System suitability parameters and column aging

Abstract

The present invention provides a method for monitoring column performance and operating a chromatography column by applying a generalized linear model to system suitability parameters (SSPs) to assess how quickly the column is changing over time and whether the column stationary phase needs to be replaced. The method leads to faster identification of column failures, helping to maintain high separation quality and consistent analytical results for analytical and preparative chromatography methods. Columns evaluated and / or monitored by the method, as well as products resulting from the use of these columns and methods, are also provided.

Description

[Technical Field]

[0001] REFERENCE TO RELATED APPLICATIONS This application claims the benefit of U.S. Provisional Patent Application No. 63 / 447,533, filed February 22, 2023, the entire contents of which are incorporated herein by reference.

[0002] The present invention relates generally to chromatography, and more particularly to methods for operating and monitoring chromatography columns and products resulting from the use of such chromatography columns. [Background technology]

[0003] In the biopharmaceutical industry, preparative chromatography using packed-bed columns is a critical component in the production of complex biological products (e.g., recombinant proteins and antibodies). The success of monoclonal antibodies, in particular, is due to their target specificity and favorable side effect profile (typically minimal compared to other therapeutic modalities). Monoclonal antibodies have been successfully developed to treat a variety of human diseases, including cancer, infectious diseases, and inflammation. However, despite advances in the selection of therapeutic targets for monoclonal antibodies, challenges remain in the manufacturing process, formulation development, and product stability during storage (S. Goswami et al. Developments and challenges for mAb-based therapeutics. Antibodies 2 (2013) 452-500).

[0004] Controlling aggregation is one of the key challenges encountered during the formulation and process development of protein-based drugs, including monoclonal antibodies. Partial unfolding of monoclonal antibody monomers, accompanied by conformational changes in structure, is thought to promote the formation of aggregates through self-association. These aggregates, ranging from dimers and trimers to higher-order oligomerization states, pose a potential threat to drug safety and efficacy (Y. Let et al., Physicochemical stability of monoclonal antibodies: A review. J. Pharm. Sci. 109 (2020) 169-190). It has been reported that the intended biological activity of monoclonal antibodies is negatively correlated with the presence of aggregates (R. Bansal, R. Dash, A. S. Rathore, Impact of mAb aggregation on its biological activity: Rituximab as a case study. J. Pharm. Sci. 109 (2020) 2684-2698). Furthermore, these aggregates can lead to the formation of insoluble particles, affecting drug quality (e.g., opalescence) (BA Salinas et al., Understanding and modulating opalescence and viscosity in a monoclonal antibody formulation. J. Pharm. Sci. 99 (2010) 82-93) and potentially eliciting undesirable immune responses (X. Wang et al., Molecular and functional analysis of monoclonal antibodies in support of biologics development. Protein Cell 9 (2018) 74-58). Therefore, aggregation levels are considered critical quality attributes (CQA) and must be closely monitored throughout the development and production of monoclonal antibodies.

[0005] Silica or polymer-based particles are commonly used to pack chromatography columns, and their surfaces are often modified according to chromatographic methods. Surface modification of silica particles involves several chemical reactions to generate covalent bonds between functional groups on the silica surface and silanol groups (EMBorges, Silica, Hybrid Silica, Hydride Silica, and Non-Silica Stationary Phases for Liquid Chromatography. J. Chromatogr. Sci. 53 (2015) 580-597). However, due to the inherent sensitivity of particles or repeated exposure to various analytical conditions (e.g., changes in mobile phase, sample composition, and pressure), alteration or loss of modified functional groups can change the interaction between the column particles and the sample composition. It has been reported that the efficiency of surface modification can vary, leaving unmodified, isolated silanol groups. This can be a potential problem. Isolated silanols, also known as activated silanols, can induce strong electrostatic interactions with biomolecules, resulting in peak tailing, peak broadening, and asymmetry. In addition to secondary interactions from active silanol groups, another challenge is ensuring uniformity of pore size and consistency of chemical group modification (S. Fekete et al., Size exclusion chromatography of protein biopharmaceuticals: past, present and future. Am. Pharm. Rev. (2018) 1-4). As a result, the column resolution and / or separation efficiency can be significantly reduced. Therefore, it is important that the performance of chromatography columns is closely monitored and well-controlled to ensure high product quality of biomolecule products.

[0006] Therefore, there is a need in the art for a method to monitor column performance to facilitate improved column performance. Summary of the Invention

[0007] The present disclosure provides a method for operating a chromatography column, the method comprising running a generalized linear model (GLM) on a set of system suitability parameter (SSP) values, the set of SSP values ​​being obtained from an initial run of an analyte through the column and one or more subsequent runs.

[0008] The slope of the linear regression line generated by the GLM can indicate the performance of the column compared to the initial state of the column during the first run.

[0009] The method can include measuring the value of the SSP in the first and subsequent runs.

[0010] The slope of the linear regression line can indicate the rate of column degradation or the rate of column aging.

[0011] The SSP may be selected from the group consisting of retention time, peak height and / or peak width, tailing factor, asymmetry factor, resolution, number of theoretical plates, or any combination thereof.

[0012] The method can include making a determination that the performance of the column is acceptable if the set of SSP values ​​fits a linear model.

[0013] The method can include making a determination that the performance of the column is unacceptable if the set of SSP values ​​does not fit a linear model.

[0014] A set of SSP values ​​may fit better to an exponential model than to a linear model.

[0015] The generalized linear model has the following formula:

number

number

[0016] The method uses R-squared (R 2 ) value.

[0017] This method is 2 If the value is less than a predetermined threshold, a determination can be made that the performance of the column is unacceptable. The predetermined threshold can be 0.7.

[0018] The method may further include replacing the column or repacking the stationary phase particles of the column.

[0019] The present invention further provides a method for monitoring a column, comprising running a generalized linear model (GLM) on a set of system suitability parameter (SSP) values, the set of SSP values ​​being obtained from an initial run of an analyte through the column and one or more subsequent runs.

[0020] The slope of the linear regression line generated by the GLM can indicate the performance of the column compared to the initial state of the column during the first run.

