Measurement of the attributes of viral gene delivery vehicle samples by isolation.

Abstract

The present invention provides an apparatus, method, and system for measuring the attributes of a viral gene delivery vehicle sample through isolation. [Solution] In one embodiment, the method, system, and computer program product perform a series of logical operations to analyze a viral gene delivery vehicle sample in a set of analytical instruments including at least one separation instrument, at least one static light scattering instrument, and at least two concentration detectors, thereby determining the capsid protein mass of the sample m A And the sample modification factor mass m B And the molar mass M of the modifying factor in the sample B This results in the molar mass of the capsid protein in the sample M A The data source receives the molar mass of the capsid protein, the injection volume v of the sample from the injection volume data source, and the total VGDV particle concentration C of the sample. A This includes performing a series of logical operations to calculate [something].

Description

[Technical Field]

[0001] Priority This application claims priority to U.S. Patent Application No. 16 / 991,016, filed on 11 August 2020. [Background technology]

[0002] background This disclosure relates to samples, and more specifically, to the measurement of attributes of viral gene delivery vehicle samples by isolation. [Overview of the project] [Means for solving the problem]

[0003] overview This disclosure describes a computer-aided method, system, and computer program product for measuring the attributes of a viral gene delivery vehicle (VGDV) sample by separation. In an exemplary embodiment, the computer-aided method, system, and computer program product (1) by performing a series of logical operations by a computer system to analyze a viral gene delivery vehicle (VGDV) sample in a set of analytical instruments including at least one separation instrument, at least one static light scattering instrument, and at least two concentration detectors, thereby determining the capsid protein mass of the sample m A And the sample modification factor mass m B And the molar mass M of the modifying factor in the sample B (2) The molar mass of the capsid protein in the sample M A (3) receiving the molar mass of the capsid protein from the data source, (4) receiving the injection volume v of the sample from the injection volume data source, and (5) receiving the total VGDV particle concentration C of the sample from the computer system. A This includes performing a series of logical operations that calculate using the following formula, C A =(m A ×N) / (M A ×v) In the formula, N is Avogadrois a number. In one embodiment, the sample is a lentiviral vector sample. In one embodiment, the sample is an adenoviral vector sample. In one embodiment, the sample is an adeno-associated virus (AAV) sample. In one embodiment, the modified factor mass m of the sample B is the nucleic acid mass of the sample. In one embodiment, the modified factor molar mass M of the sample B is the nucleic acid molar mass of the sample. BRIEF DESCRIPTION OF THE DRAWINGS

[0004] [Figure 1A] A flowchart according to an exemplary embodiment is shown. [Figure 1B] A block diagram according to an exemplary embodiment is shown. [Figure 1C] A flowchart according to an exemplary embodiment is shown. [Figure 1D] A flowchart according to an exemplary embodiment is shown. [Figure 1E] A flowchart according to an exemplary embodiment is shown. [Figure 1F] A flowchart according to an exemplary embodiment is shown. [Figure 1G] A flowchart according to an exemplary embodiment is shown. [Figure 2A] A flowchart according to one embodiment is shown. [Figure 2B] A flowchart according to one embodiment is shown. [Figure 3A] An apparatus according to one embodiment is shown. [Figure 3B] An apparatus according to one embodiment is shown. [Figure 3C] An apparatus according to one embodiment is shown. [Figure 3D] An apparatus according to one embodiment is shown. [Figure 3E] A typical set of equipment is shown. [Figure 4A] A graph according to one embodiment is shown. [Figure 4B]A graph illustrating one embodiment is shown. [Figure 4C] A graph illustrating one embodiment is shown. [Figure 5] A graph illustrating one embodiment is shown. [Figure 6A] A graph illustrating one embodiment is shown. [Figure 6B] A graph illustrating one embodiment is shown. [Figure 6C] A graph illustrating one embodiment is shown. [Figure 7A] A graph illustrating one embodiment is shown. [Figure 7B] A graph illustrating one embodiment is shown. [Figure 7C] A graph illustrating one embodiment is shown. [Figure 8] This shows a computer system according to an exemplary embodiment. [Modes for carrying out the invention]

[0005] Detailed explanation This disclosure describes a computer-aided method, system, and computer program product for measuring the attributes of a viral gene delivery vehicle (VGDV) sample by separation. In an exemplary embodiment, the computer-aided method, system, and computer program product (1) by performing a series of logical operations by a computer system to analyze a viral gene delivery vehicle (VGDV) sample in a set of analytical instruments including at least one separation instrument, at least one static light scattering instrument, and at least two concentration detectors, thereby determining the capsid protein mass of the sample m A And the sample modification factor mass m B And the molar mass M of the modifying factor in the sample B (2) The molar mass of the capsid protein in the sample M A (3) receiving the molar mass of the capsid protein from the data source, (4) receiving the injection volume v of the sample from the injection volume data source, and (5) receiving the total VGDV particle concentration C of the sample from the computer system.A This includes performing a series of logical operations that calculate using the following formula, C A =(m A ×N) / (M A ×v) In the formula, N is Avogadro It is a number. In one embodiment, the sample is a lentiviral vector sample. In one embodiment, the sample is an adenovirus vector sample. In one embodiment, the sample is an adeno-associated virus (AAV) sample. In one embodiment, the mass of the modifying factor of the sample is m B This is the nucleic acid mass of the sample. In one embodiment, the molar mass of the modifying factor M of the sample is... B This is the molar mass of the nucleic acid in the sample.

[0006] definition particle The particles may be components of the liquid sample. Such particles may be molecules, nanoparticles, virus-like particles, liposomes, emulsions, bacteria, and colloids of various types and sizes. The size of these particles may range from nanometers to several microns.

[0007] Analysis of polymer or particle species in solution Analysis of polymer or particulate species in solution can be achieved by preparing a sample in a suitable solvent and then injecting a certain amount of it into a separation system such as a liquid chromatography (LC) column or field flow fractionation (FFF) channel that separates the various particulate species contained in the sample into their various components. Once separated, generally based on size, mass, or column affinity, the sample can be subjected to analysis by light scattering, refractive index, ultraviolet absorption, electrophoretic mobility, and viscosity response.

[0008] light scattering Light scattering (LS) is a non-invasive technique for evaluating the properties of polymers and a wide range of particles in solution. Two types of light scattering detection, static and dynamic, are commonly used to evaluate polymer properties.

[0009] Dynamic light scattering Dynamic light scattering is also known as quasi-elastic light scattering (QELS) and photon correlation spectroscopy (PCS). In DLS experiments, the time-dependent variation of the scattered light signal is measured using a fast photodetector. DLS measurements can be used to determine the diffusion coefficient of a molecule or particle, which can then be used to calculate the hydrodynamic radius of the molecule or particle.

[0010] static light scattering Static light scattering (SLS) encompasses various techniques, including 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 scattered light from a sample in a solution irradiated by a narrow beam of light. Such measurements are often used to reveal the size and structure of sample molecules or particles for appropriate types of particles / molecules, and, combined with knowledge of the sample concentration, to determine the weight-average molar mass. In addition, the nonlinearity of the scattered light intensity as a function of the sample concentration can be used to measure interactions and coupling between particles.

[0011] Multi-angle light scattering Multi-angle light scattering (MALS) is a 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 a solution by detecting how they scatter light. Collimated light from a laser source is most frequently used, in which case the technique can be called multi-angle laser light scattering (MALLS). The term "multi-angle" refers to the detection of scattered light at different discrete angles, measured, for example, by moving a single detector over a range including a specific selected angle, or by an array of detectors fixed at specific angular positions.

[0012] MALS measurements require a set of auxiliary elements. Of these, the most important is a collimated or focused beam (usually from a laser source producing a monochromatic collimated beam) that illuminates a region of the sample. The beam is generally plane-polarized perpendicular to the measurement plane, although other polarizations may be used, particularly when studying anisotropic particles. Another necessary element is an optical cell for holding the sample under measurement. Alternatively, a cell incorporating means to enable measurement of fluid samples may be used. When measuring single-particle scattering properties, means must be provided to introduce such particles one at a time through the light beam at points approximately equidistant from the surrounding detectors.

[0013] Most MALS-based measurements are performed in a plane, involving a set of detectors typically positioned equidistant from the sample, which is located at the center through which the illumination beam passes. However, a three-dimensional version has also been developed in which the detectors are located on the surface of a sphere, and the sample is controlled to pass through the center of the sphere, intersecting the path of the incident light beam as it passes along the diameter of the sphere at its center. MALS techniques generally collect multiplexed data sequentially from the output of a set of discrete detectors. MALS light scattering photometers generally have multiple detectors.

[0014] Different detectors within a MALS detector may (i) have slightly different quantum efficiencies and gains, and (ii) capture different geometric scattering volumes. Therefore, it may be necessary to normalize the signals captured by the MALS detector's photodetectors at each angle. If these differences are not normalized, the results from the MALS detector may become meaningless and may be improperly weighted toward different detector angles.

[0015] DC detector Differential refractive index detector A differential refractive index detector (dRI), also known as a 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. While dRIs are considered versatile detectors because they can detect anything with a different refractive index than the solvent, they have low sensitivity. When light leaves one substance and enters another, it bends or refracts. The refractive index of a substance is an indicator of how much light bends upon entry.

[0016] A differential refractive index detector (dRI) includes a flow cell comprising two parts: a sample section and a reference solvent section. The dRI measures the refractive index of both components. When only the solvent passes through the sample component, the refractive index measured for both components is the same; however, when the analyte passes through the flow cell, the two measured refractive indices differ. This difference appears as a peak in the chromatogram. Differential refractive index detectors are often used in the analysis of polymer samples in size exclusion chromatography. The dRI can output a concentration detector signal value corresponding to the concentration value of the sample.

[0017] 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. Ultraviolet-visible detectors / spectrophotometers use light in the visible and adjacent ranges. Absorption or reflectance in the visible range directly affects the perceived color of the chemical substance in question, and in this region of the electromagnetic spectrum, atoms and molecules undergo electronic transitions. Such absorption spectroscopy measures transitions from the ground state to the excited state. Ultraviolet-visible detectors / spectrophotometers measure the intensity (I) of light passing through a sample and the intensity (I) of light before it passed through the sample. o ) compared with, here, ratio I / I o This is called transmittance and is usually expressed as a percentage (%T). Absorbance A is based on transmittance according to the following:

[0018] A = -log(%T / 100%) A UV-Vis spectrophotometer can also be configured to measure reflectance, in which case the spectrophotometer measures the intensity (I) of light reflected from the sample and the intensity (I) of light reflected from the reference material. o ) compared with, here, ratio I / I o This is called reflectance and is usually expressed as a percentage (%R). A UV absorption detector can output a concentration detector signal value that corresponds to the concentration value of the sample.

[0019] Adeno-associated virus Adeno-associated viruses (AAVs) are small viruses (approximately 20 nm) belonging to the Parvoviridae family that infect humans but are not thought to cause disease. AAVs have emerged as attractive vectors for gene therapy due to their small size, mild immune response, and ability to stably integrate their genome into a specific site (AAVS1 on human chromosome 19) in the host cell genome. Recent FDA approval of Zolgesma® for the treatment of spinal muscular dystrophy, and several promising ongoing clinical trials such as trial number NCT00516477 (Clinicaltrials.gov), demonstrate that AAV manufacturing processes require robust, reliable, and easily implementable characterization methods to meet regulatory requirements imposed by the FDA and other regulatory agencies. However, viral vector characterization remains a challenge, and new methods need to be developed to ensure safe and high-quality AAV vectors for the advancement of AAV-related clinical trials. Furthermore, the FDA recently demonstrated that its characterization methods are well-controlled and developed two reference standards (RSMs), recombinant AAV serotypes 2 and 8, which can be used as benchmark tools for certifying internal reference materials. When these RSMs were established, significant variability was observed in the determination of capsid particles and vector genomes across different institutions, further highlighting the need for robust methods for determining AAV vector titers in preclinical and clinical studies, given the rapid development of this field.

[0020] The characterization of AAV is typically separated into several different stages, namely particle titer, vector genome titer, transduction titer, infectivity titer, and determination of purity and identity. Quantification of particle titer usually involves an ELISA (enzyme-linked immunosorbent assay) to detect the presence of ligands (proteins) in solution using antibodies against the protein being measured. This test requires specialized laboratory work and typically takes 24 hours to several weeks to obtain results. The next step is to quantify the amount of viral genome. This is usually done using qPCR (quantitative polymerase chain reaction) after lysis of the viral capsid and thus after sample loss.

