Determining quality attributes of virus samples

Abstract

The present disclosure describes computer-implemented methods, systems, and computer program products for measuring quality attributes of a viral sample. In certain embodiments, the methods, systems, and computer program products include (1) receiving light scattering (LS) data, dRI data, and UV data from a light scattering detector analyzing a separation of a viral sample, (2) receiving a molecular weight M of a protein component of the sample, a refractive index increment (dn / dc) of the protein component, a refractive index increment (dn / dc) of the DNA component of the sample, and an extinction coefficient ε of the protein component, (3) calculating the protein fraction x of the sample with respect to the LS data, dRI data, M, (dn / dc) of the protein component, (dn / dc) of the DNA component, and the optical constant K, (4) calculating the DNA extinction coefficient ε of the sample, and (5) calculating a quality attribute value of the sample.

Description

[Technical Field]

[0001] (CROSS-REFERENCE TO RELATED APPLICATIONS) This application claims the benefit of the earlier filing date of U.S. Patent Application No. 17 / 939,950, filed September 7, 2022, and entitled "Measuring Quality Attributes of a Virus Sample," the entire contents of which are incorporated herein by reference. [Background technology]

[0002] The present disclosure relates to samples, and more particularly to measuring quality attributes of virus samples. Summary of the Invention [Means for solving the problem]

[0003] The present disclosure describes computer-implemented methods, systems, and computer program products for measuring quality attributes of a virus sample. In exemplary embodiments, the computer-implemented methods, systems, and computer program products include: (1) a computer system receiving light scattering data from a light scattering detector analyzing a separation of the virus sample, differential refractive index (dRI) data from a differential refractometer analyzing the separation, and UV absorbance data A from an ultraviolet (UV) detector at at least one wavelength analyzing the separation; and (2) the computer system receiving molecular weights M of protein components of the sample. protein(expected) , the refractive index increment of the protein component (dn / dc) protein , the refractive index increment of the DNA component of the sample (dn / dc) DNA , and the extinction coefficient ε of the protein component at that at least one wavelength protein (3) receiving the light scattering data, the differential refractive index data, the molecular weight M of the protein component, and the like from a data source; protein(expected) , the refractive index increment of the protein component (dn / dc) protein , the refractive index increment of the DNA component (dn / dc)DNA , and the protein fraction of the sample, x, with respect to the optical constant K. protein and (4) calculating the calculated protein fraction x protein , differential refractive index data, ultraviolet absorbance data A, refractive index increment of protein components (dn / dc) protein , the refractive index increment of the DNA component (dn / dc) DNA , the extinction coefficient ε of the protein component at at least one wavelength protein , and the DNA extinction coefficient ε of the sample at that at least one wavelength relative to the path length L of the cell in the UV detector. DNA and (5) the computer system calculates the calculated DNA extinction coefficient ε DNA and calculating a quality attribute value for the sample for [Brief explanation of the drawings]

[0004] [Figure 1A] 1 depicts a flowchart in accordance with an example embodiment. [Figure 1B] 1 depicts a block diagram in accordance with an illustrative embodiment; [Figure 2] 1 depicts a flowchart according to an embodiment. [Figure 3A] 1 depicts a graph according to an embodiment. [Figure 3B] 1 depicts a graph according to an embodiment. [Figure 4] 1 depicts a device according to an embodiment. [Figure 5] 1 illustrates a computer system in accordance with an exemplary embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0005] The present disclosure describes computer-implemented methods, systems, and computer program products for measuring quality attributes of a virus sample. In exemplary embodiments, the computer-implemented methods, systems, and computer program products include: (1) a computer system receiving light scattering data from a light scattering detector analyzing a separation of the virus sample, differential refractive index (dRI) data from a differential refractometer analyzing the separation, and UV absorbance data A from an ultraviolet (UV) detector at at least one wavelength analyzing the separation; and (2) the computer system receiving molecular weights M of protein components of the sample. protein(expected) , the refractive index increment of the protein component (dn / dc) protein , the refractive index increment of the DNA component of the sample (dn / dc) DNA , and the extinction coefficient ε of the protein component at that at least one wavelength protein (3) receiving the light scattering data, the differential refractive index data, the molecular weight M of the protein component, and the like from a data source; protein(expected) , the refractive index increment of the protein component (dn / dc) protein , the refractive index increment of the DNA component (dn / dc) DNA , and the protein fraction of the sample, x, with respect to the optical constant K. protein and (4) calculating the calculated protein fraction x protein , differential refractive index data, ultraviolet absorbance data A, refractive index increment of protein components (dn / dc) protein , the refractive index increment of the DNA component (dn / dc) DNA , the extinction coefficient ε of the protein component at at least one wavelength protein , and the DNA extinction coefficient ε of the sample at that at least one wavelength relative to the path length L of the cell in the UV detector. DNA and 5) the computer system calculates the calculated DNA extinction coefficient ε DNAand calculating a quality attribute value of the sample for the sample. In some embodiments, the light scattering data includes static light scattering (SLS) data. For example, the light scattering data is static light scattering (SLS) data. In some embodiments, the light scattering data further includes dynamic light scattering (DLS) data. For example, the light scattering data is further dynamic light scattering (DLS) data.

[0006] In some embodiments, the virus sample includes viruses with a radius of less than 30 nm (e.g., the viruses are small and non-enveloped). For example, the virus has a radius of 14 nm. In certain embodiments, the virus sample includes adeno-associated virus (AAV). For example, the virus sample is adeno-associated virus (AAV). In some embodiments, at least one wavelength is 260 nm. In some embodiments, at least one wavelength is 280 nm. In some embodiments, the protein component includes a protein capsid. For example, the protein component is a protein capsid. In some embodiments, the data source includes at least one user input and a database.