[0021] The method can include measuring the value of the SSP in the first and subsequent runs.

[0022] The slope of the linear regression line can indicate the rate of column degradation or the rate of column aging.

[0023] The SSP may be selected from the group consisting of retention time, peak height and / or peak width, tailing factor, asymmetry factor, resolution, number of theoretical plates, or any combination thereof.

[0024] The method can include making a determination that the performance of the column is acceptable if the set of SSP values ​​fits a linear model.

[0025] The method can include making a determination that the performance of the column is unacceptable if the set of SSP values ​​does not fit a linear model.

[0026] A set of SSP values ​​may fit better to an exponential model than to a linear model.

[0027] Generalized linear models are

number

number

[0028] The method uses R-squared (R 2 ) value.

[0029] This method is 2 If the value is less than a predetermined threshold, a determination can be made that the performance of the column is unacceptable. The predetermined threshold is 0.7.

[0030] The method may further include replacing the column or repacking the stationary phase particles of the column.

[0031] The present invention may further provide a method for operating a chromatography column, comprising determining the percent change in SSP between an initial run of an analyte through the column and a subsequent run.

[0032] The SSP may be selected from the group consisting of retention time, peak height and / or peak width, tailing factor, asymmetry factor, resolution, number of theoretical plates, or any combination thereof.

[0033] A positive percent change in retention time, peak width, and / or tailing factor can indicate a decrease in column performance.

[0034] A negative percent change in peak height, resolution, and / or theoretical plate number can indicate a decrease in column performance.

[0035] The method can include determining that the performance of the column is unacceptable if the percent change in the SSP exceeds a reference level. The percent change can be greater than 2.3% if the SSP is retention time, greater than 12% if the SSP is peak width, greater than 10% if the SSP is tailing factor, greater than 15.75% if the SSP is asymmetry factor, less than -9.8% if the SSP is peak height, less than -10.5% if the SSP is resolution, and / or less than -18.5% if the SSP is theoretical plate number.

[0036] The method can further include determining that the performance of the column is acceptable and continuing to use the column.

[0037] A determination that the column performance is acceptable can be made if the percent change in SSP is equal to or greater than the reference level, the percent change can be 2.3% or less when SSP is retention time, the percent change can be 12% or less when SSP is peak width, the percent change can be 10% or less when SSP is tailing factor, the percent change can be 15.75% or less when SSP is asymmetry factor, the percent change can be -9.8% or more when SSP is peak height, the percent change can be -10.5% or more when SSP is resolution, and / or the percent change can be -18.5% or more when SSP is theoretical plate number.

[0038] The method may further include replacing the column or repacking the stationary phase particles of the column.

[0039] The present disclosure provides a method for monitoring a chromatography column, comprising determining the percent change in SSP between an initial run of an analyte through the column and subsequent runs.

[0040] The SSP may be selected from the group consisting of retention time, peak height and / or peak width, tailing factor, asymmetry factor, resolution, number of theoretical plates, or any combination thereof.

[0041] A positive percent change in retention time, peak width, and / or tailing factor can indicate a decrease in column performance.

[0042] A negative percent change in peak height, resolution, and / or theoretical plate number can indicate a decrease in column performance.

[0043] The method can include determining that the performance of the column is unacceptable if the percent change in the SSP exceeds a reference level. The percent change can be greater than 2.3% if the SSP is retention time, greater than 12% if the SSP is peak width, greater than 10% if the SSP is tailing factor, greater than 15.75% if the SSP is asymmetry factor, less than -9.8% if the SSP is peak height, less than -10.5% if the SSP is resolution, and / or less than -18.5% if the SSP is theoretical plate number.

[0044] The method can include determining that the performance of the column is acceptable and continuing to use the column.

[0045] A determination that the column performance is acceptable can be made if the percent change in SSP is equal to or greater than the reference level, the percent change can be 2.3% or less if the SSP is retention time, the percent change can be 12% or less if the SSP is peak width, the percent change can be 10% or less if the SSP is tailing factor, the percent change can be 15.75% or less if the SSP is asymmetry factor, the percent change can be -9.8% or more if the SSP is peak height, the percent change can be -10.5% or more if the SSP is resolution, and / or the percent change can be -18.5% or more if the SSP is theoretical plate number.

[0046] The method may further include replacing the column or repacking the stationary phase particles of the column.

[0047] The column can include silica-based particles or polymer-based materials.

[0048] The surface of the particles can be chemically modified.

[0049] The chromatography can be selected from the group consisting of size exclusion chromatography (SEC), reversed-phase liquid chromatography (RPLC), hydrophilic interaction liquid chromatography (HILIC), hydrophobic liquid chromatography (HIC), ion exchange chromatography (IEX), and affinity chromatography (AC).

[0050] Ion exchange chromatography (IEX) can be anion exchange chromatography (AEX) or cation exchange chromatography (CEX).

[0051] The chromatography column can be a silica-based SEC column.

[0052] The analyte can be a biomolecule.

[0053] The biomolecule may be selected from the group consisting of a protein, a nucleic acid, a carbohydrate, and a lipid.

[0054] The protein may be selected from the group consisting of an antibody, an enzyme, a cytokine, a growth factor, a hormone, an interferon, an interleukin, or an anticoagulant.

[0055] Columns evaluated and / or monitored by the method, as well as products resulting from the use of the column and method, are also provided.

[0056] Non-limiting examples of the present invention will now be described with reference to the drawings attached hereto, listed after this paragraph. [Brief explanation of the drawings]

[0057] [Figure 1]FIG. 1 is a schematic showing the degradation of silica-based particles that interact with biomolecules to generate unmodified isolated silanol groups ("active silanols"), resulting in peak tailing, peak broadening, and asymmetry.

[0058] [Figure 2A] Representative chromatograms of SEC separations of in-house IgG1 mAbs are shown.

[0059] [Figure 2B] Overlaid chromatograms of increasing injection numbers from left (100 injections) to right (1250 injections) are shown. Inset: Zoomed-in and overlaid chromatograms with alignment of major peaks.