[0021] The purity and identity of the obtained AAV are evaluated by SDS-PAGE (sodium dodecyl sulfate-polyacrylamide gel electrophoresis). The resulting viral capsid protein bands are evaluated for their stoichiometry and size. However, this is a relative method that requires the use of standards. The identity of the gene vector is determined by observing the electrophoretic band pattern and comparing it with a positive control (again, a relative method).

[0022] Therefore, it is important to have a robust and reproducible method that can be easily implemented in QC during manufacturing. SEC-MALS enables rapid sample analysis with a run time of less than 30 minutes and can be used to determine important quality attributes of AAV-based gene therapies, such as the number concentration of viral capsids, the ratio of filled particles to unfilled particles, and the absolute molar mass of proteins and genomic components. There is a need to measure the attributes of viral gene delivery vehicle (VGDV) samples by isolation.

[0023] Referring to Figure 1A, in an exemplary embodiment, a computer implementation method, system, and computer program product perform a series of logical operations by the computer system to analyze a viral gene delivery vehicle (VGDV) sample in a set of analytical instruments including at least one separation instrument, at least one static light scattering instrument, and at least two concentration detectors, thereby determining the capsid protein mass of the sample m A And the sample modification factor mass m B And the molar mass M of the modifying factor in the sample B The operation 110 brings about the molar mass M of the capsid protein in the sample. A Operation 112 receives the capsid protein molar mass from the data source, operation 114 receives the sample injection volume v from the injection volume data source, and the computer system determines the total VGDV particle concentration C of the sample. A It is configured to perform operation 116, which performs a series of logical operations that calculate by the following formula, C A =(m A ×N) / (M A ×v) And in the formula, N is Avogadro It is a number.

[0024] In exemplary embodiments, the computer system is a standalone computer system such as computer system 800 shown in Figure 8, a network of distributed computers in which at least some computers are computer systems such as computer system 800 shown in Figure 8, or a cloud computing node server such as computer system 800 shown in Figure 8. In one embodiment, the computer system is computer system 800 as shown in Figure 8, which performs measurement attributes of a viral gene delivery vehicle (VGDV) sample via an isolation script or computer software application that performs at least the operations of method 100. In one embodiment, the computer system is computer system / server 812 as shown in Figure 8, which performs measurement attributes of a viral gene delivery vehicle (VGDV) sample via an isolation script or computer software application that performs at least the operations of method 100. In one embodiment, the computer system is a processing unit 816 as shown in Figure 8, which performs measurement attributes of a viral gene delivery vehicle (VGDV) sample via an isolation script or computer software application that performs at least the operations of method 100. In one embodiment, the computer system is a processor of an analytical instrument that performs measurement attributes of a viral gene delivery vehicle (VGDV) sample via an isolation script or computer software application that performs at least the operations of method 100.

[0025] In one embodiment, the computer system is a computer system 800 as shown in Figure 8, which performs measurement attributes of a viral gene delivery vehicle (VGDV) sample via an isolation script or computer software application that performs at least operations 110, 112, 114, and 116. In one embodiment, the computer system is a computer system / server 812 as shown in Figure 8, which performs measurement attributes of a viral gene delivery vehicle (VGDV) sample via an isolation script or computer software application that performs at least operations 110, 112, 114, and 116. In one embodiment, the computer system is a processing unit 816 as shown in Figure 8, which performs measurement attributes of a viral gene delivery vehicle (VGDV) sample via an isolation script or computer software application that performs at least operations 110, 112, 114, and 116.

[0026] Referring to Figure 1B, in an exemplary embodiment, the computer implementation method, system, and computer program product include an analyzer 120, a receiver 122, and a calculator 124. In one embodiment, the analyzer 120 performs a series of logical operations to analyze a viral gene delivery vehicle (VGDV) sample 132 in a set of analytical instruments 130 including at least one separation instrument, at least one static light scattering instrument, and at least two concentration detectors, to determine the capsid protein mass 140 of the sample, i.e., m A And the sample's modification factor mass is 142, i.e., m B And the molar mass of the modifying factor in the sample is 144, i.e., M BIt is configured to bring about the following. In one embodiment, the analyzer 120 includes a computer system such as computer system 800 as shown in Figure 8, which performs operation 110. In one embodiment, the analyzer 120 includes a computer system such as computer system / server 812 as shown in Figure 8, which performs operation 110. In one embodiment, the analyzer 120 includes a computer system such as processing unit 816 as shown in Figure 8, which performs operation 110. In one embodiment, the analyzer 120 is implemented as computer software that runs on a computer system such as computer system 800 as shown in Figure 8, which performs operation 110. In one embodiment, the analyzer 120 is implemented as computer software that runs on a computer system such as computer system / server 812 as shown in Figure 8, which performs operation 110. In one embodiment, the analyzer 120 is implemented as computer software that runs on a computer system such as processing unit 816 as shown in Figure 8, which performs operation 110. In one embodiment, the analyzer 120 performs operation 110 as computer software running on the processor of the analyzer 120.

[0027] In one embodiment, the receiver 122 receives the molar mass of the capsid protein of the sample, 136, i.e., M AIt is configured to receive the capsid protein molar mass from the data source 134. In one embodiment, the receiver 122 includes a computer system such as computer system 800 as shown in Figure 8, which performs operation 112. In one embodiment, the receiver 122 includes a computer system such as computer system / server 812 as shown in Figure 8, which performs operation 112. In one embodiment, the receiver 122 includes a computer system such as processing unit 816 as shown in Figure 8, which performs operation 112. In one embodiment, the receiver 122 is implemented as computer software that runs on a computer system such as computer system 800 as shown in Figure 8, which performs operation 112. In one embodiment, the receiver 122 is implemented as computer software that runs on a computer system such as computer system / server 812 as shown in Figure 8, which performs operation 112. In one embodiment, the receiver 122 is implemented as computer software that runs on a computer system such as processing unit 816 as shown in Figure 8, which performs operation 112. In one embodiment, the receiver 122 executes operation 112 as computer software running on the processor of the receiver 122.

[0028] In one embodiment, the receiver 122 is configured to receive the sample injection volume 139, i.e., v, from the injection volume data source 138. In one embodiment, the receiver 122 includes a computer system such as computer system 800 as shown in Figure 8, which performs operation 114. In one embodiment, the receiver 122 includes a computer system such as computer system / server 812 as shown in Figure 8, which performs operation 114. In one embodiment, the receiver 122 includes a computer system such as processing unit 816 as shown in Figure 8, which performs operation 114. In one embodiment, the receiver 122 is implemented as computer software that runs on a computer system such as computer system 800 as shown in Figure 8, which performs operation 114. In one embodiment, the receiver 122 is implemented as computer software that runs on a computer system such as computer system / server 812 as shown in Figure 8, which performs operation 114. In one embodiment, the receiver 122 is implemented as computer software that runs on a computer system, such as a processing unit 816 as shown in Figure 8, so that the computer system performs operation 114. In one embodiment, the receiver 122 performs operation 114 as computer software that runs on the processor of the receiver 122.

[0029] In one embodiment, the computer 124 calculates the total VGDV particle concentration of the sample, 146, i.e., C A It is configured to perform a series of logical operations that calculate the following: C A =(m A ×N) / (M A ×v) And in the formula, N is AvogadroIt is a number. In one embodiment, the calculator 124 includes a computer system such as computer system 800 as shown in Figure 8, which performs operation 116. In one embodiment, the calculator 124 includes a computer system such as computer system / server 812 as shown in Figure 8, which performs operation 116. In one embodiment, the calculator 124 includes a computer system such as processing unit 816 as shown in Figure 8, which performs operation 116. In one embodiment, the calculator 124 is implemented as computer software that runs on a computer system such as computer system 800 as shown in Figure 8, so that the computer system performs operation 116. In one embodiment, the calculator 124 is implemented as computer software that runs on a computer system such as computer system / server 812 as shown in Figure 8, so that the computer system performs operation 116. In one embodiment, the calculator 124 is implemented as computer software that runs on a computer system such as processing unit 816 as shown in Figure 8, so that the computer system performs operation 116. In one embodiment, the computer 124 executes operation 116 as computer software running on the processor of the computer 124.

[0030] device separation equipment In one embodiment, the separation apparatus includes at least one of a size exclusion chromatography (SEC) unit, a field flow fractionation (FFF) unit, and an ion exchange chromatography (IEX) unit. In one embodiment, the separation apparatus is at least one of an SEC unit, an FFF unit, and an IEX unit.

[0031] static light scattering equipment In one embodiment, at least one static light scattering (SLS) instrument includes a multi-angle light scattering (MALS) instrument. In one embodiment, at least one static light scattering (SLS) instrument is a MALS instrument.

[0032] DC detector UV-UV In one embodiment, at least two concentration detectors include a first ultraviolet absorbance (UV) detector with a first wavelength λ1 and a second ultraviolet absorbance (UV) detector with a second wavelength λ2. In one embodiment, at least two concentration detectors are a first UV detector with a first wavelength λ1 and a second UV detector with a second wavelength λ2. In a particular embodiment, the first wavelength λ1 is 260 nm and the second wavelength λ2 is 280 nm.

[0033] UV-dRI In one embodiment, at least two concentration detectors include an ultraviolet absorbance (UV) detector with wavelength λ and a differential refractive index (dRI) detector. In one embodiment, at least two concentration detectors are a UV detector and a dRI detector with wavelength λ. In a particular embodiment, the wavelength λ is one of 260 nm and 280 nm.

[0034] UV-FLD In one embodiment, at least two concentration detectors include an ultraviolet absorbance (UV) detector with wavelength λ and a fluorescence detector (FLD). In one embodiment, at least two concentration detectors are a UV detector and an FLD with wavelength λ. In a particular embodiment, the wavelength λ is one of 260 nm and 280 nm.

[0035] dRI-FLD In one embodiment, the concentration detector includes at least two differential refractive index (dRI) detectors and fluorescence detectors (FLDs). In another embodiment, the concentration detectors are a dRI detector and an FLD.

[0036] Detector Selection The use of various concentration detectors can depend on the quality, concentration, and total volume available for analysis of the starting sample. The sensitivity of this method depends on the factors summarized in the table of Figure 3A.

[0037] In general, each combination of concentration detectors can be used as follows. dRI-FLD - Used only when the sample has fluorescent tags of known excitation and emission wavelengths.

[0038] UV-FLD - For sample concentrations of ~10^10 particles / mL. UV-UV - For sample concentrations of ~10^11 particles / mL.

[0039] UV-dRI - For sample concentrations above 10^12 particles / mL. Instrument setup Referring to Figure 3B, in one embodiment, at least one separation instrument 310 is connected to a first concentration detector 312, the first concentration detector 312 is connected to at least one SLS instrument 314, and at least one SLS instrument 314 is connected to a second concentration detector 316. Referring to Figure 3C, in one embodiment, at least one separation instrument 320 is connected to a first concentration detector 322, the first concentration detector 322 is connected to a second concentration detector 324, and the second concentration detector 324 is connected to at least one SLS instrument 326. Referring to Figure 3D, in one embodiment, at least one separation instrument 330 is connected to at least one SLS instrument 332, at least one SLS instrument 332 is connected to a first concentration detector 334, and the first concentration detector 334 is connected to a second concentration detector 336. For example, Figure 3E shows a typical set of instruments.

[0040] Calculation of capsid protein molar mass In a further embodiment, a computer-implemented method, system, and computer program product perform (a) a series of logical operations by a computer system to analyze a sample in a set to determine the capsid protein molar mass M of the sample Ato result in, and (b) the capsid protein molar mass M of the sample A further comprising storing the capsid protein molar mass M in a capsid protein molar mass data source. In a further embodiment, the method, the system, and the computer program product include (a) a series of logical operations performed by a computer system to analyze a sample in set 130 to result in the capsid protein molar mass 136 of the sample, i.e., M A to result in, and (b) the capsid protein molar mass 136 of the sample, i.e., M A further comprising storing the capsid protein molar mass 136 of the sample in a capsid protein molar mass data source 134.

