled or uncooled. In certain embodiments, a MIR detector is a quantum detector, such as a mercuric cadmium telluride (MCT) detector. In certain embodiments, a MIR detector is a thermal detector, such as a - 65 - 11677372v1Attorney Docket No. 2017297-0013deuterated, L-alanine doped triglycine sulfate (DLaTGS) or deuterated triglycine sulfate (DTGS) detector. In certain embodiments, a MIR detector is a bolometer or a micro- bolometer.

[0340] In certain embodiments, a MIR analyzer comprises a single detector. In certain embodiments, a MIR analyzer comprises two or more detectors. For example, a MIR analyzer, such as the MIR analyzer shown in FIG.6B, may comprise a sample detector, that detects signal from light having passed through a sample, and a reference detector, that detects signal from a portion of an illumination beam split off (e.g., via a beam-splitter) before the sample. Among other things, a sample detector and a reference detector may be used in this fashion to compensate for laser power fluctuations. Sampling Optics and Geometries

[0341] In certain embodiments, a MIR analyzer comprises sampling optics that are used to direct a beam of MIR light, from a MIR source, on and / or into a particular region of a sample, and then to a detector for detecting signal from the region of the sample. Sampling optics may be used to interrogate a sample in a particular fashion, for example, and without limitation, by providing a transparent window through which a beam of light can pass, by directing light on / into a region of a sample at particular angles, for example via reflective elements such as mirrors and high refractive index materials, and by focusing a beam of light, using lenses or curved (e.g., parabolic) reflectors.

[0342] For example, sampling optics may be used to interrogate a sample using a particular type of sampling geometry, such as a transmission or attenuated total internal reflection (ATR) geometry. In certain embodiments, a transmission geometry uses sampling optics to direct a beam of infrared light along a substantially straight path through a sample, and onto a detector after having passed through the sample. In this manner, a transmission geometry measures absorption of IR light resulting from its propagation through a sample.

[0343] In certain embodiments, an ATR geometry uses sampling optics comprising a high-refractive index material, such as an ATR crystal, a surface of which is in contact with a sample. Sampling optics direct a beam of infrared light into the high-refractive index material, such that it is incident on the surface in contact with the sample at an angle above that required for total-internal-reflection (TIR angle). Light is, accordingly, reflected by the high-refractive index material-sample interface, and back to a detector, probing the sample - 66 - 11677372v1Attorney Docket No. 2017297-0013with an evanescent wave, rather than propagating through it. Penetration depth of the evanescent wave and, accordingly, an effective path-length within a sample can be controlled by varying angle of incidence at the interface between the high-refractive index material and the sample and / or selection of particular materials as the high-refractive index material. In certain embodiments, an ATR geometry uses an ATR crystal having a shape comprising one or more angled surfaces through which light may enter and / or exit the ATR crystal and a flat surface that makes contact with a sample. Examples of high-refractive index materials that can be used for ATR crystals include, but are not limited to, diamond, Germanium (Ge), Silicon (Si), a thallium halide (e.g., such as Thallium bromiodide, also referred to as KRS-5), and Zinc Selenide (ZnSe). In certain embodiments, an ATR crystal is a multi-bounce ATR crystal, that is shaped to cause light to reflect within the crystal multiple times, so as to increase an effective path-length used to probe a sample. In certain embodiments, an ATR crystal is situated at an end of a fiber probe. In certain embodiments, a fiber probe itself may be used as a high-refractive index material to implement an ATR sampling geometry. Examples of high-refractive index materials used for IR fiber probes include, without limitation, chalcogenide class, silver halide, fluoride glass, such as ZBLAN, etc. Flow Cells

[0344] In certain embodiments, a MIR analyzer comprises a flow cell. In accordance with various embodiments, any application-appropriate flow cell may be used. Non-limiting example MIR analyzers with flow cells are described in detail, for example, in U.S. Patent No.10,753,856, Issued August 25, 2020, in U.S. Patent Publication No.2021 / 0405001 A1, published December 30, 2021, and in U.S. Patent No.11,119,079, issued September 14, 2021, the content of each of which is hereby incorporated by reference in its entirety. Example QCL-Based MIR Spectrometer

[0345] A variety of MIR analyzers based on QCL sources are described in detail, for example, in U.S. Patent No.10,753,856, Issued August 25, 2020, in U.S. Patent Publication No.2021 / 0405001 A1, published December 30, 2021, and in U.S. Patent No.11,119,079, issued September 14, 2021, the content of each of which is hereby incorporated by reference in its entirety. - 67 - 11677372v1Attorney Docket No. 2017297-0013

[0346] FIG.9A shows an example QCL-based MIR analyzer for performing absorption measurements in solution. QCL-based MIR analyzer comprises a tunable QCL laser source. As illustrated in inset 904, QCL source is a scanning source that repeatedly sweeps its emission wavelength through a particular tuning range, completing a full spectral scan (i.e., across the entire tuning range) approximately each second. Turning to FIG.9B, different QCL sources may have different tuning windows and, accordingly, may be used to probe different portions of the MIR spectral range.

[0347] For example, as shown in FIG.9B, a commercial QCL-based IR spectrometer – Daylight Solutions’ Culpeo-LA-P – has a spectral window ranging from about 1725 cm-1to about 1375 cm-1, which can, for example, be used to measure Amide bands associated with proteins and, accordingly, can be used for protein detection and characterization. Another QCL (e.g., Daylight Culpeo-LA-S) may have a different spectral scan window, for example from about 1375 cm-1to about 1025 cm-1or from about 1225 cm-1to about 1000 cm-1, which among other things, includes bands associates with sugars, polysaccharides, and nucleic acids. In certain embodiments, multiple QCL sources may be used to cover a desired spectral range. For example, two QCL sources may be combined to cover a range from about 1725 cm-1to about 1025 cm-1. In certain embodiments, two or more QCL sources may be included in a single MIR analyzer, such that they share at least a portion of the sampling optics and / or detectors. In certain embodiments, two separate MIR analyzers, each with a particular QCL having a particular tuning window, may be used to provide a desired spectral coverage.

[0348] A commercial implementation of example QCL-based IR spectrometer offers a variety of performance features advantageous to mid-IR spectroscopy-based measurements of biological production processes. For example, a QCL-based IR spectrometer may allow for quantitative measurements to be performed over a wide dynamic range (e.g., from below 0.1 to above 300 mg / mL; e.g., from about 0.001 to above 300 g / L), in substantially real-time, for example at rates of about 1 Hz. In certain embodiments, a QCL-based IR spectrometer is compatible with flow rates from up to about 10 L / min and / or may probe sample volumes as small as picoliters. In certain embodiments, a QCL-based IR spectrometer is a modular instrument and / or suitable for in-line and / or at-line measurements.

[0349] Table 1 below shows advantages of a QCL-IR spectrometer system in comparison with other techniques for measuring biological production processes: - 68 - 11677372v1Attorney Docket No. 2017297-0013Table 1: Certain Advantages and Challenges of Process Monitoring TechnologiesA.iii Absorbance Data and Pre-Processing

[0350] In certain embodiments, IR absorption signals measured from a sample are combined and / or pre-processed mathematically to create IR absorbance spectra indicative of sample absorbance. For example, FIGs.10A-H illustrate various steps and mathematical treatments used to obtain absorbance spectra of analytes present in a mobile phase. Among other things, as shown in FIG.s 10A-H, one or more reference spectra, indicative of a mobile phase without analyte present, may be measured and divided / subtracted out to yield spectra of analytes present in a sample comprising a mobile phase. B. Real-Time BioProduction Monitoring and Process Control

[0351] In certain embodiments, bioproduction monitoring and / or control technologies described herein leverage analytical technologies – in particular mid-IR spectroscopy as described herein - for the analysis of raw materials, in process monitoring and control, and also final product analysis. In certain embodiments, technologies described herein are implemented as part of a Process Analytical Technologies (PAT) framework, for example utilizing mid-IR spectroscopy as an integrated component within bioprocessing workflow to, among other things, identify sources of variability, monitor and facilitate management (e.g., via system control and feedback) of these sources of variability, and ensure product quality - 69 - 11677372v1Attorney Docket No. 2017297-0013attributes (e.g., critical quality attributes) can be accurately and reliably predicted over the design space established for materials used, process parameters, manufacturing, environmental, and other conditions. Technologies described herein may, for example, be used as a process fingerprinting tool in bioprocess unit operations. In certain embodiments, technologies described herein may, additionally or alternatively, be used e.g., in biopharma forensic labs, to call out counterfeit drugs and biosimilars.

[0352] In certain embodiments, one or more mid-IR analyzers may be used as inline sensors, embedded within process streams, in order to monitor sample quality attributes in substantially real-time. Mid-IR-based monitoring may be used alone and / or in combination with other, other measurement modalities. IR spectral data may be processed via a variety of methods, including methods for determining particular metrics associated with certain absorption bands, as well as, advanced in machine learning techniques. Sample quality metrics may, accordingly, be monitored and / or used to control bioproduction processes. In certain embodiments, automated and / or semi-automated decision support and / or control systems including, for example artificial intelligence (AI)-based systems may be used for process control in real-time and / or refinement. B.i. Mid-IR-Based Monitoring of Sample Quality Metrics Sample Quality Metrics

[0353] In certain embodiments, IR absorption data obtained from liquid samples may be used to determine one or more sample quality metrics that characterize properties of one or more target analytes within a sample. In certain embodiments, a sample quality metric is or comprises a value and / or a set of (multiple) values that characterize one or more properties (e.g., physical, chemical, biological, or microbiological properties) of one or more target analytes in a sample. In certain embodiments, sample quality metrics characterize properties of one or more biological analytes, such as proteins, virus and / or virus-like particles, nucleic acids, and the like. In certain embodiments, a target analyte is a desired species biologic, to be purified and retained, such as a particular protein, viral vector, nucleic acid, or form thereof. In certain embodiments, a target analyte is an undesired impurity, such as a portion of a mixture to be removed. Sample quality metrics may include, but are not limited to, particular attributes that should be within an appropriate limit, range, or distribution to ensure a desired product quality (referred to as “Critical Quality Attributes (CQAs)”). - 70 - 11677372v1Attorney Docket No. 2017297-0013

[0354] A sample quality metric may be a value, such as a numerical value, that provides a measure of content of a particular target analyte, such as a particular molecular species or form thereof, in a sample. A numerical value may, for example, be a direct measurement of physical content, such as a total mass, number, concentration, etc., or may be a value that is proportional, indicates a relative change, or correlates with, physical content of a particular target analyte. In certain embodiments, a sample quality metric may be a metric that is indicative of a particular species or state based on whether its value lies within one or more particular (e.g., pre-specified) ranges and / or above or below one or more threshold values.

[0355] Content of Particular Analytes and / or Subspecies Thereof. In certain embodiments, a sample quality metric is or comprises a measure of content of a particular target analyte, such as concentration, total mass, etc. of one or more target molecules. Sample quality metrics may include, for example, real-time measurements of total protein concentration (e.g., titer), total protein mass, etc. in a sample. Additionally or alternatively, sample quality metrics may include, for example, real-time measurements of total nucleic acid concentration (e.g., titer), total nucleic acid mass, etc., in a sample. In certain embodiments, sample quality metrics include (e.g., real-time) content measures of target analytes such as a total concentration, mass, etc. of one or more of the following: lipids, polysaccharides, etc. In certain embodiments, sample quality metrics include (e.g., real-time) content measures of assemblies of multiple molecules, such as a total concentration (e.g., titer), total mass, number (e.g., discrete number) of viral and / or virus-like particles, such as viral vector assemblies, including, but not limited to, adeno-virus, adeno-associated viruses (AAV), retroviruses (e.g., lentivirus), plant-based viruses (e.g., tobacco mosaic virus), and the like.

[0356] In certain embodiments, a sample quality metric may be or comprise a measure of absolute and / or relative content of particular species or forms of a molecules, for example biomolecules such as proteins, nucleic acids, lipids, polysaccharides, etc. For example, in certain embodiments certain embodiments, one or more sample quality metrics may be or comprise measurements of molecular conformation and / or heterogeneity, such as protein secondary structure, aggregation, identity and relative concentration of various protein species, conjugation (e.g., glycosylation), anti-body drug conjugate ratios, etc.

[0357] For example, in certain embodiments, a sample quality metric may be a measure of absolute or relative content of a particular protein secondary structure motif. For - 71 - 11677372v1Attorney Docket No. 2017297-0013example, as described in further detail herein, IR spectra can be used to identify content of protein secondary structure motifs, such as alpha-helix, beta-sheet, beta-turn, and disordered secondary structures. Accordingly, in certain embodiments, a sample quality metric may be a measure, such as a numerical value that is proportional to or correlates with, content of a particular secondary structure motif. In certain embodiments, a sample quality metric may be a measure of relative content, for example between two secondary structure motifs.

[0358] For example, in certain embodiments, a sample quality metric may be or comprise a measure of absolute and / or relative content of particular forms of proteins resulting from one or more post-translational modifications, such as covalent addition of functional groups or proteins, proteolytic cleavage of regulatory subunits, or degradation of entire proteins, for example phosphorylation, glycosylation, ubiquitination, nitrosylation, lipidation and proteolysis, and the like.

[0359] In certain embodiments, a sample quality metric may be or comprise a measure of absolute and / or relative content of particular nucleic acid conformations, such as an concentration (e.g., titer), total mass, etc. of single stranded (ss) DNA, double stranded (ds) DNA, B DNA, A, DNA, Z DNA, triple-helical DNA, etc. and / or a relative fraction of any of the foregoing, for example in relation (e.g., relative to) a total DNA, nucleic acid, etc. content. In certain embodiments, a sample quality metric may be or comprise a measure of absolute and / or relative content of one or more particular types of nucleic acid bases (e.g., guanine (G), cytosine (C), thymine (T), adenine (A), uracil (U), etc.) and / or combinations thereof. For example, in certain embodiments, a sample quality metric may be or comprise a GC content metric, providing a measure of total and / or relative content of GC bases within a sample. For example, a GC content metric may be or comprise a measure of total GC content with in a sample, such as a concentration, total mass, etc. of GC. In certain embodiments, a GC content metric may be or comprise a measure of relative GC content, for example scaled relative to total nucleic acid content or, for example, incorporating known, intended, or assumed values such as strand length to provide an average measure of GC content per nucleic acid molecule / strand (e.g., a percentage of GC bases in each nucleic acid molecule, on average, in a sample).

[0360] In certain embodiments, a sample quality metric may be or comprise a value that indicates an extent of aggregation, or absence and / or presences thereof, in a sample. For example, a sample quality metric may be a value (e.g., a numerical value) that provides a measure of content a particular species of aggregate, such as monomer, dimer, trimer, multi- - 72 - 11677372v1Attorney Docket No. 2017297-0013mer, etc., in a sample. For example, one sample quality metric may be a value that provides a measure – e.g., is proportional to and / or correlates (e.g., increases or decreases) with – content of a particular species of a protein aggregate within a sample. For example, one sample quality metric may measure monomer content, another may measure dimer and / or higher molecular weight species (e.g., dimer, trimer, etc.) content, within a sample. In certain embodiments, a sample quality metric may be indicative of a particular aggregation species or state based on its value in comparison with one or more ranges and / or thresholds. For example, in certain embodiments, as described in further detail herein, a sample quality metric may be indicative of monomeric protein species when its value falls within a particular range, and indicative of presence of aggregation (e.g., dimers and / or multimers) when its value moves outside of the particular range. The particular range may be a pre-specified numerical range, may be calibrated for a particular sample or protein species, or may be determined in real-time, for example, based on measurements during a particular sample processing run, such as a chromatography elution.

[0361] Identification of Analytes. In certain embodiments, a sample quality metric may be or comprise a value that identifies presence, or absence of a particular target analyte (e.g., or sufficient content thereof) within a sample. For example, in certain embodiments, a sample quality metric may be or comprise a Boolean value, having two states (e.g., 1 or 0, True or False, etc.), indicative of whether a particular target analyte, such as a desired protein or protein species and / or an undesired impurity, is present within a sample. In certain embodiments, a sample quality metric is or comprises a value that identifies one or more particular analytes within a sample. For example, a sample quality metric may be or comprise a value or set of values that encodes an identity of one or more components within a sample, such as an alphanumeric string, a set of strings and / or alphanumeric characters, a numerical or Boolean array, etc.

[0362] In certain embodiments, sample quality metrics may relate to gene therapy products. For example, in certain embodiments, a sample quality metric may characterize a content of viral particles, nucleic acid content, and / or mixtures or assemblies thereof. In certain embodiments, a sample quality metric may be or include measurements of viral and / or capsid titer as described herein. In certain embodiments, a sample quality metric may be or comprise a measure of capsid content, such as a total content of empty capsids, a total content of full capsids, or a relative measure, such as a fraction, percentage, etc. of empty versus full capsids, etc. - 73 - 11677372v1Attorney Docket No. 2017297-0013

[0363] Certain mid-IR bands for determining sample quality metrics. In certain embodiments, sample quality metrics are determined using mid-IR absorbance data, such as mid-IR spectral data. In certain embodiments, a sample quality metric is determined using mid-IR spectral data that includes an Amide I region, ranging from about 1600 cm-1to about 1700 cm-1or about 1800 cm-1(e.g., ranging from about 1600 cm-1to about 1725 cm-1; e.g., ranging from about 1625cm-1to about 1725 cm-1; e.g., ranging from about 1630 cm-1to about 1650 cm-1), and / or an Amide II region, ranging from about 1500 to about 1600 cm-1(e.g., ranging from about 1500 cm-1to about 1575 cm-1; e.g., ranging from about 1500 cm-1to about 1550 cm-1; e.g., ranging from about 1540 cm-1to about 1560 cm-1). In certain embodiments, mid-IR spectral data including one or both of an Amide I and Amide II spectral region may be used to determine one or more sample quality metrics indicative of and / or characterizing one or more protein species within a sample. In certain embodiments, a sample quality metric is determined using mid-IR spectral data that includes a spectral range from about 1000 cm-1to about 1350 cm-1, which, for example, may be used to determine one or more sample quality metrics indicative of and / or characterizing viral and / or nucleic acid species (e.g., DNA, mRNA, etc.) within a sample. In certain embodiments, a sample quality metric is determined using mid-IR spectral data that includes a spectral range from about 1000 cm-1to about 1700 cm-1(e.g., up to about 1800 cm-1). For example, in certain embodiments, systems capable of measuring from about 1000 cm-1and up to 1800 cm-1may be used to monitor combined or multi-component process streams that include both viral and / or protein (e.g., monoclonal antibody) species.

[0364] In certain embodiments, a sample quality metric is determined using multiple bands, for example, to quantify both protein and nucleic acid content within a sample. In certain embodiments, measures of protein and nucleic acid content within a sample may be combined to determine, additionally or alternatively, sample quality metrics that measure viral capsid content and / or full / empty capsid content and / or relative fractions.

[0365] For example, FIG.11 shows an illustrative schematic of an IR absorption spectra of a sample comprising ssDNA and protein, including a composite spectrum 1102 corresponding to a raw spectrum acquired from a sample comprising both ssDNA and protein, along with spectra corresponding to individual protein 1104 and ssDNA 1106 components. As described herein, protein content may be measured using and Amide I 1112 and / or Amide II 4014 spectral band. Additionally or alternatively, in certain embodiments, protein content may be measured using IR absorption data within an Amide-III spectral - 74 - 11677372v1Attorney Docket No. 2017297-0013region 1116, ranging from about ranging from about 1250 cm-1to about 1350 cm-1(e.g., ranging from about 1250 cm-1to about 1325 cm-1; e.g., ranging from about 1275 cm-1to about 1325 cm-1; e.g., ranging from about 1280 cm-1to about 1300 cm-1).

[0366] Nucleic acid content may be quantified using IR absorption data within spectral ranges associated with antisymmetric and / or symmetric phosphate stretch (PO4) vibrations. For example, in certain embodiments, a sample quality metric measuring nucleic acid content (e.g., a nucleic acid content metric) may be determined using IR absorption data an antisymmetric-PO4spectral band 1118 (e.g., ranging from about 1150 cm-1to about 1250 cm-1, e.g., ranging from about 1175 cm-1to about 1250 cm-1; e.g., ranging from about 1200 cm-1to about 1250 cm-1; e.g., ranging from about 1210 cm-1to about 1230 cm-1) (shown, in FIG.11, to peak at around 1220 cm-1). In certain embodiments, a sample quality metric measuring nucleic acid content (e.g., a nucleic acid content metric) may be determined using IR absorption data an symmetric-PO4 spectral band 1120 (e.g., ranging from about 1000 cm-1to about 1100 cm-1, e.g., ranging from about 1050 cm-1to about 1100 cm-1; e.g., ranging from about 1075 cm-1to about 1100 cm-1; e.g., ranging from about 1075 cm-1to about 1085 cm-1) (shown to peak at around 1080 cm-1in FIG.11).

[0367] In certain embodiments, particular spectral bands may be used / selected to allow for independent quantification of protein and nucleic acid content in composite sample comprising a mixture of the two. For example, as shown in FIG.11, absorption within an Amide-I spectral region 1112 of a spectrum taken from a mixture 1102 may be contributed to by both protein 1104 and nucleic acid 1106 components, whereas Amide-II 4014 and Amide- III 1116 absorption is due mainly to protein 1104, ssDNA spectrum 4006 shown in FIG.11 being relatively flat / minimal in both these (Amide-II and Amide-III) regions. Accordingly, in certain embodiments, an Amide-I and / or Amide-III band may be used to quantify protein content in samples where nucleic acid is or may be present. Antisymmetric and symmetric PO4 regions 1118 and 1120, where absorption results primarily from nucleic acid content can be used to quantify nucleic acid content, e.g., independent of variations in protein content. Peak Metrics

[0368] In certain embodiments, values of one or more sample quality metrics as described herein may be determined and monitored by analyzing on or more absorption bands within mid-IR spectral data. In particular, in certain embodiments, values of one or - 75 - 11677372v1Attorney Docket No. 2017297-0013more peak metrics are determined for each of one or more particular absorption bands. Peak metrics aim to quantify features of absorption bands, such as a frequency position (e.g., a center frequency), a linewidth, an intensity of one or more absorption bands, and may be calculated via a variety of approaches.

[0369] Frequency Position Metrics. In certain embodiments, a peak metric is or comprises a measure of frequency position of a particular absorption band. For example, in certain embodiments, a frequency position (e.g., a center frequency) of a particular absorption band may be or comprise a peak frequency (νPeak), which may be determined directly from an absorption spectra, by determining a frequency at which an amplitude of the particular absorption band peaks (e.g., reaches a maximum), by fitting a pre-defined function, such as a Gaussian or Lorentz, and obtaining a center frequency from the fitted function, or by other methods. In certain embodiments, a frequency position (e.g., a center frequency) of a particular absorption band may be or comprise a center-of-mass frequency (νCOM). In certain embodiments, νCOMfor a particular absorption band may be computed from an absorbance spectrum (e.g., a mid-IR absorbance spectrum) A(ν) according to Equation 1 below. ^^^^^ (Eq.1) ^^ ^∙^^^^= ^^^^^(^)^^^^^^^^^^^^^^ ^^ , where νmin(maximum frequency) bounds of the particular absorption band.

[0370] Linewidth Metrics. In certain embodiments, one or more peak metrics may be or comprise a linewidth measurement, such as a full-width at half maximum (FWHM), computed, for example, by various techniques such as descending along one or two sides from a peak, or via a functional (e.g., Gaussian, Lorentzian, etc.) fit.

[0371] Peak Intensity Metrics. In certain embodiments, a peak metric may be or comprise a measure of intensity of one or more particular absorption bands, such as peak amplitude or area under the curve (AUC). In certain embodiments, a peak amplitude of a particular band is computed from an absorbance spectrum, A(ν), as a value at a particular (e.g., nominal) center frequency associated with the particular band, νband, i.e., as Aband= A(νband). In certain embodiments, a peak amplitude for a particular band is computed from an absorbance spectrum, A(ν), as a value at a peak frequency, νPeak, i.e., as Aband= peak(Band) = A(νPeak). In certain embodiments, a measure of strength of one or more particular absorption bands is determined by computing an AUC. An AUC may be computed, for a particular - 76 - 11677372v1Attorney Docket No. 2017297-0013absorption band, by integrating an absorbance spectrum, A(ν), over bounds of the particular absorption band. For example, for a particular absorption band ranging from νmin to νmax, an AUC may be computed according to Equation (2), below: (Eq.2) ^^^ =^^^^^^^^^^(^)^^ .