[0060] [Figure 3A] Figure 1 shows a control chart plotting SSP as a function of time from a single column. Points represent the mean of each SSP corresponding to 10, 118, 207, 500, 630, and 840 injections. Area %. [Figure 3B] Control chart plotting SSP as a function of time from a single column. Points represent the mean of each SSP corresponding to 10, 118, 207, 500, 630, and 840 injections. USP tailing factor. [Figure 3C] Figure 1 shows a control chart plotting SSP as a function of time from a single column. Points represent the mean of each SSP corresponding to 10, 118, 207, 500, 630, and 840 injections. Peak width at 5% height. [Figure 3D] Figure 1 shows a control chart plotting SSP as a function of time from a single column. The points represent the mean of each SSP corresponding to 10, 118, 207, 500, 630, and 840 injections. Asymmetry coefficient. [Figure 3E] Figure 1 shows a control chart plotting SSP as a function of time from a single column. Points represent the mean of each SSP corresponding to 10, 118, 207, 500, 630, and 840 injections. Retention time. [Figure 3F]Control chart plotting SSP as a function of time from a single column. Points represent the mean of each SSP corresponding to 10, 118, 207, 500, 630, and 840 injections. USP resolution. [Figure 3G] Control chart plotting SSP as a function of time from a single column. Points represent the mean of each SSP corresponding to 10, 118, 207, 500, 630, and 840 injections. USP Theoretical Plates.

[0061] [Figure 4A] Linear regression correlation between system suitability parameters and column injection number. Retention time. [Figure 4B] Linear regression correlation between system suitability parameters and column injection number. Peak width at 5% height. [Figure 4C] Linear regression correlation between system suitability parameters and column injection number. Peak height. [Figure 4D] Figure 1 shows the linear regression correlation between system suitability parameters and the number of column injections. Tailing factor. [Figure 4E] 1 shows the linear regression correlation between system suitability parameters and the number of column injections. Asymmetry coefficient. [Figure 4F] Linear regression correlation between system suitability parameters and number of column injections. Resolution. [Figure 4G] 1 shows the linear regression correlation between system suitability parameters and column injection number. Theoretical plate number. The solid line represents the common regression line of the general linear model.

[0062] [Figure 5] From top to bottom, the lines show the percent change in system suitability parameters versus number of injections: peak width, tailing factor, retention time, area percent, peak height, resolution, and theoretical plate number.

[0063] [Figure 6A]Schematic of the column performance evaluation process. The middle panel shows a non-limiting example of SSP changes, with the circles highlighting the changes in small peaks (showing increasingly poor resolution with increasing number of injections). [Figure 6B] Indicates the decision point for column replacement when column profile parameters (area%, retention time, height, USP resolution, USP theoretical plates) fall outside the control limits. If a characteristic critical to the column's quality reaches a failure point, the column is determined to fail after a certain number of runs / injections. TDB: Number of injections determined when the column fails.

[0064] [Figure 7] Figure 1 shows a non-limiting example scenario in which a column approaches the end of its life and the system suitability parameters (SSP) deviate from linear behavior. If the column condition is acceptable, the SSP and the percent change in SSP compared to the initial condition fit a linear model (e.g., after up to approximately 1300 runs, as shown in the graph). If column degradation rapidly worsens at the column's service limit, the SSP change versus the number of injections is expected to have an exponential relationship. DETAILED DESCRIPTION OF THE INVENTION

[0065] It is to be understood that this invention is not limited to the compositions and methods described herein and the experimental conditions described, which may themselves vary, and that the terminology used herein is for the purpose of describing the invention only and is not intended to be limiting.

[0066] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this invention belongs.Any compositions, methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present invention.All publications mentioned are incorporated herein by reference in their entirety.

[0067] Recitation of ranges of values ​​herein, unless otherwise indicated herein, is intended to serve merely as an efficient method of referring individually to each separate value falling within the range, and each separate value is incorporated herein as if it were individually referenced herein.

[0068] A.Definition As used herein, the term "about" in the context of numerical values ​​and ranges refers to a value or range that approximates or is close to the recited value or range such that the invention can be performed as intended, having a desired rate, amount, degree, increase, decrease, concentration, or time, as is clear from the teachings contained herein. Thus, the term encompasses values ​​other than those that result solely from systematic error.

[0069] As used herein, "asymmetry factor" refers to a general measure of peak distortion. s ) can be used to assess peak tailing and peak fronting as an indicator of loss of column quality. In some instances, the asymmetry factor is

number

[0070] As used herein, the term "analyte" refers to a substance that is separated during chromatography.

[0071] As used herein, the term "biomolecule" or "biological molecule" refers to molecules produced by cells and organisms. Biomolecules vary in size and structure and perform a wide range of functions. The four major types of biomolecules are carbohydrates, lipids, nucleic acids, and proteins. However, many biomolecules contain moieties from different categories, such as proteoglycans and glycoproteins, which are proteins containing carbohydrate moieties.

[0072] As used herein, the term "chromatography" refers to a technique that allows a mixture to be separated into its components. Chromatography is based on the principle that molecules in a mixture are carried by a fluid solvent, called the mobile phase, through a system containing a fixed material, called the stationary phase. Different components of a mixture tend to have different affinities for the stationary phase and are retained for different lengths of time depending on their interaction, so the components move at different apparent speeds in the moving fluid, causing them to separate.

[0073] Chromatography can be used to separate components for later use (i.e., purify) and / or analyze components of a mixture. Chromatography methods are well known in the art, and many methods are frequently used for purification and analytical purposes. For example, based on the physical state of the mobile phase, chromatography can be gas chromatography or liquid chromatography (see, for example, Analytical Separation Science (2015), published by Weinheim: Wiley-VCH). Based on the shape of the stationary phase, chromatography methods include column chromatography or planar chromatography (e.g., paper chromatography, thin-layer chromatography). Based on the separation mechanism, there are a series of chromatography methods, including, but not limited to, size-exclusion chromatography (SEC), reversed-phase chromatography (RPC / RPLC), hydrophilic interaction liquid chromatography (HILIC), hydrophobic liquid chromatography (HIC), ion-exchange chromatography (IEX), and affinity chromatography (AC).