[0007] In exemplary embodiments, the computer-implemented method, system, and computer program product include: (1) a computer system receiving light scattering data from a light scattering detector analyzing a separation of a virus sample, differential refractive index data from a differential refractometer analyzing the separation, and UV absorbance data A from an ultraviolet (UV) detector at at least one wavelength analyzing the separation; and (2) the computer system receiving molecular weights M of protein components of the sample. protein(expected) , the refractive index increment of the protein component (dn / dc) protein , the refractive index increment of the DNA component of the sample (dn / dc) DNA , the extinction coefficient ε of the protein component at the at least one wavelength protein , and the protein fraction of the sample x protein (3) receiving from a data source a protein fraction x protein, differential refractive index data, ultraviolet absorbance data A, refractive index increment of protein components (dn / dc) protein , the refractive index increment of the DNA component (dn / dc) DNA , the extinction coefficient ε of the protein component at at least one wavelength protein , and the DNA extinction coefficient ε of the sample at that at least one wavelength relative to the path length L of the cell in the UV detector. DNA and (4) the computer system calculates the calculated DNA extinction coefficient ε DNA In further embodiments, the method, system, and computer program product includes a computer system that processes light scattering data, refractive index data, molecular weights of protein components, M protein(expected) , the refractive index increment of the protein component (dn / dc) protein , the refractive index increment of the DNA component (dn / dc) DNA , and the protein fraction of the sample, x, with respect to the optical constant K. protein and further calculating:

[0008] In certain embodiments, the computer-implemented methods, systems, and computer program products enable accurate calculation of DNA extinction coefficients at 260 nm and 280 nm, which in turn enables accurate measurement of AAV quality attributes.

[0009] definition particle Particles can be components of a liquid sample dispense. Such particles can be molecules of various types and sizes, nanoparticles, virus-like particles, liposomes, emulsions, bacteria, and colloids. These particles can range in size from nanometers to microns.

[0010] Analysis of polymer or particle species in solution Analysis of macromolecular or particle species in solution can be accomplished by preparing the sample in an appropriate solvent and then injecting an aliquot into a separation system such as a liquid chromatography (LC) column or field flow fractionation (FFF) channel, where different particle species contained within the sample are separated into their various components. Once separated, typically based on size, mass, or column affinity, the sample can be subjected to analysis by light scattering, refractive index, ultraviolet absorbance, electrophoretic mobility, and viscosity response.

[0011] light scattering Light scattering (LS) is a non-invasive technique for characterizing macromolecules and a wide range of particles in solution. Two types of light scattering detection frequently used for macromolecular characterization are static light scattering and dynamic light scattering.

[0012] Dynamic Light Scattering Dynamic light scattering is also known as quasi-elastic light scattering (QELS) and photon correlation spectroscopy (PCS). DLS experiments use a high-speed photodetector to measure the time-dependent fluctuations of the scattered light signal. DLS measurements determine the diffusion coefficient of molecules or particles, which can then be used to calculate their hydrodynamic radius.

[0013] static light scattering Static light scattering (SLS) includes various techniques, such as single-angle light scattering (SALS), dual-angle light scattering (DALS), low-angle light scattering (LALS), and multi-angle light scattering (MALS). SLS experiments generally involve measuring the absolute intensity of light scattered from a sample in solution illuminated by a narrow beam of light. Such measurements are often used to determine the size and structure of sample molecules or particles, and, when combined with knowledge of the sample concentration, to determine the weight-average molar mass for appropriate classes of particles / molecules. Additionally, the nonlinearity of the scattered light intensity as a function of sample concentration can be used to measure interparticle interactions and associations.

[0014] Multi-angle light scattering Multi-angle light scattering (MALS) is an SLS technique for measuring light scattered at multiple angles by a sample. It is used to determine both the absolute molar mass and average size of molecules in solution by detecting how the molecules scatter light. Collimated light from a laser source is most often used, in which case the technique can be referred to as multiangle laser light scattering (MALLS). The term "multiangle" refers to the detection of scattered light at different discrete angles, measured, for example, by a single detector moved over a range that includes a selected specific angle, or by an array of detectors fixed at specific angular positions.

[0015] MALS measurements require a set of auxiliary elements. The most important of these is a parallel or focused light beam (usually from a laser source producing a parallel beam of monochromatic light) that illuminates an area of ​​the sample. The beam is generally plane-polarized perpendicular to the measurement plane, although other polarizations can be used, especially when studying anisotropic particles. Another necessary element is an optical cell to hold the sample being measured. Alternatively, cells incorporating means to allow measurement of flowing samples can be used. If one wishes to measure the scattering properties of single particles, one must provide a means to introduce such particles one by one through the light beam at points approximately equidistant from the surrounding detectors.

[0016] Most MALS-based measurements are performed in a plane with a set of detectors typically equidistant from the sample, whose center is located through which the illuminating beam passes. However, three-dimensional versions have also been developed, in which the detectors are on the surface of a sphere, and the sample is controlled to pass through its center, intersecting the path of the incident light beam, which passes along the diameter of the sphere. MALS techniques generally collect multiplexed data sequentially from the outputs of a set of discrete detectors. MALS light scattering photometers typically have multiple detectors.

[0017] Because different detectors within a MALS detector (i) may have slightly different quantum efficiencies and different gains, and (ii) may view different geometric scattering volumes, it may be necessary to normalize the signals captured by the photodetectors of the MALS detector at each angle. Without normalizing for these differences, the results of the MALS detector may be meaningless and improperly weighted for different detector angles.

[0018] Concentration Detector Refractive Index Detector A differential refractive index detector (dRI), or differential refractometer, or refractive index detector (RI or RID), is a detector that measures the refractive index of an analyte relative to a solvent. They are often used as detectors for high-performance liquid chromatography and size-exclusion chromatography. dRIs can detect substances with refractive indices different from those of the solvent, but because of their low sensitivity, they are considered general-purpose detectors. When light leaves one material and enters another, it bends or refracts. The refractive index of a material is a measure of how much light bends as it enters.