[0372] In certain embodiments, an AUC is computed for a single band. In certain embodiments, an AUC is computed for two or more bands, such as two or more neighboring bands or a region comprising a plurality of bands believed to be associated with a particular target analyte of interest. In such a case, an AUC for a collection of two or more bands or a particular overall region may be computed according to Equation (2) above, with νminand νmax specifying bounds of the two or more bands or particular overall region.

[0373] Combining Peak Metrics. In certain embodiments, a sample quality metric may be, or be computed from (e.g., as a function of) a particular peak metric. For example, in certain embodiments, a sample quality metric may be a particular peak metric, such as a measure of band (frequency) position. In certain embodiments, a sample quality metric may be determined from a combination of (e.g., computed as a function of) two or more (e.g., two; e.g., three or more; e.g., a plurality of) peak metrics, which may be from same and / or different absorption bands. For example, in certain embodiments, a sample quality metric may be determined as a sum, difference, ratio, product, or other function of two or more peak metrics. In certain embodiments, a sample quality metric may be computed as a function of two or more peak metrics, together with other values or constants, such as scaling factors, normalization constants, and the like, which may be a-priori known and / or assumed, and / or determined, e.g., via molecular structure or other known properties and / or from other (e.g., orthogonal) measurement approaches, such as other spectroscopy techniques, prior measurements, etc., as described herein. For example, in certain embodiments, a sample quality metric may be determined as a linear function or combination one or more peak metrics, for example having a form as shown in Equation 3, below, (Eq.3) ^ = ∑^^^^^^^^= ^^+ ^!^!+ ^"^"+ ⋯ + ^^^^, where S is ametrics, x1, x2, …, xN, and aiare constants. - 77 - 11677372v1Attorney Docket No. 2017297-0013Reference Spectra, Statistical Analysis, and Machine Learning

[0374] In certain embodiments, sample quality metrics may be determined based on and / or using one or more reference spectra. Reference spectra may be or comprise one or more spectra that are obtained from IR absorption measurements on reference samples.

[0375] Reference spectra may be measured previously and stored, e.g., in a proprietary database, accessed from public databases, or measured in parallel with various processing steps, e.g., substantially simultaneously.

[0376] In certain embodiments, reference samples, from which reference spectra may be obtained, may include, but are not limited to, samples for which one or more particular sample quality metrics are known (e.g., having been determined by other, orthogonal, e.g., more expensive and / or time consuming methods, not suitable for real-time and / or in-line analysis), having a known and / or desired purity, having known individual constituents, etc. Reference samples may be prepared so as to match with samples or constructs being screened for better stability, expression or a binding attribute to its cognate substrate.

[0377] For example, in certain embodiments, one or more reference samples having a known purity, e.g., of a particular molecular species (e.g., protein, nucleic acid, viral particle) and / or form thereof (e.g., a particular secondary structure, glycosylation, monomeric purity) may be obtained and their IR spectra measured. In certain embodiments, reference samples may be (e.g., intentionally) spiked with one or more impurities, such as waste products, undesired molecular forms, (e.g., known) bioprocess inputs that may be incompletely converted and / or filtered out by upstream processing, etc., and corresponding IR spectra measured.

[0378] In certain embodiments, reference spectra may be obtained and / or modified in-silico, via various computational processes. For example, reference spectra may be constructed via ab-initio calculation methods for particular molecular structures. Initial, e.g., library, reference spectra may be combined, for example according to Beer’s law, scaled, or otherwise pre-processed to create new, tailored reference spectra that, for example capture particular variations in sample parameters that may be of interest, remove baselines, reflect sub-band deconvolution, show second derivative spectra, etc., and accordingly are tailored for a particular sample quality metric and / or sample.

[0379] In certain embodiments, based on a comparison between a particular target spectrum, measured from a sample whose properties are unknown (e.g., entirely or partially), - 78 - 11677372v1Attorney Docket No. 2017297-0013and one or more such reference spectra, one or more sample quality metrics, e.g., reflecting sample purity, may be determined.

[0380] For example, in certain embodiments, a reference spectra approach as described herein may be applied to measurement of gene therapy products, such as a viral vector sample. For example, one or more reference spectra may be obtained from a high- quality reference sample, for example comprising a desired purity in terms of a fraction of full capsids (e.g., a full capsid fraction above a particular threshold), monomeric particles, lack of certain impurities (e.g., host cell proteins and / or host cell nucleic acid; e.g., aggregates; e.g., fragments), and the like. In certain embodiments, for example, a high quality viral vector sample may have a full capsid fraction above a particular threshold, such as 70%, 80%, 90%, etc.

[0381] An aqueous sample comprising one or more viral vector species may, e.g., subsequently or in parallel, be interrogated by a mid-IR analyzer as described herein to obtain one or more target IR absorption spectra. One or more target IR absorption spectra may then be compared with the high-quality reference spectra to determine a measure of sample quality.

[0382] For example, FIG.12 shows an illustrative absorbance plot 1200 of an example (scaled) high quality reference spectrum 1202 of a high quality viral vector sample, having a high content of full capsids (e.g., about or better than 80% full capsids), in comparison with a lower quality viral vector sample spectrum 1204, having a low content of full capsids. Differences between the two spectra are observable in the absorbance plot 1200. In certain embodiments, difference spectra may be determined by subtracting a target spectrum from a high quality reference spectrum (e.g., or vice versa) to show a change in absorbance as a function of wavenumber. For example, FIG.12 shows a corresponding difference spectrum 1220, determined by subtracting high quality reference spectrum 1202 from low quality viral vector sample spectrum 1204. In difference spectrum 1220, effects such as a frequency shift in an Amide-II band – in particular, a redshift (e.g., shift to lower frequency) - and a reduction in absorption at an Amide-III region are apparent as an asymmetric line-shape 1222 and a pair of negative peaks 1224, respectively. One or both of these features, and / or various peak metrics computed therefrom, could be used to determine sample quality metrics indicative of various attributes of viral vector sample quality. - 79 - 11677372v1Attorney Docket No. 2017297-0013

[0383] Comparison of target IR absorption spectra with one or more reference spectra may be accomplished in a variety of manners, such as computing a difference spectrum, to obtain comparison spectra. In certain embodiments, numerical measures of similarity may be computed using target spectra and reference spectra, pre-processed versions thereof (e.g., derivative spectra, scaled and / or baseline corrected spectra, etc.), and / or comparison spectra computed therefrom. Numerical similarity measures may include, without limitation, correlation values, covariance values, Pearson’s correlation values, overlap integrals, etc.

[0384] In certain embodiments, one or more machine learning models may be used to determine one or more sample quality metrics from IR absorbance data. Machine learning models may, among other things, be trained using various reference spectra, as examples, in order to adjust and / or optimize variable (learnable) parameter weights in one or more network layers. Once trained, a machine learning model may then be used for inference – i.e., to determine metrics from new, unknown sample spectra. For example, in certain embodiments, for example, a machine learning model may receive, as input, an IR spectrum and generate, as output (e.g., via inference) determined values of one or more sample quality metrics. In certain embodiments, a machine learning model receives a single IR spectrum (e.g., corresponding to a single time point) as input. In certain embodiments, a machine learning model receives multiple IR spectra (e.g., collected at different time points) as input.

[0385] In certain embodiments, a similarity score may be determined, for example based on correlation values, covariance values, Pearson’s correlation values, overlap integrals, etc., as well as machine learning-based techniques described herein. In certain embodiments, similarity scores may be generated and updated in substantially real time. For example, a reference spectra of full and empty capsid samples may obtained (e.g., loaded, received, or otherwise accessed) by a mid-IR analyzer and / or processor in communication therewith. As mid-IR absorption data is repeatedly obtained over time, for example to monitor viral vector production, purification, etc. (e.g., for AAV samples), a similarity score may be generated in real time, and displayed (e.g., to provide a real-time view of quality), stored (e.g., as a quality log) and / or provided for further processing, such as to control various parameters of production units as described herein. - 80 - 11677372v1Attorney Docket No. 2017297-0013Data Pre-Processing

[0386] In certain embodiments, IR absorbance data, such as mid-IR spectral data, used for determining one or more sample quality metrics is preprocessed data. For example, in certain embodiments, one or more pre-processing steps may be performed on mid-IR spectral data prior to it being used to compute a particular sample quality metric and / or being used as input to a machine learning model.

[0387] For example, in certain embodiments, mid-IR spectral data may be pre- processed via a baseline correction approach that removes background signal, such as background absorption from a mobile phase (e.g., water’s H-O-H bending mode), in order to obtain mid-IR absorption spectra indicative of one or more analytes in the mobile phase. This approach (baseline correction via removal of a background signal) may be referred to as background subtraction, and, for example, accomplished by subtracting a reference (e.g., background absorbance) spectrum, Aref, from a measured spectrum, A, to obtain a background corrected spectrum Abg = A – Aref. In certain embodiments, an reference spectrum may be computed and / or selected based on a model, such as a mixture model, in order to reflect presence and / or variations in amounts of one or more background components in a mobile phase.

[0388] For example, in certain embodiments, one or more background components are or comprise water molecules, such that a reference spectrum is selected or computed to reflect an appropriate strength / relative amplitude of absorption due to water molecules present in a sample. In certain embodiments, a reference spectrum may be computed to reflect, for example, displacement of water molecules by analyte molecules, for example as described herein. In certain embodiments, multiple reference spectra may be computed, for example, to reflect variation in certain background molecules over time, during a particular biological and / or sample processing step.

[0389] For example, during a chromatography elution, parameters such as salt content, pH, etc., may be varied, for example in a step-wise or gradient fashion, such that, when IR spectral data is measured from an aqueous sample exiting from a chromatography column, desired, time-varying protein absorption spectra is superimposed on a time-varying background spectrum. Variations in background spectrum may be due, for example in the case of ion-exchange chromatography, where salt content is varied, to displacement of water molecules by salt. Accordingly, in certain embodiments, multiple and / or a continuously - 81 - 11677372v1Attorney Docket No. 2017297-0013scaled reference spectra are used to reflect variation in background absorption as salt concentration increases. In certain embodiments, selecting and / or computing a particular reference spectra may comprise using one or more template reference spectra together with a value of an input parameter (e.g., such as a salt concentration curve used by a chromatography column) and / or a measured sensor value, such as a conductivity or pH value, measured by a sensor.

[0390] For example, in certain embodiments, conductivity may be measured with a conductivity sensor as mid-IR spectral data is obtained during an IEX chromatography column elution. Conductivity measured by a conductivity sensor may then be used to select or compute a particular reference spectrum that reflects a particular water molecule concentration as salt concentration is increased and, accordingly, salt displaces water molecules. Akhgar et al., “QCL-IR Spectroscopy for In-Line Monitoring of Proteins from Preparative Ion-Exchange Chromatography,” Anal. Chem.94:5583-90 (2022), the content of which is hereby incorporated by reference in its entirety, for example, used a conductivity sensor to perform background compensation due to a salt (NaCl) gradient.

[0391] In certain embodiments, IR spectra may be averaged, for example, to improve their quality (e.g., signal to noise ratio). For example, to obtain an IR spectrum at a particular time point, t1, multiple IR absorption spectra may be acquired in succession about t1, e.g., within a window t1+ δ and averaged to create a single, signal averaged, spectrum. Accordingly, in certain embodiments, an IR spectrum corresponding to a particular time point is itself a function of (e.g., an average) of a plurality of IR spectra collected about the particular time point. Incorporating Multiple Time Points and Temporal Change

[0392] In certain embodiments, sample quality metrics may be determined based on values of IR absorption at multiple (e.g., not necessarily just a current) time points. For example, a sample quality metric may measure a temporal change or aggregated value of one or more features of IR absorption spectra. In certain embodiments, for example, where a particular sample quality metric may be determined using values computed from an IR absorption spectrum corresponding to a measurement performed at a single (e.g., current) time point, a differential or time-aggregated sample quality metric may be determined using values computed from multiple IR absorption spectra, each corresponding to a different time - 82 - 11677372v1Attorney Docket No. 2017297-0013point. In certain embodiments, individual values of a particular, single time-point, sample quality metric may be determined at multiple time points (e.g., each value corresponding to a particular time point) and then combined, for example via computing a difference, average, median, variance, etc.

[0393] In certain embodiments, a differential sample quality metric is computed as a difference between values of a particular (e.g., other) sample quality metric at two time- points, for example as a difference between consecutive times. In certain embodiments, a time-aggregated sample quality metric may be computed based on a running sum, mean, median, mode, variance, standard deviation, etc. over a particular time window, such as a backward looking window of a particular number of seconds and / or measurements, and / or in a cumulative fashion, aggregating measurements from an initial time point to a current one. Various differential and / or aggregated sample quality metrics may be determined, for example based on temporal differences, cumulative (over time) sums, time-averages, etc. between sample quality metrics such as absorbance values at particular wavenumbers, ratio’s between multiple absorbance values, and various peak metrics as described herein.

[0394] In certain embodiments, spectra may be manipulated in order to emphasize particular features and or changes of interest when computing differential and / or time- aggregated metrics. For example, in certain embodiments, a normalization approach may be used that allows for creation of normalized spectral difference metric that facilitates identification of compositional changes in a sample.

[0395] Turning to equations (4-6), below, spectra may be normalized by a reference in order to produce a normalized spectra for a sample that does not depend on concentration of a particular composition (e.g., a single particular analyte or composition of one or more analytes). That is, absorbance at a particular wavenumber, νi, due to a particular composition at concentration C in a sample, is (Eq.4) ^(^^) = ^^= $^× ^ × & , where l is the

[0396] This absorbance may be normalized via division by a reference absorbance, Aref, taken at a reference wavenumber, νi, where (Eq.5) ^'()= ^*^'()+ = $'()× ^ × & 11677372v1Attorney Docket No. 2017297-0013

[0397] In this manner, a normalized absorbance spectrum A / Arefmay be determined, such that, at each wavenumber νi, the normalized absorbance is: (Eq.6)^^ / ^^,-.= / ,-.

[0398] Accordingly, a normalized absorbance spectra, ^0(^), may be determined in accordance with Eq.6, by dividing by a reference value taken at a particular wavenumber. For un-normalized absorption spectra taken at multiple time points, if composition and concentration stay constant, there will be no difference between spectra taken at multiple, e.g., consecutive, time points. A change in concentration, however, will cause an overall increase in absorption at each wavelength, such that at each wavenumber a difference in absorption will be approximately proportional to a change in concentration. If a normalization, in accordance with Eq.6, is carried out, to obtain, at each time point, a normalized spectra, then changes in concentration will not influence a spectral difference at one or more wavelengths. That is, at each wavenumber, νi, the change, ∆, in normalized absorbance, ^0(^^), due to a change in concentration, but not composition, is equal to zero, plus or minus an (e.g., small) baseline noise term, 2^(Eq.7a)∆ = ^0^,: − ^0^,:<=: =^^,:^^,:<=:^ −= 0 ± 2^ '^'

[0399] difference (∆), will include an additional contribution, beyond the baseline noise term (e.g., ∆= @^± 2^). Accordingly, by detecting whether a change in normalized spectral differencepurely noise, or includes additional factors a change in sample composition can be determined. A composition may be a single analyte, or a mixture of different analytes and / or species, forms etc. of analytes. A change in composition may occur, accordingly, due to addition of new, different analytes, as well as due to a difference in relative fractions of particular analytes (e.g., ratios between) and / or species thereof. Where a mixture is present, a change in concentration (e.g., as opposed to composition) refers to an overall concentration of the mixture, holding ratios between its components constant. As explained above, such changes in concentration will not impact normalized absorbance spectra.

[0400] A normalized spectral difference, Δ, may be determined in a variety of manners. For example, Eq.7a shows a difference at a particular wavelength. In certain - 84 - 11677372v1Attorney Docket No. 2017297-0013embodiments, a normalized spectral difference, Δ may be computed by taking an integral over one or more particular bands, as shown in Eq.7b, below. The one or more particular bands may include any bands described herein, for example an Amide I, Amide II, Amide III, asymmetric and / or symmetric PO4 stretch bands, as well as other bands of interest, not necessarily described herein. (Eq.7b)∆BCD^ = E ^0:(F)^F − E ^0:<=:(F)^Fwhere the integral is of interest (e.g., asingle contiguous region and / or a combination of two or more non-contiguous spectral regions).

[0401] A normalized spectral difference may, accordingly, be determined and monitored in real-time, and used to identify if and / or when a change in composition occurs. In certain embodiments, identifying a change in composition may comprise analyzing the normalized spectral difference signal to detect occurrence of a change point, for example using various approaches including, but not limited to, those described in Killick R., P. Fearnhead, and I.A. Eckley. "Optimal detection of changepoints with a linear computational cost." Journal of the American Statistical Association. Vol.107, Number 500, 2012, pp.1590- 1598. In certain embodiments, a step change may be detected to identify a change in composition. In certain embodiments, a variation in one or more statistical properties of a normalized spectral difference signal may be used to identify a change in composition, for example based on whether they exceed a particular threshold value and / or move outside a particular window (e.g., acceptable range). In certain embodiments, multiple changes in composition may be identified, for example, among other things, due to multiple variations in analyte compositions, addition of different analytes at different times, as well as aggregation, temperature and / or other buffer (e.g., salt gradient) induced conformational changes, etc. (e.g., any alteration in spectral line-shape). These changes in concentration may occur on different time-scales and / or alter various statistical properties in distinctive manners and, accordingly, may be used to distinguish between various distinct mechanisms that change sample composition.

[0402] Equations 7a and 7b show subtraction of an absorbance at time t + Δt from an earlier measurement of absorbance, at time t. Additionally or alternatively, it should be understood that a normalized spectral difference may be determined by subtracting in the - 85 - 11677372v1Attorney Docket No. 2017297-0013other direction, that is, subtracting prior data from more recent (e.g., current) data, for example as shown in equations 7c and 7d, below: (Eq.7c) ∆ = ^0^,:− ^0^,:H=:

[0403] monitored via IRspectroscopy can be monitored using a normalize spectral difference signal. That is, while changes in analyte concentration will produce nominally zero variations in differences between normalized absorbance spectra, changes in sample composition will produce changes that appear in differential spectra above the baseline cumulative noise. This approach can be used to monitor composition of a chromatography column effluent, a composition of retentate and / or permeate in a UF / DF process, progress of a chemical reaction.

[0404] In certain embodiments, integrals, subtractions, and the like, for example, such as those shown in equations 7a through 7d, above, may be carried out over IR absorbance spectra and / or functions thereof, for example pre-processed or adjusted versions of IR absorbance spectra. For example, in certain embodiments, IR absorbance spectra may be base-line corrected spectra. In certain embodiments, absolute value, squared, shifted version, etc. of IR absorption spectra may be used, for example to ensure a particular (e.g., positive) sign of a differential signal, such as those shown and / or time-aggregated signal. B.ii. Combination with Additional Sensors

[0405] In certain embodiments, process monitoring and / or control technologies described herein may include and / or use data generated by, one or more additional sensors (e.g., other than mid-IR analyzers). In certain embodiments, one or more additional sensors comprise sensors for measuring parameters such as measure parameters such as temperature, pressure, pH, conductivity, flow rate etc. Such sensors may include, without limitation, one or more temperature sensors, one or more pressure sensors, one or more pH sensors, one or more conductivity sensors, one or more flow rate sensors, optical sensors, etc.

[0406] In certain embodiments, one or more additional sensors may comprise sensors that are also capable of measuring one or more physical, chemical, biological, or - 86 - 11677372v1Attorney Docket No. 2017297-0013microbiological properties of one or more analytes within a sample. In certain embodiments, one or more additional sensors may be used, for example together with, one or more mid-IR analyzer(s) to generate data used for determining one or more sample quality metrics. In certain embodiments, for example, mid-IR spectral data may be used together with data from one or more additional sensors to determine one or more sample quality metrics.

[0407] For example, in certain embodiments, an additional sensor is or comprises a UV absorption sensor. A UV absorption sensor may be or comprise any sensor operable to measure absorption of a sample in a UV (e.g., from about 200 nm to about 300 nm) spectral range. In certain embodiments, a UV absorption sensor may be or comprise a fixed path- length sensor, that measures UV absorption of a sample using a fixed path-length cell. In certain embodiments, a UV absorption sensor may be or comprise a slope spectroscopy sensor, such as the CTechTMSoloVPE®and / or a variation / embodiment thereof, which measures UV absorption while varying path-length through a sample. Among other things, in certain embodiments UV absorption measurements may be used together with mid-IR absorption measurements as, for example, an internal check and / or a complementary technology. For example, in certain embodiments, a combined and / or expanded range of data acquisition may provide, among other things, intrinsic verification and the quantification of different types of data. For example, in certain embodiments, total protein concentration may be measured with one or both of UV absorption and mid-IR absorption spectral data. In certain embodiments, additionally or alternatively, label and tagging solutions in the mid-IR would add value for the UV based methods as well for species identification, combatting counterfeit products and traceability of product. B.iii Real-Time Control of PAT Systems

[0408] In certain embodiments, data analytics, machine learning and artificial intelligence, and the like can be leveraged with IR spectroscopic measurements and / or sample quality metrics determined as described herein not only provide real time monitoring and reporting of sample quality metrics, but can, additionally or alternatively, be used for predictive analytics whereby data collected are analyzed in real time and, additionally or alternatively, together with historical data sets and / or empirical models to predict future states of processes and / or the qualities of the materials in the process streams. - 87 - 11677372v1Attorney Docket No. 2017297-0013

[0409] IR measurement and data analysis tools described herein, for example, may provide detailed information about process parameters, process performance and process stability. They may be used to control process parameters, for example to improve performance in various growth and purification (filtration) steps, including, but not limited to cell culture, virus production, clarification, concentration, diafiltration, chromatography, purification, direct flow filtration, tangential flow filtration, tangential flow depth filtration. Additionally or alternatively, predictive analytics may be leveraged during analytical development, process development, and formulation to design experiments to develop extremely detailed process understanding, potential failure mode and effect analysis and sensitivity analysis in modeled processes. Production Units

[0410] Approaches such as these may be used in both upstream processes such as cell culture and harvest as well as in downstream application including purification / filtration, formulation and fill finish unit processes. For example, FIG.13 shows various upstream and downstream bioproduction process steps together with properties that may be, among other things, monitored via MIR analyzer(s) 1302 and / or used to control process parameters via systems and methods described herein.

[0411] For example, as shown in FIG.13, raw materials used in biologic (e.g., protein, nucleic acid, viral vector, etc.) production may be tested initially and / or monitored as they are provided, e.g., to various processing steps and production units to evaluate, among other things, sample quality metrics pertaining to material purity, identity, and presence of impurities. Various inputs, outputs, and portions of a bioreactor production unit, such as a seed bioreactor and / or production bioreactor, may be monitored using techniques described herein, for example to confirm identity of desired biomolecules produced, determine titer, and ensure adequate nutrients are present in a bioreactor and / or being provided.

[0412] In certain embodiments, for example, one or more MIR analyzers as described herein may be used in connection with purification (filtration) units, such as alternating tangential flow filtration (ATF) systems, tangential flow depth filtration (TFDF) systems, tangential flow filtration (TFF) systems, chromatography columns, direct, or normal, flow filtration, ultra-filtration, dia-filtration, and the like. - 88 - 11677372v1Attorney Docket No. 2017297-0013

[0413] In certain embodiments, for example, one or more sample quality metrics and / or IR spectral data may be provided to control software and / or hardware systems and components such as Supervisory Control and Data Acquisition (SCADA), Manufacturing Execution System (MES) systems, and the like, for use in making decisions on changes to process control parameters and produce release.

[0414] For example, data such as empty / full ratios (e.g., in the context of viral vector production processes) or the presence of high weight molecules such as dimers, trimers and multimers when processing proteins may be used to adjust process parameters such as flow rate, flow direction, pressures, temperatures, pH, etc. In certain embodiments, parameters such as addition and / or variation of quantities of raw materials in process streams may be adjusted. Process parameters controlled and / or adjusted as described herein may include, but are not limited to, process parameters that impact certain attributes which should be within an appropriate limit, range, or distribution to ensure a desired product quality (i.e., CQAs) (e.g., process parameters that impact CQAs, referred to as “Critical Process Parameters (CPPs)”).