[0041] Analysis of the sample In one embodiment, analyzing comprises analyzing the sample in the set by an analytical technique, which is one of virus vector analysis, protein conjugate analysis, and copolymer composition analysis. In one embodiment, the act of analyzing 110 comprises the act of analyzing the sample 132 in set 130 by an analytical technique, which is one of virus vector analysis, protein conjugate analysis, and copolymer composition analysis.

[0042] VGDV concentration In a further embodiment, the computer-implemented method, system, and computer program product include (a) receiving, by a computer system, the molar mass M of the full modification factor in the full VGDV sample from a full modification factor molar mass data source, and (b) performing, by the computer system, a series of logical operations to calculate the full VGDV concentration C of the full VGDV sample according to the following formula Full and (b) performing, by the computer system, a series of logical operations to calculate the full VGDV concentration C of the full VGDV sample according to the following formula Full C C Full =(m B ×N) / (M Full ×v) (c) further comprising performing, by the computer system, a series of logical operations to calculate the empty VGDV concentration C of the full VGDV sample according to the following formula. Empty

[0043] C Empty =C A -C Full Referring to Figure 2A, the computer implementation method, system, and computer program product are used by the computer system to determine the molar mass M of the full modification factor in a full VGDV sample. Full Operation 210 receives this from the full modification factor molar mass data source, and the computer system determines the full VGDV concentration C of the full VGDV sample. Full Operation 212 performs a series of logical operations that calculate using the following formula, C Full =(m B ×N) / (M Full ×v) The computer system determines the empty VGDV concentration C of a full VGDV sample. Empty Operation 214 is configured to perform a series of logical operations that calculate by the following formula.

[0044] C Empty =C A -C Full In one embodiment, the computer system is a computer system 800 as shown in Figure 8, which performs measurement attributes of a viral gene delivery vehicle (VGDV) sample via an isolation script or computer software application that performs at least the operations of Method 200. In one embodiment, the computer system is a computer system / server 812 as shown in Figure 8, which performs measurement attributes of a viral gene delivery vehicle (VGDV) sample via an isolation script or computer software application that performs at least the operations of Method 200. In one embodiment, the computer system is a processing unit 816 as shown in Figure 8, which performs measurement attributes of a viral gene delivery vehicle (VGDV) sample via an isolation script or computer software application that performs at least the operations of Method 200. In one embodiment, the computer system is a processor of an analytical instrument that performs measurement attributes of a viral gene delivery vehicle (VGDV) sample via an isolation script or computer software application that performs at least the operations of Method 200.

[0045] In one embodiment, the computer system is a computer system 800 as shown in Figure 8, which performs measurement attributes of a viral gene delivery vehicle (VGDV) sample via an isolation script or computer software application that performs at least operations 210, 212, and 214. In one embodiment, the computer system is a computer system / server 812 as shown in Figure 8, which performs measurement attributes of a viral gene delivery vehicle (VGDV) sample via an isolation script or computer software application that performs at least operations 210, 212, and 214. In one embodiment, the computer system is a processing unit 816 as shown in Figure 8, which performs measurement attributes of a viral gene delivery vehicle (VGDV) sample via an isolation script or computer software application that performs at least operations 210, 212, and 214.

[0046] In further embodiments, the method, system, and computer program product (a) by the computer system perform a series of logical operations to analyze a full VGDV sample in a set, determining the molar mass M of the full modification factor in the full VGDV sample. Full (b) the molar mass M of the full modification factor in the full VGDV sample Full The method further includes storing the molar mass of the full modification factor in a data source. In further embodiments, the method, the system, and the computer program product (a) by the computer system perform a series of logical operations to analyze a full VGDV sample in set 130 to determine the molar mass M of the full modification factor in the full VGDV sample. Full (b) the molar mass M of the full modification factor in the full VGDV sample Full This further includes storing the molar mass of the fully modified factor in a data source. In one embodiment, the modifying factor is a nucleic acid.

[0047] Total VGDV peak particle concentration In further embodiments, the method, system, and computer program product (a) by performing a series of logical operations by the computer system to analyze the entire VGDV signal region of the sample in a set and analyze the aggregated peak region of the sample in a set, thereby determining the total VGDV peak protein mass of the sample corresponding to the entire VGDV signal region of the sample m A,ent , the mass of the substance modifying the entire VGDV peak of the sample corresponding to the entire VGDV signal region of the sample B,ent , the total VGDV peak protein molar mass M of the sample corresponding to the entire VGDV signal region of the sample. A,ent , the molar mass of the VGDV peak modifier of the sample corresponding to the entire VGDV signal region of the sample M B,ent The VGDV aggregated peak protein mass of the sample corresponding to the aggregated peak region of the sample. A,agg The mass of the VGDV aggregation peak modifier in the sample corresponding to the aggregation peak region of the sample. B,agg , the VGDV aggregated peak protein molar mass M of the sample corresponding to the aggregated peak region of the sample. A,agg, and the molar mass M of the VGDV aggregation peak modification factor of the sample corresponding to the aggregation peak region of the sample B,agg resulting in, and (b) by a computer system, the total VGDV overall peak particle concentration C of the sample corresponding to the entire VGDV signal region of the sample A,ent executing a series of logical operations to calculate by the following formula C A,ent = (m A,ent × N) / (M A,ent × v) (c) by a computer system, further including executing a series of logical operations to calculate the total VGDV aggregation peak particle concentration C of the sample corresponding to the aggregation peak region of the sample by the following formula A,agg

[0048] C A,agg = (m A,agg × N) / (M A,agg × v) Referring to FIG. 2B, the computer-implemented method, the system, and the computer program product analyze the entire VGDV signal region of the sample in a set and analyze the aggregation peak region of the sample in a set by a computer system, and execute a series of logical operations to obtain the VGDV overall peak protein mass m of the sample corresponding to the entire VGDV signal region of the sample A,ent , the VGDV overall peak modification factor mass m of the sample corresponding to the entire VGDV signal region of the sample B,ent , the VGDV overall peak protein molar mass M of the sample corresponding to the entire VGDV signal region of the sample A,ent , the VGDV overall peak modification factor molar mass M of the sample corresponding to the entire VGDV signal region of the sample B,ent , the VGDV aggregation peak protein mass m of the sample corresponding to the aggregation peak region of the sample A,agg , the VGDV aggregation peak modification factor mass m of the sample corresponding to the aggregation peak region of the sample B,agg , the VGDV aggregation peak protein molar mass M of the sample corresponding to the aggregation peak region of the sample A,agg , and the molar mass M of the VGDV aggregation peak modification factor of the sample corresponding to the aggregation peak region of the sample B,aggAn operation 222 that results in, and a total VGDV overall peak particle concentration C of the sample corresponding to the entire VGDV signal region of the sample, by a computer system A,ent An operation 224 that executes a series of logical operations to calculate, by the following formula C A,ent =(m A,ent ×N) / (M A,ent ×v) An operation 226 that executes a series of logical operations to calculate, by the following formula, a total VGDV aggregation peak particle concentration C of the sample corresponding to the aggregation peak region of the sample, by a computer system A,agg It is further configured to perform

[0049] C A,agg =(m A,agg ×N) / (M<6000098>×v) In one embodiment, the computer system is the computer system 800 as shown in FIG. 8 that executes the measured attributes of a virus gene delivery vehicle (VGDV) sample via a separation script or computer software application that performs at least the operations of method 220. In one embodiment, the computer system is the computer system / server 812 as shown in FIG. 8 that executes the measured attributes of a virus gene delivery vehicle (VGDV) sample via a separation script or computer software application that performs at least the operations of method 220. In one embodiment, the computer system is the processing unit 816 as shown in FIG. 8 that executes the measured attributes of a virus gene delivery vehicle (VGDV) sample via a separation script or computer software application that performs at least the operations of method 220. In one embodiment, the computer system is the processor of an analytical instrument that executes the measured attributes of a virus gene delivery vehicle (VGDV) sample via a separation script or computer software application that performs at least the operations of method 220.

[0050] In one embodiment, the computer system is a computer system 800 as shown in Figure 8, which performs measurement attributes of a viral gene delivery vehicle (VGDV) sample via an isolation script or computer software application that performs at least operations 222, 224, and 226. In one embodiment, the computer system is a computer system / server 812 as shown in Figure 8, which performs measurement attributes of a viral gene delivery vehicle (VGDV) sample via an isolation script or computer software application that performs at least operations 222, 224, and 226. In one embodiment, the computer system is a processing unit 816 as shown in Figure 8, which performs measurement attributes of a viral gene delivery vehicle (VGDV) sample via an isolation script or computer software application that performs at least operations 222, 224, and 226.

[0051] In further embodiments, the method, system, and computer program product (a) by performing a series of logical operations by the computer system to analyze the entire VGDV signal region of a full viral gene delivery vehicle sample in a set and analyze the agglutination peak region of a full sample in a set, thereby determining the total VGDV peak molar mass M of the full modifying factor in the full sample corresponding to the entire VGDV signal region of the full sample. Full,ent , and the VGDV aggregation peak molar mass M of the full modification factor within the full sample corresponding to the aggregation peak region of the full sample. Full,agg (b) The computer system determines the total VGDV peak of the full sample corresponding to the entire VGDV signal region of the VGDV sample, and the full VGDV concentration C Full,ent Perform a series of logical operations that calculate using the following formula, C Full,ent =(m B,ent ×N) / (M Full,ent ×v) (c) Computer system determines the VGDV aggregation peak of the full sample corresponding to the aggregation peak region of the full sample, full VGDV concentration C Full,agg Perform a series of logical operations that calculate using the following formula, C Full,agg =(m B,agg ×N) / (M Full,agg ×v) (d) The computer system determines the total VGDV peak of the full sample corresponding to the entire VGDV signal region of the full sample, and the VGDV concentration C Empty,ent Perform a series of logical operations that calculate using the following formula, C Empty,ent =C A,ent -C Full,ent (e) The computer system determines the VGDV agglutination peak of the full sample corresponding to the agglutination peak region of the full sample, and the VGDV concentration C Empty,agg Perform a series of logical operations that calculate using the following formula, It also includes.

[0052] C Empty,agg =C A,agg -C Full,agg In further embodiments, the method, system, and computer program product (a) by performing a series of logical operations by the computer system to analyze the entire VGDV signal region of the full viral gene delivery vehicle sample in set 130 and analyze the agglutination peak region of the full sample in set 130, thereby determining the total VGDV peak molar mass M of the full modifying factor in the full sample corresponding to the entire VGDV signal region of the full sample. Full,ent , and the VGDV aggregation peak molar mass M of the full modification factor within the full sample corresponding to the aggregation peak region of the full sample. Full,agg (b) The computer system determines the total VGDV peak of the full sample corresponding to the entire VGDV signal region of the VGDV sample, and the full VGDV concentration C Full,ent Perform a series of logical operations that calculate using the following formula, C Full,ent =(m B,ent ×N) / (M Full,ent ×v) (c) Computer system determines the VGDV aggregation peak of the full sample corresponding to the aggregation peak region of the full sample, full VGDV concentration C Full,agg Perform a series of logical operations that calculate using the following formula, C Full,agg = (m B,agg × N) / (M Full,agg × v) (d) The computer system performs a series of logical operations to calculate the full-sample VGDV overall peak empty VGDV concentration C corresponding to the entire VGDV signal region of the full sample by the following formula, Empty,ent and C Empty,ent = C A,ent - C Full,ent (e) The computer system performs a series of logical operations to calculate the full-sample VGDV aggregation peak empty VGDV concentration C corresponding to the aggregation peak region of the full sample by the following formula, Empty,agg and further includes.

[0053] C Empty,agg = C A,agg - C Full,agg Approximation of total VGDV particle concentration In an exemplary embodiment, the computer-implemented method, the system, and the computer program product (1) perform a series of logical operations by a computer system to analyze a virus gene delivery vehicle (VGDV) sample in a set of analytical instruments including at least one separation instrument, at least one static light scattering (SLS) instrument, and at least one concentration detector, resulting in the modification factor mass m B of the sample, the modification factor molar mass M B of the sample, and at least one UV absorption coefficient of the sample; (2) perform a series of logical operations to calculate the capsid protein mass m A of the sample and the capsid protein molar mass M A of the sample with respect to at least one refractive index increment value from at least one concentration detector; (3) receive the injection volume v of the sample from an injection volume data source; and (4) perform a series of logical operations by the computer system to calculate the total VGDV particle concentration C A of the sample by the following formula, C A = (m A×N) / (M A ×v) And in the formula, N is Avogadro It is a number. In one embodiment, at least one concentration detector is a dRI detector.