[0019] A differential refractive index detector contains a flow cell with two sections, one for the sample and one for the reference solvent. The dRI measures the refractive index of both sections. When only the solvent passes through the sample section, the measured refractive index of both sections is the same, but when the analyte passes through the flow cell, the two measured refractive indices are different. This difference appears as a peak in the chromatogram. Differential refractive index detectors are often used for the analysis of polymer samples in size exclusion chromatography. The dRI can output a concentration detector signal value that corresponds to the concentration value of the sample.

[0020] UV-visible spectroscopy Ultraviolet-visible spectroscopy or ultraviolet-visible spectrophotometry (UV-Vis or UV / Vis) refers to absorption or reflectance spectroscopy in the ultraviolet-visible spectral region. UV-visible detectors / UV-visible spectrophotometers use light in the visible and adjacent ranges; absorption or reflectance in the visible range directly affects the perceived color of the chemicals involved, and it is in this region of the electromagnetic spectrum that atoms and molecules undergo electronic transitions. Such absorption spectroscopy measures the transition from a ground state to an excited state. UV-visible detectors / UV-visible spectrophotometers measure the intensity of light (I) passing through a sample, which is then compared to the intensity of the light before passing through the sample (I o ) where the ratio I / I o is called transmittance and is usually expressed as a percentage (%T). The absorbance A is based on the transmittance according to the formula A = -log(%T / 100%).

[0021] The UV-Visible spectrophotometer can also be configured to measure reflectance, where the spectrophotometer measures the intensity of light reflected from a sample (I) and correlates it with the intensity of light reflected from a reference material (I o ) compared to the ratio I / I o is called reflectance and is usually expressed as a percentage (%R). The ultraviolet absorption detector can output a concentration detector signal value that corresponds to the concentration value of the sample.

[0022] Current Technology Current techniques used to measure AAV quality attributes require the following sample constants: the respective dn / dc values ​​and the extinction coefficients of the AAV protein capsid and encapsulated DNA. While the dn / dc values ​​are well known, the extinction coefficients of the protein capsid at 260 nm and 280 nm can be estimated from the amino acid sequence of the capsid protein or can be determined experimentally using software. However, the extinction coefficient of the encapsulated DNA is not well known. Current techniques back-calculate these values ​​by assuming that a "perfect" AAV sample is 100% intact. However, in the real world, 100% intact AAV samples are often unavailable, and the extinction coefficient of the encapsulated DNA can vary depending on the length of the DNA. Therefore, there is a need for more accurate measurement of the quality attributes of viral samples.

[0023] Referring to FIG. 1A , in an exemplary embodiment, a computer-implemented method, system, and computer program product includes an operation 110 in which a computer system receives light scattering (LS) data from a light scattering detector analyzing a separation of a virus sample, differential refractive index (dRI) data from a differential refractometer analyzing the separation, and UV absorbance data A from an ultraviolet (UV) detector at at least one wavelength analyzing the separation; and the computer system receives molecular weights M of protein components of the sample. protein(expected) , the refractive index increment of the protein component (dn / dc) protein, the refractive index increment of the DNA component of the sample (dn / dc) DNA , and the extinction coefficient ε of the protein component at that at least one wavelength protein and an operation 112 of receiving from a data source the light scattering data, the differential refractive index data, the molecular weight M of the protein component, and protein(expected) , the refractive index increment of the protein component (dn / dc) protein , the refractive index increment of the DNA component (dn / dc) DNA , and the protein fraction of the sample, x, with respect to the optical constant K. protein and an operation 114 of calculating 114 the calculated protein fraction x protein , differential refractive index data, ultraviolet absorbance data A, refractive index increment of protein components (dn / dc) protein , the refractive index increment of the DNA component (dn / dc) DNA , the extinction coefficient ε of the protein component at the at least one wavelength protein , and the DNA extinction coefficient ε of the sample at that at least one wavelength relative to the path length L of the cell in the UV detector. DNA and an operation 116 of calculating 116 the calculated DNA extinction coefficient ε DNA and operation 118 of calculating a quality attribute value of the sample for

[0024] In an exemplary embodiment, the computer system is a standalone computer system such as computer system 500 shown in FIG. 5 , a network of distributed computers in which at least some of the computers are computer systems such as computer system 500 shown in FIG. 5 , or a cloud computing node server such as computer system 500 shown in FIG. 5 . In an embodiment, the computer system is computer system 500 as shown in FIG. 5 that executes a script or computer software application that performs measurements of quality attributes of virus samples to perform at least the operations of method 100. In an embodiment, the computer system is computer system / server 512 as shown in FIG. 5 that executes a script or computer software application that performs measurements of quality attributes of virus samples to perform at least the operations of method 100. In an embodiment, the computer system is processing unit 516 as shown in FIG. 5 that executes a script or computer software application that performs measurements of quality attributes of virus samples to perform at least the operations of method 100. In an embodiment, the computer system is machine learning computer software / program / algorithm that executes a script or computer software application that performs measurements of quality attributes of virus samples to perform at least the operations of method 100.

[0025] In one embodiment, the computer system is computer system 500 as shown in Figure 5 that executes a script or computer software application that performs measurements of quality attributes of virus samples, performing at least operations 110, 112, 114, 116, and 118. In one embodiment, the computer system is computer system / server 512 as shown in Figure 5 that executes a script or computer software application that performs measurements of quality attributes of virus samples, performing at least operations 110, 112, 114, 116, and 118. In one embodiment, the computer system is processing unit 516 as shown in Figure 5 that executes a script or computer software application that performs measurements of quality attributes of virus samples, performing at least operations 110, 112, 114, 116, and 118.