[0415] Additionally or alternatively, data such as particular sample quality metrics characterizing protein content, secondary structure, protein aggregation, viral vector content, empty-full ratio, capsid aggregation, etc., in real time can be used to direct decisions such as when to stop a processing, open or close valves direct sample collection and fraction collection and pooling of different materials. For example, in certain embodiments, decisions on column loading can be made by monitoring breakthrough from the chromatography columns. For example, in one example of control, upon detection of breakthrough a continuous production system can be issued commands to open / close values redirecting process flow to a next chromatography column inline and / or transitioning a fully loaded column into elute and / or wash stages of the process.

[0416] Approaches described herein may be used together with a variety of chromatography columns, including, without limitation an affinity chromatography (AC) (e.g., Protein A) column, a hydrophobic interaction chromatography (HIC) column, an ion exchange chromatograph (IEX) column, a size exclusion chromatography (SEC) column, and a mixed-mode chromatography column [e.g., which implements any combination of the foregoing (e.g., IEX and HIC; e.g., IEX and SEC)].

[0417] In certain embodiments, approaches described herein can be used in connection with a TFF concentration production unit, for example during viral vector and / or - 89 - 11677372v1Attorney Docket No. 2017297-0013antibody production process(es) to monitor aggregation and continue and / or halt concentration, e.g., based on a level of measured aggregation.

[0418] For example, in certain embodiments, during discovery and manufacturing of protein therapeutics and / or diagnostic reagents, including, for example, monoclonal antibodies, fusion proteins, viral capsid proteins, antibody drug conjugates etc., it is highly desirable to accurately measure both the total concentration (also referred to as titer) of aqueous protein mixtures as well as a degree of their molecular heterogeneity over a wide dynamic range of concentrations, e.g., from approximately 1 picogram-per-liter to approximately 500 grams-per-liter. Additionally or alternatively, it is desirable to make such measurements in either static or dynamic flow condition up to 100 liters-per-minute or more. Protein Heterogeneity and Chromatography Elution Control

[0419] In certain embodiments, sample quality metrics computed from IR absorption spectra as described herein may be used to measure different types of molecular heterogeneity. For example, in certain embodiments, a mixture may be heterogeneous in terms of having different species of free (unbound) proteins. In certain embodiments, a heterogeneity may result from aggregation, with a mixture comprising a population of identical proteins, each protein being either free (unbound) or chemically bound to one (dimer) or more (trimer, tetramer, pentamer, etc.) identical proteins, thus forming varying degrees of aggregation. Additionally or alternatively, a desirable form of molecular heterogeneity to measure may include a population of identical proteins having different types or degrees of molecular conjugation, e.g. polysaccharides, glycans, polyethylene glycol, or small molecules used for therapeutic means.

[0420] In certain embodiments, approaches described herein may quantify protein heterogeneity can be quantified in a number of different ways. For example, in certain embodiments (e.g., as described in further detail in certain Examples, below), a protein aggregation metric that quantifies a total or percent level of aggregation may be determined. In certain embodiments, a conjugation-based metric that quantifies a total or percent level of glycation or small molecule conjugation may be computed from IR spectra. In certain embodiments, a molecular weight may be determined and a histogram of molecular weight displayed. - 90 - 11677372v1Attorney Docket No. 2017297-0013

[0421] Among other things, in certain embodiments, quantifying a level of aggregation is of particular importance because aggregates can degrade the efficacy and safety of the drug product.

[0422] For example, during ion exchange chromatography (IEX), a heterogenous aqueous mixture of proteins is intentionally separated into its individual protein constituents in time by using a chromatographic column and an ionic salt gradient. In certain embodiments, it is desirable to continuously and non-invasively monitor, in real-time both, a total protein concentration as well as a degree of heterogeneity of the eluent so that a collection window for target protein may be dynamically controlled to produce optimal results (e.g. highest purity of monomer). Said another way, it may be desirable to accurately quantify the level of protein aggregation (high molecular weight species) most often occurring during the trailing end of the elution. Optimizing a collection window can maximize the protein target quality and yield while also maximizing life of a column.

[0423] In certain embodiments, columns are increasingly loaded with higher concentrations of total protein in order to maximize the target protein yield and extend a useful life of a column. Such practices, however, tend to lead to more aggregates being formed, as well as the reduction of a separation time between a target protein (monomer) peak and a first protein aggregate peak (dimer). That is, monomer and dimer peaks become increasingly overlapped and therefore more ambiguous – creating challenges for determining an appropriate (e.g., optimal) target protein capture window.

[0424] In certain embodiments, approaches as described herein may be used for other types of separation (e.g., not limited to aggregate removal) where a product (e.g., or an impurity) breakthrough may occur, for example, removal of HCPs and / or DNA onto a direct flow filter in flow-through mode during clarification before chromatography.

[0425] In certain embodiments, systems and methods described herein may be used to monitor protein secondary / tertiary / quaternary structure. Secondary / tertiary / quaternary structure metrics may be used to control processes in production of antibodies, as well as in production of viral vector samples (e.g., by monitoring capsid protein secondary / tertiary / quaternary structure). In one example, changes in a secondary / tertiary / quaternary structure of a protein molecule may be detected and used to e.g., shunt flow differently as an action (e.g., based on an electronic trigger signal). - 91 - 11677372v1Attorney Docket No. 2017297-0013

[0426] Sample quality metrics indicative of protein aggregation, secondary structure motif, and other properties may, for example, as described in examples below, be monitored by calculating one or more peak metrics from IR absorption spectra. For example, in certain embodiments, a frequency position, such as a center frequency and / or a center of mass frequency as described herein may be determined for one or more of an Amide-I band, an Amide-II band, and Amide-III band and monitored to track levels of protein aggregation. In certain embodiments, a sample quality metric is a protein aggregation metric indicative of a level of protein aggregation within a sample. In certain embodiments the protein aggregation metric is determined based on (e.g., as) a frequency position (e.g., center frequency; e.g., center of mass frequency) of an Amide I band. In certain embodiments the protein aggregation metric is determined based on (e.g., as) a frequency position (e.g., center frequency; e.g., center of mass frequency) of an Amide II band. In certain embodiments the protein aggregation metric is determined based on (e.g., as) a frequency position (e.g., center frequency; e.g., center of mass frequency) of an Amide III band. Viral Vector Production Monitoring and Control

[0427] In certain embodiments, approaches described herein may be used to monitor and control viral vector production control. In certain embodiments, technologies described herein, are suitable for use with various viral vector production approaches, including, for example, transfection-based techniques as well as those that utilize stable producer cell lines (e.g., for producing viral vectors or other products, for example, antibodies). Among other things, viral vectors are a class of large molecules, having molecular weights, in certain embodiments, above 1 MDa. Viral vectors may be used to infect a targeted host cell with genetic material, for example for purposes such as editing a genome of an infected cell or directly translating specific protein(s) within an infected cell. A viral vector used to edit an infected cell genome may, accordingly, be used as a gene therapy device. In certain embodiments, by directly translating specific proteins within an infected cell, a viral vector may be used to trigger an immune response, e.g., accomplishing vaccine functionality.

[0428] Viral vectors include, without limitation, adeno viruses, adeno associated viruses (AAV), retroviruses (e. g. lentiviruses), and plant-based viruses (e. g. tobacco mosaic viruses). As illustrated in FIG.14, viral vector capsids comprise (e.g., are loaded with) a gene cassette. During production, certain viral vector particles may be empty – lacking the - 92 - 11677372v1Attorney Docket No. 2017297-0013desired genetic payload to be delivered to an infected cell. Accordingly, in certain embodiments, determining, not only overall viral particle amount, but also, fraction of full viral particles, that encapsulate desired genetic payload and, accordingly, are suitable for their intended application, is valuable to controlling production and evaluating process yield.

[0429] Structurally, viral vectors comprise a (e.g., approximately spherical) protein shell, about 100 nm or less in diameter, and comprising (e.g., encapsulating) one or more nucleic acid strands, such as DNA or RNA (e.g., mRNA) of varying lengths in terms of number of nucleotide bases. Accordingly, approaches for quantifying protein and nucleic acid content in a mixture, as described herein, may be leveraged to determine sample quality metrics such as total nucleic acid content (e.g., concentration), viral capsid content (e.g., concentration) and a fraction of full capsids. In particular, as described herein, mid-IR organic fingerprint band spanning approximately one thousand (1,000) to eighteen hundred (1,800) wavenumbers comprises multiple spectral sub-regions (sub-bands) which can be assigned to either a capsid, a genetic payload (cassette) contained within the capsid, or to a combination of the capsid and the genetic payload. Methods described herein may exploit an entire range of a mid-IR fingerprint spectral region (from about 1,000 cm-1 to about 1800 cm-1), and / or various sub-bands thereof. Such methods may quantify a concentrations of capsid, genetic material and / or their volumetric ratio, as well as, additionally or alternatively, quantify differences between the composite spectrum of the sample and that of a purified, high-quality sample.

[0430] For example, as described herein and illustrated in FIG.11, various spectral bands can be used to measure content of protein and / or nucleic acid in a sample, including in mixtures, where certain bands, such as an Amide-II and / or Amide-III may be used to quantify protein content independently with respect to nucleic acid concentration. Since viral vectors are structurally, a protein capsid encasing nucleic acid material, spectral absorption within these bands can be used (e.g., together with Beer Lambert law) to determine protein content metrics and nucleic acid metrics that quantitate protein and nucleic acid concentration, respectively, which, in turn, may be used to quantify (protein) capsid and (nucleic acid) payload metrics.

[0431] For example, in certain embodiments, a total capsid concentration may be computed based on a (e.g., as a scaled version of) a protein content metric, which may be determined based on absorption in an Amide-I, Amide-II, and / or Amide-III region. In certain embodiments, use of Amide-II and / or Amide-III spectral regions is desirable, and facilitates - 93 - 11677372v1Attorney Docket No. 2017297-0013independent quantification of protein content, since nucleic acid spectra has relatively little absorption in those (Amide-II and Amide-III) regions. Absorption strength in Amide-II and / or Amide-III regions may be determined using a peak intensity metric that measures intensity of an Amide-II and / or Amide-III band, such as peak amplitude or area under the curve (AUC) measure. A protein content metric and / or total capsid content may, accordingly, be determined based on peak intensity measures for one or both (e.g., a linear combination) of the Amide-II and Amide-III bands.

[0432] In certain embodiments, a nucleic acid content metric, such as a total nucleic acid concentration, may be computed via one or more peak metrics computed based on antisymmetric and / or symmetric PO4bands. Absorption strength in asymmetric and / or symmetric PO4 regions may be determined using a peak intensity metric that measures intensity of an antisymmetric PO4and / or symmetric PO4band, such as peak amplitude (“peak”) or area under the curve (“AUC”) measure. Accordingly, a nucleic acid metric may be determined based on peak intensity measures for one or both (e.g., a linear combination) of the antisymmetric PO4 and / or symmetric PO4 bands

[0433] In certain embodiments, a protein content metric and / or nucleic acid metric may be used to compute a full capsid fraction that provides a measure of a fraction (e.g., a ratio, a percentage, etc.) of capsids that are full – i.e., successfully loaded with desired genetic payload. For example, a full capsid fraction may be determined based on a ratio of (i) a nucleic acid content metric to (ii) a protein content metric and / or a total capsid content determined therefrom.

[0434] In certain embodiments, other peak metrics may be used to determine sample quality metrics such as a capsid content and / or capsid full fraction. For example, in certain embodiments, a frequency position (e.g., center frequency, center of mass frequency) may be determined for one or more of an Amide-I band, an Amide-II band, and Amide-III band, an antisymmetric PO4band, and a symmetric PO4band. In certain embodiments, a frequency position may be indicative of a particular percentage content of full versus empty capsids.

[0435] In certain embodiments, additionally or alternatively, one or more peak metrics may be used to determine a level of aggregation of capsids in a sample, for example, based on frequency position variations. In certain embodiments, one or more protein secondary structure metrics may be determined, as described herein, for a viral vector sample. As an example, combining ion exchange chromatography (charge separation of viral capsids) - 94 - 11677372v1Attorney Docket No. 2017297-0013with mid-IR measurement (change in protein secondary structure) could lead to higher purity by selectively isolating full capsids

[0436] Sample quality metrics pertaining to viral vector production as described herein may be stored, displayed, or provided, for example as trigger signals, in order to monitor, interactively adjust, and / or automatically tune process parameters. FIG.15 shows an example process 1500 for real-time evaluation and monitoring of viral process production via mid-IR spectroscopy. In certain embodiments, a raw IR absorption spectra from an aqueous sample comprising a viral vector species is collected 4302. In certain embodiments, various pre-processing steps, such as smoothing, decimation, baseline correction (e.g., to account for water temperature drift, displacement of water, etc.), and the like, may be performed 1504. IR absorption spectra may then be used to determine sample quality metrics, such as protein content, nucleic acid content, viral capsid content and full capsid fraction 1506. In certain embodiments sample quality metrics such as these may be CQA’s, and / or used to determine one or more CQA’s and / or CPP’s. In certain embodiments, sample quality metrics and / or parameters determined therefrom may be displayed 1508a and / or stored in memory 1508c. In certain embodiments, a determined sample quality metric, such as a viral capsid content and / or full capsid fraction may be used to produce digital and / or analog electronic triggers signals 1508b, that can be used for, for example, feed-forward and / or feedback process control. For example, as described herein, processes such as flow rate, flow direction, pressures, temperatures, pH, etc. may be adjusted. In certain embodiments, trigger signals may be used to direct decisions such as when to stop a processing, open or close valves direct sample collection and fraction collection, e.g., to collect a particular fraction of sample eluting from a chromatography column comprising, e.g., high titer and / or high full capsid fraction.

[0437] Turning to FIGs.16A and 16B, such trigger signals may be used to various processing steps in production of viral vectors. FIGs.16A and 16B illustrate process flow for AAV and lentiviral vector production, respectively. Viral capsid content and / or full fraction may, accordingly, be monitored from aqueous sample, for example during the and / or various steps including production and subsequent steps.

[0438] For example, in-line measurements of viral vector full fraction (e.g., for AAV capsids, lentiviral capsids, and other) can be used to monitor separation of empty and full capsids during a chromatography polishing step. Chromatography polishing may, for example, utilize anion exchange (AEX) chromatography to separate empty capsids from full - 95 - 11677372v1Attorney Docket No. 2017297-0013capsids. In certain embodiments, other chromatography techniques, such as affinity chromatography (AC) column, a hydrophobic interaction chromatography (HIC) column, an ion exchange chromatograph (IEX) column, a size exclusion chromatography (SEC) column, and a mixed-mode chromatography column [e.g., which implements any combination of the foregoing (e.g., IEX and HIC; e.g., IEX and SEC)] may be used. In certain embodiments, in- line monitoring of aqueous sample as it elutes from a chromatography column can allow observation and / or control based on measured viral capsid content and / or full fraction to select particular target fractions of the eluate to retain or discard depending on desired target purity and / or yield.

[0439] Turning to FIG.17, in certain embodiments, reference spectra, as described herein, may be used to determine sample quality metrics. For example, as shown in FIG.17, in one example process 1700, raw spectral data may be converted into quantitative sample quality metrics, such as CQA’s, and then displayed, stored, or used to trigger process control. As shown in FIG.17, a raw IR absorption spectra from an aqueous sample comprising a viral vector species is collected 1702. In certain embodiments, various pre-processing steps, such as smoothing, decimation, baseline correction (e.g., to account for water temperature drift, displacement of water, etc.), and the like, may be performed 1704. In certain embodiments, raw spectra 1702, with or without preprocessing 1704, may be scaled 1706, for example to adjust overall amplitude. In certain embodiments, raw spectra may be scaled by a constant equal to and / or based on (e.g., determined using) one or more peak metrics, such as a peak amplitude, area under the curve, etc., computed for one or more particular absorption bands. A target spectrum may be compared to one or more reference spectra, such as high quality viral vector spectra, as described herein, to determine one or more sample quality metrics 1708. Comparison between target spectrum and reference spectrum may comprise computing a difference spectrum, a difference first derivative, a difference second derivative, a correlation, a covariance, a Pearson’s correlation, an overlap integral, etc. In certain embodiments, comparison between target spectra and reference spectra yields a comparison spectrum, such as a difference spectrum, which may in term be used to compute peak metrics and, ultimately, sample quality metrics. In certain embodiments, sample quality metrics may be computed based on target and reference spectra, without necessarily computing a comparison spectra, for example by computing a covariance, overlap integral, etc. In certain embodiments sample quality metrics such as these may be CQA’s, and / or used to determine one or more CQA’s and / or CPP’s. In certain embodiments, sample quality metrics and / or - 96 - 11677372v1Attorney Docket No. 2017297-0013parameters determined therefrom may be displayed 1710a and / or stored in memory 1710c. In certain embodiments, a determined sample quality metric, such as a viral capsid content and / or full capsid fraction may be used to produce digital and / or analog electronic triggers signals 1710b, that can be used for, for example, feed-forward and / or feedback process control. For example, as described herein, processes such as flow rate, flow direction, pressures, temperatures, pH, etc. may be adjusted. In certain embodiments, trigger signals may be used to direct decisions such as when to stop a processing, open or close valves direct sample collection and fraction collection, e.g., to collect a particular fraction of sample eluting from a chromatography column comprising, e.g., high titer and / or high full capsid fraction. Integration of MIR Analyzers into Production Units and / or Process Streams

[0440] In certain embodiments, one or more mid-IR analyzer(s) are incorporated into a production unit and / or the process stream, e.g., measuring liquid input and / or output from production units. In certain embodiments, one or more mid-IR analyzer(s) are incorporated into in-line, for example via a split stream whereby a portion of input / output stream is sampled through an analyzer and then returned to the main process stream for continued processing.

[0441] In certain embodiments, ATR sampling geometries offer advantages for integration with pilot and / or commercial scale manufacturing production units which rely on in / out-flow through large diameter channels, ranging from a millimeter or more to ¼ inch to an inch in diameter. In certain embodiments, transmission through more than 40 microns (e.g., more than 100 microns) may be impractical and, accordingly, ability of ATR geometries to provide a fixed, limited path-length via an evanescent wave, which is independent of the size of a channel through which liquid flows, dramatically facilitates integration with production scale systems. B.iv Control Signal Implementations

[0442] In certain embodiments, processing, communication, instrument control, and the like as described herein may be implemented in whole or in part via a variety of components associated with production units, central processing systems, or remote devices. For example, various processing, communication, and control steps may be carried out by - 97 - 11677372v1Attorney Docket No. 2017297-0013one or more of firmware embedded on one or more particular devices (e.g., mid-IR analyzers, other, complementary sensor systems, production unit controllers, etc.), software of a connected microprocessor system and / or an external computer, for example connected directly, via Ethernet, or cloud-based. In certain embodiments, a connected computer may control process parameters directly or may transmit and / or the data, process commands, control signals and the like one or more communication channels.

[0443] A variety of communication channels may be used, including, but not limited to, data packets shared over a communication network and / or communication port, an analog signal transmitted as a voltage or a current to a device that can decode the signal such as a PLC or another computer, a standardized communication protocol / system such as OPC-UA, Profibus, ModBus etc., or a dedicated proprietary communication channel. Communication channels may be wired or use wireless protocols such as Bluetooth, WiFI, RF, or other technologies. In certain embodiments, data and / or commands are encoded prior to being transmitted and / or shared and decrypted and used (e.g., to adjust process parameters) by a receiving device. C. Computer System and Network Environment

[0444] Turning to FIG.18, an implementation of a network environment 1800 for use in providing systems, methods, and architectures as described herein is shown and described. In brief overview, referring now to FIG.18, a block diagram of an exemplary cloud computing environment 1800 is shown and described. The cloud computing environment 1800 may include one or more resource providers 1802a, 1802b, 1802c (collectively, 1802). Each resource provider 1802 may include computing resources. In some implementations, computing resources may include any hardware and / or software used to process data. For example, computing resources may include hardware and / or software capable of executing algorithms, computer programs, and / or computer applications. In some implementations, exemplary computing resources may include application servers and / or databases with storage and retrieval capabilities. Each resource provider 1802 may be connected to any other resource provider 1802 in the cloud computing environment 1800. In some implementations, the resource providers 1802 may be connected over a computer network 1808. Each resource provider 1802 may be connected to one or more computing device 1804a, 1804b, 1804c (collectively, 1804), over the computer network 1808. - 98 - 11677372v1Attorney Docket No. 2017297-0013

[0445] The cloud computing environment 1800 may include a resource manager 1806. The resource manager 1806 may be connected to the resource providers 1802 and the computing devices 1804 over the computer network 1808. In some implementations, the resource manager 1806 may facilitate the provision of computing resources by one or more resource providers 1802 to one or more computing devices 1804. The resource manager 1806 may receive a request for a computing resource from a particular computing device 1804. The resource manager 1806 may identify one or more resource providers 1802 capable of providing the computing resource requested by the computing device 1804. The resource manager 1806 may select a resource provider 1802 to provide the computing resource. The resource manager 1806 may facilitate a connection between the resource provider 1802 and a particular computing device 1804. In some implementations, the resource manager 1806 may establish a connection between a particular resource provider 1802 and a particular computing device 1804. In some implementations, the resource manager 1806 may redirect a particular computing device 1804 to a particular resource provider 1802 with the requested computing resource.

[0446] FIG.19 shows an example of a computing device 1900 and a mobile computing device 1950 that can be used to implement the techniques described in this disclosure. The computing device 1900 is intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The mobile computing device 1950 is intended to represent various forms of mobile devices, such as personal digital assistants, cellular telephones, smart-phones, and other similar computing devices. The components shown here, their connections and relationships, and their functions, are meant to be examples only, and are not meant to be limiting.

[0447] The computing device 1900 includes a processor 1902, a memory 1904, a storage device 1906, a high-speed interface 1908 connecting to the memory 1904 and multiple high-speed expansion ports 1910, and a low-speed interface 1912 connecting to a low-speed expansion port 1914 and the storage device 1906. Each of the processor 1902, the memory 1904, the storage device 1906, the high-speed interface 1908, the high-speed expansion ports 1910, and the low-speed interface 1912, are interconnected using various busses, and may be mounted on a common motherboard or in other manners as appropriate. The processor 1902 can process instructions for execution within the computing device 1900, including instructions stored in the memory 1904 or on the storage device 1906 to display - 99 - 11677372v1Attorney Docket No. 2017297-0013graphical information for a GUI on an external input / output device, such as a display 1916 coupled to the high-speed interface 1908. In other implementations, multiple processors and / or multiple buses may be used, as appropriate, along with multiple memories and types of memory. Also, multiple computing devices may be connected, with each device providing portions of the necessary operations (e.g., as a server bank, a group of blade servers, or a multi-processor system). Thus, as the term is used herein, where a plurality of functions are described as being performed by “a processor”, this encompasses embodiments wherein the plurality of functions are performed by any number of processors (one or more) of any number of computing devices (one or more). Furthermore, where a function is described as being performed by “a processor”, this encompasses embodiments wherein the function is performed by any number of processors (one or more) of any number of computing devices (one or more) (e.g., in a distributed computing system).

[0448] The memory 1904 stores information within the computing device 1900. In some implementations, the memory 1904 is a volatile memory unit or units. In some implementations, the memory 1904 is a non-volatile memory unit or units. The memory 1904 may also be another form of computer-readable medium, such as a magnetic or optical disk.

[0449] The storage device 1906 is capable of providing mass storage for the computing device 1900. In some implementations, the storage device 1906 may be or contain a computer-readable medium, such as a floppy disk device, a hard disk device, an optical disk device, or a tape device, a flash memory or other similar solid state memory device, or an array of devices, including devices in a storage area network or other configurations. Instructions can be stored in an information carrier. The instructions, when executed by one or more processing devices (for example, processor 1902), perform one or more methods, such as those described above. The instructions can also be stored by one or more storage devices such as computer- or machine-readable mediums (for example, the memory 1904, the storage device 1906, or memory on the processor 1902).