[0074] As used herein, "chromatograph" refers to an instrument used to perform a chromatographic process.

[0075] As used herein, "column chromatography" refers to a chromatography method in which a stationary phase is packed into a tube or column. The stationary phase material can be interchangeably referred to in the art as a "resin," "beads," or "particles." Particles of a support coated with a solid or liquid stationary phase can fill the entire internal volume of the tube (packed column) or be concentrated on or along the inner wall of the tube, leaving an open, unrestricted path for the mobile phase to travel in the central portion of the tube. Typically, the particles are tightly packed in the tube or column in a manner that minimizes the interstitial volume between the particles, so as to increase the separation efficiency of the column.

[0076] Typically, a column is first packed with stationary particles and filled with a mobile phase. When the column is prepared for an analysis or run, a sample is loaded onto the top of the packed column. In many chromatography systems, a series of tubing and pumps are connected to the column to generate pressure that forces the solvent (e.g., mobile phase) through the column, and the sample is injected into the system where it is loaded onto the column. As used herein, the term "injection" refers to a sample load or run of a sample through a column. The term "number of injections" can be understood as the number of runs or analyses performed on a column.

[0077] Detectors are used to monitor the separation of analytes in a sample as they migrate through a chromatography column. Detectors are typically placed where the analytes are eluted from the column. Detection methods are selected according to the type of analyte and chromatography technique, and include, but are not limited to, UV, fluorescence, refractive index, conductivity, thermal conductivity, electron capture, and photoionization detection.

[0078] Measurement of the elution solvent alone by the detector is used to establish a baseline, and the detector response to the analyte is often recorded as a series of peaks rising from the baseline. Each peak represents a compound. Many characteristics of the peaks, such as peak width, peak height, peak area, symmetry / asymmetry, and separation / overlap of adjacent peaks, are used to evaluate the analyte, as well as the efficiency of the chromatographic run.

[0079] As used herein, "general linear model" refers to a multivariate statistical analysis used to compare two sets of variables in a model function, encompassing linear regression and normal distribution conditions. General linear models are often used in many fields to analyze measurement data, for example, to compare a series of measured observations over time. As used herein, "generalized linear model" is an extension of the general linear model, and can encompass linear / nonlinear regression and normal / nonnormal distributions.

[0080] As used herein, "mobile phase" refers to a phase that moves in a certain direction in chromatography. A mobile phase is a fluid, e.g., a liquid or a gas. The mobile phase includes the sample to be separated / analyzed and a solvent that moves the sample through the stationary phase.

[0081] As used herein, the terms "peptide," "polypeptide," and "protein" are used interchangeably and refer to polymeric forms of amino acids of any length, which can include coded and non-coded amino acids, chemically or biochemically modified or derivatized amino acids, and polypeptides having modified peptide backbones.

[0082] As used herein, "theoretical plate number" refers to a theoretical number that describes the separation efficiency of a chromatography column. In some examples, the theoretical plate number is defined as follows:

number

[0083] As used herein, "purification" means a process performed to isolate an analyte (e.g., a biomolecule such as a peptide, protein, oligonucleotide, DNA, RNA, etc.) from one or more other impurities or components present in a fluid. Purification can be performed using chromatographic methods.

[0084] As used herein, "reference level" refers to a change in the level of one or more SSPs that indicates significant column aging, significant column degradation, and / or poor column performance such that the column needs to be replaced.

[0085] As used herein, "resolution" refers to the degree of separation between two eluting peaks based on their retention time and peak width in a chromatogram. In some instances, the resolution measurement is

number

[0086] As used herein, a "sample" refers to a mixture of compounds obtained from any source. The compounds in the sample are separated using chromatographic methods.

[0087] As used herein, the term "such as" is used to mean, and is used interchangeably with, "such as, but not limited to."

[0088] As used herein, "retention time" refers to the measurement of the time required for a molecule to pass through a separation system from injection to detection. As used herein, "retention time" and "elution time" are used interchangeably.

[0089] As used herein, "stationary phase" refers to a material that is fixed in place for a chromatographic process. While the mobile phase moves in one direction, the analytes in the sample interact with the stationary phase to different extents and are therefore separated.

[0090] As used herein, "system suitability parameters" (SSPs) refer to measurements used to verify the performance of a system. In chromatography, SSPs include, but are not limited to, asymmetry, retention time, resolution, theoretical plates, peak width, peak height, peak area, tailing factor, selectivity, and detection limit.

[0091] As used herein, "tailing factor," also known as "symmetry factor," refers to a measure of peak tailing that indicates the degree of symmetry of a peak. The USP tailing factor (T f )teeth,

number

[0092] All numerical limits and ranges set forth herein include all numbers or values ​​around or between the numbers in the range or limit. The ranges and limits set forth herein expressly represent and indicate all integers, decimals, and fractional values ​​defined and encompassed by the range or limit. The ranges and limits set forth herein expressly represent and indicate all integers, decimals, and fractional values ​​defined and encompassed by the range or limit. Thus, unless otherwise indicated herein, reference to a range of values ​​herein is intended to serve merely as an efficient way of individually referring to each separate value included within the range, and each separate value is incorporated herein as if it were individually referred to herein. For example, a range of 1 to 50 is understood to mean any number (including fractional values, combinations of numbers, or subranges) from the group consisting of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, or 50.

[0093] DETAILED DESCRIPTION OF THE INVENTION

[0023] Embodiments of the present invention will now be described in detail. While the present invention will be described in conjunction with examples, it will be understood that it is not intended to limit the invention to those examples. On the contrary, it is intended to cover alternatives, modifications, and equivalents as may be included within the spirit and scope of the invention as defined by the appended claims.

[0094] B. Method Figure 1 shows the degradation of silica-based particles, which generates unmodified, isolated silanol groups ("active silanols") that interact with biomolecules and result in peak tailing, peak broadening, and asymmetry. The degradation results in performance degradation caused by use.

[0095] In view of performance degradation, there is a need for, and provided herein, methods and systems for operating, evaluating, and / or monitoring the performance of chromatography columns.