[0026] 1B , in an exemplary embodiment, a computer-implemented method, system, and computer program product includes a receiver 120 and a calculator 122. In an embodiment, receiver 120 is configured to receive light scattering (LS) data 130 from a light scattering detector 140 analyzing a separation 150 of a virus sample, differential refractive index (dRI) data 132 from a differential refractometer 142 analyzing the separation 150, and UV absorbance data A 134 from an ultraviolet (UV) detector 144 at at least one wavelength analyzing the separation 150. In an embodiment, receiver 120 includes a computer system, such as computer system 500 as shown in FIG. 5 , that performs operation 110. In an embodiment, receiver 120 includes a computer system, such as computer system / server 512 as shown in FIG. 5 , that performs operation 110. In an embodiment, receiver 120 includes a computer system, such as processing unit 516 as shown in FIG. 5 , that performs operation 110. In one embodiment, receiver 120 is implemented as computer software executing on a computer system, such as computer system 500 as shown in Figure 5, such that the computer system performs operation 110. In one embodiment, receiver 120 is implemented as computer software executing on a computer system, such as computer system / server 512 as shown in Figure 5, such that the computer system performs operation 110. In one embodiment, receiver 120 is implemented as computer software executing on a computer system, such as processing unit 516 as shown in Figure 5, such that the computer system performs operation 110. In one embodiment, receiver 120 performs operation 110 as computer software executing on a processor of receiver 120.

[0027] In one embodiment, the receiver 120 detects the molecular weight M of the protein component of the sample. protein(expected) , the refractive index increment of the protein component (dn / dc) protein , the refractive index increment of the DNA component of the sample (dn / dc) DNA , and the extinction coefficient ε of the protein component at at least one wavelengthprotein from data source 146. In one embodiment, receiver 122 comprises a computer system, such as computer system 500 as shown in FIG. 5 , that performs operation 112. In one embodiment, receiver 120 comprises a computer system, such as computer system / server 512 as shown in FIG. 5 , that performs operation 112. In one embodiment, receiver 120 comprises a computer system, such as processing unit 516 as shown in FIG. 5 , that performs operation 112. In one embodiment, receiver 120 is implemented as computer software running on a computer system, such as computer system 500 as shown in FIG. 5 , such that the computer system performs operation 112. In one embodiment, receiver 120 is implemented as computer software running on a computer system, such as computer system / server 512 as shown in FIG. 5 , such that the computer system performs operation 112. In one embodiment, receiver 120 is implemented as computer software running on a computer system, such as processing unit 516 as shown in FIG. 5 , such that the computer system performs operation 112. In one embodiment, receiver 120 performs operations 112 as computer software executing on a processor of receiver 120 .

[0028] In one embodiment, the calculator 122 calculates the light scattering (LS) data 130, the differential refractive index (dRI) data 132, the molecular weights M of the protein components, and the protein(expected) , the refractive index increment of the protein component (dn / dc) protein , the refractive index increment of the DNA component (dn / dc) DNA , and the protein fraction of the sample, x, with respect to the optical constant K. protein160. In one embodiment, calculator 122 comprises a computer system, such as computer system 800 as shown in FIG. 8, that performs operation 114. In one embodiment, calculator 122 comprises a computer system, such as computer system / server 812 as shown in FIG. 8, that performs operation 114. In one embodiment, calculator 122 comprises a computer system, such as processing unit 816 as shown in FIG. 8, that performs operation 114. In one embodiment, calculator 122 is implemented as computer software running on a computer system, such as computer system 800 as shown in FIG. 8, such that the computer system performs operation 114. In one embodiment, calculator 122 is implemented as computer software running on a computer system, such as computer system / server 812 as shown in FIG. 8, such that the computer system performs operation 114. In one embodiment, calculator 122 is implemented as computer software running on a computer system, such as processing unit 816 as shown in FIG. 8, such that the computer system performs operation 114. In one embodiment, calculator 122 performs operations 114 as computer software executing on a processor of calculator 122 .

[0029] In one embodiment, the calculator 122 calculates the calculated protein fraction x protein 160, differential refractive index (dRI) data 132, ultraviolet (UV) absorbance data A134, refractive index increment of protein components (dn / dc) protein , the refractive index increment of the DNA component (dn / dc) DNA , the extinction coefficient ε of the protein component at at least one wavelength protein , and the DNA extinction coefficient ε of the sample at that at least one wavelength versus the path length L of the cell in the UV detector. DNA162. In one embodiment, calculator 122 comprises a computer system, such as computer system 800 as shown in FIG. 8, that performs operation 116. In one embodiment, calculator 122 comprises a computer system, such as computer system / server 812 as shown in FIG. 8, that performs operation 116. In one embodiment, calculator 122 comprises a computer system, such as processing unit 816 as shown in FIG. 8, that performs operation 116. In one embodiment, calculator 122 is implemented as computer software running on a computer system, such as computer system 800 as shown in FIG. 8, such that the computer system performs operation 116. In one embodiment, calculator 122 is implemented as computer software running on a computer system, such as computer system / server 812 as shown in FIG. 8, such that the computer system performs operation 116. In one embodiment, calculator 122 is implemented as computer software running on a computer system, such as processing unit 816 as shown in FIG. 8, such that the computer system performs operation 116. In one embodiment, calculator 122 performs operations 116 as computer software executing on a processor of calculator 122 .