[0450] The high-speed interface 1908 manages bandwidth-intensive operations for the computing device 1900, while the low-speed interface 1912 manages lower bandwidth- intensive operations. Such allocation of functions is an example only. In some implementations, the high-speed interface 1908 is coupled to the memory 1904, the display 1916 (e.g., through a graphics processor or accelerator), and to the high-speed expansion ports 1910, which may accept various expansion cards (not shown). In the implementation, - 100 - 11677372v1Attorney Docket No. 2017297-0013the low-speed interface 1912 is coupled to the storage device 1906 and the low-speed expansion port 1914. The low-speed expansion port 1914, which may include various communication ports (e.g., USB, Bluetooth®, Ethernet, wireless Ethernet) may be coupled to one or more input / output devices, such as a keyboard, a pointing device, a scanner, or a networking device such as a switch or router, e.g., through a network adapter.

[0451] The computing device 1900 may be implemented in a number of different forms, as shown in the figure. For example, it may be implemented as a standard server 1920, or multiple times in a group of such servers. In addition, it may be implemented in a personal computer such as a laptop computer 1922. It may also be implemented as part of a rack server system 1924. Alternatively, components from the computing device 1900 may be combined with other components in a mobile device (not shown), such as a mobile computing device 1950. Each of such devices may contain one or more of the computing device 1900 and the mobile computing device 1950, and an entire system may be made up of multiple computing devices communicating with each other.

[0452] The mobile computing device 1950 includes a processor 1952, a memory 1964, an input / output device such as a display 1954, a communication interface 1966, and a transceiver 1968, among other components. The mobile computing device 1950 may also be provided with a storage device, such as a micro-drive or other device, to provide additional storage. Each of the processor 1952, the memory 1964, the display 1954, the communication interface 1966, and the transceiver 1968, are interconnected using various buses, and several of the components may be mounted on a common motherboard or in other manners as appropriate.

[0453] The processor 1952 can execute instructions within the mobile computing device 1950, including instructions stored in the memory 1964. The processor 1952 may be implemented as a chipset of chips that include separate and multiple analog and digital processors. The processor 1952 may provide, for example, for coordination of the other components of the mobile computing device 1950, such as control of user interfaces, applications run by the mobile computing device 1950, and wireless communication by the mobile computing device 1950.

[0454] The processor 1952 may communicate with a user through a control interface 1958 and a display interface 1956 coupled to the display 1954. The display 1954 may be, for example, a TFT (Thin-Film-Transistor Liquid Crystal Display) display or an OLED (Organic - 101 - 11677372v1Attorney Docket No. 2017297-0013Light Emitting Diode) display, or other appropriate display technology. The display interface 1956 may comprise appropriate circuitry for driving the display 1954 to present graphical and other information to a user. The control interface 1958 may receive commands from a user and convert them for submission to the processor 1952. In addition, an external interface 1962 may provide communication with the processor 1952, so as to enable near area communication of the mobile computing device 1950 with other devices. The external interface 1962 may provide, for example, for wired communication in some implementations, or for wireless communication in other implementations, and multiple interfaces may also be used.

[0455] The memory 1964 stores information within the mobile computing device 1950. The memory 1964 can be implemented as one or more of a computer-readable medium or media, a volatile memory unit or units, or a non-volatile memory unit or units. An expansion memory 1974 may also be provided and connected to the mobile computing device 1950 through an expansion interface 1972, which may include, for example, a SIMM (Single In Line Memory Module) card interface. The expansion memory 1974 may provide extra storage space for the mobile computing device 1950, or may also store applications or other information for the mobile computing device 1950. Specifically, the expansion memory 1974 may include instructions to carry out or supplement the processes described above, and may include secure information also. Thus, for example, the expansion memory 1974 may be provide as a security module for the mobile computing device 1950, and may be programmed with instructions that permit secure use of the mobile computing device 1950. In addition, secure applications may be provided via the SIMM cards, along with additional information, such as placing identifying information on the SIMM card in a non-hackable manner.

[0456] The memory may include, for example, flash memory and / or NVRAM memory (non-volatile random access memory), as discussed below. In some implementations, instructions are stored in an information carrier. The instructions, when executed by one or more processing devices (for example, processor 1952), perform one or more methods, such as those described above. The instructions can also be stored by one or more storage devices, such as one or more computer- or machine-readable mediums (for example, the memory 1964, the expansion memory 1974, or memory on the processor 1952). In some implementations, the instructions can be received in a propagated signal, for example, over the transceiver 1968 or the external interface 1962. - 102 - 11677372v1Attorney Docket No. 2017297-0013

[0457] The mobile computing device 1950 may communicate wirelessly through the communication interface 1966, which may include digital signal processing circuitry where necessary. The communication interface 1966 may provide for communications under various modes or protocols, such as GSM voice calls (Global System for Mobile communications), SMS (Short Message Service), EMS (Enhanced Messaging Service), or MMS messaging (Multimedia Messaging Service), CDMA (code division multiple access), TDMA (time division multiple access), PDC (Personal Digital Cellular), WCDMA (Wideband Code Division Multiple Access), CDMA2000, or GPRS (General Packet Radio Service), among others. Such communication may occur, for example, through the transceiver 1968 using a radio-frequency. In addition, short-range communication may occur, such as using a Bluetooth®, Wi-Fi™, or other such transceiver (not shown). In addition, a GPS (Global Positioning System) receiver module 1970 may provide additional navigation- and location-related wireless data to the mobile computing device 1950, which may be used as appropriate by applications running on the mobile computing device 1950.

[0458] The mobile computing device 1950 may also communicate audibly using an audio codec 1960, which may receive spoken information from a user and convert it to usable digital information. The audio codec 1960 may likewise generate audible sound for a user, such as through a speaker, e.g., in a handset of the mobile computing device 1950. Such sound may include sound from voice telephone calls, may include recorded sound (e.g., voice messages, music files, etc.) and may also include sound generated by applications operating on the mobile computing device 1950.

[0459] The mobile computing device 1950 may be implemented in a number of different forms, as shown in the figure. For example, it may be implemented as a cellular telephone 1980. It may also be implemented as part of a smart-phone 1982, personal digital assistant, or other similar mobile device.

[0460] Various implementations of the systems and techniques described here can be realized in digital electronic circuitry, integrated circuitry, specially designed ASICs (application specific integrated circuits), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device. - 103 - 11677372v1Attorney Docket No. 2017297-0013

[0461] Actions associated with implementing the systems may be performed by one or more programmable processors executing one or more computer programs. All or part of the systems may be implemented as special purpose logic circuitry, for example, a field programmable gate array (FPGA) or an application-specific integrated circuit (ASIC), or both. All or part of the systems may also be implemented as special purpose logic circuitry, for example, a specially designed (or configured) central processing unit (CPU), conventional central processing units (CPU) a graphics processing unit (GPU), and / or a tensor processing unit (TPU).

[0462] These computer programs (also known as programs, software, software applications or code) include machine instructions for a programmable processor, and can be implemented in a high-level procedural and / or object-oriented programming language, and / or in assembly / machine language. As used herein, the terms machine-readable medium and computer-readable medium refer to any computer program product, apparatus and / or device (e.g., magnetic discs, optical disks, memory, Programmable Logic Devices (PLDs)) used to provide machine instructions and / or data to a programmable processor, including a machine- readable medium that receives machine instructions as a machine-readable signal. The term machine-readable signal refers to any signal used to provide machine instructions and / or data to a programmable processor.

[0463] To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the computer. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0464] The systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a client computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication - 104 - 11677372v1Attorney Docket No. 2017297-0013(e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), and the Internet.

[0465] The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.

[0466] In some implementations, modules described herein can be separated, combined or incorporated into single or combined modules. The modules depicted in the figures are not intended to limit the systems described herein to the software architectures shown therein.

[0467] Elements of different implementations described herein may be combined to form other implementations not specifically set forth above. Elements may be left out of the processes, computer programs, databases, etc. described herein without adversely affecting their operation. In addition, the logic flows depicted in the figures do not require the particular order shown, or sequential order, to achieve desirable results. Various separate elements may be combined into one or more individual elements to perform the functions described herein. E. Examples Example 1: Linearity Over Wide Dynamic Ranges and at High Concentrations.

[0468] This example demonstrates capabilities of a QCL-based IR spectrometer in accordance with certain embodiments described herein to measure protein concentrations in aqueous solutions over a wide dynamic range, and with a high degree of linearity. FIGs. 20A-D demonstrate measurement of IR spectra from several different protein mixtures, each comprising bovine serum albumin (BSA) at a particular concentration, along with graphs comparing QCL-measured concentration / related peak metrics with a-priori known concentration. FIG.20A shows several IR absorbance spectra measured for samples having different BSA concentrations. FIG.20B shows a value of measured concentration, determined by computing an AUC of a protein absorption region, by integrating each spectrum from a minimum frequency (around 1360 cm-1) to about 1700cm-1. The measured concentration was determined by scaling the determined AUC and displayed against nominal reference concentration in FIG.20B. FIGs.20C and 20D show similar measurements, with - 105 - 11677372v1Attorney Docket No. 2017297-0013FIG.20D displaying AUC directly against nominal BSA concentration and showing parameters of a linear fit, along with an R2value, indicating highly linear correlation. Accordingly, As shown in the graphs of FIG.20B and 20D, measured concentration closely matches the nominal concentration of the prepared samples and is highly linear, even at high concentrations. Example 2: Analytical Chromatography Measurements and Comparison with UV Absorption

[0469] This example demonstrates use of a mid-IR QCL-based spectrometer to record absorbance spectra in substantially real-time to monitor protein content of mobile phase flowing out of a chromatography column during elution. FIG.21 shows recording of mid-IR spectra over time, during an elution. FIGs.22A and 22B compare protein content as measured by UV absorbance (FIG.22A) with protein content measured via mid-IR absorbance (FIG.22B, showing AUC, computed as an integrated absorbance over Amide-I and Amide-II bands, variation over time). The mid-IR data sample quality metric – i.e., AUC – graphed in FIG.22B, shows lower temporal dispersion than the UV data, providing for more accurate elution monitoring and control. Example 3: Amide Sub-Band Deconvolution

[0470] This example demonstrates use of a mid-IR QCL-based spectrometer to record amide-band spectra of protein mixtures in aqueous solution and monitor changes in protein secondary structure as a function of temperature.

[0471] FIG.23A shows IR spectra of a 10mg / mL BSA solution measured while flowing at a rate of 400 μL / min, as temperature is varied (each curve obtained at a different time / temperature). FIG. 23B shows second derivative spectra determined from each of the spectra shown in FIG.23A. Second derivative spectra may be used to emphasize / monitor variations in protein secondary structure, which is reflected in changes in sub-peaks that make up the Amide band region. FIGs.23C and 23D show variations in secondary structure components such as alpha-helical, turn, beta-sheet, and disordered content as temperature is varied. In FIGs.23C and 23D, content of a particular secondary structure motif was measured by determining absorbance at a particular, nominal, frequency associated with a particular secondary structure motif. For example, as shown in FIG.23C, absorbance at 1618 - 106 - 11677372v1Attorney Docket No. 2017297-0013cm-1was used to measure beta sheet content, absorbance at 1692 cm-1was used to measure turn content, absorbance at 1656 cm-1was used to measure alpha-helix content, and absorbance at 1645 cm-1was used as a measure of unordered content.

[0472] Another approach for monitoring protein secondary content is shown in FIG. 24. FIG.24 shows heat maps that display Amide sub-band intensities as they vary with temperature increases from room temperature to about 75ºC for five different proteins. To compute each heat map, rather than monitor intensity at a fixed, nominal band position, Amide band spectra for each of the five proteins were de-convolved to allow particular peak frequencies and intensities of constituent sub-bands (e.g., indicative of various secondary structure motifs) to be determined directly from spectra recorded at each temperature, for each of the five proteins shown in FIG.24.

[0473] Among other things, tracking position of sub-bands associated with secondary structure motifs allows stability of proteins in different solutions / formulations to be observed and characterized. For example, comparing the two right most heat maps, shows differences in temperature stability for hen egg-white lysosome (HEWL) protein in phosphate buffer solution (PBS) versus acetate. For example, the HEWL in PBS shows a single relatively stable dominant peak over a wide range of lower temperatures, whereas the HEWL in acetate map shows meandering bands even at lower temperatures, indicative of lower stability.

[0474] Accordingly, this example demonstrates capability to monitor variations in protein secondary structure in substantially real time. Example 4: Protein Biophysical Characteristics Based on Isobestic Point

[0475] This example demonstrates how sample quality metrics that characterize protein density may be calculated using IR absorption spectra across and just above an Amide band region.

[0476] FIG.25 shows spectra of BSA at various concentrations. As described herein, amide band spectra can be used to determine a variety of information about a protein under study. The inset shows an expanded view of the spectra in the vicinity of 1700 cm-1. Without wishing to be bound to any particular theory, absorbance at a particular wavenumber of a protein in water sample, relative to (i.e., having been normalized to) a background spectrum of pure water, may be computed as indicated in FIG.25, where A is the absorbance - 107 - 11677372v1Attorney Docket No. 2017297-0013at a particular wavenumber, σpis the absorption cross section for protein, γ is the relative density of protein to water, σw is the absorption cross section for water, Cp(t1) is the concentration of protein (at the time measured) and L is the path length.

[0477] The protein absorption cross section, σp, is about zero for wavenumbers greater than about 1695 cm-1. Accordingly, above 1695 cm-1, A = - (γσw)⋅Cp(t1)⋅L. Protein still influences the absorption, but not because it absorbs light itself, but, instead, because it displaces water. Since σw is a known, physical constant and Cp(t1)⋅L can be measured (e.g., by integrating over the amide I and II regions), γ - the relative (to water) protein density - can be calculated.

[0478] Accordingly, this example demonstrates how a measure of protein density (relative to water) can be calculated from mid-IR spectra. In certain embodiments, other measures, such as hydrodynamic radius and diffusion constant can be calculated. Example 5: Baseline Correction During Elution Using Conductivity Sensors

[0479] This example shows baseline variations due to increased presence of ions in measurements recorded during elution of a chromatography column. FIG.26A shows variation in spectra before and after elution. FIG.26B shows variation in absorption with conductivity.

[0480] Without wishing to be bound to any particular theory, it is believed that the relatively flat shape of the water absorption curves shown in FIG.26A allow the position of the amide-II band, for example as computed by a center of mass frequency, to be insensitive to baseline fluctuations during an elution. Accordingly, this allows the Amide-II band to be used to measure protein structural changes without, in certain embodiments, having to precisely correct for baseline variations during elution. Example 6: Protein Aggregation Metrics from IR Absorption Spectra

[0481] This example demonstrates calculation of sample quality metrics that provide measures of protein aggregation in accordance with various embodiments described herein.

[0482] An absorption spectrum of a static or flowing aqueous mixture of proteins may be collected approximately over a range of about 800 cm-1to about 1800 cm-1, or any sub- - 108 - 11677372v1Attorney Docket No. 2017297-0013divided continuous or discontinuous range thereof. Such absorption spectra may be obtained using a variety of infrared absorption spectrometers, including, for example, Fourier transform infrared (FT-IR), quantum cascade laser infrared (QCL-IR) analyzers, etc.

[0483] FIG.27 shows a typical IR absorption spectrum of a protein measured in an aqueous buffer. The absorption spectrum of FIG.27 was computed using a reference background taken from a nominal zero-protein aqueous buffer. Protein infrared absorption spectra such as that shown in FIG.27 may be analyzed via one or more of the techniques described in this example to determine sample quality metrics indicative of protein heterogeneity, in particular, aggregation (protein aggregation metrics) as well as total protein content. These sample quality metrics may then be used to create a digital or analog signal that can be used for dynamic process control and / or process optimization.

[0484] In certain embodiments, sample quality metrics relating to protein content, heterogeneity, aggregation, and the like, may be computed based on properties of absorption peaks associated with an Amide-I and / or an Amide-II band in IR spectral data. Table 2, below, shows values of approximate ranges in the mid-IR for Amide-I and / or Amide-II spectral bands.

[0485] FIGs.28A and 28B illustrate a first protein aggregation metric computed as a particular peak metric – namely, a “center of mass” of an Amide II band approximately corresponding to a region from about 1500 to about 1600 cm-1(νCOM Amide-II). FIG.28A shows an example spectrum of a zero aggregation state (e.g., all monomer). FIG.28B shows a spectrum of a 5% by mass aggregation state, showing that a center of mass of an Amide II band changes in proportion to a relative concentration of aggregates. A nominal Amide II center of mass for a high-purity protein (e.g. monoclonal antibody) may be about 1546.2 cm- 1 (FIG.28A), whereas protein aggregates or fragments could be higher or lower than this nominal center-of-mass value by plus or minus 0.5 cm-1(FIG.28B). Small frequency shifts such as this can readily be observed using high-performance QCL-based infrared based mid- IR analyzers. - 109 - 11677372v1Attorney Docket No. 2017297-0013Table 2: Approximate Ranges for Amide-I and Amide-II Bands Spectral Band Approximate Range 1 Approximate Range 2 Approximate Range 3 Amide I 1575 to 1725 cm-1 1600 to 1700 cm-1 1625 to 1675 cm-1 Amide II1475 to 1625 cm-1 1500 to 1600 cm-1 1525 to 1575 cm-1

[0486] Among other things, the Amide-II center of mass frequency has been found to be relatively insensitive to baseline fluctuations during elution, which allows it to serve as a useful metric even in the absence of precise baseline correction. Moreover, the Amide-II center of mass frequency has been found to be relatively stable within a small range for measurements of monomeric protein species, but deviates from its stable range once aggregated protein, such as dimers or multimers, is present. Accordingly, in certain embodiments, a value of an Amide-II band may be calibrated for a particular protein (this may be done before or during an elution) and then used as a trigger, e.g., when it deviates from a stable range, to indicate presence of aggregates.

[0487] FIGs.29A and 29B shows a second protein aggregation metric computed as a ratio of two peak metrics. A first, Amide-I, peak metric characterizes an Amide-I band and is computed as an area under the curve (AUC) for the Amide-I band (corresponds to the region of 1600 to 1700 wavenumbers), and Amide-II, peak metric characterizes an Amide-II band and is computed as an area under the curve (AUC) for the Amide-II band (approximately corresponds to the region of 1500 to 1600 wavenumbers). Second protein aggregation metric RAmide-I to Amide-II is then computed as the ratio of the Amide-I AUC to the Amide II AUC (alternatively, Amide II to Amide I). Typical values for the ratio are provided in Tables 3A and 3B, below. High-purity protein monomers typically have ratios in the range of 1.2 to 1.6. Aggregates typically have ratios between 0.8 and 1.0 and fragments have ratios between 0.4 and 0.7. Table 3A: Ranges and typical values for four peak metrics Meas. Units Approximate Approximate Approximate Typical- 110 - 11677372v1Attorney Docket No. 2017297-0013RAmideI to Ratio (a.u.) 0.0 – 10.0 0.0 – 3.0 0.0 – 2.0 1.3 – 1.6 Amide I ATable 3B: Examples of possible values for four peak metrics Meas. Value Units Examples of possible values νCOM-Amide-II Wavenumber 1475, 1485.1, 1500.3, 1510, 1515, 1517, 1525, 1535, 1553, ,

[0488] A third embodiment (FIGs.30A and 30B) involves computing the ratio of the peak heights of Amide I to Amide II (alternatively, Amide II to Amide I) where the Amide I band approximately corresponds to the region of 1600 to 1700 wavenumbers and Amide II band approximately corresponds to the region of 1500 to 1600 wavenumbers. Typical values for the ratio are provided in FIG.26A. High-purity protein monomers typically have ratios in the range of 1.2 to 1.6. Aggregates typically have ratios between 0.8 and 1.0 and fragments have ratios between 0.4 and 0.7.

[0489] It was found that first aggregation metric – νCOM Amide-II provided highest correlation with aggregation level and performance as a quantitative measure of % aggregation.

[0490] Turning to FIG.31, total protein content was measured using a total area under the curve for the Amide-I and Amide-II bands.

[0491] Turning to FIGs.32A and 32B, these sample quality metrics may then be used to create a digital or analog signal that can be used for dynamic process control and / or process optimization. For example, FIG.32B is an illustrative sketch showing anticipated (hypothetical) variation in sample quality metrics that measure total protein content and protein aggregation, as described herein, over time, during elution from an IEX - 111 - 11677372v1Attorney Docket No. 2017297-0013chromatography column. The solid (black) curve shows anticipated variation in value of a total protein content metric, computed by integrating over an Amide-I and Amide-II band region, as described in FIG.31. Total protein content is expected to peak as monomeric protein begins to elute from a column. Dashed (black) curve shows protein content as would be measured via UV absorption, which mirrors variation in the mid-IR measurement. Dash- dot (red) curve shows anticipated variation in a protein aggregation metric, such as νCOM Amide-II. Protein aggregation metric curve peaks initially 3202 as low molecular weight species, such as fragments, are eluted first, and then reaches and stays at a relatively stable value over a period of time 3204 as high purity monomer elutes, after which its value shifts to reflect elution of higher molecular weight species, such as dimers, trimers, etc.3208. In certain embodiments, as illustrated in FIG.32B, it is expected that use of a protein aggregation metric such as νCOM Amide-II, may allow for collection over an additional time period 3206 during which a total protein content metric, measured either by IR absorption spectroscopy or UV absorption, begins to decrease, but high purity monomer continues to elute, thereby improving yield. Additional discussion of process control based on protein aggregation metrics is provided in Example 10, below. Example 7: Protein Identification and Metric Development Workflows

[0492] This example shows illustrative embodiments of example workflows that can be used to create sample quality metrics and identification reference spectra.

[0493] FIGs.33A and 33B show an example methodology for creating a protein identification method. FIG.33C provides a schematic showing a non-limiting list of functional modules and sample quality metrics that can be used to evaluate bioproduction process control in accordance with various embodiments described herein. Example 8: Downstream Purification Process Monitoring and Control

[0494] This example provides an example control strategy based on measurement of multiple sample quality metrics in order to provide real time control of collection start / stop based on protein purity. Turning to FIG.34A, in one example control strategy, two sample quality metrics are monitored in real-time – a total protein content metric and a protein aggregation metric, for example a total Amide band AUC and an Amide-II center of mass as described in Example 6. These two metrics may be used to compute an output analog - 112 - 11677372v1Attorney Docket No. 2017297-0013voltage that triggers start and stop collection of a desired elution fraction that optimizes purity (e.g., in terms of monomer) collected.

[0495] In particular, FIG.34A shows variation of voltage signals used to control a chromatography elution in an IEX column over time. A first, top-most trace shows a signal that initiates a conductivity ramp to begin elution. A second trace from the top shows a signal that triggers a mid-IR analyzer to record a reference background spectrum, e.g., of water absorbance. As indicated in the figure, the background spectrum is recorded just before the conductivity ramp begins. Following the initiation of the conductivity ramp, the figure shows a short time period 3402 (shaded light blue region) before protein begins to elute, while conductivity is increased. This time period may be used to calibrate a conductivity dependent baseline removal function (e.g., depending one amount of water displaced for a given conductivity level), if desired. A third trace from the top shows variation in an analog voltage output that measures total protein content. This voltage output may, for example, be used to trigger a start of collection, as it rises and stabilizes once pure monomer begins to elute. Below the total protein content voltage trace is an analog voltage trace proportional to an Amide-II center of mass frequency (computed as described in Example 6, above). As shown in the figure, this voltage is stable while predominantly monomeric protein is eluting, and then deviates from its table value once dimer begins to elute. Accordingly, the Amide-II center of mass voltage can be used to trigger a stop to collection.

[0496] Turning to FIG.34B, in certain embodiments, additional sample quality metrics may be computed and used to further refine and / or optimize collection windows. For example, in certain embodiments an “other species” protein metric may be computed. In certain embodiments, sample quality metrics that measure content of low molecular weight (e.g., fragments) and high molecular weight species may be computed and used to generate analog and / or digital control signals. Example 9: Downstream Filtration Process Monitoring

[0497] This example demonstrates use of systems and methods as described herein to perform accurate real-time quantitation of protein from 1 to 300+ g / L, provide real-time quantitation and control of buffer stoichiometry, and to provide real-time monitoring of protein aggregation and / or structural changes (e.g., denaturation). - 113 - 11677372v1Attorney Docket No. 2017297-0013

[0498] FIG.35 shows data created via several sequential injections in a TFF system, including Amide-I sub-band deconvolution heatmaps that can be used to visualize secondary structure variations and a total protein concentration. Visualizing secondary structure variation, in either filtrate and / or retentate from a TFF system can be used to optimize a filtration or buffer exchange process, for example to determine if protein aggregation or degradation in secondary structure is occurring. Example 10: Broad Spectral Coverage and Low Noise QCL Systems

[0499] This example demonstrates improved performance QCL mid-IR analyzer systems in accordance with certain embodiments described herein. For example, FIG.36 shows use of multiple QCL’s to obtain continuous coverage from about 1025 cm-1to about 1725 cm-1. FIG.37 shows capabilities for > 10X sensitivity improvements. Example 11: Simultaneous Measurement of Multiple Analytes

[0500] This example demonstrates simultaneous measurement of multiple analyzes in solution via a QCL-based mid-IR spectrometer in accordance with certain embodiments described herein.