[0096] 1. How to monitor and operate a chromatography column The method described herein is based on the key finding that careful examination of SSP before and during column use reveals that SSP is an important tool for detecting column aging and performance. Monitoring SSP changes over time helps establish realistic, historically based acceptance criteria for determining when a column should be replaced. Another approach is to use the percent change and estimated intercept obtained from a linear regression between SSP and injection number to predict column aging rates or to screen and evaluate the initial performance of new columns. Replicate injections of in-house test standards on multiple columns and the establishment of long-term internal control standards for SSP ensure consistent analytical results, leading to faster identification of column failures, more efficient production, and higher-quality products.

[0097] This disclosure provides a method for monitoring and operating one or more chromatography columns based on the discovery that several important system suitability parameters (SSPs) strongly correlate with column changes over time. This surprising observation points to a rigorous approach for qualifying columns and predicting their long-term performance.

[0098] Methods are provided for assessing chromatography column performance, column aging, and / or column degradation. The methods can include running a generalized linear model (GLM) on a set of system suitability parameter (SSP) values ​​obtained from an initial run of an analyte through the column and one or more subsequent runs.

[0099] Also provided is a method for monitoring chromatography column performance, column aging, and / or column degradation, which can include running a generalized linear model (GLM) on a set of system suitability parameter (SSP) values ​​obtained from an initial run of an analyte through the column and one or more subsequent runs.

[0100] Methods are provided for predicting chromatography column performance, column aging, and / or column degradation. The methods can include running a generalized linear model (GLM) on a set of system suitability parameter (SSP) values ​​obtained from an initial run of an analyte through the column and one or more subsequent runs.

[0101] Methods are provided for operating a chromatography column, which can include running a generalized linear model (GLM) on a set of system suitability parameter (SSP) values ​​obtained from an initial run of an analyte through the column and one or more subsequent runs.

[0102] System suitability parameters (SSP) can be selected from the group consisting of retention time, peak height, peak width, tailing factor, asymmetry factor, resolution, and theoretical plate number. Methods for determining general SSP are routine and well known in the art (see, for example, Sankar, Ravi. (2019). Fundamental Chromatographic Parameters. International Journal of Pharmaceutical Sciences Review and Research. 55(2): 46-50).

[0103] Preferably, at least three values ​​are obtained for the set of SSP values, and the number of values ​​in the set is at least 10, 20, 30, 40, 50, 75, 100, 150, 200, 250, 300, 350, 400, 450, or 500 values.

[0104] SSP values ​​can be obtained for columns in their original condition, where the column is performing optimally before wear from use adversely affects column quality. Runs for obtaining original SSP values ​​are designated to have a run number of 0.

[0105] After the value of SSP is obtained in the initial state, subsequent values ​​of SSP are obtained after the column has undergone one or more separation processes (ie, runs or injections).

[0106] SSP values ​​are obtained after greater than about 10, 20, 30, 40, 50, 60, 70, 80, 90, or 100 runs. SSP values ​​are obtained after greater than about 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 1100, 1200, 1300, 1400, or 1500 runs.

[0107] SSP values ​​for use in the methods disclosed herein can be obtained from replicate runs of the same sample. SSP values ​​can be obtained from runs of samples containing the same analyte.

[0108] The method can include measuring the SSP value. The method can include obtaining the SSP value.

[0109] In the methods provided herein, the SSP values ​​can be fitted using a generalized linear model (GLM) to correlate the SSP measurements with the number of runs (or injections) the column has undergone.

[0110] The generalized linear model (GLM) is based on the following formula:

number

number

[0111] Methods for fitting a data set to generalized linear modeling are known in the art. Software can be used to fit a set of SSP values ​​to a GLM and generate the coefficients of Formula I. For example, a useful software for this method is JMP®, and a set of SSP values ​​can be fitted to a linear model using the "standard least squares model" of JMP®.

[0112] For fitting a set of SSP values ​​to a GLM, an R-squared value can also be obtained. 2 or coefficient of determination) is a statistical measure in a regression model that determines the proportion of variance in the dependent variable that can be explained by the independent variables. In other words, R 2The value can indicate how well the data fit the regression model (goodness of fit).

[0113] The slope of the linear regression line can be obtained from a generalized linear model that describes the rate of column aging and / or column degradation.

[0114] The method can include determining whether the values ​​of the SSP fit a linear model.

[0115] The method can include determining that the performance of the column is unacceptable if the set of SSP values ​​does not fit a linear model. The set of SSP values ​​can be determined to fit an exponential model better than a linear model.

[0116] The method can include making a determination that the performance of the column is acceptable if the set of SSP values ​​fits a linear model.

[0117] The method is such that the set of SSP values ​​is R 2 The set of SSP values ​​can include determining whether to fit a linear model based on the R 2 If the value is less than a predetermined threshold, it can be determined that the linear model does not fit.

[0118] This method is 2 If the value is less than a predetermined threshold, a determination can be made that the performance of the column is unacceptable.

[0119] R 2The given thresholds are 0.9, 0.89, 0.88, 0.87, 0.86, 0.85, 0.84, 0.83, 0.82, 0.81, 0.8, 0.79, 0.78, 0.77, 0.76, 0.75, 0.74, 0.73, 0.72, 0.71, 0.7, 0.69, 0.68, 0.67, 0.66, 0.65 , 0.64, 0.63, 0.62, 0.61, 0.6, 0.59, 0.58, 0.57, 0.56, 0.55, 0.54, 0.53, 0.52, 0.51, 0.5, 0.49, 0.48, 0.47, 0.46, 0.45, 0.44, 0.43, 0.42, 0.41, or 0.4. 2 The predetermined threshold for may be 0.7.

[0120] This method is 2 If the value is less than 0.7, it may include making a determination that the performance of the column is unacceptable.

[0121] A particular feature of the methods disclosed herein can include determining the percent change in SSP after several runs compared to the SSP value at the initial state.

[0122] A positive percent change in retention time, peak width, and / or tailing factor can indicate a decrease in column performance.

[0123] A negative percent change in peak height, resolution, and / or theoretical plate number can indicate a decrease in column performance.