[0030] In one embodiment, the calculator 122 calculates the calculated DNA extinction coefficient ε DNA8 , configured to calculate a quality attribute value 164 for the sample relative to 162. In an embodiment, calculator 122 comprises a computer system, such as computer system 800 as shown in FIG. 8 , that performs operation 118. In an embodiment, calculator 122 comprises a computer system, such as computer system / server 812 as shown in FIG. 8 , that performs operation 118. In an embodiment, calculator 122 comprises a computer system, such as processing unit 816 as shown in FIG. 8 , that performs operation 118. In an embodiment, calculator 122 is implemented as computer software running on a computer system, such as computer system 800 as shown in FIG. 8 , such that the computer system performs operation 118. In an embodiment, calculator 122 is implemented as computer software running on a computer system, such as computer system / server 812 as shown in FIG. 8 , such that the computer system performs operation 118. In an embodiment, calculator 122 is implemented as computer software running on a computer system, such as processing unit 816 as shown in FIG. 8 , such that the computer system performs operation 118. In one embodiment, calculator 122 performs operations 118 as computer software executing on a processor of calculator 122 .

[0031] Referring to FIG. 2 , in an exemplary embodiment, a computer-implemented method, system, and computer program product includes an operation 210 in which a computer system receives light scattering data from a light scattering detector analyzing a separation of a virus sample, differential refractive index data from a differential refractometer analyzing the separation, and UV absorbance data A from an ultraviolet (UV) detector at at least one wavelength analyzing the separation; and the computer system receives molecular weights M of protein components of the sample. protein(expected) , the refractive index increment of the protein component (dn / dc) protein , the refractive index increment of the DNA component of the sample (dn / dc) DNA , the extinction coefficient ε of the protein component at the at least one wavelength protein , and the protein fraction of the sample x proteinfrom a data source; and the computer system receives 212 the protein fraction x protein , differential refractive index data, ultraviolet absorbance data A, refractive index increment of protein components (dn / dc) protein , the refractive index increment of the DNA component (dn / dc) DNA , the extinction coefficient ε of the protein component at at least one wavelength protein , and the DNA extinction coefficient ε of the sample at that at least one wavelength relative to the path length L of the cell in the UV detector. DNA and an operation 214 in which the computer system calculates the calculated DNA extinction coefficient ε DNA and operation 216 of calculating a quality attribute value of the sample for

[0032] In one embodiment, the computer system is computer system 500 as shown in Figure 5 that executes a script or computer software application that performs measurements of quality attributes of virus samples to perform at least the operations of method 200. In one embodiment, the computer system is computer system / server 512 as shown in Figure 5 that executes a script or computer software application that performs measurements of quality attributes of virus samples to perform at least the operations of method 200. In one embodiment, the computer system is processing unit 516 as shown in Figure 5 that executes a script or computer software application that performs measurements of quality attributes of virus samples to perform at least the operations of method 200. In one embodiment, the computer system is machine learning computer software / program / algorithm that executes a script or computer software application that performs measurements of quality attributes of virus samples to perform at least the operations of method 200.

[0033] In one embodiment, the computer system is computer system 500 as shown in Figure 5 that executes a script or computer software application that performs measurements of quality attributes of virus samples that perform at least operations 210, 212, 214, and 216. In one embodiment, the computer system is computer system / server 512 as shown in Figure 5 that executes a script or computer software application that performs measurements of quality attributes of virus samples that perform at least operations 210, 212, 214, and 216. In one embodiment, the computer system is processing unit 516 as shown in Figure 5 that executes a script or computer software application that performs measurements of quality attributes of virus samples that perform at least operations 210, 212, 214, and 216.

[0034] Protein fraction calculation In one embodiment, the protein fraction x of the sample protein Calculating the protein fraction x of the sample is performed by the computer system. protein This includes calculating:

[0035]

number

[0036] where R θ is the excess Rayleigh ratio derived from light scattering data, and dRI is the differential refractive index (dRI) data. In a further embodiment, the protein fraction of the sample, x protein is calculated by a computer system using the refractive index of the solvent, n0, the wavelength of the light scattering detector, λ, and the Avogrado number, N A In some embodiments, calculating the optical constant K includes calculating, by the computer system, the optical constant K according to the following equation:

[0037]

number

[0038] Calculation of DNA extinction coefficient In one embodiment, the DNA extinction coefficient ε of the sample DNA Calculating the DNA extinction coefficient ε of the sample DNA This includes calculating:

[0039]

number

[0040] Calculating quality attribute values In one embodiment, calculating the quality attribute value of the sample comprises calculating a quality attribute value of the sample using a computer system that calculates a quality attribute value of the sample using a calculated DNA extinction coefficient ε DNA the ratio value of intact capsids to total capsids in the sample, V g / C p In one embodiment, calculating the quality attribute value of the sample includes calculating a calculated DNA extinction coefficient ε DNA The particle concentration value C of the sample p In one embodiment, calculating the quality attribute value of the sample includes calculating a calculated DNA extinction coefficient ε DNA This involves calculating the molar mass value M of the sample relative to

[0041] Example In one embodiment, FIGS. 3A and 3B illustrate methods, systems, and computer products that can be used to generate a ratio of intact capsids to total capsids in a sample, V g / C p In particular, FIG. 3A illustrates how well the quality attributes of the measured V g / C p Value and expected V g / C pFigures 3A, 3B, and Table 1 provide examples of a series of AAV samples for which encapsulated DNA with optimized extinction coefficients was collected using the method, system, and computer product at 260 nm, 280 nm, or both 260 nm and 280 nm in the case of UV data at both wavelengths.

[0042] AAV samples were prepared by mixing known amounts of "intact" and "empty" AAV of the same serotype together. Mixtures ranged from 3% intact (Vg / Cp = 0.03) to 97% intact (Vg / Cp = 0.97); data for 100% empty and 100% intact were also collected. Each sample was analyzed in duplicate. For each measurement, particle concentration, molar mass value, and intact-to-intact ratio (Vg / Cp) were calculated using (i) a non-optimized "seed value" and (ii) optimized coefficients obtained by the method, system, and computer product. Input parameters are summarized in Table 1.