[0501] FIGs.38A and 38B show measured absorbance spectra for several example analytes in solution, and FIGs.39A and 39B demonstrate excellent linearity for glucose in water (FIG.39A) and ammonia in water (FIG.39B). FIG.40A and 40B shows ability to identify and measure, at high degree of linearity (RMS concentration error ~ 10 micrograms / mL), target analytes in complex mixtures (e.g., in presence of other analytes). Example 12: Formulation Development and Forced Degradation

[0502] This example demonstrates use of mid-IR absorption spectroscopy to observe variations in protein secondary structure over time, for example relevant to formulation development.

[0503] FIG.41A shows variations in protein Amide band spectra as temperature is varied. Without wishing to be bound to any particular theory, IR spectra (e.g., when measured at sufficient sensitivity and / or spectral resolution) in the ~ 1750 cm-1 – 1300 cm-1- 114 - 11677372v1Attorney Docket No. 2017297-0013range provide rich information about intermolecular interactions with side chains and NH bending from Amide-II peaks.

[0504] FIG.41B shows a view of the Amide-I band region of the spectra shown in FIG.41A, and FIG.41C shows second derivative spectra over the Amide-I band region, illustrating, among other things, changes in secondary structure such as relative decreases in alpha helical content and increasing turn content.

[0505] FIG.42 shows a spectrum of a 10 mg / ml mAb in a particular formulation buffer (blue) together with a deconvolution of constituent sub bands (red curves).

[0506] FIG.43A shows variation in Amide-I band structure for a mAb with a high beta sheet content as temperature is increased from 25C to 80C. The central panel is a heat map showing changes in sub-band intensities with temperature. FIG.43B summarizes changes in secondary structure motifs and content as temperature is increased, as indicated via overlaid trajectories on the heat map. Example 13: Data Automation and Stability

[0507] This example demonstrates automation capability and reproducibility and applicability of mid-IR analyzers as described in certain embodiments herein, relevant, for example, for GMP-compliant bioproduction.

[0508] FIG.44 shows an example analysis system with multiple mid-IR analyzers stacked and linked together and connected to a central computer. In certain embodiments, the mid-IR system is connected to a processor that allows workflow management of multiple instruments and fluid handlers. In certain embodiments, the system provides for automated self-check for wavelength accuracy and optical power. In certain embodiments, the systems comprise an alarm system for leaks and / or volatile compounds. In certain embodiments, the systems comprise OPC-UA secure communication and instrument control interface, allowing for 21 CFR P11 compliance.

[0509] FIG.45A-45E show results of several tests of reproducibility, including, among other things, high reproducibility over sequential injections, and repeated sets of injections over multiple days. - 115 - 11677372v1Attorney Docket No. 2017297-0013Example 14: Independent Protein and Nucleic Acid Quantification and Viral Capsid Titer and Full Fraction Metrics

[0510] This example demonstrates use of a QCL-based mid-IR analyzer to independently quantify protein and nucleic acid content, and describes several example approaches whereby protein and nucleic acid content metrics can be used to determine viral capsid concentration and full fraction.

[0511] In particular, as described herein, Amide-I, Amide-II, and Amide-III bands may be used to measure protein content in a sample, for example based on a peak intensity metric, such as a peak amplitude or AUC, measured across one or more of an Amide-I, Amide-II, and Amide-III spectral region. Likewise, content of nucleic acid in a sample may be determined using peak intensity metrics for antisymmetric and / or symmetric PO4bands. In the context of a viral vector sample, comprising a protein capsid encapsulating a genetic payload, protein content measures computed from Amide-I, II, and / or III spectral bands may, accordingly, provide a measure of total capsid content, while nucleic acid content can be used to confirm presence of genetic payload and compared with capsid content to determine an full capsid fraction.

[0512] FIGs.46A and 46B demonstrate potential for independent quantification of nucleic acid (DNA in this example) and protein content within a mixture. FIG.46A plots absorbance spectra measured from pure samples of nucleic acid and protein, in particular, ssDNA and bovine serum albumin (BSA). In accordance with various embodiments described herein, DNA solution spectrum includes absorption peaks within asymmetric and symmetric PO4 bands, as well a feature in an Amide-I region, arising, without wishing to be bound to any particular theory, from presence of C=O groups in nucleic acid bases (see, e.g., FIG.46C). BSA solution spectrum includes Amide-I and Amide-II spectral features. In accordance with certain embodiments described herein, as shown in FIG.46A, absorption features of both protein and nucleic acid overlap in the Amide-I spectral region, whereas in the Amide-II region, the BSA solution spectrum includes an absorption peak while DNA solution spectrum remains negligible and relatively flat, indicating usefulness of Amide-II peak intensity for quantification of protei...

Claims

Attorney Docket No. 2017297-0013What is claimed is:

1. A method for obtaining a purified sample of a target protein species via real-time monitoring of protein heterogeneity and (e.g., automated; e.g., semi-automated) control of purification processing, the method comprising: (a) measuring, via one or more mid-infrared (MIR) analyzer(s), at each of one or more time points, a corresponding infrared (IR) absorbance signal from an aqueous sample exiting from a purification unit (e.g., a chromatography column), the aqueous sample comprising one or more protein species including the target protein species; (b) receiving, by a processor of a computing device, IR absorbance data corresponding to the IR absorbance signal(s) at each of the one or more time points; (c) determining, by the processor, values of one or more sample quality metrics based on the IR absorbance data, the one or more sample quality metrics comprising a protein aggregation metric indicative of a level of protein aggregation within the aqueous sample; and (d) using the one or more sample quality metrics to control collection of a target fraction of the aqueous sample (e.g., during a particular collection window), thereby obtaining the purified sample of the target protein species.

2. The method of claim 1, wherein the purification unit is or comprises a chromatography column.

3. The method of claim 2, wherein the chromatography column is a member selected from the group consisting of an affinity chromatography (AC) column, a hydrophobic interaction chromatography (HIC) column, an ion exchange chromatograph (IEX) column, a size exclusion chromatography (SEC) column, and a mixed-mode chromatography column [e.g., any combination of the foregoing (e.g., IEX and HIC; e.g., IEX and SEC)].

4. The method of any one of the preceding claims, wherein the target protein species is or comprises one or more members selected from the group consisting of a monoclonal - 137 - 11677372v1Attorney Docket No. 2017297-0013antibody (mAb), a fusion protein, a viral capsid protein, an antibody-drug conjugate, a recombinant protein, and a plasmatic protein.

5. The method of any one of the preceding claims, wherein the target protein species is or comprises a peptide chain and / or a protein fragment.

6. The method of any one of the preceding claims, wherein the aqueous sample comprises a plurality of different protein species.

7. The method of any one of the preceding claims, wherein the aqueous sample comprises a heterogeneous population of the target protein species, comprising a monomeric portion and an aggregated portion.

8. The method of any one of the preceding claims, wherein the target protein species is a sub-species of a particular protein species, the target protein species having a particular desired level and / or type of molecular conjugation (e.g. glycan, small-molecule drug, polyethylene glycol, etc.).

9. The method of any one of the preceding claims, wherein at least one of the one or more MIR analyzers is or comprises a MIR spectrometer comprising: a MIR source aligned and operable to emit a beam of MIR light [e.g., comprising a range of wavelengths substantially within the MIR spectral range (e.g., ranging from about 5000 cm-1to about 500 cm-1(e.g., about 2 to 20 microns))]; one or more sampling optics, aligned to direct and / or allow passage of the beam of MIR light, and / or at least a portion thereof, through and / or into contact with at least a portion of the aqueous sample [e.g., wherein the beam of MIR light contacts the portion of the aqueous sample via reflection at an interface between a solid material (e.g., an ATR crystal and / or optical fiber) and the aqueous sample (e.g., wherein the beam of MIR light undergoes total internal reflection, and contacts / probes the portion of the aqueous sample via an - 138 - 11677372v1Attorney Docket No. 2017297-0013evanescent wave extending into the aqueous sample)] and, following passage through or contact with the portion of the aqueous sample, towards one or more detectors; and the one or more detectors, aligned and operable to detect the beam of MIR light following its passage through and / or contact with the aqueous sample.

10. The method of claim 9, wherein: the one or more sampling optics comprise a high-refractive index material (e.g., an ATR crystal; e.g., an optical fiber) aligned such that the beam of MIR light is directed towards, incident upon, and reflected internally (e.g., back within the high-refractive index material) by an interface between the high-refractive index material and the aqueous sample (e.g., such that the beam of MIR light is incident upon the interface at an angle above a critical angle for total internal reflection); and the one or more detectors are aligned and operable to detect the beam of MIR light exiting from, following its internal reflection by, the high-refractive index material.

11. The method of claim 10, wherein the high-refractive index material is an ATR crystal.

12. The method of claim 10, wherein the high-refractive index material is an optical fiber.

13. The method of any one of claims 9 to 12, wherein: the one or more sampling optics comprise a flow cell comprising a detection channel through which the aqueous sample flows; and the one or more detectors are aligned and operable to detect the beam of MIR light exiting from, following its transmission through, the detection channel.

14. The method of claim 13, wherein a path length (e.g., followed by the beam of MIR light upon transmission) through the detection channel is about 10 μm or greater (e.g., about or at least 15 μm or greater; e.g., about 25 μm or greater; e.g., about 30 μm or greater; e.g., about 40 μm or greater; e.g., about 50 μm or greater). - 139 - 11677372v1Attorney Docket No. 2017297-001315. The method of any one of claims 9 to 14, wherein the one or more MIR analyzer(s) is or comprises a quantum cascade laser (QCL)-based MIR spectrometer comprising a QCL source operable to emit a beam of MIR light [e.g., comprising a range of wavelengths substantially within the MIR spectral range (e.g., ranging from about 5000 cm-1to about 500 cm-1(e.g., about 2 to 20 microns))].

16. The method of any one of claims 9 to 15, wherein (e.g., the MIR source is a laser and) the beam of MIR light has spectral line width of about 4 cm-1or less (e.g., about 2 cm-1or less; e.g., about 1 cm-1or less; e.g., about 0.5 cm-1or less).

17. The method of any one of claims 9 to 16, wherein a power of the beam of MIR light is about 1 mW or greater (e.g., about 10 mW; e.g., about 50 mW or greater; e.g., about 100 mW or greater; e.g., about 500 mW or greater; e.g., about 1000 mW or greater).

18. The method of any one of claims 9 to 17, wherein a spectral resolution of the MIR spectrometer is about 4 cm-1or better (e.g., less) [e.g., about 2 cm-1or better (e.g., less); e.g., about 1 cm-1or better (e.g., less); e.g., about 0.5 cm-1or better (e.g., less); e.g., about 0.25 cm- 1 or better (e.g., less); e.g., about 0.1 cm-1or better (e.g., less); e.g., about 0.05 cm-1or better (e.g., less)].

19. The method of any one of claims 9 to 18, wherein an (e.g., frequency / wavelength) accuracy of the MIR spectrometer is about 2 cm-1or better (e.g., less) [e.g.; about 1 cm-1or better (e.g., less); e.g., about 0.5 cm-1or better (e.g., less); e.g., about 0.25 cm-1or better (e.g., less); e.g., about 0.1 cm-1or better (e.g., less); e.g., about 0.01 cm-1or better (e.g., less)].

20. The method of any of claims 9 to 19, wherein a (e.g., frequency / wavelength) repeatability of the MIR spectrometer is about 0.5 cm-1or better (e.g., less) [e.g., about 0.25 cm-1or better (e.g., less); e.g., about 0.1 cm-1or better (e.g., less); e.g., about 0.05 cm-1or better (e.g., less); e.g., about 0.001 cm-1or better (e.g., less)]. - 140 - 11677372v1Attorney Docket No. 2017297-001321. The method of any one of claims 9 to 20, wherein the MIR source is a tunable laser (e.g., a tunable QCL) (e.g., operable sweep an emission frequency of the beam of MIR light through a plurality of frequencies across a scan range), and the method comprises, at each of the one or more time points: sweeping an emission frequency of the beam MIR light across a scan range of the tunable laser, thereby illuminating the aqueous sample with a plurality of emission frequencies; and detecting, with the one or more detectors, the beam of MIR light (e.g., having been (i) internally reflected by an interface between the high-index material and the aqueous sample and / or (ii) transmitted through the detection channel through which the aqueous sample flows) at each of the plurality of emission frequencies, thereby measuring, as the corresponding infrared (IR) absorbance signal from the aqueous sample, a corresponding IR spectrum comprising a plurality of values, each associated with and representing and / or based on a detected power at a particular one of the plurality of emission frequencies.

22. The method of claim 21, wherein the plurality of emission wavelengths comprises one or more wavelengths within a spectral band ranging from about 1800 to about 800 cm-1(e.g., from about 1725 to about 1025 cm-1; e.g., from about 1750 to about 1350 cm-1; e.g., from about 1725 to about 1375 cm-1; e.g., from about 1700 to about 1500 cm-1; e.g., from about 1700 to about 1600 cm-1; e.g., from about 1700 to about 1000 cm-1).

23. The method of claim 22, wherein the plurality of emission wavelengths comprise one or more wavelengths within a spectral band ranging from about 1600 cm-1to about 1500 cm- 1.

24. The method of any one of the preceding claims, wherein the MIR analyzer is an on- line sensor (e.g., as opposed to an off-line or at-line sensor) that measures the IR absorbance signal in substantially real-time, as the aqueous solution exits from the purification unit. - 141 - 11677372v1Attorney Docket No. 2017297-001325. The method of any one of the preceding claims, wherein the IR absorbance data comprises, for each of the one or more time points, a corresponding Amide band spectrum [e.g., the Amide band spectrum comprising, for each particular wavelength of a plurality of sampled (e.g., emission) wavelengths within a range from about 1800 to about 800 cm-1, an associated absorption value representing a level of absorption, by a portion of the aqueous sample, at the particular wavelength].

26. The method of claim 25, wherein step (d) comprises determining, for each particular time point of at least a portion of the one or more time points, a corresponding value of the protein aggregation metric.

27. The method of claim 26, wherein, for each particular time point, determining the corresponding value of the protein aggregation metric comprises: computing, from the Amide band spectrum corresponding to the particular time point, a value of an Amide II peak metric that quantifies one or more properties of an Amide II band (e.g., a frequency position, a linewidth, an intensity) at the particular time point; and using the Amide II peak metric value to determine the corresponding value of the protein aggregation metric (e.g., wherein the protein aggregation metric is or is a function of the Amide II peak metric).

28. The method of claim 27, wherein the Amide II peak metric is a frequency position metric that quantifies a frequency about which the Amide II band is substantially centered at the particular time point [e.g., a center of mass frequency, a frequency of a maximal height of the Amide II band, a center frequency of a fitted peak function (e.g., a Gaussian, a Lorentz, etc.), etc.].

29. The method of claim 28, wherein the frequency position metric is a center of mass frequency for the Amide II band. - 142 - 11677372v1Attorney Docket No. 2017297-001330. The method of claim 26, wherein for each particular time point, determining the corresponding value of the protein aggregation metric comprises: computing, from the Amide band spectrum corresponding to the particular time point, a value of an Amide I peak metric that quantifies one or more properties of an Amide I band (e.g., frequency position, a linewidth, an intensity) at the particular time point; and using both the Amide I peak metric value and the Amide II peak metric value to determine the corresponding value of the protein aggregation metric (e.g., wherein the protein aggregation metric is a function of the Amide I peak metric and the Amide II peak metric).

31. The method of claim 30, wherein: the Amide I peak metric is a peak intensity metric that quantifies an intensity of the Amide I band at the particular time point (e.g., a peak height of the Amide I band, an area under the curve (AUC) for the Amide I band); the Amide II peak metric is a peak intensity metric that quantifies an intensity of the Amide II band at the particular time point (e.g., a peak height of the Amide I band, an area under the curve (AUC) for the Amide I band); and determining the value of the protein aggregation metric comprises computing (i) a ratio of the Amide I peak metric value to the Amide II peak metric value and / or (ii) a ratio of the Amide II peak metric value to the Amide I peak metric value.

32. The method of any one of the preceding claims, wherein the one or more sample quality metrics further comprises a total protein content metric indicative of a level of protein content within the aqueous sample.

33. The method of claim any one of the preceding claims, wherein step (d) comprises causing, by the processor, transmission of one or more trigger signals (e.g., voltages) to a controller unit of the purification unit. - 143 - 11677372v1Attorney Docket No. 2017297-001334. The method of claim 33, wherein the one or more trigger signals comprise an analog voltage signal having a time varying amplitude based on (e.g., substantially proportional to) a value of the protein aggregation metric.

35. The method of claim 33 or 34, wherein the one or more trigger signals comprise an analog voltage signal having a time varying amplitude based on (e.g., substantially proportional to) a value of a total protein content metric.

36. The method of any one of claims 33 to 35, wherein step (d) comprises one or both of: initiating, by the controller unit, based on the one or more trigger signals, collection of the target fraction of the aqueous sample [e.g., wherein a particular one of the one or more trigger signals is an analog signal and the controller unit initiates collection of the target fraction based on an amplitude of the analog signal (e.g., when it exceeds a particular threshold; e.g., when it drops below a particular threshold); e.g., wherein a particular one of the one or more trigger signals is a digital signal that triggers (e.g., by transitioning from a 0 voltage level to 1 voltage level or vice-a-versa) initiating collection of the target fraction] and stopping, by the controller unit, based the one or more trigger signals, collection of the target fraction of the aqueous sample [e.g., wherein a particular one of the one or more trigger signals is an analog signal and the controller unit stops collection of the target fraction based on an amplitude of the analog signal (e.g., when it exceeds a particular threshold; e.g., when it drops below a particular threshold); e.g., wherein a particular one of the one or more trigger signals is a digital signal that triggers (e.g., by transitioning from a 0 voltage level to 1 voltage level or vice-a-versa) stopping collection of the target fraction].

37. A method for real-time monitoring of protein aggregation in a sample, the method comprising: (a) repeatedly receiving, by a processor of a computing device, infrared (IR) absorbance data corresponding to IR absorbance signals measured at each of a plurality of time points, the IR absorbance data comprising, for each particular time point of the plurality of time points, a corresponding IR absorbance spectrum measured from the sample at the - 144 - 11677372v1Attorney Docket No. 2017297-0013particular time point and comprising a plurality of absorbance values, each associated with a particular wavenumber; (b) analyzing (e.g., automatically), by the processor, the IR absorbance data to obtain a real-time protein aggregation signal providing a measure of protein aggregation in the sample as a function of time, by, for each particular time point of the plurality of time points: determining, using the IR absorbance spectrum corresponding to the particular time point, values of one or more peak metrics for one or both of an Amide I band and an Amide II band; determining, using the values of the one or more peak metrics, a value of a protein aggregation metric indicative of a level of protein aggregation within the sample at the particular time point; and updating the real-time protein aggregation signal with the determined value of the protein aggregation metric for the particular time point; and (c) storing and / or providing, by the processor, the real-time protein aggregation signal for one or more of (i) further processing, (ii) display, and (iii) use as a control signal for adjusting one or more purification units (e.g., chromatography systems).

38. The method of claim 37, wherein step (b) comprises, for each particular time point, determining, as the value of the protein aggregation metric indicative of the level of protein aggregation within the sample at the particular time point, a value of a frequency position metric that quantifies a frequency about which the Amide II band is substantially centered at the particular time point [e.g., a center of mass frequency, a frequency of a maximal height of the Amide II band, a center frequency of a fitted peak function (e.g., a Gaussian, a Lorentz, etc.), etc.].

39. The method of claim 38, wherein the frequency position metric is a center of mass frequency for the Amide II band. - 145 - 11677372v1Attorney Docket No. 2017297-001340. The method of any one of claims 37 to 39, wherein step (b) comprises, for each particular time point: determining a value of an Amide I peak intensity metric that quantifies an intensity of the Amide I band at the particular time point (e.g., a peak height of the Amide I band, an area under the curve (AUC) for the Amide I band); determining a value of an Amide II peak intensity metric that quantifies an intensity of the Amide II band at the particular time point (e.g., a peak height of the Amide I band, an area under the curve (AUC) for the Amide I band); and determining, as the value of the protein aggregation metric, (i) a ratio of the Amide I peak metric value to the Amide II peak metric value and / or (ii) a ratio of the Amide II peak metric value to the Amide I peak metric value.

41. A method for mid-IR (MIR)-spectroscopy-based monitoring and control of a production unit for manufacture of a biological product (e.g., a protein; e.g., a virus) the method comprising: (a) measuring, via one or more (e.g., integrated) mid-infrared (MIR) analyzer(s) [e.g., MIR analyzer(s) as recited in any one of claims 9 to 24], at each of one or more time points, a corresponding infrared (IR) absorbance signal from an aqueous sample flowing to and / or from the production unit (e.g., and which comprises one or more inputs, output products, waste products, or in-progress products of the production unit); (b) receiving, by a processor of a computing device, IR absorbance data corresponding to the IR absorbance signal(s) at each of the one or more time points; and (c) using the received IR absorbance data to adjust one or more process parameters of: (i) the production unit and / or (ii) a second (e.g., upstream and / or downstream) production unit.

42. The method of claim 41, wherein the production unit is a purification unit.

43. The method of claim 42, wherein the purification unit is a member selected from the group consisting of an alternating tangential flow filtration (ATF) system, tangential flow - 146 - 11677372v1Attorney Docket No. 2017297-0013depth filtration (TFDF) system, tangential flow filtration (TFF) system, a chromatography column, a direct, or normal, flow filtration unit, an ultra-filtration unit, and a dia-filtration unit.

44. The method of claim 43, wherein the purification unit is a chromatography column {e.g., and wherein the chromatography column is a member selected from the group consisting of an affinity chromatography (AC) column, a hydrophobic interaction chromatography (HIC) column, an ion exchange chromatograph (IEX) column, a size exclusion chromatography (SEC) column, and a mixed-mode chromatography column [e.g., any combination of the foregoing (e.g., IEX and HIC; e.g., IEX and SEC)]}.

45. The method of claim 41, wherein the production unit is a bioreactor (e.g., a seed bioreactor; e.g., a production bioreactor).

46. The method of any one of claims 41 to 45, wherein the aqueous sample comprises one or more protein species selected from the group consisting of a monoclonal antibody (mAb), a fusion protein, a viral capsid protein, an antibody-drug conjugate, a recombinant protein, and a plasmatic protein.

47. The method of any one of claims 41 to 46, wherein the aqueous sample comprises a peptide chain and / or a protein fragment.

48. The method of any one of claims 41 to 47, wherein the aqueous sample comprises a plurality of different protein species.

49. The method of any one of claims 41 to 48, wherein the aqueous sample comprises a heterogeneous population of a target protein species, comprising a monomeric portion and an aggregated portion. - 147 - 11677372v1Attorney Docket No. 2017297-001350. The method of any one of claims 41 to 49, wherein the aqueous sample comprises one or more sub-species of a particular protein species, having a particular desired level and / or type of molecular conjugation (e.g. glycan, small-molecule drug, polyethylene glycol, etc.).

51. The method of any one of claims 41 to 50, wherein the aqueous sample comprises nucleic acid (e.g., DNA, RNA, mRNA, etc.).

52. The method of any one of claims 41 to 51, wherein the aqueous sample comprises one or more species of virus and / or virus-like particles [e.g., adeno-associated viral vectors (AAV); e.g., lentiviral vectors].

53. The method of any one of claims 41 to 52, wherein step (c) comprises using the IR absorbance data to determine values one or more sample quality metrics at each of the one or more time points (e.g., and adjusting the one or more process parameters based thereon).

54. The method of claim 53, wherein the one or more sample quality metrics comprise(s) a total protein content metric that quantifies a quantity and / or concentration of protein within the aqueous sample.