[0124] The method can include making a determination that the performance of the column is unacceptable if the percent change in the SSP exceeds the reference level.The method can include making a determination that the performance of the column is acceptable if the percent change in the SSP is equal to or less than the reference level.

[0125] When the SSP is retention time, the reference level can be about 1%, 1.1%, 1.2%, 1.3%, 1.4%, 1.5%, 1.6%, 1.7%, 1.8%, 1.9%, 2%, 2.1%, 2.2%, 2.3%, 2.4%, 2.5%, 2.6%, 2.7%, 2.8%, 2.9%, 3.0%, 3.1%, 3.2%, 3.3%, 3.4%, 3.5%, 3.6%, 3.7%, 3.8%, 3.9%, 4.0%, 4.5%, or 5%. A determination that column performance is unacceptable can be made if the percent change in retention time is greater than 1%, 1.1%, 1.2%, 1.3%, 1.4%, 1.5%, 1.6%, 1.7%, 1.8%, 1.9%, 2%, 2.1%, 2.2%, 2.3%, 2.4%, 2.5%, 2.6%, 2.7%, 2.8%, 2.9%, 3.0%, 3.1%, 3.2%, 3.3%, 3.4%, 3.5%, 3.6%, 3.7%, 3.8%, 3.9%, 4.0%, 4.5%, or 5%. A determination that the column performance is acceptable can be made if the percent change in retention time is 1%, 1.1%, 1.2%, 1.3%, 1.4%, 1.5%, 1.6%, 1.7%, 1.8%, 1.9%, 2%, 2.1%, 2.2%, 2.3%, 2.4%, 2.5%, 2.6%, 2.7%, 2.8%, 2.9%, 3.0%, 3.1%, 3.2%, 3.3%, 3.4%, 3.5%, 3.6%, 3.7%, 3.8%, 3.9%, 4.0%, 4.5%, or 5% or less.

[0126] If the SSP is the peak width (e.g., peak width at 5% peak height), the reference levels are approximately 6%, 6.5%, 7%, 7.5%, 8%, 8.5%, 9%, 9.5%, 10%, 10.2%, 10.4%, 10.5%, 10.6%, 10.8%, 11%, 11.2%, 11.4%, 11.5%, 10.6%, 10.8%, 12%, 12.2%, 12.4%, 12.5%, 12.6%, 12.7%, 12.8%, 12.9%, 12.1%, 12.1%. It can be 6%, 12.8%, 13%, 13.2%, 13.4%, 13.5%, 13.6%, 13.8%, 14%, 14.2%, 14.4%, 14.5%, 14.6%, 14.8%, 15%, 15.2%, 15.4%, 15.5%, 15.6%, 15.8%, 16%, 16.5%, 17%, 17.5%, 18%, 18.5%, 19%, 19.5%, or 20%. The percent change in peak width was 6%, 6.5%, 7%, 7.5%, 8%, 8.5%, 9%, 9.5%, 10%, 10.2%, 10.4%, 10.5%, 10.6%, 10.8%, 11%, 11.2%, 11.4%, 11.5%, 10.6%, 10.8%, 12%, 12.2%, 12.4%, 12.5%, 12.6%, 12.8%, 13%, 13.2%, 13.4%, 13. If it is greater than 5%, 13.6%, 13.8%, 14%, 14.2%, 14.4%, 14.5%, 14.6%, 14.8%, 15%, 15.2%, 15.4%, 15.5%, 15.6%, 15.8%, 16%, 16.5%, 17%, 17.5%, 18%, 18.5%, 19%, 19.5%, or 20%, a determination can be made that the column performance is unacceptable. The percent change in peak width was 6%, 6.5%, 7%, 7.5%, 8%, 8.5%, 9%, 9.5%, 10%, 10.2%, 10.4%, 10.5%, 10.6%, 10.8%, 11%, 11.2%, 11.4%, 11.5%, 10.6%, 10.8%, 12%, 12.2%, 12.4%, 12.5%, 12.6%, 12.8%, 13%, 13.2%, 13.4%, 13. If the difference is less than 0.5%, 13.6%, 13.8%, 14%, 14.2%, 14.4%, 14.5%, 14.6%, 14.8%, 15%, 15.2%, 15.4%, 15.5%, 15.6%, 15.8%, 16%, 16.5%, 17%, 17.5%, 18%, 18.5%, 19%, 19.5%, or 20%, a determination can be made that the column performance is acceptable.

[0127] If the SSP is a tailing factor, the reference levels are approximately 5%, 6%, 7%, 8%, 9%, 9.2%, 9.4%, 9.5%, 9.6%, 9.8%, 10%, 10.2%, 10.4%, 10.5%, 10.6%, 10.8%, 11%, 11.2%, 11.4%, 11.5%, 10.6%, 10.8%, 12%, 12.2%, 12.4%, 12.5%, 12.6%, 12.8%, 12.9%, 12.1%, 12.1%, 12.2%, 12.3%, 12.4%, 12.5%, 12.6 ... It can be 2.8%, 13%, 13.2%, 13.4%, 13.5%, 13.6%, 13.8%, 14%, 14.2%, 14.4%, 14.5%, 14.6%, 14.8%, 15%, 15.2%, 15.4%, 15.5%, 15.6%, 15.8%, 16%, 16.5%, 17%, 17.5%, 18%, 18.5%, 19%, 19.5%, or 20%. A determination that column performance is unacceptable is made when the percentage change in tailing factor is 5%, 6%, 7%, 8%, 9%, 9.2%, 9.4%, 9.5%, 9.6%, 9.8%, 10%, 10.2%, 10.4%, 10.5%, 10.6%, 10.8%, 11%, 11.2%, 11.4%, 11.5%, 10.6%, 10.8%, 12%, 12.2%, 12.4%, 12.5%, 12.6%, 13%, 14%, 15%, 16%, 17%, 18%, 19%, 20%, 21%, 22%, 23%, 24%, 25%, 26%, 27%, 28%, 29%, 30%, 31%, 32%, 33%, 34%, 35%, 36%, 37%, 38%, 39%, 40%, 41%, 42%, 43%, 44%, 45%, 46%, 47%, 48%, 49%, 50%, 51%, 52%, 53%, 54%, 55%, 56%, 57%, 58%, 59%, 60%, 61%, 62%, 63%, 64%, 65%, 66%, 67%, 68%, 69%, 70%, 71%, 72%, 73%, 74%, 75%, 76%, 77%, 78%, 79%, 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%, 100%, This can be done if it is greater than 2.8%, 13%, 13.2%, 13.4%, 13.5%, 13.6%, 13.8%, 14%, 14.2%, 14.4%, 14.5%, 14.6%, 14.8%, 15%, 15.2%, 15.4%, 15.5%, 15.6%, 15.8%, 16%, 16.5%, 17%, 17.5%, 18%, 18.5%, 19%, 19.5%, or 20%.A determination that column performance is acceptable is made when the percent change in tailing factor is 5%, 6%, 7%, 8%, 9%, 9.2%, 9.4%, 9.5%, 9.6%, 9.8%, 10%, 10.2%, 10.4%, 10.5%, 10.6%, 10.8%, 11%, 11.2%, 11.4%, 11.5%, 10.6%, 10.8%, 12%, 12.2%, 12.4%, 12.5%, 12.6%, This can be done if the following are true: 12.8%, 13%, 13.2%, 13.4%, 13.5%, 13.6%, 13.8%, 14%, 14.2%, 14.4%, 14.5%, 14.6%, 14.8%, 15%, 15.2%, 15.4%, 15.5%, 15.6%, 15.8%, 16%, 16.5%, 17%, 17.5%, 18%, 18.5%, 19%, 19.5%, or 20% or less.