[0043] [Table 1]

[0044] Although the optimized coefficients do not differ significantly from the seed values, their impact on the measured Vg / Cp is significant. Figure 3A shows the Vg / Cp measured using the optimized extinction coefficients compared to the seed values. As shown in Figures 3A and 3B, for mixtures with a low percentage of intact AAV (low Vg / Cp), the impact of the improved extinction coefficient is negligible, but at higher Vg / Cp, typical of purified samples, the difference becomes significant.

[0045] With a non-optimized extinction coefficient, the error in Vg / Cp gets progressively worse as Vg / Cp increases, as shown in Figure 3B. As shown in Figure 3B, in the worst case, with a non-optimized coefficient, a sample known to be 97% complete is measured to be 88% complete, whereas with the optimized coefficient, the error in Vg / Cp is within 0.04, with the majority of the data falling within ±0.02 of the actual value.

[0046] 4 depicts a typical hardware / equipment configuration for methods, systems, and computer products. For example, the typical hardware / equipment configuration may include a degasser 410, a pump 412, an autosampler 414, a UV detector 416, an SLS instrument 418, and a dRI detector 420.

[0047] Computer Systems In an exemplary embodiment, the computer system is computer system 500 as shown in Figure 5. Computer system 500 is merely one example of a computer system and is not intended to suggest any limitation as to the scope of use or functionality of embodiments of the present invention. In any event, computer system 500 is implemented and / or capable of performing any of the functions / operations of the present invention.

[0048] Computer system 500 includes a computer system / server 512 that is operational with numerous other general purpose or special purpose computing system environments or configurations. Examples of well-known computing systems, environments, and / or configurations that may be suitable for use with computer system / server 512 include, but are not limited to, personal computer systems, server computer systems, thin clients, thick clients, handheld or laptop devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputer systems, mainframe computer systems, and distributed cloud computing environments that include any of the above systems or devices.

[0049] The computer system / server 512 may be described in the general context of computer system-executable instructions, such as program modules, being executed by a computer system. Generally, program modules may include routines, programs, objects, components, logic, and / or data structures that perform particular tasks or implement particular abstract data types. The computer system / server 512 may be practiced in a distributed cloud computing environment where tasks are performed by remote processing devices linked through a communications network. In a distributed cloud computing environment, program modules may be located in both local and remote computer system storage media, including memory storage devices.

[0050] 5, computer system / server 512 in computer system 500 is shown in the form of a general-purpose computing device. Components of computer system / server 512 may include, but are not limited to, one or more processors or processing units 516, a system memory 528, and a bus 518 that couples various system components including the system memory 528 to the processor 516.

[0051] Bus 518 represents any one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, a high-speed graphics port, and a processor or local bus using any of a variety of bus architectures. By way of example and not limitation, such architectures include an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MCA) bus, an Enhanced ISA (EISA) bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus.

[0052] Computer system / server 512 typically includes a variety of computer system-readable media. Such media can be any available media that can be accessed by computer system / server 512 and includes both volatile and nonvolatile media, removable and non-removable media.

[0053] The system memory 528 may include computer system-readable media in the form of volatile memory, such as random access memory (RAM) 530 and / or cache memory 532. The computer system / server 512 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 534 may be provided for reading from and writing to a non-removable, non-volatile magnetic medium (not shown, typically referred to as a "hard drive"). Although not shown, a magnetic disk drive may be provided for reading from and writing to a removable, non-volatile magnetic disk (e.g., a "floppy disk"), and an optical disk drive may be provided for reading from and writing to a removable, non-volatile optical disk, such as a CD-ROM, DVD-ROM, or other optical medium. In such cases, each may be connected to the bus 518 by one or more data medium interfaces. As further depicted and described below, the memory 528 may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions / operations of embodiments of the present invention.

[0054] A program / utility 540 having a set (at least one) of program modules 542 may be stored in memory 528, by way of example and not limitation. Exemplary program modules 542 may include an operating system, one or more application programs, other program modules, and program data. Each of the operating system, one or more application programs, other program modules, and program data, or any combination thereof, may comprise an implementation of a network environment. The program modules 542 generally perform the functions and / or methods of embodiments of the present invention.

[0055] The computer system / server 512 may also communicate with one or more external devices 514, such as a keyboard, a pointing device, a display 524, one or more devices that allow a user to interact with the computer system / server 512, and / or any device (e.g., a network card, a modem, etc.) that allows the computer system / server 512 to communicate with one or more other computing devices. Such communication may occur via an input / output (I / O) interface 522. Additionally, the computer system / server 512 may communicate with one or more networks, such as a local area network (LAN), a general wide area network (WAN), and / or a public network (e.g., the Internet), via a network adapter 520. As depicted, the network adapter 520 communicates with other components of the computer system / server 512 via a bus 518. It should be understood that other hardware and / or software components, not shown, may be used with the computer system / server 512. Examples include, but are not limited to, microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data archival storage systems.

[0056] computer program products The present invention may be a system, a method, and / or a computer program product. The computer program product may include a computer-readable storage medium having computer-readable program instructions for causing a processor to perform aspects of the present invention.

[0057] A computer-readable storage medium may be a tangible device that can hold and store instructions for use by an instruction execution device. The computer-readable storage medium may be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of computer-readable storage media includes portable computer diskettes, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital versatile disk (DVD), memory sticks, floppy disks, mechanically encoded devices such as punch cards or ridge structures in grooves with instructions recorded on them, and any suitable combination of the above. Computer-readable storage medium, as used herein, should not be construed as being a transitory signal per se, such as an electric wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., a light pulse passing through a fiber optic cable), or an electrical signal transmitted through an electrical wire.

[0058] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device or to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network may include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in the respective computing / processing device.