55. The method of claim 53 or 54, wherein the one or more sample quality metrics comprise(s) a protein aggregation metric indicative of a level of protein aggregation within the aqueous sample.

56. The method of any one of claims 53 to 55, wherein the one or more sample quality metrics comprise(s) one or more protein species metrics that identify presence and / or quantify content (e.g., absolute content; e.g., relative content) of one or more particular protein species within the aqueous sample. - 148 - 11677372v1Attorney Docket No. 2017297-001357. The method of any one of claims 53 to 56, wherein the one or more sample quality metrics comprise a protein conjugation metric that quantifies a level and / or type of molecular conjugation (e.g. glycan, small-molecule drug, polyethylene glycol, etc.).

58. The method of any one of claims 53 to 57, wherein the one or more sample quality metrics comprise one or more protein secondary structure metrics that quantify presence and or content of one or more protein secondary structure motifs (e.g., alpha-helical content, beta- sheet content, turn content, disordered content).

59. The method of any one of claims 53 to 58, wherein the one or more sample quality metrics comprise one or more nucleic acid content metrics that quantify a content of nucleic acid [e.g., a total content of nucleic acid (e.g., concentration (e.g., titer), mass per volume (e.g., mg / mL), number of particles per volume, number of viral genome copies, etc.); e.g., a total and / or relative content of one or more particular types of nucleic acid (e.g., DNA, RNA, ssDNA, dsDNA)] within the aqueous sample.

60. The method of any one of claims 53 to 59, wherein the one or more sample quality metrics comprise one or more viral content metrics that quantify a content of viral and / or virus like particles within the aqueous sample [e.g., a concentration (e.g., titer), mass per volume (e.g. mg / mL), number of (viral) particles per volume, etc.].

61. The method of any one of claims 53 to 60, wherein the one or more sample quality metrics comprise one or more empty / full metrics that quantify an content and / or relative fraction of empty and / or full viral vectors within the aqueous sample (e.g., percent, ratio, etc. of full viral vectors).

62. The method of any one of claims 53 to 61, wherein the one or more sample quality metrics comprise a capsid aggregation metric indicative of a level of capsid aggregation within the viral vector sample. - 149 - 11677372v1Attorney Docket No. 2017297-001363. The method of any one of claims 53 to 62, wherein the one or more sample quality metrics comprise a viral nucleic acid (e.g., viral DNA, RNA, etc.) content metric that differentiates the viral nucleic acid from the host cell proteins and host cell nucleic acid content.

64. The method of any one of claims 53 to 62, wherein at least a portion (e.g., one or more) of the sample quality metrics are computed based on one or more peak metrics that measure features of one or more absorption bands in IR spectral data {e.g., wherein each peak metric is associated with one or more particular spectral bands [e.g., a continuous range of wavelengths / wavenumbers (e.g., an Amide-I band, an Amide-II band, an Amide-III band, e.g.; an Amide region, spanning two or more of the Amide bands; e.g., an antisymmetric PO4 band; e.g.; a symmetric PO4 band)] and quantifies a particular structural feature [e.g., an intensity (e.g., a peak amplitude; e.g., an Area Under the Curve (AUC)); e.g., a linewidth; e.g., a frequency position (e.g., peak frequency; e.g., center of mass frequency)] of one or more absorption peaks within the particular spectral band}.

65. The method of any one of claims 53 to 64, wherein the IR absorbance data comprises: (i) one or more (e.g., a plurality of) Amide II absorbance value(s), associated with and measuring IR absorption (of the viral sample) at wavenumbers within an Amide II spectral band (e.g., ranging from about 1500 cm-1to about 1600 cm-1, e.g., ranging from about 1500 cm-1to about 1575 cm-1; e.g., ranging from about 1500 cm-1to about 1550 cm-1; e.g., ranging from about 1540 cm-1to about 1560 cm-1); and / or (ii) one or more (e.g., a plurality of) Amide III absorbance value(s), associated with and measuring IR absorption (of the viral sample) at wavenumbers within an Amide II spectral band (e.g., ranging from about 1250 cm-1to about 1350 cm-1, e.g., ranging from about 1250 cm-1to about 1325 cm-1; e.g., ranging from about 1275 cm-1to about 1325 cm-1; e.g., ranging from about 1280 cm-1to about 1300 cm-1).

66. The method of claim 65, wherein determining the one or more sample quality metrics comprises determining values of a protein content metric [e.g., concentration (e.g., titer)] that - 150 - 11677372v1Attorney Docket No. 2017297-0013quantifies protein content within the sample based at least in part on the Amide II and / or Amide III absorbance value(s).

67. The method of claim 66, comprising: determining a value of an Amide II peak metric based on the Amide II absorbance values and / or a value of an Amide III peak metric based on the Amide III absorbance values; and using the Amide II peak metric value and / or the Amide III peak metric value to determine the protein content metric value.

68. The method of claim 67, wherein the Amide II peak metric and / or the Amide III peak metric is a peak intensity metric that quantifies an intensity of the Amide II band and / or Amide III band, respectively [e.g., a peak height, an area under the curve (AUC), etc.].

69. The method of any one of claims 53 to 68, wherein the IR absorbance data comprises: (i) one or more (e.g., a plurality of) antisymmetric Phosphate Stretch (antisymmetric- PO4) absorbance value(s), associated with and measuring IR absorption (of the viral sample) at wavenumbers within an antisymmetric-PO4spectral band (e.g., ranging from about 1150 cm-1to about 1250 cm-1, e.g., ranging from about 1175 cm-1to about 1250 cm-1; e.g., ranging from about 1200 cm-1to about 1250 cm-1; e.g., ranging from about 1210 cm-1to about 1230 cm-1); and / or (ii) one or more (e.g., a plurality of) symmetric Phosphate Stretch (symmetric-PO4) absorbance value(s), associated with and measuring IR absorption (of the viral sample) at wavenumbers within a symmetric-PO4 spectral band (e.g., ranging from about 1000 cm-1to about 1100 cm-1, e.g., ranging from about 1050 cm-1to about 1100 cm-1; e.g., ranging from about 1075 cm-1to about 1100 cm-1; e.g., ranging from about 1075 cm-1to about 1085 cm-1).

70. The method of claim 69, wherein determining the one or more sample quality metric values comprises determining values of a nucleic acid (e.g., DNA, RNA, etc.) content metric - 151 - 11677372v1Attorney Docket No. 2017297-0013that quantifies nucleic acid content [e.g., concentration (e.g., titer)] within the sample based at least in part on the antisymmetric-PO4 and / or symmetric-PO4 absorbance value(s).

71. The method of claim 70, comprising: determining a value of an antisymmetric-PO4peak metric based on the antisymmetric-PO4 absorbance values and / or a value of an symmetric-PO4 peak metric based on the symmetric-PO4absorbance values; and using the antisymmetric-PO4peak metric value and / or the symmetric-PO4peak metric value to determine the nucleic acid content metric value.

72. The method of claim 71, wherein the antisymmetric-PO4 peak metric and / or the symmetric-PO4peak metric is a peak intensity metric that quantifies an intensity of the antisymmetric-PO4 band and / or symmetric-PO4 band, respectively [e.g., a peak height, an area under the curve (AUC), etc.].

73. The method of any one of claims 53 to 72, wherein determining the one or more sample quality metric values comprises determining (i) value(s) of a protein content metric [e.g., concentration (e.g., titer)] that quantifies protein content within the sample and (ii) values of a nucleic acid (e.g., DNA, RNA, etc.) content metric that quantifies nucleic acid content [e.g., concentration (e.g., titer)] within the sample, thereby independently quantifying total protein and nucleic acid content within the sample.

74. The method of claim 73, wherein determining the one or more sample quality metric values comprises determining a total capsid content based at least in part on (e.g., as a function of) the value(s) of the protein content metric.

75. The method of claim 73 or 74, wherein determining the one or more sample quality metric values comprises determining a full capsid fraction based at least in part on (e.g., as a function of) (i) the value(s) of the protein content metric and / or the total capsid content and (ii) the value(s) of the nucleic acid content metric. - 152 - 11677372v1Attorney Docket No. 2017297-001376. The method of any one of claims 53 - 75, wherein the IR absorbance data is or comprises one or more IR absorbance spectra, each IR absorbance spectra comprising, for each particular wavenumber of a plurality of wavenumber spanning a measured spectral band, a corresponding IR absorbance value representing a measure of absorption of IR light, by the aqueous sample, at the particular wavenumber.

77. The method of claim 76, wherein the measured spectral band spans one or more bands selected from the group consisting of an Amide II band, an Amide III band, an asymmetric- PO4 band, and a symmetric-PO4 band.

78. The method of any one of claims 53 - 77, comprising determining values of the one or more sample quality metrics for each of the one or more time points, thereby monitoring the one or more sample quality metrics over time.

79. The method of claim 78, comprising determining values of the one or more sample quality metrics in substantially real-time.

80. The method of any one of claims 53 to 79, wherein at least one particular sample quality metric of the one or more sample quality metrics is computed using a machine learning model that receives, as input, one or more IR spectra and generates the particular sample quality metric as output.

81. The method of any one of claims 53 to 80, wherein computing a particular sample quality metric comprises de-convolving an amide spectral region into sub-bands and / or computing a second derivative spectra. - 153 - 11677372v1Attorney Docket No. 2017297-001382. The method of any one of claims 53 to 81, wherein the IR absorbance data comprises an IR absorbance spectrum and wherein step (c) comprises: receiving (e.g., and / or accessing) one or more reference spectra, each measured from a corresponding (e.g., high-quality) reference sample [e.g., comprising a target viral vector species at high purity and / or concentration and / or one or more model constituents thereof (e.g., a model protein solution; e.g., a model ssDNA solution)]; and determining (e.g., automatically), the values of at least a portion of the one or more sample quality metrics using the IR absorbance spectrum and the one or more reference spectra [e.g., determining, as the values of the portion of the one or more viral vector sample quality metrics, one or more (e.g., a plurality) measure(s) of deviation between the reference spectra and the IR absorbance spectrum].

83. The method of claim 82, wherein the one or more reference spectra comprises a high- quality viral vector spectrum measured from a reference sample having a full capsid fraction (e.g., a-priori known; e.g., determined to be) at or above a particular threshold fraction.

84. The method of claim 83, wherein the threshold fraction is about 75% [e.g., about 80% (e.g., about 90%)].

85. The method of any one of claims 82 to 84, wherein step (c) comprises computing a difference spectrum based on at least one of the one or more reference spectra and the IR absorbance spectrum (e.g., by subtracting an IR absorbance spectrum, and / or a scaled or otherwise pre-processed version thereof, from a reference spectrum, and / or a scaled or otherwise pre-processed version thereof, or vice-versa).

86. The method of any one of claims 82 to 85, wherein step (c) comprises computing one or more derivative spectra (e.g., a first derivative; e.g., a second derivative) of at least one of the one or more reference spectra and / or the IR absorbance spectrum. - 154 - 11677372v1Attorney Docket No. 2017297-001387. The method of any one of claims 82 to 86, wherein step (c) comprises computing (e.g., as values of one or more of the sample quality metrics) one or more members selected from the group consisting of: a correlation value based on a correlation of (i) a particular one of the one or more reference spectra and / or one or more derivatives thereof, and (ii) the IR absorbance spectrum and / or one or more derivatives thereof; a covariance value based on a covariance of (i) a particular one of the one or more reference spectra and / or one or more derivatives thereof, and (ii) the IR absorbance spectrum and / or one or more derivatives thereof; a Pearson’s correlation value between (i) a particular one of the one or more reference spectra and / or one or more derivatives thereof, and (ii) the IR absorbance spectrum and / or one or more derivatives thereof; and an overlap integral value based on an overlap integral of (i) a particular one of the one or more reference spectra and / or one or more derivatives thereof, and (ii) the IR absorbance spectrum and / or one or more derivatives thereof.

88. The method of any one of claims 82 to 87, wherein step (c) comprises: determining values for a set of one or more particular peak metrics from the IR absorbance spectrum, thereby obtaining a set of sample peak metric values; and determining values of one or more of the sample quality metrics based the set of sample peak metric values and a set of reference peak metric values having been determined for the one or more particular peak metrics from the one or more reference spectra.

89. The method of any one of claims 82 to 88, comprising determining (e.g., as one or more of the sample quality metric values) a similarity score that measures a similarity between the one or more reference spectra and the IR absorbance spectrum. - 155 - 11677372v1Attorney Docket No. 2017297-001390. The method of any one of claims 82 to 89, comprising performing steps (a) – (d) repeatedly, in substantially real-time, thereby monitoring deviation from the one or more reference spectra in real-time.

91. The method of any one of claims 53 to 90, wherein the one or more time points are a plurality of time points [e.g., step (a) comprises (e.g., repeatedly) measuring an IR absorption signal at each of a plurality of time points (e.g., continuously, in real time)].

92. The method of claim 91, comprising determining values of a first sample quality metric at each of the plurality of time points and determining a value of a second (e.g., time differential; e.g., time aggregated) sample quality metric using values of the first sample quality metric corresponding to two or more of the plurality of time points.

93. The method of claim 92, wherein the second sample quality metric is a time differential metric that measure a temporal change in the first sample quality metric and is computed based on a difference between (i) value(s) of the first sample quality metric at a first set of time point(s) and (ii) value(s) of the first sample quality metric at a second set of time point(s) [e.g., a difference between a value of the first sample quality metric at a first (e.g., current) time point and a value of the first sample quality metric at a second (e.g., prior) time point (e.g., a difference between values at consecutive time points)].

94. The method of claim 92 or 93, wherein the second sample quality metric is a (e.g., real-time) time-aggregated signal that is a function of at least a portion [e.g., a cumulative, increasing portion, e.g., beginning at a particular time point and ending at a current time point; e.g., a temporal window of a particular size (e.g., a backward looking window)] of the plurality of time points (e.g., a running sum, mean, median, mode, variance, standard deviation, etc. over a particular time window). - 156 - 11677372v1Attorney Docket No. 2017297-001395. The method of any one of claims 41 to 94, wherein step (c) comprises causing, by the processor, transmission of one or more trigger signals (e.g., voltages) to a controller unit of the production unit.

96. The method of claim 95, wherein the one or more trigger signals comprise an analog voltage signal having a time varying amplitude based on (e.g., substantially proportional to) values of at least a portion of one or more sample quality metric values.

97. The method of any one of claims 41 to 96, wherein step (c) comprises using a machine learning model to adjust the one or more process parameters [e.g., wherein the machine learning model receives one or more sample quality metrics as input and generates an adjustment to and / or a target process parameter as output; e.g., wherein the machine learning model receives one or more IR spectra as input and generates an adjustment to and / or a target process parameter as output].

98. The method of any one of claims 41 to 97, wherein the one or more process parameters comprise one or more members selected from the group consisting of a flow rate, a flow direction a pressure, a temperature, and a pH.

99. The method of any one of claims 41 to 98, wherein the one or more process parameters comprise an amount (e.g., absolute and / or relative) of one or more raw materials (e.g., used as input to the production unit).

100. The method of any one of claims 41 to 99, wherein the one or more process parameters comprise a time to initiate and / or halt a sub-process (e.g., heating, collection of an eluted fraction, growth, etc.).

101. The method of any one of claims 41 to 100, wherein: the one or more IR absorbance signal(s), to which the IR absorbance data received at step (b) corresponds, is / are measured from the aqueous sample, at each of one or more time - 157 - 11677372v1Attorney Docket No. 2017297-0013points, as it (the aqueous sample) exits from a purification unit (e.g., a chromatography column); and the method comprises: using the IR absorption data to determine one or both of (i) a total capsid content and (ii) a full capsid fraction; and using the determined total capsid content and / or full capsid fraction to control collection of a target fraction of the aqueous sample (e.g., during a particular collection window), thereby obtaining a purified sample of viral vector material.

102. The method of any one of claims 41 to 101, wherein: the one or more IR absorbance signal(s), to which the IR absorbance data received at step (b) corresponds, is / are measured from the aqueous sample, at each of one or more time points, as it (the aqueous sample) exits from a purification unit (e.g., a chromatography column); and the method comprises: using the IR absorption data to determine a capsid aggregation metric that measures a level of aggregation between capsids in the viral vector sample; and using the capsid aggregation metric to control collection of a target fraction of the aqueous sample (e.g., during a particular collection window), thereby obtaining a purified sample of viral vector material.

103. A system for obtaining a purified sample of a target protein species via real-time monitoring of protein heterogeneity and (e.g., automated; e.g., semi-automated) control of purification processing, the system comprising: (a) one or more mid-infrared (MIR) analyzer(s), aligned and operable to measure, at each of one or more time points, a corresponding infrared (IR) absorbance signal from an aqueous sample exiting from a purification unit (e.g., a chromatography column), the aqueous sample comprising one or more protein species including the target protein species; (b) a processor of a computing device; and - 158 - 11677372v1Attorney Docket No. 2017297-0013(c) memory having instructions stored thereon, wherein the instructions, when executed by the processor cause the processor to: receive IR absorbance data corresponding to the IR absorbance signal(s) at each of the one or more time points; determine values of one or more sample quality metrics based on the IR absorbance data, the one or more sample quality metrics comprising a protein aggregation metric indicative of a level of protein aggregation within the aqueous sample; and provide (e.g., transmit to a controller unit of the purification unit) and / or use the one or more sample quality metrics for control collection of a target fraction of the aqueous sample (e.g., during a particular collection window), thereby causing the purified sample of the target protein species to be obtained.

104. The system of claim 103, further comprising the purification unit and / or a controller unit thereof.

105. The system of claim 104, wherein the purification unit is or comprises a chromatography column.

106. A system for real-time monitoring of protein aggregation in a sample, the system comprising: a processor of a computing device; and memory having instructions stored thereon, wherein the instructions, when executed by the processor, cause the processor to: (a) repeatedly receive infrared (IR) absorbance data corresponding to IR absorbance signals measured at each of a plurality of time points, the IR absorbance data comprising, for each particular time point of the plurality of time points, a corresponding IR absorbance spectrum measured from the sample at the particular time point and comprising a plurality of absorbance values, each associated with a particular wavenumber; - 159 - 11677372v1Attorney Docket No. 2017297-0013(b) analyze (e.g., automatically) the IR absorbance data to obtain a real- time protein aggregation signal providing a measure of protein aggregation in the sample as a function of time, by, for each particular time point of the plurality of time points: determining, using the IR absorbance spectrum corresponding to the particular time point, values of one or more peak metrics for one or both of an Amide I band and an Amide II band; determining, using the values of the one or more peak metrics, a value of a protein aggregation metric indicative of a level of protein aggregation within the sample at the particular time point; and updating the real-time protein aggregation signal with the determined value of the protein aggregation metric for the particular time point; and (c) store and / or provide the real-time protein aggregation signal for one or more of (i) further processing, (ii) display, and (iii) use as a control signal for adjusting one or more purification units (e.g., chromatography systems).

107. A system for mid-IR (MIR)-spectroscopy-based monitoring and control of a production unit for manufacture of a biological product (e.g., a protein; e.g., a virus) the method comprising: (a) one or more (e.g., integrated) mid-infrared (MIR) analyzer(s) [e.g., MIR analyzer(s) as recited in any one of claims 9 to 24] aligned and operable to measure, at each of one or more time points, a corresponding infrared (IR) absorbance signal from an aqueous sample flowing to and / or from the production unit (e.g., and which comprises one or more inputs, output products, waste products, or in-progress products of the production unit); (b) a processor of a computing device; and (c) memory having instructions stored thereon, wherein the instructions, when executed by the processor cause the processor to: receive IR absorbance data corresponding to the IR absorbance signal(s) at each of the one or more time points; and - 160 - 11677372v1Attorney Docket No. 2017297-0013use the received IR absorbance data to cause adjustment to one or more process parameters of the production unit.

108. The system of claim 107, further comprising the production unit and / or a controller unit thereof.

109. A method for quantifying and / or monitoring (e.g., in real-time) viral vector quality within an aqueous sample comprising one or more species of virus and / or virus-like particles, the method comprising: (a) receiving (e.g., repeatedly), by a processor of a computing device, infrared (IR) absorbance data corresponding to one or more IR absorbance signal(s) measured from the sample; (b) determining (e.g., automatically), by the processor, using the IR absorbance data, values of one or more viral vector sample quality metrics; and (c) storing and / or providing for display and / or further processing, the one or more viral vector sample quality metric value(s).

110. The method of claim 109, wherein the one or more viral vector quality metrics comprise a total capsid content that quantifies a content of viral capsids within the sample [e.g., a concentration (e.g., titer), mass per volume (e.g. mg / mL), number of (viral) particles per volume, etc.].

111. The method of claim 109 or claim 110, wherein the one or more viral vector sample quality metrics comprise a full capsid fraction (e.g., percent, ratio, etc. of full viral vectors).

112. The method of any one of claims 109 to 111, wherein the one or more viral vector sample quality metrics comprise a capsid aggregation metric indicative of a level of capsid aggregation within the viral vector sample. - 161 - 11677372v1Attorney Docket No. 2017297-0013113. The method of any one of claims 109 to 112, wherein the one or more viral vector sample quality metrics comprise a protein content metric that quantifies protein content within the sample [e.g., a concentration (e.g., titer), mass per volume (e.g. mg / mL), number of particles per volume, etc.].

114. The method of any one of claims 109 to 113, wherein the one or more viral vector sample quality metrics comprise a nucleic acid (e.g., DNA, RNA, etc.) content metric that quantifies nucleic acid content within the sample [e.g., a concentration (e.g., titer), mass per volume (e.g. mg / mL), number of particles per volume, number of viral genome copies, etc.].

115. The method of any one of claims 109 to 114, wherein the one or more viral vector sample quality metrics comprise a viral nucleic acid (e.g., viral DNA, RNA, etc.) content metric that differentiates the viral nucleic acid from the host cell proteins and host cell nucleic acid content.

116. The method of any one claims 109 to 115, wherein step (b) comprises: determining, by the processor, a value for each of one or more peak metrics for the IR absorption data, wherein each peak metric is associated with one or more particular spectral bands [e.g., a continuous range of wavelengths / wavenumbers (e.g., an Amide-I band, an Amide-II band, an Amide-III band, e.g.; an Amide region, spanning two or more of the Amide bands; e.g., an antisymmetric PO4 band; e.g.; a symmetric PO4 band)] and quantifies a particular structural feature [e.g., an intensity (e.g., a peak amplitude; e.g., an Area Under the Curve (AUC)); e.g., a linewidth; e.g., a frequency position (e.g., peak frequency; e.g., center of mass frequency)] of one or more absorption peaks within the particular spectral band; and using the determined values of the one or more peak metrics to determine the values of at least a portion of the viral vector sample quality metrics.

117. The method of any one of claims 109 to 116, wherein the IR absorbance data comprises: - 162 - 11677372v1Attorney Docket No. 2017297-0013(i) one or more (e.g., a plurality of) Amide II absorbance value(s), associated with and measuring IR absorption (of the viral sample) at wavenumbers within an Amide II spectral band (e.g., ranging from about 1500 cm-1to about 1600 cm-1, e.g., ranging from about 1500 cm-1to about 1575 cm-1; e.g., ranging from about 1500 cm-1to about 1550 cm-1; e.g., ranging from about 1540 cm-1to about 1560 cm-1); and / or (ii) one or more (e.g., a plurality of) Amide III absorbance value(s), associated with and measuring IR absorption (of the viral sample) at wavenumbers within an Amide II spectral band (e.g., ranging from about 1250 cm-1to about 1350 cm-1, e.g., ranging from about 1250 cm-1to about 1325 cm-1; e.g., ranging from about 1275 cm-1to about 1325 cm-1; e.g., ranging from about 1280 cm-1to about 1300 cm-1).

118. The method of claim 117, wherein step (b) comprises determining values of a protein content metric [e.g., concentration (e.g., titer)] that quantifies protein content within the sample based at least in part on the Amide II and / or Amide III absorbance value(s).

119. The method of claim 118, comprising: determining a value of an Amide II peak metric based on the Amide II absorbance values and / or a value of an Amide III peak metric based on the Amide III absorbance values; and using the Amide II peak metric value and / or the Amide III peak metric value to determine the protein content metric value.

120. The method of claim 119, wherein the Amide II peak metric and / or the Amide III peak metric is a peak intensity metric that quantifies an intensity of the Amide II band and / or Amide III band, respectively [e.g., a peak height, an area under the curve (AUC), etc.].