[0054] Referring to Figure 1C, in an exemplary embodiment, the computer implementation, the system, and the computer program product perform a series of logical operations by the computer system to analyze a viral gene delivery vehicle (VGDV) sample in a set of analytical instruments including at least one separation instrument, at least one static light scattering (SLS) instrument, and at least one concentration detector, thereby determining the modification factor mass of the sample. B And the molar mass M of the modifying factor in the sample B The operation 152 yields at least one UV extinction coefficient of the sample, and the computer system determines the mass of the sample's capsid protein m with respect to at least one refractive index increment value from at least one concentration detector. A and the molar mass M of the capsid protein in the sample A Operation 154 performs a series of logical operations to calculate the total VGDV particle concentration C of the sample by the computer system, and Operation 156 receives the sample injection volume v from the injection volume data source, and (4) the total VGDV particle concentration C of the sample by the computer system. A It is configured to perform operation 158, which performs a series of logical operations that calculate by the following formula, C A =(m A ×N) / (M A ×v) And in the formula, N is Avogadro It is a number.

[0055] In exemplary embodiments, the computer system is a standalone computer system such as computer system 800 shown in Figure 8, a network of distributed computers in which at least some computers are computer systems such as computer system 800 shown in Figure 8, or a cloud computing node server such as computer system 800 shown in Figure 8. In one embodiment, the computer system is computer system 800 as shown in Figure 8, which performs measurement attributes of a viral gene delivery vehicle (VGDV) sample via an isolation script or computer software application that performs at least the operations of method 150. In one embodiment, the computer system is computer system / server 812 as shown in Figure 8, which performs measurement attributes of a viral gene delivery vehicle (VGDV) sample via an isolation script or computer software application that performs at least the operations of method 150. In one embodiment, the computer system is a processing unit 816 as shown in Figure 8, which performs measurement attributes of a viral gene delivery vehicle (VGDV) sample via an isolation script or computer software application that performs at least the operations of method 150. In one embodiment, the computer system is a processor of an analytical instrument that performs measurement attributes of a viral gene delivery vehicle (VGDV) sample via an isolation script or computer software application that performs at least the operations of method 150.

[0056] In one embodiment, the computer system is a computer system 800 as shown in Figure 8, which performs measurement attributes of a viral gene delivery vehicle (VGDV) sample via an isolation script or computer software application that performs at least operations 152, 154, 156, and 158. In one embodiment, the computer system is a computer system / server 812 as shown in Figure 8, which performs measurement attributes of a viral gene delivery vehicle (VGDV) sample via an isolation script or computer software application that performs at least operations 152, 154, 156, and 158. In one embodiment, the computer system is a processing unit 816 as shown in Figure 8, which performs measurement attributes of a viral gene delivery vehicle (VGDV) sample via an isolation script or computer software application that performs at least operations 152, 154, 156, and 158.

[0057] Total VGDV particle concentration measured by UV detector In exemplary embodiments, the computer implementation, the system, and the computer program product (1) the computer system performs a series of logical operations to analyze a viral gene delivery vehicle (VGDV) sample in a set of analytical instruments including at least one separation instrument, at least one static light scattering (SLS) instrument, and at least two concentration detectors; and (2) the computer system calculates the ultraviolet absorbance A collected from the sample at a first wavelength λ1. λ1 The ultraviolet absorbance value A collected from the sample at the second wavelength λ2. λ2 , the extinction coefficient of the protein at the first wavelength λ1 ε A λ1 , the extinction coefficient of the protein at the second wavelength λ2 ε A λ2 , the extinction coefficient ε of the modifying factor in the sample at the first wavelength λ1 B λ1 , and the extinction coefficient ε of the modifying factor in the sample at a second wavelength λ2 B λ2Regarding the mass fraction X of protein in the sample A (3) The computer system calculates the mass fraction X of the protein in the sample. A , the extinction coefficient of the protein at the first wavelength ε A λ1 , and the extinction coefficient ε of the modifying factor in the sample at the first wavelength B λ1 Regarding the extinction coefficient ε of the sample at the first wavelength VGDV λ1 (4) The computer system calculates the mass fraction X of the protein in the sample. A , the extinction coefficient of the protein at the second wavelength ε A λ2 , and the extinction coefficient ε of the modifying factor in the sample at the second wavelength B λ2 Regarding the absorption coefficient of the sample at the second wavelength ε VGDV λ2 (5) The computer system calculates the mass fraction X of the protein in the sample. A , the refractive index coefficient of proteins (dn / dc) A , and the refractive index coefficient (dn / dc) of the modifying factor in the sample. B Regarding the refractive index increment of the sample (dn / dc) VGDV (6) The computer system calculates the ultraviolet absorbance A collected from the sample at wavelength λ, which is one of the first wavelength λ1 and the second wavelength λ2. λ , the mass fraction X of protein in the sample A , the extinction coefficient of the protein at wavelength λ ε A λ , and the extinction coefficient ε of the modifying factor in the sample at wavelength λ B λ Regarding the total mass of protein m A and the total mass m of the modifying factors B (7) The computer system calculates the total VGDV particle concentration C of the sample. AThis includes performing a series of logical operations that calculate using the following formula, C A =(m A ×N) / (M A ×v) In the formula, N is Avogadro It is a number, M A is the molar mass of the capsid protein of the sample from the capsid protein molar mass data source. In one embodiment, at least two concentration detectors include a first ultraviolet absorbance (UV) detector at a first wavelength λ1 and a second ultraviolet absorbance (UV) detector at a second wavelength λ2. In one embodiment, at least two concentration detectors are a first ultraviolet absorbance (UV) detector at a first wavelength λ1 and a second ultraviolet absorbance (UV) detector at a second wavelength λ2.

[0058] Referring to Figures 1D and 1E, in an exemplary embodiment, the computerized method, the system, and the computer program product perform a series of logical operations 161 by the computer system to analyze a viral gene delivery vehicle (VGDV) sample in a set of analytical instruments including at least one separation instrument, at least one static light scattering (SLS) instrument, and at least two concentration detectors, and by the computer system to collect ultraviolet absorbance values ​​A from the sample at a first wavelength λ1. λ1 The ultraviolet absorbance value A collected from the sample at the second wavelength λ2. λ2 , the extinction coefficient of the protein at the first wavelength λ1 ε A λ1 , the extinction coefficient of the protein at the second wavelength λ2 ε A λ2 , the extinction coefficient ε of the modifying factor in the sample at the first wavelength λ1 B λ1 , and the extinction coefficient ε of the modifying factor in the sample at a second wavelength λ2 B λ2 Regarding the mass fraction X of protein in the sample A Operation 162 involves performing a series of logical operations to calculate the mass fraction X of the protein in the sample, and the computer system calculates the mass fraction X of the protein in the sample. A , the extinction coefficient of the protein at the first wavelength εA λ1 , and the extinction coefficient ε of the modifying factor in the sample at the first wavelength B λ1 Regarding the extinction coefficient ε of the sample at the first wavelength VGDV λ1 Operation 163 involves performing a series of logical operations to calculate the mass fraction X of the protein in the sample, and the computer system calculates the mass fraction X of the protein in the sample. A , the extinction coefficient of the protein at the second wavelength ε A λ2 , and the extinction coefficient ε of the modifying factor in the sample at the second wavelength B λ2 Regarding the absorption coefficient of the sample at the second wavelength ε VGDV λ2 Operation 164 performs a series of logical operations to calculate the mass fraction X of the protein in the sample, and the computer system calculates the mass fraction X of the protein in the sample. A , the refractive index coefficient of proteins (dn / dc) A , and the refractive index coefficient (dn / dc) of the modifying factor in the sample. B Regarding the refractive index increment of the sample (dn / dc) VGDV Operation 165 performs a series of logical operations to calculate the ultraviolet absorbance A collected from the sample at wavelength λ, which is one of the first wavelength λ1 and the second wavelength λ2, by the computer system. λ , the mass fraction X of protein in the sample A , the extinction coefficient of the protein at wavelength λ ε A λ , and the extinction coefficient ε of the modifying factor in the sample at wavelength λ B λ Regarding the total mass of protein m A and the total mass m of the modifying factors B Operation 166 performs a series of logical operations to calculate the total VGDV particle concentration C of the sample by the computer system. A It is configured to perform operation 167, which performs a series of logical operations that calculate by the following formula, C A =(m A ×N) / (M A ×v) In the formula, N is Avogadro It is a number, MA This is the molar mass of the capsid protein in the sample from the capsid protein molar mass data source.

[0059] In exemplary embodiments, the computer system is a standalone computer system such as computer system 800 shown in Figure 8, a network of distributed computers in which at least some computers are computer systems such as computer system 800 shown in Figure 8, or a cloud computing node server such as computer system 800 shown in Figure 8. In one embodiment, the computer system is computer system 800 as shown in Figure 8, which performs measurement attributes of a viral gene delivery vehicle (VGDV) sample via an isolation script or computer software application that performs at least the operations of method 160. In one embodiment, the computer system is computer system / server 812 as shown in Figure 8, which performs measurement attributes of a viral gene delivery vehicle (VGDV) sample via an isolation script or computer software application that performs at least the operations of method 160. In one embodiment, the computer system is a processing unit 816 as shown in Figure 8, which performs measurement attributes of a viral gene delivery vehicle (VGDV) sample via an isolation script or computer software application that performs at least the operations of method 160. In one embodiment, the computer system is a processor of an analytical instrument that performs measurement attributes of a viral gene delivery vehicle (VGDV) sample via an isolation script or computer software application that performs at least the operations of method 160.

[0060] In one embodiment, the computer system is a computer system 800 as shown in Figure 8, which performs measurement attributes of a viral gene delivery vehicle (VGDV) sample via an isolation script or computer software application that performs at least operations 161, 162, 163, 164, 165, 166, and 167. In one embodiment, the computer system is a computer system / server 812 as shown in Figure 8, which performs measurement attributes of a viral gene delivery vehicle (VGDV) sample via an isolation script or computer software application that performs at least operations 161, 162, 163, 164, 165, 166, and 167. In one embodiment, the computer system is a processing unit 816 as shown in Figure 8, which performs measurement attributes of a viral gene delivery vehicle (VGDV) sample via an isolation script or computer software application that performs at least operations 161, 162, 163, 164, 165, 166, and 167.

[0061] In one embodiment, the mass fraction X of protein in the sample A To calculate the mass fraction X of protein in the sample, the following formula is used: A This includes calculating, X A =((A λ1 ×ε B λ2 )-(A λ2 ×ε B λ1 )) / ((A λ2 ×ε A λ1 )-(A λ2 ×ε B λ1 )-(A λ1 ×ε A λ2 )+(A λ1 ×ε B λ2 )) The extinction coefficient ε of the sample at the first wavelength VGDV λ1 The absorption coefficient ε of the sample at the first wavelength is calculated by the following equation:VGDV λ1 This includes calculating, ε VGDV λ1 =( X A ×ε A λ1 )+((1-X A )×ε B λ1 ) The extinction coefficient ε of the sample at the second wavelength VGDV λ2 The absorption coefficient ε of the sample at the second wavelength is calculated by the following equation: VGDV λ2 This includes calculating, ε VGDV λ2 =( X A ×ε A λ2 )+((1-X A )×ε B λ2 ) Increment in refractive index of the sample (dn / dc) VGDV The refractive index increment of the sample (dn / dc) can be calculated using the following formula: VGDV This includes calculating, (dn / dc) VGDV =( X A ×(dn / dc) A )+((1-X A )×(dn / dc) B ) Total mass of protein m A The calculation of the total protein mass m is given by the following equation: A This includes calculating, m A =( A λ ×X A ) / ((X A ×ε A λ )+((1-X A )×ε B λ )) Total mass m of modifying factors B Calculating the total mass m of the modifying factor is done by the following equation: B This includes calculating [something].