[0128] When SSP is the asymmetry factor, the reference levels are approximately 7%, 7.5%, 8%, 8.5%, 9%, 9.5%, 10%, 10.5%, 11%, 11.5%, 12%, 12.5%, 13%, 13.2%, 13.4%, 13.5%, 13.6%, 13.8%, 14%, 14.2%, 14.4%, 14.5%, 14.6%, 14.8%, 15%, 15.2%, 15.4%, 15.5%, It can be 15.6%, 15.8%, 16%, 16.5%, 17%, 17.5%, 18%, 18.5%, 19%, 19.5%, 20%, 20.5%, 21%, 21.5%, 22%, 22.5%, 23%, 23.5%, 24%, 24.5%, 25%, 25.5%, 26%, 26.5%, 27%, 27.5%, 28%, 28.5%, 29%, 29.5%, or 30%. A determination that column performance is unacceptable is made when the percent change in asymmetry factor is 7%, 7.5%, 8%, 8.5%, 9%, 9.5%, 10%, 10.5%, 11%, 11.5%, 12%, 12.5%, 13%, 13.2%, 13.4%, 13.5%, 13.6%, 13.8%, 14%, 14.2%, 14.4%, 14.5%, 14.6%, 14.8%, 15%, 15.2%, 15.4%, 15.5%. %, 15.6%, 15.8%, 16%, 16.5%, 17%, 17.5%, 18%, 18.5%, 19%, 19.5%, 20%, 20.5%, 21%, 21.5%, 22%, 22.5%, 23%, 23.5%, 24%, 24.5%, 25%, 25.5%, 26%, 26.5%, 27%, 27.5%, 28%, 28.5%, 29%, 29.5%, or greater than 30%.A determination that column performance is acceptable is made when the percent change in asymmetry factor is 7%, 7.5%, 8%, 8.5%, 9%, 9.5%, 10%, 10.5%, 11%, 11.5%, 12%, 12.5%, 13%, 13.2%, 13.4%, 13.5%, 13.6%, 13.8%, 14%, 14.2%, 14.4%, 14.5%, 14.6%, 14.8%, 15%, 15.2%, 15.4%, 15.5%. %, 15.6%, 15.8%, 16%, 16.5%, 17%, 17.5%, 18%, 18.5%, 19%, 19.5%, 20%, 20.5%, 21%, 21.5%, 22%, 22.5%, 23%, 23.5%, 24%, 24.5%, 25%, 25.5%, 26%, 26.5%, 27%, 27.5%, 28%, 28.5%, 29%, 29.5%, or 30% or less.

[0129] If the SSP is the peak height, the reference levels are approximately -4%, -4.5%, -5%, -5.5%, -6%, -6.5%, -7%, -8%, -8.5%, -9%, -9.2%, -9.4%, -9.5%, -9.6%, -9.8%, -10%, -10.2%, -10.4%, -10.5%, -10.6%, -10.8%, -11%, -11.2%, -11.4%, -11.5%, -10.6%, -10.8%, -12%, -12.2%, -12.4%, -12.6%, -12.8%. The offset can be -1.5%, -12.6%, -12.8%, -13%, -13.2%, -13.4%, -13.5%, -13.6%, -13.8%, -14%, -14.2%, -14.4%, -14.5%, -14.6%, -14.8%, -15%, -15.2%, -15.4%, -15.5%, -15.6%, -15.8%, -16%, -16.5%, -17%, -17.5%, -18%, -18.5%, -19%, -19.5%, or -20%. Percent change in peak height was -4%, -4.5%, -5%, -5.5%, -6%, -6.5%, -7%, -8%, -8.5%, -9%, -9.2%, -9.4%, -9.5%, -9.6%, -9.8%, -10%, -10.2%, -10.4%, -10.5%, -10.6%, -10.8%, -11%, -11.2%, -11.4%, -11.5%, -10.6%, -10.8%, -12%, -12.2%, -12.4%, -12.5%, -12.6%, -12.8% , -13%, -13.2%, -13.4%, -13.5%, -13.6%, -13.8%, -14%, -14.2%, -14.4%, -14.5%, -14.6%, -14.8%, -15%, -15.2%, -15.4%, -15.5%, -15.6%, -15.8%, -16%, -16.5%, -17%, -17.5%, -18%, -18.5%, -19%, -19.5%, or -20%, a determination can be made that the column performance is unacceptable.A determination that column performance is acceptable is made when the percent change in peak height is -4%, -4.5%, -5%, -5.5%, -6%, -6.5%, -7%, -8%, -8.5%, -9%, -9.2%, -9.4%, -9.5%, -9.6%, -9.8%, -10%, -10.2%, -10.4%, -10.5%, -10.6%, -10.8%, -11%, -11.2%, -11.4%, -11.5%, -10.6%, -10.8%, -12%, -12.2%, -12.4%, -13%. This can be done if the rate is 12.5%, -12.6%, -12.8%, -13%, -13.2%, -3.4%, -13.5%, -13.6%, -13.8%, -14%, -14.2%, -14.4%, -14.5%, -14.6%, -14.8%, -15%, -15.2%, -15.4%, -15.5%, -15.6%, -15.8%, -16%, -16.5%, -17%, -17.5%, -18%, -18.5%, -19%, -19.5%, or -20% or more.