121. The method of any one of claims 109 to 120, wherein the one or more viral vector sample quality metrics comprise one or more protein structure metrics (e.g., protein structure metrics; e.g., protein tertiary and / or quaternary structure metrics) indicative of presence and / or content (e.g., absolute content; e.g., relative content) of one or more particular protein - 163 - 11677372v1Attorney Docket No. 2017297-0013structural forms (e.g., particular secondary structure motifs; e.g., particular tertiary and / or quaternary structure motifs / forms) within the sample (e.g., thereby providing for monitoring variation in capsid protein secondary / tertiary / quaternary structure).

122. The method of any one of claims 109 to 121, wherein the IR absorbance data comprises: (i) one or more (e.g., a plurality of) antisymmetric Phosphate Stretch (antisymmetric- PO4) absorbance value(s), associated with and measuring IR absorption (of the viral sample) at wavenumbers within an antisymmetric-PO4spectral band (e.g., ranging from about 1150 cm-1to about 1250 cm-1, e.g., ranging from about 1175 cm-1to about 1250 cm-1; e.g., ranging from about 1200 cm-1to about 1250 cm-1; e.g., ranging from about 1210 cm-1to about 1230 cm-1); and / or (ii) one or more (e.g., a plurality of) symmetric Phosphate Stretch (symmetric-PO4) absorbance value(s), associated with and measuring IR absorption (of the viral sample) at wavenumbers within a symmetric-PO4 spectral band (e.g., ranging from about 1000 cm-1to about 1100 cm-1, e.g., ranging from about 1050 cm-1to about 1100 cm-1; e.g., ranging from about 1075 cm-1to about 1100 cm-1; e.g., ranging from about 1075 cm-1to about 1085 cm-1).

123. The method of claim 122, wherein step (b) comprises determining values of a nucleic acid (e.g., DNA, RNA, etc.) content metric that quantifies nucleic acid content [e.g., concentration (e.g., titer)] within the sample based at least in part on the antisymmetric-PO4 and / or symmetric-PO4absorbance value(s).

124. The method of claim 123, comprising: determining a value of an antisymmetric-PO4 peak metric based on the antisymmetric-PO4absorbance values and / or a value of an symmetric-PO4peak metric based on the symmetric-PO4 absorbance values; and using the antisymmetric-PO4 peak metric value and / or the symmetric-PO4 peak metric value to determine the nucleic acid content metric value. - 164 - 11677372v1Attorney Docket No. 2017297-0013125. The method of claim 124, wherein the antisymmetric-PO4peak metric and / or the symmetric-PO4 peak metric is a peak intensity metric that quantifies an intensity of the antisymmetric-PO4band and / or symmetric-PO4band, respectively [e.g., a peak height, an area under the curve (AUC), etc.].

126. The method of any one of claims 109 to 125, wherein step (b) comprises determining (i) value(s) of a protein content metric [e.g., concentration (e.g., titer)] that quantifies protein content within the sample and (ii) values of a nucleic acid (e.g., DNA, RNA, etc.) content metric that quantifies nucleic acid content [e.g., concentration (e.g., titer)] within the sample, thereby independently quantifying total protein and nucleic acid content within the sample.

127. The method of claim 126, wherein step (b) comprises determining as one of the viral vector sample quality metrics, a total capsid content based at least in part on (e.g., as a function of) the value(s) of the protein content metric.

128. The method of claim 126 or 127, wherein step (b) comprises determining, as one of the viral vector sample quality metrics, a full capsid fraction based at least in part on (e.g., as a function of) (i) the value(s) of the protein content metric and / or the total capsid content and (ii) the value(s) of the nucleic acid content metric.

129. The method of any one of claims 109 to 128, wherein the IR absorbance data is or comprises one or more IR absorbance spectra, each IR absorbance spectra comprising, for each particular wavenumber of a plurality of wavenumber spanning a measured spectral band, a corresponding IR absorbance value representing a measure of absorption of IR light, by the aqueous sample, at the particular wavenumber.

130. The method of claim 129, wherein the measured spectral band spans one or more bands selected from the group consisting of an Amide II band, an Amide III band, an asymmetric-PO4 band, and a symmetric-PO4 band. - 165 - 11677372v1Attorney Docket No. 2017297-0013131. The method of any one of claims 109 to 130, wherein: step (a) comprises repeatedly receiving the IR absorbance data at a plurality of time points, thereby obtaining, for each of the plurality of time points, a corresponding set of IR absorbance data; and the method comprises performing steps (b) through (c) for each set of IR absorbance data, thereby monitoring the total capsid content and / or full capsid fraction over time.

132. The method of claim 131, comprising performing steps (a) through (c) in substantially real-time to obtain (i) a real-time capsid content signal providing a measure of capsid content in the sample as a function of time and / or full capsid fraction signal providing a measure of a fraction of capsids within the sample that are full, as a function of time.

133. The method of any one of claims 109 to 132, comprising: measuring, via one or more (e.g., integrated) mid-infrared (MIR) analyzer(s) [e.g., MIR analyzer(s) as recited in any one of claims 9 to 24], the one or more IR absorbance signal(s).

134. The method of claim 133, comprising measuring, at each of one or more time points, a corresponding one of the one or more infrared (IR) absorbance signal.

135. The method of any one of claims 133 to 134, comprising measuring the one or more IR absorbance signal(s) from the aqueous sample as it (the aqueous sample) flows to (e.g., into) and / or from a production unit (e.g., the aqueous sample comprising one or more inputs, output products, waste products, or in-progress products of the production unit).

136. The method of any one of claims 109 to 135, wherein the one or more species of virus and / or virus-like particles comprise one or more species of adeno-associated virus (AAV). - 166 - 11677372v1Attorney Docket No. 2017297-0013137. The method of any one of claims 109 to 136, wherein the one or more species of virus comprises adeno viruses and / or retroviruses (e.g., lentiviruses).

138. The method of any one of claims 109 to 137, wherein the one or more species of virus comprises plant-based viruses (e.g., tobacco mosaic viruses).

139. The method of any one of claims 109 to 138, wherein the one or more IR absorbance signal(s), to which the IR absorbance data correspond, is / are measured from the aqueous sample as it (the aqueous sample) flows to (e.g., into) and / or from a production unit (e.g., the aqueous sample comprising one or more inputs, output products, waste products, or in- progress products of the production unit).

140. The method of claim 139, wherein the production unit is a purification unit.

141. The method of claim 140 wherein the purification unit is a member selected from the group consisting of an alternating tangential flow filtration (ATF) system, tangential flow depth filtration (TFDF) system, tangential flow filtration (TFF) system, a chromatography column, a direct, or normal, flow filtration unit, an ultra-filtration unit, and a dia-filtration unit.

142. The method of claim 141, wherein the purification unit is a chromatography column {e.g., and wherein the chromatography column is a member selected from the group consisting of an affinity chromatography (AC) column, a hydrophobic interaction chromatography (HIC) column, an ion exchange chromatograph (IEX) column, a size exclusion chromatography (SEC) column, and a mixed-mode chromatography column [e.g., any combination of the foregoing (e.g., IEX and HIC; e.g., IEX and SEC)]}.

143. The method of any one of claims 139 to 142, wherein the production unit is or comprises a bioreactor (e.g., a seed bioreactor; e.g., a production bioreactor). - 167 - 11677372v1Attorney Docket No. 2017297-0013144. The method of any one of claims 109 to 143, wherein step (c) comprises causing, by the processor, generation and / or transmission of one or more trigger signals (e.g., voltages) to a controller unit of the production unit based at least in part on (e.g., a value of) one or more of the determined viral vector sample quality metrics [e.g., a value of a determined capsid content and / or (e.g., a value of) a determined full capsid fraction].

145. The method of claim 144, wherein step (c) comprises causing, by the processor, generation of a trigger signal (e.g., an analog signal) having a value based at least in part on a determined viral vector quality metric [e.g., a capsid content; e.g., a full capsid fraction; e.g., a capsid aggregation metric].

146. The method of any one of claims 109 to 145, wherein: the one or more IR absorbance signal(s), to which the IR absorbance data received at step (a) corresponds, is / are measured from the aqueous sample, at each of one or more time points, as it (the aqueous sample) exits from a purification unit (e.g., a chromatography column); and the method comprises: using the IR absorption data to determine one or both of (i) a total capsid content and (ii) a full capsid fraction; and using the determined total capsid content and / or full capsid fraction to control collection of a target fraction of the aqueous sample (e.g., during a particular collection window), thereby obtaining a purified sample of viral vector material.

147. The method of any one of claims 109 to 146, wherein: the one or more IR absorbance signal(s), to which the IR absorbance data received at step (a) corresponds, is / are measured from the aqueous sample, at each of one or more time points, as it (the aqueous sample) exits from a purification unit (e.g., a chromatography column); and the method comprises: - 168 - 11677372v1Attorney Docket No. 2017297-0013using the IR absorption data to determine a capsid aggregation metric that measures a level of aggregation between capsids in the viral vector sample; and using the capsid aggregation metric to control collection of a target fraction of the aqueous sample (e.g., during a particular collection window), thereby obtaining a purified sample of viral vector material.

148. The method of any one of claims 109 to 147, wherein the IR absorbance data comprises an IR absorbance spectrum and wherein step (b) comprises: receiving (e.g., and / or accessing) one or more reference spectra, each measured from a corresponding (e.g., high-quality) reference sample comprising the target viral vector species at high purity and / or concentration and / or one or more model constituents thereof (e.g., a model protein solution; e.g., a model ssDNA solution); and determining (e.g., automatically), the values of at least a portion of the one or more viral vector sample quality metrics using the IR absorbance spectrum and the one or more reference spectra [e.g., determining, as the values of the portion of the one or more viral vector sample quality metrics, one or more (e.g., a plurality) measure(s) of deviation between the reference spectra and the IR absorbance spectrum].

149. The method of claim 148, wherein the one or more reference spectra comprises a high-quality viral vector spectrum measured from a reference sample having a full capsid fraction (e.g., a-priori known; e.g., determined to be) at or above a particular threshold fraction.

150. The method of claim 149, wherein the threshold fraction is about 75% [e.g., about 80% (e.g., about 90%)].

151. The method of any one of claims 148 to 150, wherein step (b) comprises computing a difference spectrum based on at least one of the one or more reference spectra and the IR - 169 - 11677372v1Attorney Docket No. 2017297-0013absorbance spectrum (e.g., by subtracting an IR absorbance spectrum, and / or a scaled or otherwise pre-processed version thereof, from a reference spectrum, and / or a scaled or otherwise pre-processed version thereof, or vice-versa).

152. The method of any one of claims 148 to 151, wherein step (b) comprises computing one or more derivative spectra (e.g., a first derivative; e.g., a second derivative) of at least one of the one or more reference spectra and / or the IR absorbance spectrum.

153. The method of any one of claims 148 to 152, wherein step (b) comprises computing (e.g., as the measure of deviation) one or more members selected from the group consisting of: a correlation value based on a correlation of (i) a particular one of the one or more reference spectra and / or one or more derivatives thereof, and (ii) the IR absorbance spectrum and / or one or more derivatives thereof; a covariance value based on a covariance of (i) a particular one of the one or more reference spectra and / or one or more derivatives thereof, and (ii) the IR absorbance spectrum and / or one or more derivatives thereof; a Pearson’s correlation value between (i) a particular one of the one or more reference spectra and / or one or more derivatives thereof, and (ii) the IR absorbance spectrum and / or one or more derivatives thereof; and an overlap integral value based on an overlap integral of (i) a particular one of the one or more reference spectra and / or one or more derivatives thereof, and (ii) the IR absorbance spectrum and / or one or more derivatives thereof.

154. The method of any one of claims 148 to 153, wherein step (b) comprises: determining values for a set of one or more particular peak metrics from the IR absorbance spectrum, thereby obtaining a set of sample peak metric values; and determining the measure of deviation based the set of sample peak metric values and a set of reference peak metric values having been determined for the one or more particular peak metrics from the one or more reference spectra. - 170 - 11677372v1Attorney Docket No. 2017297-0013155. The method of any one of claims 148 to 154, comprising determining, as the measure of deviation, a similarity score that measures a similarity between the one or more reference spectra and the IR absorbance spectrum.

156. The method of any one of claims 148 to 155, comprising performing steps (a) – (c) repeatedly, in substantially real-time, thereby monitoring deviation from the one or more reference spectra in real-time.

157. A method for evaluating and / or monitoring (e.g., in real-time) quality of viral vector content within an aqueous sample comprising a target viral vector species, the method comprising: (a) receiving (e.g., repeatedly), by a processor of a computing device, infrared (IR) absorbance data corresponding to one or more IR absorbance signal(s) measured from the sample, the IR absorbance data comprising an (e.g., at least one) IR absorbance spectrum measured from the sample and comprising a plurality of absorbance values, each associated with a particular wavenumber; (b) receiving (e.g., and / or accessing), by the processor, one or more reference spectra, each measured from a corresponding (e.g., high-quality) reference sample comprising the target viral vector species at high purity and / or concentration and / or one or more model constituents thereof (e.g., a model protein solution; e.g., a model ssDNA solution); (c) determining (e.g., automatically), by the processor, one or more (e.g., a plurality) measure(s) of deviation using the IR absorbance spectrum and the one or more reference spectra; (d) storing and / or providing for display and / or further processing, the measure(s) of deviation. - 171 - 11677372v1Attorney Docket No. 2017297-0013158. A system for quantifying and / or monitoring (e.g., in real-time) viral vector quality within an aqueous sample comprising one or more species of virus and / or virus-like particles, the system comprising: a processor of a computing device; and memory having instructions stored thereon, wherein the instructions, when executed by the processor, cause the processor to perform the method of any one of claims 109 to 157.

159. A method for (e.g., real-time) monitoring of compositional changes of a sample via infrared (IR) absorption spectroscopy, the method comprising: (a) repeatedly receiving, by a processor of a computing device, infrared (IR) absorbance data corresponding to IR absorbance signals measured at each of a plurality of time points, the IR absorbance data comprising, for each particular time point of the plurality of time points, a corresponding IR absorbance spectrum measured from the sample at the particular time point and comprising a plurality of absorbance values, each associated with a particular wavenumber; (b) analyzing (e.g., automatically), by the processor, the IR absorbance data to obtain a (e.g., real-time) normalized spectral difference signal that measures a change normalized spectral absorbance between consecutive time points, by, for each particular time point of the plurality of time points: normalizing a current IR absorbance spectrum that corresponds to the particular time point using a reference absorbance value determined from values of the current IR absorbance spectrum at one or more reference wavenumbers, thereby obtaining a current normalized spectrum; determining a current value of the spectral difference metric based on (e.g., computed as) a difference between the current normalized spectrum and a prior normalized spectrum, wherein the prior normalized spectrum is based on one or more previously obtained IR absorption spectra (e.g., is a particular previously obtained IR absorption spectrum; e.g., is an average of a plurality of previously obtained IR absorption spectra), each corresponding to and having been measured at a particular previous time point (e.g., preceding the current particular time point by a particular time interval and / or multiples - 172 - 11677372v1Attorney Docket No. 2017297-0013thereof) and each particular previously obtained IR absorption spectrum having been normalized using a reference value determined from values of the that particular previously obtained IR absorbance spectrum at the one or more reference wavenumbers; and updating the real-time normalized spectral difference signal according to the current value of the normalized spectral difference metric; and (c) storing and / or providing, by the processor, the real-time normalized spectral difference signal for one or more of (i) further processing, (ii) display, and (iii) use as a control signal for adjustment of one or more process parameters of a production unit (e.g., a chromatography unit; e.g., a filtration unit).

160. The method of claim 159, further comprising identifying (e.g., by the processor) a change in composition of the sample (e.g., at a particular time) based on the real-time normalized spectral difference signal.

161. The method of claim 160, comprising detecting a changepoint [e.g., a change statistical properties (e.g., mean, median, mode, variance, etc.); e.g., a step-change] in the real-time normalized spectral difference signal and identifying the change in composition of the sample based on the detected changepoint.

162. The method of claim 160 or 161, comprising determining (e.g., as a sample quality metric) (e.g., at each time point, e.g., in real-time) values of one or more statistical parameter(s) of the real-time normalized spectral difference signal.

163. The method of claim 162, wherein the one or more statistical parameter(s) comprise one or more members selected from the group consisting of: a mean [e.g., running (e.g., backward looking) mean, e.g., computed as a mean of the real-time normalized spectral difference signal over a time window comprising (e.g., ending at) the current time point and one or more previous time point(s)]; - 173 - 11677372v1Attorney Docket No. 2017297-0013a variance [e.g., running (e.g., backward looking) variance, e.g., computed as a variance of the real-time normalized spectral difference signal over a time window comprising (e.g., ending at) the current time point and one or more previous time point(s)]; a mode; and a standard deviation.

164. The method of claim 162 or 163, comprising identifying the change in composition based on a value of at least one of the one or more statistical parameter(s) (i) exceeding one or more threshold values and / or (ii) varying outside a particular range [e.g., predetermined threshold values and / or ranges; e.g., threshold values and / or ranges that are determined on- the-fly, e.g., during an initial phase of a process run (e.g., during an initial time-window of a chromatography run, e.g., during an initial ramp-up of a salt gradient, e.g., before protein elutes)].

165. The method of any one of the preceding claims, wherein the sample is or comprises an aqueous sample.

166. The method of claim any one of the preceding claims, wherein the sample comprises one or more protein species [e.g., a target protein species, such as a monoclonal antibody; e.g., as recited in any one of claims 46 to 49].

167. The method of any one of claims 166, further comprising identifying (e.g., by the processor) a change in composition of the sample (e.g., at a particular time) corresponding to a change in purity [e.g., presence of protein species other than the target; e.g., presence of undesired forms (e.g., non-monomeric) of the target protein species] and / or properties (e.g., secondary structure composition) of a target protein species.

168. The method of claim 167, wherein the identified change in composition is or comprises (e.g., is indicative of) a change in level and / or presence of protein aggregation within the aqueous sample. - 174 - 11677372v1Attorney Docket No. 2017297-0013169. The method of claim 167 or 168, wherein the identified change in composition is or comprises (e.g., is indicative of) a one or more members selected from the group consisting of: a change in content (e.g., relative content) of one or more particular protein species within the (e.g., aqueous) sample; a change in a level and / or type of molecular conjugation (e.g. glycan, small-molecule drug, polyethylene glycol, etc.); and a change in content of one or more protein secondary structure motifs (e.g., alpha- helical content, beta-sheet content, turn content, disordered content).

170. The method of any one of the preceding claims, wherein the sample comprises nucleic acid (e.g., DNA, RNA, mRNA, etc.).

171. The method of claim 170, further comprising identifying (e.g., by the processor) a change in composition of the sample (e.g., at a particular time) corresponding to a change in purity and / or properties of the nucleic acid within the sample (e.g., a change in relative content of one or more particular types of nucleic acid (e.g., DNA, RNA, ssDNA, dsDNA)] within the (e.g., aqueous) sample.

172. The method of any one of the preceding claims, wherein the aqueous sample comprises one or more species of virus and / or virus-like particles [e.g., adeno-associated viral vectors (AAV); e.g., lentiviral vectors].

173. The method of claim 172, further comprising identifying (e.g., by the processor) a change in composition of the sample (e.g., at a particular time) corresponding to a change in purity and / or properties of the virus and / or virus like particles within the sample. - 175 - 11677372v1Attorney Docket No. 2017297-0013174. The method of claim 173, wherein the change in composition corresponds to (e.g., is indicative of) a change in a relative fraction of empty and / or full viral vectors within the aqueous sample (e.g., percent, ratio, etc. of full viral vectors).

175. The method of claim 173 or claim 174, wherein the change in composition corresponds to (e.g., is indicative of) a level of capsid aggregation within the sample.

176. The method of any one of claims 173 to 175, wherein the change in composition corresponds to (e.g., is indicative of) a change in a relative content between viral nucleic acid from host cell proteins and host cell nucleic acid content.

177. The method of any one of claims 160 to 176, comprising causing (e.g., triggering) adjustment of one or more process parameters of a production unit based on (e.g., triggered upon) the identification of the change in composition of the sample (e.g., detection of a changepoint; e.g., based on values of one or more statistical parameter(s) of the real-time normalized spectral difference signal).

178. The method of claim 177, wherein the production unit is or comprises a purification unit.

179. The method of claim 178, wherein the purification unit is or comprises a chromatography column.

180. The method of any one of claims 177 to 179, wherein the production unit is or comprises one or more members selected from the group consisting of a flow controller, a valve controller (e.g. for adjustment of a buffer composition (e.g., via valve switching), a temperature controller (e.g., for adjustment of one or more temperature set points and / or (e.g., temporal) profiles. - 176 - 11677372v1Attorney Docket No. 2017297-0013181. The method of any one of claims 177 to 180, comprising triggering a response of a production unit (e.g., any of the parameters discussed herein) [e.g., wherein the production unit is a first production unit and the sample is associated with (e.g., is an input, an output, or component processed by) a second (e.g., upstream or downstream) production unit].

182. The method of claim 178 to 181, wherein the sample is an aqueous sample and the method comprises causing adjustment a collection window to control collection of a target fraction of the aqueous sample (e.g., a monomeric species of protein), thereby obtaining a purified sample.

183. The method of any one of claims 178 to 182, wherein the production unit is or comprises a filtration unit (e.g., an ultrafiltration and / or diafiltration unit) (e.g., and wherein the method comprises causing adjustment to a flow rates, transmembrane pressure, processing time, etc., to control a composition of retentate and / or permeate).

184. The method of any one of claims 177 to 183, wherein the method comprises monitoring progress of a chemical reaction [e.g., within the production unit (e.g., a bioreactor, a transfection unit, a pegylation unit, an antibody drug conjugation unit]based on (e.g., identification of a compositional change using) the real-time normalized spectral difference signal.

185. The method of any one of claims 177 to 184, wherein the method comprises causing adjustment to one or more members selected from the group consisting of an inline buffer preparation, a mixing process (e.g., in mixing tanks), a temperature controller.

186. The method of any one of the preceding claims, wherein the reference absorbance value is determined from a value of the current IR absorbance spectrum at a single reference wavenumber and the prior reference value is determined from a value of the prior IR absorbance spectrum at the single reference wavenumber. - 177 - 11677372v1Attorney Docket No. 2017297-0013187. The method of any one of the preceding claims, wherein determining the current value of the spectral difference metric comprises computing, for each of the current normalized spectrum and the prior normalized spectrum, an integrated absorbance over one or more particular spectral bands (e.g., and subtracting the integrated absorbance values).

188. The method of claim 187, wherein the one or more particular spectral bands comprise one or more members selected from the group consisting of: an Amide I spectral band (e.g., ranging from about 1600 cm-1to about 1700 cm-1or about 1800 cm-1(e.g., ranging from about 1600 cm-1to about 1725 cm-1; e.g., ranging from about 1625cm-1to about 1725 cm-1; e.g., ranging from about 1630 cm-1to about 1650 cm-1), and / or an Amide II region, ranging from about 1500 to about 1600 cm-1(e.g., ranging from about 1500 cm-1to about 1575 cm-1; e.g., ranging from about 1500 cm-1to about 1550 cm-1; e.g., ranging from about 1540 cm-1to about 1560 cm-1)); an Amide II spectral band (e.g., ranging from about 1500 cm-1to about 1600 cm-1, e.g., ranging from about 1500 cm-1to about 1575 cm-1; e.g., ranging from about 1500 cm-1to about 1550 cm-1; e.g., ranging from about 1540 cm-1to about 1560 cm-1); and an Amide III spectral band (e.g., ranging from about 1250 cm-1to about 1350 cm-1, e.g., ranging from about 1250 cm-1to about 1325 cm-1; e.g., ranging from about 1275 cm-1to about 1325 cm-1; e.g., ranging from about 1280 cm-1to about 1300 cm-1).