[0062] mB =( A λ ×(1-X A )) / ((X A ×ε A λ )+((1-X A )×ε B λ )) In one embodiment, the mass fraction X of protein in the sample A The calculation operation 162 calculates the mass fraction X of protein in the sample using the following formula. A This includes calculating, X A =((A λ1 ×ε B λ2 )-(A λ2 ×ε B λ1 )) / ((A λ2 ×ε A λ1 )-(A λ2 ×ε B λ1 )-(A λ1 ×ε A λ2 )+(A λ1 ×ε B λ2 )) The extinction coefficient ε of the sample at the first wavelength VGDV λ1 The calculation operation 163 calculates the absorption coefficient ε of the sample at the first wavelength by the following equation: VGDV λ1 This includes calculating, ε VGDV λ1 =( X A ×ε A λ1 )+((1-X A )×ε B λ1 ) The extinction coefficient ε of the sample at the second wavelength VGDV λ2 The calculation operation 164 calculates the absorption coefficient ε of the sample at the second wavelength by the following equation: VGDV λ2 This includes calculating, ε VGDV λ2 =( XA ×ε A λ2 )+((1-X A )×ε B λ2 ) Increment in refractive index of the sample (dn / dc) VGDV Calculation operation 165 calculates the refractive index increment of the sample (dn / dc) using the following formula: VGDV This includes calculating, (dn / dc) VGDV =( X A ×(dn / dc) A )+((1-X A )×(dn / dc) B ) Total mass of protein m A The calculation operation 166 that calculates the total mass of the protein m is calculated by the following equation: A This includes calculating, m A =( A λ ×X A ) / ((X A ×ε A λ )+((1-X A )×ε B λ )) Total mass m of modifying factors B The calculation operation 167 that calculates the total mass m of the modification factor is calculated by the following equation. B This includes calculating [something].

[0063] m B =( A λ ×(1-X A )) / ((X A ×ε A λ )+((1-X A )×ε B λ )) In one embodiment, the first wavelength λ1 is 260 nm, and the second wavelength λ2 is 280 nm. In one embodiment, the modifying factor is nucleic acid.

[0064] Total VGDV particle concentration measured by UV detector and dRI detector In exemplary embodiments, the computer implementation, the system, and the computer program product include: (1) a computer system performing a series of logical operations to analyze a viral gene delivery vehicle (VGDV) sample in a set of analytical instruments including at least one separation instrument, at least one static light scattering (SLS) instrument, and at least two concentration detectors; and (2) the computer system analyzing the ultraviolet absorbance A collected from the sample at wavelength λ. λ , the refractive index coefficient (dn / dc) of the modifying factor in the sample B The differential refractive index dRI of the solution containing the sample, and the extinction coefficient ε of the modification factor at wavelength λ. B λ , the extinction coefficient of the protein at wavelength λ ε A λ , and the refractive index coefficient of proteins (dn / dc) A Regarding the mass fraction X of protein in the sample A (3) The computer system calculates the mass fraction X of the protein in the sample. A , wavelength The extinction coefficient of proteins in ε A λ , and the extinction coefficient ε of the modifying factor in the sample at wavelength B λ Regarding the extinction coefficient ε of the sample at wavelength VGDV λ (4) The computer system calculates the mass fraction X of the protein in the sample. A , the refractive index coefficient of proteins (dn / dc) A , and the refractive index coefficient (dn / dc) of the modifying factor in the sample. B Regarding the refractive index increment of the sample (dn / dc) VGDV (5) The computer system calculates the differential refractive index dRI of the solution containing the sample, and the mass fraction X of the protein in the sample. A , the refractive index coefficient of proteins (dn / dc) A , and the refractive index coefficient (dn / dc) of the modifying factor in the sample. B Regarding the total mass of protein mA and the total mass m of the modifying factors B (6) The computer system calculates the total VGDV particle concentration C of the sample. A This includes performing a series of logical operations that calculate using the following formula, C A =(m A ×N) / (M A ×v) In the formula, N is Avogadro It is a number, M A This is the molar mass of the capsid protein in the sample from the capsid protein molar mass data source. In one embodiment, at least two concentration detectors include an ultraviolet absorbance (UV) detector at wavelength λ and a differential refractive index (dRI) detector. In one embodiment, at least two concentration detectors are a UV detector and a dRI detector at wavelength λ.

[0065] Referring to Figures 1F and 1G, in an exemplary embodiment, the computer implementation, the system, and the computer program product perform a series of logical operations 171 by the computer system to analyze a viral gene delivery vehicle (VGDV) sample in a set of analytical instruments including at least one separation instrument, at least one static light scattering (SLS) instrument, and at least two concentration detectors, and by the computer system to collect ultraviolet absorbance values ​​A from the sample at wavelength λ. λ , the refractive index coefficient (dn / dc) of the modifying factor in the sample B The differential refractive index dRI of the solution containing the sample, and the extinction coefficient ε of the modification factor at wavelength λ. B λ , the extinction coefficient of the protein at wavelength λ ε A λ , and the refractive index coefficient of proteins (dn / dc) A Regarding the mass fraction X of protein in the sample A Operation 172 involves performing a series of logical operations to calculate the mass fraction X of the protein in the sample, and the computer system calculates the mass fraction X of the protein in the sample. A , the extinction coefficient of proteins at wavelength ε A λ, and the extinction coefficient ε of the modifying factor in the sample at wavelength B λ Regarding the extinction coefficient ε of the sample at wavelength VGDV λ Operation 173 involves performing a series of logical operations to calculate the mass fraction X of the protein in the sample, and the computer system calculates the mass fraction X of the protein in the sample. A , the refractive index coefficient of proteins (dn / dc) A , and the refractive index coefficient (dn / dc) of the modifying factor in the sample. B Regarding the refractive index increment of the sample (dn / dc) VGDV Operation 174 performs a series of logical operations to calculate the differential refractive index dRI of the solution containing the sample and the mass fraction X of the protein in the sample, respectively, by the computer system. A , the refractive index coefficient of proteins (dn / dc) A , and the refractive index coefficient (dn / dc) of the modifying factor in the sample. B Regarding the total mass of protein m A and the total mass m of the modifying factors B Operation 175 performs a series of logical operations to calculate the total VGDV particle concentration C of the sample by the computer system. A It is configured to perform operation 176, which performs a series of logical operations that calculate by the following formula, C A =(m A ×N) / (M A ×v) In the formula, N is Avogadro It is a number, M A This is the molar mass of the capsid protein in the sample from the capsid protein molar mass data source.

[0066] In exemplary embodiments, the computer system is a standalone computer system such as computer system 800 shown in Figure 8, a network of distributed computers in which at least some computers are computer systems such as computer system 800 shown in Figure 8, or a cloud computing node server such as computer system 800 shown in Figure 8. In one embodiment, the computer system is computer system 800 as shown in Figure 8, which performs measurement attributes of a viral gene delivery vehicle (VGDV) sample via an isolation script or computer software application that performs at least the operations of method 170. In one embodiment, the computer system is computer system / server 812 as shown in Figure 8, which performs measurement attributes of a viral gene delivery vehicle (VGDV) sample via an isolation script or computer software application that performs at least the operations of method 170. In one embodiment, the computer system is processing unit 816 as shown in Figure 8, which performs measurement attributes of a viral gene delivery vehicle (VGDV) sample via an isolation script or computer software application that performs at least the operations of method 170. In one embodiment, the computer system is a processor of an analytical instrument that performs measurement attributes of a viral gene delivery vehicle (VGDV) sample via an isolation script or computer software application that performs at least the operations of Method 170.

[0067] In one embodiment, the computer system is a computer system 800 as shown in Figure 8, which performs measurement attributes of a viral gene delivery vehicle (VGDV) sample via an isolation script or computer software application that performs at least operations 171, 172, 173, 174, 175, and 176. In one embodiment, the computer system is a computer system / server 812 as shown in Figure 8, which performs measurement attributes of a viral gene delivery vehicle (VGDV) sample via an isolation script or computer software application that performs at least operations 171, 172, 173, 174, 175, and 176. In one embodiment, the computer system is a processing unit 816 as shown in Figure 8, which performs measurement attributes of a viral gene delivery vehicle (VGDV) sample via an isolation script or computer software application that performs at least operations 171, 172, 173, 174, 175, and 176.

[0068] In one embodiment, the mass fraction X of protein in the sample A To calculate the mass fraction X of protein in the sample, the following formula is used: A This includes calculating, X A =((A λ ×(dn / dc) B )-(dRI×ε B λ )) / ((dRI×ε A λ )-(dRI×ε B λ )-(A λ ×(dn / dc) A )+(A λ ×(dn / dc) B )) Absorption coefficient of the sample at wavelength ε VGDV λ The absorption coefficient ε of the sample at wavelength can be calculated using the following equation: VGDV λ This includes calculating, ε VGDV λ =( XA ×ε A λ )+((1-X A )×ε B λ ) Increment in refractive index of the sample (dn / dc) VGDV The refractive index increment of the sample (dn / dc) can be calculated using the following formula: VGDV This includes calculating, (dn / dc) VGDV =( X A ×(dn / dc) A )+((1-X A )×(dn / dc) B ) Total mass of protein m A The calculation of the total protein mass m is given by the following equation: A This includes calculating, m A =(dRI×X A ) / ((X A ×(dn / dc) A )+((1-X A )×(dn / dc) B )) Total mass m of modifying factors B Calculating the total mass m of the modifying factor is done by the following equation: B This includes calculating [something].

[0069] m B =(dRI×(1-X A )) / ((X A ×(dn / dc) A )+((1-X A )×(dn / dc) B )) In one embodiment, the wavelength λ is one of 260 nm and 280 nm. In one embodiment, the modifying factor is nucleic acid.

[0070] Total VGDV particle concentration measured by UV detector and FLD In one embodiment, the computer implementation, the system, and the computer program product (1) perform a series of logical operations by the computer system to analyze a viral gene delivery vehicle (VGDV) sample in a set of analytical instruments including at least one separation instrument, at least one static light scattering (SLS) instrument, and at least two concentration detectors; and (2) perform by the computer system the area below the peak FLD of fluorescence emission data collected from the sample at the excitation wavelength, and the ultraviolet absorbance A collected from the sample at the ultraviolet wavelength λ. λ The extinction coefficient of proteins at ultraviolet wavelength λ ε A λ , a proportionality constant ε that correlates protein concentration with fluorescence intensity for FLD FLD,A The extinction coefficient ε of the modifying factor in the sample at ultraviolet wavelength λ. B λ , and the proportionality constant ε that correlates the concentration of the modifying factor with the fluorescence intensity for FLD. FLD,B Regarding the mass fraction X of protein in the sample A (3) The computer system calculates the mass fraction X of the protein in the sample. A , the extinction coefficient of proteins at ultraviolet wavelengths ε A λ , and the extinction coefficient ε of the modifying factor in the sample at ultraviolet wavelengths B λ Regarding the absorption coefficient ε of the sample at ultraviolet wavelengths VGDV λ (4) The computer system calculates the mass fraction X of the protein in the sample. A , a proportionality constant ε that correlates protein concentration with fluorescence intensity for FLD FLD,A , and the proportionality constant ε that correlates the concentration of the modifying factor with the fluorescence intensity for FLD. FLD,B Regarding the extinction coefficient ε of the sample at the excitation wavelength FLD,VGDV (5) The computer system calculates the mass fraction X of the protein in the sample. A , the refractive index coefficient of proteins (dn / dc) A, and the refractive index coefficient (dn / dc) of the modifying factor in the sample. B Regarding the refractive index increment of the sample (dn / dc) VGDV (6) The computer system calculates the area below the peak (FLD) of the fluorescence emission data collected from the sample at the excitation wavelength, and the mass fraction X of the protein in the sample. A , a proportionality constant ε that correlates protein concentration with fluorescence intensity for FLD FLD,A , and the proportionality constant ε that correlates the concentration of the modifying factor with the fluorescence intensity for FLD. FLD,B Regarding the total mass of protein m A and the total mass m of the modifying factors B (7) The computer system calculates the total VGDV particle concentration C of the sample. A This includes performing a series of logical operations that calculate using the following formula, C A =(m A ×N) / (M A ×v) In the formula, N is Avogadro It is a number, M A This is the molar mass of the capsid protein in the sample from the capsid protein molar mass data source. In one embodiment, the concentration detector includes at least two ultraviolet absorbance (UV) detectors at ultraviolet wavelength λ and fluorescence detectors (FLDs). In one embodiment, the concentration detector is at least two ultraviolet absorbance (UV) detectors at ultraviolet wavelength λ and an FLD.