[0059] The computer-readable program instructions for carrying out the operations of the present invention may be either source code or object code written in any combination of one or more programming languages, including assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state-setting data, or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, and conventional procedural programming languages ​​such as the "C" programming language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection to the external computer may be made (e.g., via the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, a programmable logic circuit, a field-programmable gate array (FPGA), or a programmable logic array (PLA) may execute computer-readable program instructions by utilizing state information of the computer-readable program instructions to customize the electronic circuitry to perform aspects of the present invention.

[0060] Aspects of the present invention are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0061] These computer-readable program instructions may be provided to a processor of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, executed by the processor of the computer or other programmable data processing apparatus, create means for performing the functions / acts specified in one or more blocks of the flowcharts and / or block diagrams. These computer-readable program instructions may also be stored on a computer-readable storage medium that can direct a computer, programmable data processing apparatus, and / or other device to function in a particular manner, such that the computer-readable storage medium on which the instructions are stored comprises a product containing instructions that implement aspects of the functions / acts specified in one or more blocks of the flowcharts and / or block diagrams.

[0062] The computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus, or other device to generate a computer-implemented process, such that the instructions executing on the computer, other programmable apparatus, or other device perform the functions / acts specified in one or more blocks of the flowcharts and / or block diagrams.

[0063] The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of instructions, including one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the blocks may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending on the functionality involved. It should also be noted that each block of the block diagrams and / or flowchart illustrations, and combinations of blocks in the block diagrams and / or flowchart illustrations, may be implemented by a dedicated hardware-based system that performs the specified functions or operations or executes a combination of dedicated hardware and computer instructions.

[0064] The description of various embodiments of the present disclosure has been presented for purposes of illustration and is not intended to be exhaustive or limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terms used herein have been selected to explain the principles of the embodiments, practical applications or technical improvements to technology found in the market, or to enable those skilled in the art to understand the embodiments disclosed herein.

Claims

1. 1. A computer-implemented method comprising: a computer system receiving light scattering data from a light scattering detector analyzing a separation of a virus sample, differential refractive index data from a differential refractometer analyzing said separation, and UV absorbance data A from an ultraviolet (UV) detector at at least one wavelength analyzing said separation; The computer system calculates the molecular weight M of the protein component of the sample. ｐｒｏｔｅｉｎ（ｅｘｐｅｃｔｅｄ） , the refractive index increment of the protein component (dn / dc) ｐｒｏｔｅｉｎ , the refractive index increment of the DNA component of the sample (dn / dc) ＤＮＡ and the extinction coefficient ε of the protein component at the at least one wavelength ｐｒｏｔｅｉｎ from a data source; The computer system calculates the light scattering data, the differential refractive index data, and the molecular weight M ｐｒｏｔｅｉｎ（ｅｘｐｅｃｔｅｄ） , the refractive index increment (dn / dc) of the protein component ｐｒｏｔｅｉｎ , the refractive index increment (dn / dc) of the DNA component ＤＮＡ , and the protein fraction x of the sample relative to the optical constant K ｐｒｏｔｅｉｎ and The computer system calculates the protein fraction x ｐｒｏｔｅｉｎ , the differential refractive index data, the ultraviolet absorbance data A, and the refractive index increment (dn / dc) of the protein component. ｐｒｏｔｅｉｎ , the refractive index increment (dn / dc) of the DNA component ＤＮＡ , the extinction coefficient ε of the protein component at the at least one wavelength ｐｒｏｔｅｉｎ and the DNA extinction coefficient ε of the sample at the at least one wavelength relative to the path length L of a cell in the UV detector. ＤＮＡ and The computer system calculates the DNA extinction coefficient ε ＤＮＡ and calculating a quality attribute value of the sample relative to

2. The method of claim 1 , wherein the light scattering data comprises static light scattering (SLS) data.

3. The method of claim 2 , wherein the light scattering data further comprises dynamic light scattering (DLS) data.

4. 10. The method of claim 1, wherein the virus sample comprises viruses having a radius of less than 30 nm.

5. 5. The method of claim 4, wherein the virus sample comprises an adeno-associated virus (AAV).

6. The method of claim 1 , wherein the at least one wavelength is 260 nm.

7. The method of claim 1 , wherein the at least one wavelength is 280 nm.

8. The protein fraction x of the sample ｐｒｏｔｅｉｎ said calculating The computer system calculates the solvent refractive index n ０ , the wavelength λ of the light scattering detector, and the Avogrado number N Ａ The method of claim 1 further comprising calculating the optical constant K for

9. said calculating said quality attribute value of said sample further comprising: The computer system calculates the calculated DNA extinction coefficient ε ＤＮＡ the ratio value V of intact capsids to total capsids of the sample ｇ / C ｐ The method of claim 1 , comprising calculating:

10. said calculating said quality attribute value of said sample further comprising: The computer system calculates the calculated DNA extinction coefficient ε ＤＮＡ The particle concentration value C of the sample ｐ The method of claim 1 , comprising calculating:

11. said calculating said quality attribute value of said sample further comprising: The computer system calculates the calculated DNA extinction coefficient ε ＤＮＡ 2. The method of claim 1, further comprising calculating a molar mass value M of the sample relative to