189. The method of claim 187 or claim 188, wherein the one or more particular spectral bands comprise one or more members selected from the group consisting of: an antisymmetric-PO4spectral band (e.g., ranging from about 1150 cm-1to about 1250 cm-1, e.g., ranging from about 1175 cm-1to about 1250 cm-1; e.g., ranging from about 1200 cm-1to about 1250 cm-1; e.g., ranging from about 1210 cm-1to about 1230 cm-1); and a symmetric-PO4spectral band (e.g., ranging from about 1000 cm-1to about 1100 cm- 1, e.g., ranging from about 1050 cm-1to about 1100 cm-1; e.g., ranging from about 1075 cm-1to about 1100 cm-1; e.g., ranging from about 1075 cm-1to about 1085 cm-1). - 178 - 11677372v1Attorney Docket No. 2017297-0013190. The method of any one of the preceding claims, further comprising measuring the IR absorbance signals using one or more MIR analyzer(s) (e.g., as recited in any one of claims 9 to 24).

191. A method for (e.g., real-time) monitoring of temporal changes of a sample via infrared (IR) absorption spectroscopy, the method comprising: (a) repeatedly receiving, by a processor of a computing device, infrared (IR) absorbance data corresponding to IR absorbance signals measured at each of a plurality of time points, the IR absorbance data comprising, for each particular time point of the plurality of time points, a corresponding IR absorbance spectrum measured from the sample at the particular time point and comprising a plurality of absorbance values, each associated with a particular wavenumber; (b) analyzing (e.g., automatically), by the processor, the IR absorbance data to obtain one or both of: a (e.g., real-time) a time differential signal that measure a temporal change between values one or more features (e.g., sample quality metrics) determined using (i) a first set of one or more IR absorbance spectra that correspond to a first set of particular time point(s) and (ii) a second set of one or more IR absorbance spectra that correspond to a first set of particular time point(s); and a (e.g., real-time) time-aggregated signal that is a function of at least a portion [e.g., a cumulative, increasing portion, e.g., beginning at a particular time point and ending at a current time point; e.g., a temporal window of a particular size (e.g., a backward looking window)] of the plurality of time points (e.g., a running sum, mean, median, mode, variance, standard deviation, etc. over a particular time window); and (c) storing and / or providing, by the processor, the a time differential signal and / or the time-aggregated signal for one or more of (i) further processing, (ii) display, and (iii) use as a control signal for adjustment of one or more process parameters of a production unit (e.g., a chromatography unit; e.g., a filtration unit).

192. A system for (e.g., real-time) monitoring of temporal (e.g., compositional) changes of a sample via infrared (IR) absorption spectroscopy, the system comprising: - 179 - 11677372v1Attorney Docket No. 2017297-0013a processor of a computing device; and memory having instructions stored thereon, wherein the instructions, when executed by the processor, cause the processor to perform the method of any one of claims 159 to 191.

193. The system of claim 192, further comprising one or more MIR analyzer(s) (e.g., as recited in any one of claims 9 to 24).

194. The system of claim 192 or 193, comprising a production unit (e.g., a chromatography unit; e.g., a filtration unit).

195. A method for obtaining a purified sample of a target protein species via mid-infrared (IR) spectroscopy-based bioprocess monitoring and control, the method comprising: (a) measuring, via one or more mid-infrared (MIR) analyzer(s), at each of a plurality of time points, a corresponding mid-IR absorbance spectrum from an aqueous sample exiting from a purification unit, the aqueous sample comprising one or more protein species including the target protein species, thereby measuring a plurality of mid-IR absorbance spectra over time; (b) receiving, by a processor of a computing device, spectral data corresponding to the plurality of measured mid-IR absorbance spectra; (c) determining, by the processor, for each of at least a portion of the plurality of time points, corresponding values of one or more sample quality metrics based on the spectral data, the one or more sample quality metrics comprising a measure of concentration and / or purity of the target protein species in the aqueous sample; and (d) using the determined values of the one or more sample quality metrics to control collection of a target fraction of the aqueous sample (e.g., during a particular collection window), thereby obtaining the purified sample of the target protein species.

196. The method of claim 195, wherein the purification unit is or comprises a chromatography column {e.g., wherein the chromatography column is a member selected from the group consisting of an affinity chromatography (AC) column, a hydrophobic - 180 - 11677372v1Attorney Docket No. 2017297-0013interaction chromatography (HIC) column, an ion exchange chromatograph (IEX) column, a size exclusion chromatography (SEC) column, and a mixed-mode chromatography column [e.g., any combination of the foregoing (e.g., IEX and HIC; e.g., IEX and SEC)]}.

197. The method of claim 195 or 196, wherein the purification unit is or comprises an ultrafiltration and diafiltration system (UF / DF) [e.g., a tangential flow filtration (TFF) system].

198. The method of any one of claims 195-197, wherein the target protein species is selected from the group consisting of a monoclonal antibody (mAb), a fusion protein, a viral capsid protein, an antibody-drug conjugate, a recombinant protein, and a plasmatic protein.

199. The method of any one of claims 195-198, wherein the aqueous sample comprises a plurality of different molecular forms of a particular protein [e.g., a therapeutic protein (e.g., a mAb)], including a monomeric form and one or more aggregated forms (e.g., dimer and / or other multimers) and wherein the target protein species is the monomeric form of the particular protein.

200. The method of any one of claims 195-199, wherein the aqueous sample comprises one or more sub-species of a particular protein, each having a particular desired level and / or type of molecular conjugation (e.g., glycan, small-molecule drug, polyethylene glycol, etc.), and wherein the target protein species is a particular one of the one or more sub-species.

201. The method of any one of claims 195-200, wherein the one or more MIR analyzer(s) comprise a quantum-cascade laser (QCL)-based mid-IR spectrometer comprising: a QCL-based source, aligned and operable to emit a beam of MIR light [e.g., comprising one or more wavelengths substantially within the MIR spectral range (e.g., ranging from about 5000 cm-1to about 500 cm-1(e.g., about 2 to 20 microns))]; one or more sampling optics, aligned to direct and / or allow passage of the beam of MIR light, and / or at least a portion thereof, through and / or into contact with at least a portion - 181 - 11677372v1Attorney Docket No. 2017297-0013of the aqueous sample [e.g., wherein the beam of MIR light contacts the portion of the aqueous sample via reflection at an interface between a solid material (e.g., an ATR crystal and / or optical fiber) and the aqueous sample (e.g., wherein the beam of MIR light undergoes total internal reflection, and contacts / probes the portion of the aqueous sample via an evanescent wave extending into the aqueous sample)] and, following passage through or contact with the portion of the aqueous sample, towards one or more detectors; and the one or more detectors, aligned and operable to detect the beam of MIR light following its passage through and / or contact with the aqueous sample.

202. The method of claim 201, wherein: the one or more sampling optics comprise a flow cell comprising a detection channel through which the aqueous sample flows; and the one or more detectors are aligned and operable to detect the beam of MIR light exiting from, following its transmission through, the detection channel.

203. The method of claim 201 or 202, wherein the QCL-based source is a tunable QCL operable sweep an emission frequency of the beam of MIR light through a plurality of frequencies across a scan range (e.g., wherein the scan range comprises a range from about 1700 cm-1to 1400 cm-1; e.g., wherein the scan range comprises a range from 1300 cm-1to 1050 cm-1; e.g., wherein the scan range comprises a range from at least 1200 cm-1to 1000 cm-1) and the method comprises, at each of the one or more time points: sweeping the emission frequency of the beam MIR light across the scan range of the tunable laser, thereby illuminating the aqueous sample with a plurality of emission frequencies; and detecting, with the one or more detectors, the beam of MIR light (e.g., having been (i) internally reflected by an interface between the high-index material and the aqueous sample and / or (ii) transmitted through the detection channel through which the aqueous sample flows) at each of the plurality of emission frequencies, thereby measuring, as the corresponding infrared (IR) absorbance signal from the aqueous sample, a corresponding IR spectrum comprising a plurality of values, each associated with and representing and / or based on a detected power at a particular one of the plurality of emission frequencies. - 182 - 11677372v1Attorney Docket No. 2017297-0013204. The method of any one of claims 195-203, wherein the MIR analyzer is an on-line sensor (e.g., as opposed to an off-line or at-line sensor) and wherein step (a) comprises repeatedly measuring IR absorbance spectra over time {e.g., every 20s or less [e.g., every 10s or less (e.g., every 5s or less; (e.g., every second or less))]}, as the aqueous solution exits from the purification unit (e.g., thereby measuring IR absorbance spectra from the aqueous sample in substantially real time).

205. The method of any one of claims 195-204, wherein the spectral data comprises, for each of the one or more time points, a corresponding Amide band spectrum [e.g., the Amide band spectrum comprising, for each particular wavelength of a plurality of sampled (e.g., emission) wavelengths within a range from about 1800 to about 800 cm-1(e.g., with a range from about 1700 to 1400 cm-1), an associated absorption value representing a level of absorption, by a portion of the aqueous sample, at the particular wavelength].

206. The method of any one of claims 195-205, wherein step (c) comprises: receiving (e.g., and or accessing), by the processor, a reference spectrum for the target protein species, said reference having been measured from a particular corresponding reference sample comprising the target protein species substantially in isolation and / or at high purity [e.g., 75% purity or better (e.g., 90% purity or better (e.g., 95% purity or better))]; and repeatedly, at each of the plurality of time points, using the reference spectrum to determine a concentration of the target protein species within the aqueous sample at each time point, thereby tracking a concentration of the target protein species over time.

207. The method of any one of claims 195-206, wherein step (c) comprises: receiving (e.g., and or accessing), by the processor, one or more impurity reference spectra, each associated with a particular impurity of interest and having been measured from a particular corresponding reference sample comprising the impurity of interest substantially in isolation and / or at high purity [e.g., 75% purity or better (e.g., 90% purity or better (e.g., 95% purity or better))]; and - 183 - 11677372v1Attorney Docket No. 2017297-0013repeatedly, at each of the plurality of time points, using the one or more impurity reference spectra reference spectrum to determine a concentration of each of the impurities of interest within the aqueous sample.

208. The method of any one of claims 195-207, wherein the spectral data comprises, for each of the one or more time points, a corresponding Amide band spectrum and wherein step (c) comprises determining, as the measure of sample purity, a ratio of absorbance at at least two wavenumbers within the Amide band spectrum.

209. The method of claim any one of claims 195-208, wherein step (d) comprises causing, by the processor, transmission of one or more trigger signals (e.g., voltages) to a controller unit of the purification unit and / or a downstream (from the purification unit) valve.

210. The method of claim 209, wherein step (d) comprises one or both of: initiating, by the controller unit, based on the one or more trigger signals, collection of the target fraction of the aqueous sample [e.g., wherein a particular one of the one or more trigger signals is an analog signal and the controller unit initiates collection of the target fraction based on an amplitude of the analog signal (e.g., when it exceeds a particular threshold; e.g., when it drops below a particular threshold); e.g., wherein a particular one of the one or more trigger signals is a digital signal that triggers (e.g., by transitioning from a 0 voltage level to 1 voltage level or vice-a-versa) initiating collection of the target fraction] and stopping, by the controller unit, based the one or more trigger signals, collection of the target fraction of the aqueous sample [e.g., wherein a particular one of the one or more trigger signals is an analog signal and the controller unit stops collection of the target fraction based on an amplitude of the analog signal (e.g., when it exceeds a particular threshold; e.g., when it drops below a particular threshold); e.g., wherein a particular one of the one or more trigger signals is a digital signal that triggers (e.g., by transitioning from a 0 voltage level to 1 voltage level or vice-a-versa) stopping collection of the target fraction]. - 184 - 11677372v1Attorney Docket No. 2017297-0013211. The method of any one of claims 195-210, wherein the target protein species is a monomeric form of a particular protein (e.g., a monoclonal antibody) and the method comprises: at step (c), determining, over time, values of (i) a concentration of the monomeric form of the particular protein and / or (ii) a cumulative purity [e.g., a relative fraction (e.g., mass) of the monomeric form of the particular protein collected relative to total protein collected] of the monomeric form of the particular protein within a total collected volume of sample exiting from the purification unit; and at step (d), stopping collection of aqueous sample exiting from the purification unit at a particular stop time based at least in part on the values of the concentration and / or cumulative purity of the monomeric form of the particular protein.

212. The method of claim 211, wherein the aqueous sample comprises (i) one or more high aggregated forms of the particular protein and / or (ii) one or more fragmented species of the particular protein and wherein step (c) comprises determining concentrations of the one or more aggregated forms and / or concentrations of the one or more fragmented species of the particular protein over time.

213. The method of any one of claims 195-212, wherein the aqueous sample comprises one or more excipients and the method comprises, at step (c): determining, based on the spectral data, values of concentrations and / or quantities of the one or more excipients within the aqueous sample exiting the purification unit at one or more time points; and at step (d), using the determined values of excipient concentrations and / or quantities to control collection of the target fraction of the aqueous sample.

214. A method for preparing a biologic drug formulation comprising one or more excipients, the method comprising: (a) receiving a solution comprising a purified drug substance comprising a protein species (e.g., a monoclonal antibody); - 185 - 11677372v1Attorney Docket No. 2017297-0013(b) injecting and / or mixing, into the solution of the purified drug substance, one or more excipients, over a period of time, thereby creating an in-process drug substance solution comprising the purified drug substance and the one or more excipients at relative concentrations that vary over the period of time, as the one or more excipients are injected and / or mixed; (c) measuring, via one or more mid-infrared (MIR) analyzer(s), at each of one or more of time points, one or both of: (i) a corresponding mid-IR absorbance spectrum from the in-process drug substance solution; and (ii) a corresponding mid-IR absorbance spectrum from a stock solution comprising at least one of the one or more excipients, thereby measuring one or more mid-IR absorbance spectra; (d) receiving, by a processor of a computing device, spectral data corresponding to the one or more measured mid-IR absorbance spectra; (e) determining, by the processor, for each of at least a portion of the one or more time points, corresponding values of one or more sample quality metrics based on the spectral data, the one or more sample quality metrics comprising a measure / measures of concentration and / or purity of (i) the protein species and / or (ii) at a subset of the one or more excipients; and (f) using the determined values of the one or more sample quality metrics to control the injection and / or mixing of the one or more excipients, thereby obtaining a final drug substance having desired protein and / or excipient content and / or purity.

215. The method of claim 214, wherein step (b) comprises using an ultra- filtration / diafiltration (UF / DF) system (e.g., to perform buffer exchange).

216. The method of claim 214 or 215, wherein the protein species is or comprises a monoclonal antibody. - 186 - 11677372v1Attorney Docket No. 2017297-0013217. The method of any one of claims 214 to 216, wherein the one or more excipients are or comprise one or more surfactants {e.g., detergents; e.g., wetting and / or solubilizing agents [e.g., Polysorbate 20 (Tween 20), Polysorbate 80 (Tween 80), Poloxamer (Pluronic F68 and F127), Triton X-100, Brij 30, Brij 35, etc.]}.

218. The method of any one of claims 214 to 217, wherein the one or more excipients are or comprise one or more bulking agents {e.g., sugars and / or polyols [e.g., Sucrose, Trehalose, Glucose, Lactose, Sorbitol, Mannitol, Glycerol, etc.]; e.g., amino acids [e.g., Arginine, Aspartic Acid, Glutamic acid, Lysine, Proline, Glycine, Histidine, Methionine, Alanine, etc.]; e.g., polymers and proteins [e.g., Gelatin, PVP, PLGA, PEG, dextran, cyclodextrin and derivatives, starch derivatives, HSA, BSA]}.

219. The method of any one of claims 214 to 218, wherein the one or more MIR analyzer(s) comprise a quantum-cascade laser (QCL)-based mid-IR spectrometer comprising: a QCL-based source, aligned and operable to emit a beam of MIR light [e.g., comprising one or more wavelengths substantially within the MIR spectral range (e.g., ranging from about 5000 cm-1to about 500 cm-1(e.g., about 2 to 20 microns))]; one or more sampling optics, aligned to direct and / or allow passage of the beam of MIR light, and / or at least a portion thereof, through and / or into contact with at least a portion of the stock solution and / or a portion of the in-process drug substance solution [e.g., wherein the beam of MIR light contacts the portion of the stock solution and / or the portion of the in- process drug substance solution via reflection at an interface between a solid material (e.g., an ATR crystal and / or optical fiber) and the portion of the stock solution and / or the portion of the in-process drug substance solution (e.g., wherein the beam of MIR light undergoes total internal reflection, and contacts / probes the portion of the stock solution and / or the portion of the in-process drug substance solution via an evanescent wave extending into the aqueous sample)] and, following passage through or contact with the portion of the stock solution and / or the portion of the in-process drug substance solution, towards one or more detectors; and the one or more detectors, aligned and operable to detect the beam of MIR light following its passage through and / or contact with the portion of the stock solution and / or the portion of the in-process drug substance solution. - 187 - 11677372v1Attorney Docket No. 2017297-0013220. The method of claim 219, wherein: the one or more sampling optics comprise a flow cell comprising a detection channel through which the portion of the stock solution and / or the portion of the in-process drug substance solution flow; and the one or more detectors are aligned and operable to detect the beam of MIR light exiting from, following its transmission through, the detection channel.

221. The method of claims 219 or 220, wherein the QCL-based source is a tunable QCL operable sweep an emission frequency of the beam of MIR light through a plurality of frequencies across a scan range (e.g., wherein the scan range comprises a range from about 1700 cm-1to 1400 cm-1; e.g., wherein the scan range comprises a range from 1300 cm-1to 1050 cm-1; e.g., wherein the scan range comprises a range from at least 1200 cm-1to 1000 cm-1) and the method comprises, at each of the one or more time points: sweeping the emission frequency of the beam MIR light across the scan range of the tunable laser, thereby illuminating the portion of the stock solution and / or the portion of the in-process drug substance solution with a plurality of emission frequencies; and detecting, with the one or more detectors, the beam of MIR light (e.g., having been (i) internally reflected by an interface between the high-index material and the portion of the stock solution and / or the portion of the in-process drug substance solution and / or (ii) transmitted through the detection channel through which the portion of the stock solution and / or the portion of the in-process drug substance solution flows) at each of the plurality of emission frequencies, thereby measuring, as the corresponding infrared (IR) absorbance signal from the portion of the stock solution and / or the portion of the in-process drug substance solution, a corresponding IR spectrum comprising a plurality of values, each associated with and representing and / or based on a detected power at a particular one of the plurality of emission frequencies.

222. The method of any one of claims 214 to 221, wherein the MIR analyzer is an on-line sensor (e.g., as opposed to an off-line or at-line sensor) and wherein step (c) comprises repeatedly measuring IR absorbance spectra over time {e.g., every 20s or less [e.g., every 10s - 188 - 11677372v1Attorney Docket No. 2017297-0013or less (e.g., every 5s or less; (e.g., every second or less))]}, as one or more excipients are injected and / or mixed (e.g., thereby measuring IR absorbance spectra from the in-process drug substance solution in substantially real time).

223. The method of any one of claims 214 to 222, wherein the spectral data comprises, for each of the one or more time points, a corresponding Amide band spectrum [e.g., the Amide band spectrum comprising, for each particular wavelength of a plurality of sampled (e.g., emission) wavelengths within a range from about 1800 to about 800 cm-1(e.g., with a range from about 1700 to 1400 cm-1), an associated absorption value representing a level of absorption, by a portion of the aqueous sample, at the particular wavelength].

224. The method of any one of claims 214 to 223, wherein the spectral data comprises, for each of the one or more time points, a corresponding sugar band spectrum [e.g., the sugar band spectrum comprising, for each particular wavelength of a plurality of sampled (e.g., emission) wavelengths within a range from about 1400 to about 800 cm-1(e.g., with a range from about 1200 to 1000 cm-1), an associated absorption value representing a level of absorption, by a portion of the aqueous sample, at the particular wavelength].

225. The method of any one of claims 214 to 224, wherein step (e) comprises: receiving (e.g., and or accessing), by the processor, a reference spectrum for the protein species, said reference having been measured from a particular corresponding reference sample comprising the protein species substantially in isolation and / or at high purity [e.g., 75% purity or better (e.g., 90% purity or better (e.g., 95% purity or better))]; and repeatedly, at each of the plurality of time points, using the reference spectrum to determine a concentration of the protein species within the in-process drug substance solution at each time point, thereby tracking a concentration of the protein species over time.

226. The method of any one of claims 214 to 225, wherein step (e) comprises: receiving (e.g., and or accessing), by the processor, one or more excipient reference spectra, each associated with a particular excipient of interest (of the one or more excipients) - 189 - 11677372v1Attorney Docket No. 2017297-0013and having been measured from particular corresponding reference sample comprising the particular excipient of interest substantially in isolation and / or at high purity [e.g., 75% purity or better (e.g., 90% purity or better (e.g., 95% purity or better))]; and repeatedly, at each of the plurality of time points, using the one or more excipient reference spectra reference spectrum to determine a concentration of each of the one or more excipients of interest within the stock solution and / or in-process drug substance solution.

227. The method of claim any one of claims 214 to 226, wherein step (f) comprises causing, by the processor, transmission of one or more trigger signals (e.g., voltages) to a controller unit (e.g., of a UF / DF system; e.g., of one or more valves).

228. The method of claims 227, wherein step (f) comprises one or both of: initiating, by the controller unit, injection and / or mixing of the one or more excipients [e.g., wherein a particular one of the one or more trigger signals is an analog signal and the controller unit initiates the injection and / or mixing based on an amplitude of the analog signal (e.g., when it exceeds a particular threshold; e.g., when it drops below a particular threshold); e.g., wherein a particular one of the one or more trigger signals is a digital signal that triggers (e.g., by transitioning from a 0 voltage level to 1 voltage level or vice-a-versa) initiating the injection and / or mixing] and stopping, by the controller unit, based the one or more trigger signals, injection and / or mixing of the one or more excipients [e.g., wherein a particular one of the one or more trigger signals is an analog signal and the controller unit stops injection and / or mixing of the one or more excipients based on an amplitude of the analog signal (e.g., when it exceeds a particular threshold; e.g., when it drops below a particular threshold); e.g., wherein a particular one of the one or more trigger signals is a digital signal that triggers (e.g., by transitioning from a 0 voltage level to 1 voltage level or vice-a-versa) stopping injection and / or mixing of the one or more excipients].

229. A system for obtaining a purified sample of a target protein species via mid-infrared (IR) spectroscopy-based bioprocess monitoring and control, the system comprising: - 190 - 11677372v1Attorney Docket No. 2017297-0013one or more mid-infrared (MIR) analyzer(s) [e.g., each operable to (e.g., based on one or more signals / communication with a processor) measure, at each of a plurality of time points, a corresponding mid-IR absorbance spectrum from an aqueous sample exiting from a purification unit, the aqueous sample comprising one or more protein species including the target protein species, thereby measuring a plurality of mid-IR absorbance spectra over time]; a processor of a computing device; and memory having instructions stored thereon, wherein the instructions, when executed by the processor, cause the processor to: (a) receive spectral data corresponding to a plurality of measured mid-IR absorbance spectra, each having been measured, by the one or more MIR analyzers at a corresponding one of a plurality of time points, from an aqueous sample exiting from a purification unit, the aqueous sample comprising one or more protein species including the target protein species; (b) determine for each of at least a portion of the plurality of time points, corresponding values of one or more sample quality metrics based on the spectral data, the one or more sample quality metrics comprising a measure of concentration and / or purity of the target protein species in the aqueous sample; and (c) use the determined values of the one or more sample quality metrics to control collection of a target fraction of the aqueous sample (e.g., during a particular collection window), thereby obtaining the purified sample of the target protein species.

230. A system for preparing a biologic drug formulation comprising one or more excipients, the system comprising: one or more mid-infrared (MIR) analyzer(s); a processor of a computing device; and memory having instructions stored thereon, wherein the instructions, when executed by the processor, cause the processor to: - 191 - 11677372v1Attorney Docket No. 2017297-0013(a) receiving spectral data corresponding to one or more mid-IR absorbance spectra having been measured, via the one or more MIR anlayzer(s) at each of one or more time points, from one or both of: (i) an in-process drug substance solution comprising a purified drug substance and one or more excipients being injected and / or mixed therein / therewith, over time; and (ii) a stock solution comprising at least one of the one or more excipients; (b) determine for each of at least a portion of the one or more time points, corresponding values of one or more sample quality metrics based on the spectral data, the one or more sample quality metrics comprising a measure / measures of concentration and / or purity of (i) the protein species and / or (ii) at a subset of the one or more excipients; and (c) use the determined values of the one or more sample quality metrics to control the injection and / or mixing of the one or more excipients, thereby obtaining a final drug substance having desired protein and / or excipient content and / or purity. - 192 - 11677372v1

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