[0071] In one embodiment, the computer implementation, the system, and the computer program product perform a series of logical operations by the computer system to analyze a viral gene delivery vehicle (VGDV) sample in a set of analytical instruments including at least one separation instrument, at least one static light scattering (SLS) instrument, and at least two concentration detectors; and by the computer system to obtain the area below the peak (FLD) of fluorescence emission data collected from the sample at the excitation wavelength, and the ultraviolet absorbance value A collected from the sample at the ultraviolet wavelength λ. λ The extinction coefficient of proteins at ultraviolet wavelength λ εA λ , a proportionality constant ε that correlates protein concentration with fluorescence intensity for FLD FLD,A The extinction coefficient ε of the modifying factor in the sample at ultraviolet wavelength λ. B λ , and the proportionality constant ε that correlates the concentration of the modifying factor with the fluorescence intensity for FLD. FLD,B Regarding the mass fraction X of protein in the sample A The operation involves performing a series of logical operations to calculate the mass fraction X of the protein in the sample, and the computer system calculates X. A , the extinction coefficient of proteins at ultraviolet wavelengths ε A λ , and the extinction coefficient ε of the modifying factor in the sample at ultraviolet wavelengths B λ Regarding the absorption coefficient ε of the sample at ultraviolet wavelengths VGDV λ The operation involves performing a series of logical operations to calculate the mass fraction X of the protein in the sample, and the computer system calculates X. A , a proportionality constant ε that correlates protein concentration with fluorescence intensity for FLD FLD,A , and the proportionality constant ε that correlates the concentration of the modifying factor with the fluorescence intensity for FLD. FLD,B Regarding the extinction coefficient ε of the sample at the excitation wavelength FLD,VGDV The operation involves performing a series of logical operations to calculate the mass fraction X of the protein in the sample, and the computer system calculates X. A , the refractive index coefficient of proteins (dn / dc) A , and the refractive index coefficient (dn / dc) of the modifying factor in the sample. B Regarding the refractive index increment of the sample (dn / dc) VGDV The computer system performs a series of logical operations to calculate the area below the peak (FLD) of the fluorescence emission data collected from the sample at the excitation wavelength, and the mass fraction X of the protein in the sample. A , a proportionality constant ε that correlates protein concentration with fluorescence intensity for FLD FLD,A , and the proportionality constant ε that correlates the concentration of the modifying factor with the fluorescence intensity for FLD. FLD,B Regarding the total mass of protein m A and the total mass m of the modifying factorsB The operation involves performing a series of logical operations to calculate the total VGDV particle concentration C of the sample by the computer system. A It is configured to perform an operation that performs a series of logical operations that calculate by the following formula, C A =(m A ×N) / (M A ×v) In the formula, N is Avogadro It is a number, M A This is the molar mass of the capsid protein in the sample from the capsid protein molar mass data source.

[0072] In one embodiment, the mass fraction X of protein in the sample A To calculate the mass fraction X of protein in the sample, the following formula is used: A This includes calculating, X A =((FLD×ε B λ )-(A λ ×ε FLD,B )) / ((A λ ×ε FLD,A )-(A λ ×ε FLD,B )-(FLD×ε A λ )+(FLD×ε B λ )) Absorption coefficient ε of the sample at ultraviolet wavelengths VGDV λ The absorption coefficient ε of the sample at ultraviolet wavelength can be calculated using the following formula. VGDV λ This includes calculating, ε VGDV λ =( X A ×ε A λ )+((1-X A )×ε B λ ) Extinction coefficient ε of the sample at the excitation wavelength FLD,VGDV The absorption coefficient ε of the sample at the excitation wavelength is calculated using the following equation: FLD,VGDV This includes calculating, εFLD,VGDV =( X A ×ε FLD,A )+((1-X A )×ε FLD,B ) Increment in refractive index of the sample (dn / dc) VGDV The refractive index increment of the sample (dn / dc) can be calculated using the following formula: VGDV This includes calculating, (dn / dc) VGDV =( X A ×(dn / dc) A )+((1-X A )×(dn / dc) B ) Total mass of protein m A The calculation of the total protein mass m is given by the following equation: A This includes calculating, m A =(FLD×X A ) / ((X A ×ε FLD,A )+((1-X A )×ε FLD,B )) Total mass m of modifying factors B Calculating the total mass m of the modifying factor is done by the following equation: B This includes calculating [something].

[0073] m B =(FLD×(1-X A )) / ((X A ×ε FLD,A )+((1-X A )×ε FLD,B )) In one embodiment, the UV wavelength λ is one of 260 nm and 280 nm. In one embodiment, the modifying factor is nucleic acid.

[0074] Total VGDV particle concentration by dRI and FLD In exemplary embodiments, the computer implementation, the system, and the computer program product (1) perform a series of logical operations by the computer system to analyze a viral gene delivery vehicle (VGDV) sample in a set of analytical instruments including at least one separation instrument, at least one static light scattering (SLS) instrument, and at least two concentration detectors; and (2) perform the computer system to obtain the area below the peak (FLD) of fluorescence emission data collected from the sample at the excitation wavelength, the differential refractive index (dRI) of the solution containing the sample, and the refractive index coefficient (dn / dc) of the protein. A , the refractive index coefficient (dn / dc) of the modifying factor in the sample B , a proportionality constant ε that correlates protein concentration with fluorescence intensity for FLD FLD,A , and the proportionality constant ε that correlates the concentration of the modifying factor with the fluorescence intensity for FLD. FLD,B Regarding the mass fraction X of protein in the sample A (3) The computer system calculates the mass fraction X of the protein in the sample. A , the refractive index coefficient of proteins (dn / dc) A , and the refractive index coefficient (dn / dc) of the modifying factor in the sample. B Regarding the refractive index increment of the sample (dn / dc) VGDV (4) The computer system calculates the mass fraction X of the protein in the sample. A , a proportionality constant ε that correlates protein concentration with fluorescence intensity for FLD FLD,A , and the proportionality constant ε that correlates the concentration of the modifying factor with the fluorescence intensity for FLD. FLD,B Regarding the extinction coefficient ε of the sample at the excitation wavelength FLD,VGDV (5) The computer system calculates the total VGDV particle concentration C of the sample. A This includes performing a series of logical operations that calculate using the following formula, C A =(m A ×N) / (M A ×v) In the formula, N is Avogadro It is a number, mA This is the total mass of protein, M A This is the molar mass of the capsid protein in the sample from the capsid protein molar mass data source. In one embodiment, at least two concentration detectors include a differential refractive index (dRI) detector and a fluorescence detector (FLD). In one embodiment, at least two concentration detectors are a dRI detector and an FLD.

[0075] In exemplary embodiments, the computer implementation, the system, and the computer program product perform a series of logical operations by the computer system to analyze a viral gene delivery vehicle (VGDV) sample in a set of analytical instruments including at least one separation instrument, at least one static light scattering (SLS) instrument, and at least two concentration detectors; and by the computer system to obtain the area below the peak (FLD) of fluorescence emission data collected from the sample at the excitation wavelength, the differential refractive index (dRI) of the solution containing the sample, and the refractive index coefficient (dn / dc) of the protein. A , the refractive index coefficient (dn / dc) of the modifying factor in the sample B , a proportionality constant ε that correlates protein concentration with fluorescence intensity for FLD FLD,A , and the proportionality constant ε that correlates the concentration of the modifying factor with the fluorescence intensity for FLD. FLD,B Regarding the mass fraction X of protein in the sample A The operation involves performing a series of logical operations to calculate the mass fraction X of the protein in the sample, and the computer system calculates X. A , the refractive index coefficient of proteins (dn / dc) A , and the refractive index coefficient (dn / dc) of the modifying factor in the sample. B Regarding the refractive index increment of the sample (dn / dc) VGDV The operation involves performing a series of logical operations to calculate the mass fraction X of the protein in the sample, and the computer system calculates X. A , a proportionality constant ε that correlates protein concentration with fluorescence intensity for FLD FLD,A , and the proportionality constant ε that correlates the concentration of the modifying factor with the fluorescence intensity for FLD. FLD,B Regarding the extinction coefficient ε of the sample at the excitation wavelengthFLD,VGDV The operation involves performing a series of logical operations to calculate the total VGDV particle concentration C of the sample by the computer system. A It is configured to perform an operation that performs a series of logical operations that calculate by the following formula, C A =(m A ×N) / (M A ×v) In the formula, N is Avogadro It is a number, m A This is the total mass of protein, M A This is the molar mass of the capsid protein in the sample from the capsid protein molar mass data source.

[0076] In one embodiment, the mass fraction X of protein in the sample A To calculate the mass fraction X of protein in the sample, the following formula is used: A This includes calculating, X A =((FLD×(dn / dc) B )-(dRI×ε FLD,B )) / ((dRI×ε FLD,A )-(dRI×ε FLD,B )-(FLD×(dn / dc) A ) + (FLD × (dn / dc) B )) Increment in refractive index of the sample (dn / dc) VGDV The refractive index increment of the sample (dn / dc) can be calculated using the following formula: VGDV This includes calculating, (dn / dc) VGDV =( X A ×(dn / dc) A )+((1-X A )×(dn / dc) B ) Extinction coefficient ε of the sample at the excitation wavelength FLD,VGDV The absorption coefficient ε of the sample at the excitation wavelength is calculated using the following equation: FLD,VGDV This includes calculating [something].

[0077] ε FLD,VGDV =( X A ×ε FLD,A )+((1-XA )×ε FLD,B ) Examples For example, Figures 4A, 4B, and 4C show the particle concentration obtained by this method, i.e., the total VGDV particle concentration (C) of the sample. A This shows that the capsid content ((C) of the sample could be calculated consistently, and "full:empty" reflects the mixing ratio of the first sample to the second sample. Figure 4C shows, in particular, that this method can calculate the capsid content ((C) of the sample. p / V g ), (C A / C FULL This demonstrates that the method can accurately calculate the VGDV concentration of a sample. Figure 4A shows representative data (chromatogram) collected at 90 degrees using an SLS instrument. Figure 4B demonstrates that this method can calculate the total VGDV concentration of a sample.

[0078] Figure 5 illustrates the ability of this method to quantify the aggregation content of AAV samples. Figure 5 shows the total AAV particle concentration superimposed on the UV trace of the AAV sample. The peak that eluted before the main peak (6.5 mL to 7.5 mL) represents AAV aggregation. Using this method, the degree of aggregation is determined by calculating the particle concentration for all elution data slices (chromatogram data slices).

[0079] Figure 6A shows that a fluorescence detector (FLD) may be used as one of the concentration detectors. Figure 6A shows representative data (chromatograms) collected by a 90-degree SLS instrument, a UV detector, and an FLD. Figure 6B shows the molar mass (MM) results / molecular weight (MW) results obtained by analyzing an AAV sample using this method with UV and FLD as concentration detectors, and these are in agreement with the predicted molar mass / predicted molecular weight results. Figure 6C shows the molecular weight (MW) results / molar mass (MM) results obtained by analyzing an AAV sample using this method with dRI and FLD as concentration detectors, and these are in agreement with the predicted molecular weight / predicted molar mass values.

[0080] Figure 7A shows data collected by this method using ion exchange chromatography (IEX) as the separation instrument. Figure 7A shows representative data (chromatogram) collected by a 90°C SLS instrument. Figure 7B shows data collected by this method using field flow fractionation (FFF) as the separation instrument. Figure 7B shows representative data (chromatogram) collected by a 90°C SLS instrument. Figure 7C shows molar mass (MM) results obtained by analyzing AAV samples using this method with UV and dRI as concentration detectors and FFF as the separation system, and these are in agreement with the expected molar mass value / expected molecular weight value.

[0081] Computer system In an exemplary embodiment, the computer system is shown in Figure 8 Computer systems such as those shown 8 It is 00. Computer system 8 00 is merely an example of a computer system and is not intended to imply any limitation on the scope of use or functionality of the embodiments of the present invention. Nevertheless, computer systems 8 00 can be implemented and / or performed to perform any of the functions / operations of the present invention.

[0082] Computer system 8 00 is a computer system / server that can operate with a large number of other general-purpose or dedicated computing system environments or configurations. 8 Includes 12. Computer systems / servers 8Examples of well-known computing systems, environments, and / or configurations that can be suitably used with 12 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.