12. 1. A computer-implemented method comprising: a computer system receiving light scattering data from a light scattering detector analyzing a separation of a virus sample, differential refractive index data from a differential refractometer analyzing said separation, and UV absorbance data A from an ultraviolet (UV) detector at at least one wavelength analyzing said separation; The computer system calculates the molecular weight M of the protein component of the sample. ｐｒｏｔｅｉｎ（ｅｘｐｅｃｔｅｄ） , the refractive index increment of the protein component (dn / dc) ｐｒｏｔｅｉｎ , the refractive index increment of the DNA component of the sample (dn / dc) ＤＮＡ , the extinction coefficient ε of the protein component at the at least one wavelength ｐｒｏｔｅｉｎ and the protein fraction x of said sample ｐｒｏｔｅｉｎ from a data source; The computer system ｐｒｏｔｅｉｎ , the differential refractive index data, the ultraviolet absorbance data A, and the refractive index increment (dn / dc) of the protein component. ｐｒｏｔｅｉｎ , the refractive index increment (dn / dc) of the DNA component ＤＮＡ , the extinction coefficient ε of the protein component at the at least one wavelength ｐｒｏｔｅｉｎ and the DNA extinction coefficient ε of the sample at the at least one wavelength relative to the path length L of a cell in the UV detector. ＤＮＡ and The computer system calculates the DNA extinction coefficient ε ＤＮＡ and calculating a quality attribute value of the sample relative to

13. The computer system calculates the light scattering data, the differential refractive index data, and the molecular weight M ｐｒｏｔｅｉｎ（ｅｘｐｅｃｔｅｄ） , the refractive index increment (dn / dc) of the protein component ｐｒｏｔｅｉｎ , the refractive index increment (dn / dc) of the DNA component ＤＮＡ , and the protein fraction x of the sample relative to the optical constant K. ｐｒｏｔｅｉｎ The method of claim 12 further comprising calculating:

14. The protein fraction x of the sample ｐｒｏｔｅｉｎ said calculating The computer system calculates the solvent refractive index n ０ , the wavelength λ of the light scattering detector, and the Avogrado number N Ａ The method of claim 13 further comprising calculating the optical constant K for

15. said calculating said quality attribute value of said sample further comprising: The computer system calculates the calculated DNA extinction coefficient ε ＤＮＡ the ratio value V of intact capsids to total capsids of the sample ｇ / C ｐ The method of claim 12, comprising calculating:

16. said calculating said quality attribute value of said sample further comprising: The computer system calculates the calculated DNA extinction coefficient ε ＤＮＡ The particle concentration value C of the sample ｐ The method of claim 12, comprising calculating:

17. said calculating said quality attribute value of said sample further comprising: The computer system calculates the calculated DNA extinction coefficient ε ＤＮＡ 13. The method of claim 12, comprising calculating a molar mass value M of the sample relative to

18. 1. A system comprising: Memory and a processor in communication with the memory, the processor comprising: receiving light scattering data from a light scattering detector analyzing a separation of a virus sample, differential refractive index data from a differential refractometer analyzing said separation, and UV absorbance data A from an ultraviolet (UV) detector at at least one wavelength analyzing said separation; The molecular weight M of the protein component of the sample ｐｒｏｔｅｉｎ（ｅｘｐｅｃｔｅｄ） , the refractive index increment of the protein component (dn / dc) ｐｒｏｔｅｉｎ , the refractive index increment of the DNA component of the sample (dn / dc) ＤＮＡ and the extinction coefficient ε of the protein component at the at least one wavelength ｐｒｏｔｅｉｎ from a data source; The light scattering data, the differential refractive index data, the molecular weight M of the protein component ｐｒｏｔｅｉｎ（ｅｘｐｅｃｔｅｄ） , the refractive index increment (dn / dc) of the protein component ｐｒｏｔｅｉｎ , the refractive index increment (dn / dc) of the DNA component ＤＮＡ , and the protein fraction x of the sample relative to the optical constant K ｐｒｏｔｅｉｎ and The calculated protein fraction x ｐｒｏｔｅｉｎ , the differential refractive index data, the ultraviolet absorbance data A, and the refractive index increment (dn / dc) of the protein component. ｐｒｏｔｅｉｎ , the refractive index increment (dn / dc) of the DNA component ＤＮＡ , the extinction coefficient ε of the protein component at the at least one wavelength ｐｒｏｔｅｉｎ and the DNA extinction coefficient ε of the sample at the at least one wavelength relative to the path length L of a cell in the UV detector. ＤＮＡ and The calculated DNA extinction coefficient ε ＤＮＡ and calculating a quality attribute value of the sample relative to the

19. 1. A computer program product comprising a computer-readable storage medium having program instructions embodied thereon, the program instructions causing a processor to: receiving light scattering data from a light scattering detector analyzing a separation of a virus sample, differential refractive index data from a differential refractometer analyzing said separation, and UV absorbance data A from an ultraviolet (UV) detector at at least one wavelength analyzing said separation; The molecular weight M of the protein component of the sample ｐｒｏｔｅｉｎ（ｅｘｐｅｃｔｅｄ） , the refractive index increment of the protein component (dn / dc) ｐｒｏｔｅｉｎ , the refractive index increment of the DNA component of the sample (dn / dc) ＤＮＡ and the extinction coefficient ε of the protein component at the at least one wavelength ｐｒｏｔｅｉｎ from a data source; The light scattering data, the differential refractive index data, the molecular weight M of the protein component ｐｒｏｔｅｉｎ（ｅｘｐｅｃｔｅｄ） , the refractive index increment (dn / dc) of the protein component ｐｒｏｔｅｉｎ , the refractive index increment (dn / dc) of the DNA component ＤＮＡ , and the protein fraction x of the sample relative to the optical constant K ｐｒｏｔｅｉｎ and The calculated protein fraction x ｐｒｏｔｅｉｎ , the differential refractive index data, the ultraviolet absorbance data A, and the refractive index increment (dn / dc) of the protein component. ｐｒｏｔｅｉｎ , the refractive index increment (dn / dc) of the DNA component ＤＮＡ , the extinction coefficient ε of the protein component at the at least one wavelength ｐｒｏｔｅｉｎ and the DNA extinction coefficient ε of the sample at the at least one wavelength relative to the path length L of a cell in the UV detector. ＤＮＡ and The calculated DNA extinction coefficient ε ＤＮＡ and calculating a quality attribute value of the sample for the

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