[0083] Computer systems / servers 8 12 can be described in the general context of computer system executable instructions, such as program modules, which are executed by computer systems. Generally, a program module may include routines, programs, objects, components, logic, and / or data structures that perform a specific task or implement a specific abstract data type. Computer system / server 8 12 may be implemented in a distributed cloud computing environment in which tasks are performed by remote processing devices linked via a communication network. In a distributed cloud computing environment, program modules can reside on both local and remote computer system storage media, including memory storage devices.

[0084] figure 8 As shown, computer systems 8 Computer systems / servers within 00 8 12 is shown in the form of a general-purpose computing device: computer system / server 8 The twelve components include, but are not limited to, one or more processors or processing units. 8 16. System memory 8 28, and system memory 8 The processor includes various system components, including 28.8 Bus to be connected to 16 8 I can list 18.

[0085] bus 8 18 represents one or more of several types of bus structures, such as memory buses or memory controllers, peripheral buses, accelerated graphics ports, and processor or local buses using any of the various bus architectures. For example, such architectures include, but are not limited to, the Industry Standard Architecture (ISA) bus, Microchannel Architecture (MCA) bus, Extended ISA (EISA) bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Components Interconnect (PCI) bus.

[0086] Computer systems / servers 8 12 typically includes various computer system-readable media. Such media are computer systems / servers 8 Any available medium accessible by 12 may include both volatile and non-volatile media, removable media and non-removable media.

[0087] System memory 8 28 is Random Access Memory (RAM) 8 30 and / or cache memory 8 It may include computer system-readable media in the form of volatile memory such as 32. Computer system / server 8 12 may further include other removable / non-removable, volatile / non-volatile computer system storage media. This is merely an example of a storage system. 834 may be provided for reading from and writing to a non-removable non-volatile magnetic medium (not shown, but typically called a “hard drive”). 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 bused by one or more data medium interfaces. 8 It can be connected to 18. As further illustrated and described below, memory 8 28 may include at least one program product having a set of (e.g., at least one) program modules configured to perform the functions / operations of embodiments of the present invention.

[0088] A set of (at least one) program modules 8 Programs / utilities with 42 entries 8 40 is, for example, not limited to this, memory 8 It may be stored in 28. An example program module 8 42 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 include an implementation of a networking environment. Program module 8 42 generally performs the functions and / or methodologies of embodiments of the present invention.

[0089] Furthermore, computer systems / servers 8 12 is a keyboard, pointing device, and display. 824. Users and computer systems / servers 8 One or more devices, and / or computer systems / servers, that enable interaction with 12. 8 12 One or more external devices that enable communication between the and one or more other computing devices (e.g., network cards, modems, etc.) 8 It can communicate with 14. Such communication is an input / output (I / O) interface. 8 This can be done via 22. Furthermore, computer systems / servers 8 12 is the network adapter 8 It can communicate with one or more networks via 20, such as a local area network (LAN), a general-purpose wide area network (WAN), and / or a public network (e.g., the Internet). As shown in the figure, network adapter 8 20 is bus 8 Computer systems / servers via 18 8 It communicates with 12 other components. Although not shown, it communicates with other hardware and / or software components of the computer system / server. 8 It should be understood that it can be used with version 12. Examples, but not limited to, include microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data archive storage systems.

[0090] Computer program products The present invention may be a system, method, and / or a computer program product. The computer program product may include one or more computer-readable storage media having computer-readable program instructions for causing a processor to perform an aspect of the present invention.

[0091] A computer-readable storage medium may be a tangible device capable of holding and storing instructions for use by an instruction execution device. A computer-readable storage medium may be, but is not limited to, electronic storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination thereof. 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 disk read-only memory (CD-ROM), digital multipurpose disks (DVDs), memory sticks, floppy disks, mechanically encoded devices such as punch cards or grooved raised structures on which instructions are recorded, and any suitable combination thereof. When used herein, a computer-readable storage medium should not be construed as a transient signal itself, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., optical pulses through optical fiber cables), or electrical signals transmitted through wires.

[0092] The computer-readable program instructions described herein are downloadable from a computer-readable storage medium to each computing / processing device, or downloadable 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 transmission fibers, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives computer-readable program instructions from the network and transfers the computer-readable program instructions for storage in a computer-readable storage medium within each computing / processing device.

[0093] The computer-readable program instructions for performing the operation of the present invention may be assembler instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk or C++, and conventional procedural programming languages ​​such as the "C" programming language or similar programming languages. The computer-readable program instructions may be executed 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 case, the remote computer may be connected to the user's computer via any type of network, such as a local area network (LAN) or wide area network (WAN), or the connection may be to an external computer (for example, via the Internet using an Internet service provider). In some embodiments, for example, an electronic circuit such as a programmable logic circuit, a field-programmable gate array (FPGA), or a programmable logic array (PLA) can execute a computer-readable program instruction by personalizing the electronic circuit using state information of the computer-readable program instruction in order to perform an aspect of the present invention.

[0094] Aspects of the present invention are described herein with reference to flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present invention. It will be understood that each block in the flowcharts and / or block diagrams, as well as combinations of blocks in the flowcharts and / or block diagrams, can be implemented by computer-readable program instructions.

[0095] These computer-readable program instructions can be provided to the processor of a general-purpose computer, a dedicated computer, or other programmable data processing device to generate a machine such that the instructions, when executed by the processor of the computer or other programmable data processing device, produce means for performing functions / operations specified in one or more blocks of a flowchart and / or block diagram. Furthermore, these computer-readable program instructions may be stored in a computer-readable storage medium capable of directing computers, programmable data processing devices, and / or other devices to function in a particular manner, and as a result, the computer-readable storage medium storing the instructions comprises a product containing instructions that perform the modes of functions / operations specified in one or more blocks of a flowchart and / or block diagram.

[0096] Furthermore, computer-readable program instructions may be loaded into a computer, another programmable data processing device, or other device to cause the execution of a series of operational steps on the computer, another programmable device, or other device to generate a computer-executed process, such that the instructions are executed on the computer, another programmable device, or other device to perform the functions / operations specified in one or more blocks of a flowchart and / or block diagram.

[0097] 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 containing one or more executable instructions for performing a specified logical function. In some alternative embodiments, the functions described in a block may be performed in a different order than shown in the figure. For example, two blocks shown consecutively may actually be executed substantially simultaneously, or they may sometimes be executed in reverse order depending on the functions they relate to. Furthermore, it should be noted that each block in a block diagram and / or flowchart, as well as combinations of blocks in a block diagram and / or flowchart, can be implemented by a dedicated hardware-based system that performs a specified function or operation, or a combination of dedicated hardware and computer instructions.

[0098] The descriptions of the various embodiments of this disclosure are presented for illustrative purposes only and are not intended to be exhaustive or to limit 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 embodiments described. The terms used herein have been chosen to describe the principles of the embodiments, their practical applications, or technical improvements to the technology available on the market, or to make the embodiments disclosed herein understandable to those skilled in the art.

Claims

1. A computer system performs a series of logical operations to analyze a viral gene delivery vehicle (VGDV) sample in a set of analytical instruments including at least one separation instrument, at least one static light scattering instrument, and at least two concentration detectors, thereby determining the capsid protein mass of the sample. Ａ And the modification factor mass m of the sample Ｂ And the molar mass M of the modifying factor of the sample. Ｂ To bring about, The molar mass M of the capsid protein in the aforementioned sample. Ａ This involves receiving the data from the capsid protein molar mass data source, The injection volume v of the aforementioned sample is received from the injection volume data source, The computer system determines the total VGDV particle concentration C of the sample. Ａ of C Ａ =(m Ａ ×N) / (M Ａ ×v) The process of performing a series of logical operations calculated by, where N is the Avograd number, and the process of performing A computer implementation method, including

2. The computer system performs a series of logical operations to analyze the sample in the set, resulting in the capsid protein molar mass M of the sample Ａ to yield The molar mass M of the capsid protein in the sample Ａ To store the capsid protein molar mass in the aforementioned capsid protein molar mass data source. The method according to claim 1, further comprising:

3. The aforementioned analysis includes analyzing the sample in the set using analytical techniques, The method according to claim 1, wherein the analytical technique is one of viral vector analysis, protein conjugate analysis, and copolymer composition analysis.

4. The method according to claim 1, wherein the at least one separation device comprises at least one of a size exclusion chromatography unit, a field flow fractionation unit, and an ion exchange chromatography unit.

5. The method according to claim 1, wherein the at least one static light scattering device comprises a multi-angle light scattering device.

6. The method according to claim 1, wherein the at least two concentration detectors include a first ultraviolet absorbance detector with a first wavelength λ1 and a second ultraviolet absorbance detector with a second wavelength λ2.

7. The first wavelength λ1 is 260 nm. The second wavelength λ2 is 280 nm. The method according to claim 6.

8. The method according to claim 1, wherein the at least two concentration detectors include an ultraviolet absorbance detector with wavelength λ and a differential refractive index detector.

9. The method according to claim 8, wherein the wavelength λ is one of 260 nm and 280 nm.

10. The method according to claim 1, wherein the at least two concentration detectors include an ultraviolet absorbance detector with a wavelength λ and a fluorescence detector.

11. The method according to claim 10, wherein the wavelength λ is one of 260 nm and 280 nm.

12. The method according to claim 1, wherein the at least two concentration detectors include a differential refractive index detector and a fluorescence detector.

13. The mass m of the modifying factor in the sample Ｂ The method according to claim 1, wherein is the nucleic acid mass of the sample.

14. The molar mass M of the modifying factor in the sample Ｂ The method according to claim 1, wherein is the molar mass of nucleic acid of the sample.

15. The aforementioned computer system determines the molar mass M of the full modification factor in the full VGDV sample. Ｆｕｌｌ This is obtained from the molar mass data source of the full modification factor, The computer system determines the full VGDV concentration C of the full VGDV sample. Ｆｕｌｌ of C Ｆｕｌｌ =(m Ｂ ×N) / (M Ｆｕｌｌ ×v) Performing a series of logical operations calculated by, The computer system determines the empty VGDV concentration C of the full VGDV sample. Ｅｍｐｔｙ of C Ｅｍｐｔｙ =C Ａ -C Ｆｕｌｌ Performing a series of logical operations calculated by and The method according to claim 1, further comprising:

16. The computer system performs a series of logical operations to analyze the full VGDV sample in the set, determining the molar mass M of the full modification factor in the full VGDV sample. Ｆｕｌｌ To bring about, The molar mass M of the full modification factor in the full VGDV sample Ｆｕｌｌ To store the full modification factor molar mass data in the aforementioned full modification factor data source. The method according to claim 15, further comprising:

17. The method according to claim 15, wherein the modifying factor is a nucleic acid.

18. The computer system performs a series of logical operations to analyze the entire VGDV signal region of the sample in the set and analyze the aggregated peak region of the sample in the set, thereby determining the total VGDV peak protein mass of the sample corresponding to the entire VGDV signal region of the sample. Ａ，ｅｎｔ , the mass of the VGDV peak modification factor of the sample corresponding to the entire VGDV signal region of the sample m Ｂ，ｅｎｔ , the total VGDV peak protein molar mass M of the sample corresponding to the entire VGDV signal region of the sample. Ａ，ｅｎｔ , the molar mass M of the VGDV peak modification factor of the sample corresponding to the entire VGDV signal region of the sample. Ｂ，ｅｎｔ , the VGDV aggregated peak protein mass of the sample corresponding to the aggregated peak region of the sample m Ａ，ａｇｇ , the mass of the VGDV aggregation peak modifying factor of the sample corresponding to the aggregation peak region of the sample m Ｂ，ａｇｇ , the molar mass of the VGDV aggregated peak protein of the sample corresponding to the aggregated peak region of the sample M Ａ，ａｇｇ , and the molar mass M of the VGDV aggregation peak modifying factor of the sample corresponding to the aggregation peak region of the sample. Ｂ，ａｇｇ To bring about, The computer system determines the total peak particle concentration C of the sample corresponding to the entire VGDV signal region of the sample. Ａ，ｅｎｔ of C Ａ，ｅｎｔ =(m Ａ，ｅｎｔ ×N) / (M Ａ，ｅｎｔ ×v) Performing a series of logical operations calculated by, The computer system determines the total VGDV aggregated peak particle concentration C of the sample corresponding to the aggregated peak region of the sample. Ａ，ａｇｇ of C Ａ，ａｇｇ =(m Ａ，ａｇｇ ×N) / (M Ａ，ａｇｇ ×v) Performing a series of logical operations calculated by and The method according to claim 1, further comprising:

19. The computer system performs a series of logical operations to analyze the entire VGDV signal region of the full virus gene delivery vehicle sample in the set and analyze the agglutination peak region of the full sample in the set, thereby determining the total VGDV peak molar mass M of the full modification factor in the full sample corresponding to the entire VGDV signal region of the full sample. Ｆｕｌｌ，ｅｎｔ , and the VGDV aggregation peak molar mass M of the full-size modifying factor in the full-size sample corresponding to the aggregation peak region of the full-size sample. Ｆｕｌｌ，ａｇｇ To bring about, The computer system determines the total peak full VGDV concentration C of the full sample, which corresponds to the entire VGDV signal region of the VGDV sample. Ｆｕｌｌ，ｅｎｔ of C Ｆｕｌｌ，ｅｎｔ =(m Ｂ，ｅｎｔ ×N) / (M Ｆｕｌｌ，ｅｎｔ ×v) Performing a series of logical operations calculated by, The computer system determines the VGDV concentration of the full sample corresponding to the aggregation peak region of the full sample. Ｆｕｌｌ，ａｇｇ of C Ｆｕｌｌ，ａｇｇ =(m Ｂ，ａｇｇ ×N) / (M Ｆｕｌｌ，ａｇｇ ×v) Performing a series of logical operations calculated by, The computer system determines the overall peak VGDV concentration C of the full sample, which corresponds to the entire VGDV signal region of the full sample. Ｅｍｐｔｙ，ｅｎｔ of C Ｅｍｐｔｙ，ｅｎｔ =C Ａ，ｅｎｔ -C Ｆｕｌｌ，ｅｎｔ Performing a series of logical operations calculated by, The computer system determines the VGDV concentration of the full sample corresponding to the aggregation peak region of the full sample. Ｅｍｐｔｙ，ａｇｇ of C Ｅｍｐｔｙ，ａｇｇ =C Ａ，ａｇｇ -C Ｆｕｌｌ，ａｇｇ Performing a series of logical operations calculated by and The method according to claim 18, further comprising:

20. A computer system performs a series of logical operations to analyze a viral gene delivery vehicle (VGDV) sample in a set of analytical instruments including at least one separation instrument, at least one static light scattering instrument, and at least one concentration detector, thereby determining the modification factor mass of the sample. Ｂ And the molar mass M of the modifying factor of the sample. Ｂ This results in at least one UV absorption coefficient of the sample, The computer system determines the mass of the capsid protein in the sample with respect to at least one refractive index increment from the at least one concentration detector. Ａ and the molar mass M of the capsid protein of the sample. Ａ Performing a series of logical operations to calculate, The injection volume v of the aforementioned sample is received from the injection volume data source, The total VGDV particle concentration of the sample is determined by the aforementioned computer system. Ａ of C Ａ =(m Ａ ×N) / (M Ａ ×v) The process of performing a series of logical operations calculated by, where N is the Avograd number, and the process of performing A computer implementation method, including

21. A computer implementation method (UV-UV), A computer system performs a series of logical operations to analyze a viral gene delivery vehicle (VGDV) sample in a set of analytical instruments including at least one separation instrument, at least one static light scattering instrument, and at least two concentration detectors. The computer system collects from the sample at a first wavelength λ1. UV absorbance value A λ１ , the ultraviolet absorbance value A collected from the sample at a second wavelength λ2 λ２ , the extinction coefficient ε of the protein at the first wavelength λ1 Ａ λ１ , the extinction coefficient ε of the protein at the second wavelength λ2 Ａ λ２ , the absorption coefficient ε of the modification factor in the sample at the first wavelength λ1 Ｂ λ１ , and the absorption coefficient ε of the modification factor in the sample at the second wavelength λ2 Ｂ λ２ Regarding the mass fraction X of the protein in the sample Ａ Performing a series of logical operations to calculate, The computer system determines the mass fraction X of the protein in the sample. Ａ , the extinction coefficient ε of the protein at the first wavelength Ａ λ１ , and the absorption coefficient ε of the modifying factor in the sample at the first wavelength Ｂ λ１ Regarding the absorption coefficient ε of the sample at the first wavelength, ＶＧＤＶ λ１ Performing a series of logical operations to calculate, The computer system calculates the mass fraction X of the protein in the sample Ａ and the absorption coefficient ε of the protein at the second wavelength Ａ λ２ and the absorption coefficient ε of the modification factor in the sample at the second wavelength Ｂ λ２ and executes a series of logical operations to calculate the absorption coefficient ε of the sample at the second wavelength with respect to ＶＧＤＶ λ２ the above The computer system determines the mass fraction X of the protein in the sample. Ａ , the refractive index coefficient (dn / dc) of the protein Ａ , and the refractive index coefficient (dn / dc) of the modification factor in the sample. Ｂ Regarding the refractive index increment (dn / dc) of the aforementioned sample ＶＧＤＶ Performing a series of logical operations to calculate, The ultraviolet absorbance value A collected from the sample at a wavelength λ, which is one of the first wavelength λ1 and the second wavelength λ2, by the computer system λ , the mass fraction X of the protein in the sample Ａ , the absorption coefficient ε of the protein at the wavelength λ Ａ λ , and the absorption coefficient ε of the modifying factor in the sample at the wavelength λ Ｂ λ , with respect to the total mass m of the protein Ａ and the total mass m of the modifying factor Ｂ , performing a series of logical operations to calculate The computer system determines the total VGDV particle concentration C of the sample. Ａ of C Ａ =(m Ａ ×N) / (M Ａ ×v) This involves performing a series of logical operations calculated by, In the formula, N is the Avograd number, and M Ａ This is the molar mass of the capsid protein of the sample from the capsid protein molar mass data source, and A computer implementation method, including

22. The mass fraction X of the protein in the sample Ａ Calculating is X Ａ =((A λ１ ×ε Ｂ λ２ )-(A λ２ ×ε Ｂ λ１ )) / ((A λ２ ×ε Ａ λ１ )-(A λ２ ×ε Ｂ λ１ )-(A λ１ ×ε Ａ λ２ )+(A λ１ ×ε Ｂ λ２ )) The mass fraction X of the protein in the sample Ａ This includes calculating, The absorption coefficient ε of the sample at the first wavelength ＶＧＤＶ λ１ Calculating is e ＶＧＤＶ λ１ =(G) Ａ ×e Ａ λ１ )+((1-+ Ａ )×e Ｂ λ１ ) The absorption coefficient ε of the sample at the first wavelength is determined by the above. ＶＧＤＶ λ１ This includes calculating, The absorption coefficient ε of the sample at the second wavelength ＶＧＤＶ λ２ Calculating is e ＶＧＤＶ λ２ =(G) Ａ ×e Ａ λ２ )+((1-+ Ａ )×e Ｂ λ２ ) The absorption coefficient ε of the sample at the second wavelength is determined by the above. ＶＧＤＶ λ２ This includes calculating, The refractive index increment (dn / dc) of the aforementioned sample ＶＧＤＶ Calculating is (dn / dc) ＶＧＤＶ =(X Ａ ×(dn / dc) Ａ )+((1-X Ａ )×(dn / dc) Ｂ ) The refractive index increment (dn / dc) of the sample is determined by ＶＧＤＶ This includes calculating, The total mass m of the protein Ａ Calculating is m Ａ =(A λ ×X Ａ ) / ((X Ａ ×ε Ａ λ )+((1-X Ａ )×ε Ｂ λ )) The total mass m of the protein Ａ This includes calculating, The total mass m of the modifying factor Ｂ Calculating is m Ｂ =(A λ ×(1-X Ａ )) / ((X Ａ ×ε Ａ λ )+((1-X Ａ )×ε Ｂ λ )) The total mass m of the modifying factor Ｂ The method according to claim 21, which includes calculating

23. The first wavelength λ1 is 260 nm. The second wavelength λ2 is 280 nm. The method according to claim 21.

24. The method according to claim 21, wherein the modifying factor is a nucleic acid.

25. A computer implementation method (UV-dRI), A computer system performs a series of logical operations to analyze a viral gene delivery vehicle (VGDV) sample in a set of analytical instruments including at least one separation instrument, at least one static light scattering instrument, and at least two concentration detectors. The aforementioned computer system collects the ultraviolet absorbance value A from the sample at wavelength λ. λ , the refractive index coefficient (dn / dc) of the modifying factor in the sample Ｂ , the differential refractive index dRI of the solution containing the sample, and the absorption coefficient ε of the modification factor at the wavelength λ. Ｂ λ , the extinction coefficient of the protein at the wavelength λ ε Ａ λ , and the refractive index coefficient (dn / dc) of the protein Ａ Regarding the mass fraction X of the protein in the sample Ａ Performing a series of logical operations to calculate, The computer system determines the mass fraction X of the protein in the sample. Ａ , the extinction coefficient ε of the protein at the aforementioned wavelength Ａ λ , and the absorption coefficient ε of the modifying factor in the sample at the wavelength. Ｂ λ Regarding the absorption coefficient ε of the sample at the aforementioned wavelength, ＶＧＤＶ λ Performing a series of logical operations to calculate, The computer system determines the mass fraction X of the protein in the sample. Ａ , the refractive index coefficient (dn / dc) of the protein Ａ , and the refractive index coefficient (dn / dc) of the modifying factor in the sample Ｂ Regarding the refractive index increment (dn / dc) of the aforementioned sample ＶＧＤＶ Performing a series of logical operations to calculate, The computer system determines the differential refractive index dRI of the solution containing the sample, and the mass fraction X of the protein in the sample. Ａ , the refractive index coefficient (dn / dc) of the protein Ａ , and the refractive index coefficient (dn / dc) of the modifying factor in the sample Ｂ Regarding the total mass m of the protein, Ａ and the total mass m of the modifying factors Ｂ Performing a series of logical operations to calculate, The computer system determines the total VGDV particle concentration C of the sample. Ａ of C Ａ =(m Ａ ×N) / (M Ａ ×v) This involves performing a series of logical operations calculated by, In the formula, N is the Avograd number, and M Ａ This is the molar mass of the capsid protein of the sample from the capsid protein molar mass data source, and A computer implementation method, including

26. The mass fraction X of the protein in the sample Ａ Calculating is X Ａ =((A λ ×(dn / dc) Ｂ )-(dRI×ε Ｂ λ )) / ((dRI×ε Ａ λ )-(dRI×ε Ｂ λ )-(A λ ×(dn / dc) Ａ )+(A λ ×(dn / dc) Ｂ )) The mass fraction X of the protein in the sample Ａ This includes calculating, The absorption coefficient ε of the sample at the aforementioned wavelength ＶＧＤＶ λ Calculating is e ＶＧＤＶ λ =(G) Ａ ×e Ａ λ )+((1-+ Ａ )×e Ｂ λ ) The absorption coefficient ε of the sample at the wavelength is determined by the above ＶＧＤＶ λ This includes calculating, The refractive index increment (dn / dc) of the aforementioned sample ＶＧＤＶ Calculating is (dn / dc) ＶＧＤＶ =(X Ａ ×(dn / dc) Ａ )+((1-X Ａ )×(dn / dc) Ｂ ) The refractive index increment (dn / dc) of the sample is determined by ＶＧＤＶ This includes calculating, The total mass m of the protein Ａ Calculating is m Ａ =(dRI×X Ａ ) / ((X Ａ ×(dn / dc) Ａ )+((1-X Ａ )×(dn / dc) Ｂ )) The total mass m of the protein Ａ This includes calculating, The total mass m of the modifying factor Ｂ Calculating is m Ｂ =(dRI×(1-X Ａ )) / ((X Ａ ×(dn / dc) Ａ )+((1-X Ａ )×(dn / dc) Ｂ )) The total mass m of the modifying factor Ｂ The method according to claim 25, which includes calculating [a certain value].

27. The method according to claim 25, wherein the wavelength λ is one of 260 nm and 280 nm.

28. The method according to claim 25, wherein the modifying factor is a nucleic acid.

Images