[0130] If the SSP is the degree of separation, the reference levels are approximately -4.5%, -5%, -5.5%, -6%, -6.5%, -7%, -8%, -8.5%, -9%, -9.2%, -9.4%, -9.5%, -9.6%, -9.8%, -10%, -10.2%, -10.4%, -10.5%, -10.6%, -10.8%, -11%, -11.2%, -11.4%, -11.5%, -10.6%, -10.8%, -12%, -12.2%, -12.4%, -12.5% , -12.6%, -12.8%, -13%, -13.2%, -3.4%, -13.5%, -13.6%, -13.8%, -14%, -14.2%, -14.4%, -14.5%, -14.6%, -14.8%, -15%, -15.2%, -15.4%, -15.5%, -15.6%, -15.8%, -16%, -16.5%, -17%, -17.5%, -18%, -18.5%, -19%, -19.5%, or -20%. The percent change in separation was -4.5%, -5%, -5.5%, -6%, -6.5%, -7%, -8%, -8.5%, -9%, -9.2%, -9.4%, -9.5%, -9.6%, -9.8%, -10%, -10.2%, -10.4%, -10.5%, -10.6%, -10.8%, -11%, -11.2%, -11.4%, -11.5%, -10.6%, -10.8%, -12%, -12.2%, -12.4%, -12.5%, -12.6%, -12.8%, -1 If the difference is less than 3%, -13.2%, 1-3.4%, -13.5%, -13.6%, -13.8%, -14%, -14.2%, -14.4%, -14.5%, -14.6%, -14.8%, -15%, -15.2%, -15.4%, -15.5%, -15.6%, -15.8%, -16%, -16.5%, -17%, -17.5%, -18%, -18.5%, -19%, -19.5%, or -20%, a determination can be made that the column performance is unacceptable.A determination that column performance is acceptable is made when the percent change in resolution is -4.5%, -5%, -5.5%, -6%, -6.5%, -7%, -8%, -8.5%, -9%, -9.2%, -9.4%, -9.5%, -9.6%, -9.8%, -10%, -10.2%, -10.4%, -10.5%, -10.6%, -10.8%, -11%, -11.2%, -11.4%, -11.5%, -10.6%, -10.8%, -12%, -12.2%, -12.4%, -12.6%. This can be done if the rate is 5%, -12.6%, -12.8%, -13%, -13.2%, -3.4%, -13.5%, -13.6%, -13.8%, -14%, -14.2%, -14.4%, -14.5%, -14.6%, -14.8%, -15%, -15.2%, -15.4%, -15.5%, -15.6%, -15.8%, -16%, -16.5%, -17%, -17.5%, -18%, -18.5%, -19%, -19.5%, or -20% or more.

[0131] When SSP is the number of theoretical plates, the reference levels are approximately -9%, -9.5%, -10%, -10.5%, -11%, -11.5%, -12%, -12.5%, -13%, -13.5%, -14%, -14.5%, -15%, -15.2%, -15.4%, -15.5%, -15.6%, -15.8%, -16%, -16.5%, -17%, -17.5%, -18%, -18.5%, -19%, -19.5%, -20%, -20.5%, -21%, -21.5%, It can be −22%, −22.5%, −23%, −23.5%, −24%, −24.5%, −25%, −25.5%, −26%, −26.5%, −27%, −27.5%, −28%, −28.5%, −29%, −29.5%, −30%, −30.5%, −31%, −31.5%, −32%, −32.5%, −33%, −33.5%, −34%, −34.5%, −35%, −35.5%, −36%, −37%, −38%, −39%, or −40%. The percent change in theoretical plate count was -9%, -9.5%, -10%, -10.5%, -11%, -11.5%, -12%, -12.5%, -13%, -13.5%, -14%, -14.5%, -15%, -15.2%, -15.4%, -15.5%, -15.6%, -15.8%, -16%, -16.5%, -17%, -17.5%, -18%, -18.5%, -19%, -19.5%, -20%, -20.5%, -21%, -21.5%, -22%, -22.5%, -23%, - If the difference is less than 23.5%, −24%, −24.5%, −25%, −25.5%, −26%, −26.5%, −27%, −27.5%, −28%, −28.5%, −29%, −29.5%, −30%, −30.5%, −31%, −31.5%, −32%, −32.5%, −33%, −33.5%, −34%, −34.5%, −35%, −35.5%, −36%, −37%, −38%, −39%, or −40%, a determination can be made that the performance of the column is unacceptable.A determination that column performance is acceptable is made when the percent change in theoretical plate number is -9%, -9.5%, -10%, -10.5%, -11%, -11.5%, -12%, -12.5%, -13%, -13.5%, -14%, -14.5%, -15%, -15.2%, -15.4%, -15.5%, -15.6%, -15.8%, -16%, -16.5%, -17%, -17.5%, -18%, -18.5%, -19%, -19.5%, -20%, -20.5%, -21%, and -21.5% , -22%, -22.5%, -23%, -23.5%, -24%, -24.5%, -25%, -25.5%, -26%, -26.5%, -27%, -27.5%, -28%, -28.5%, -29%, -29.5%, -30%, -30.5%, -31%, -31.5%, -32%, -32.5%, -33%, -33.5%, -34%, -34.5%, -35%, -35.5%, -36%, -37%, -38%, -39%, or -40% or more.

[0132] One or more SSP criteria can be established to evaluate column performance and identify column failures.

[0133] Column performance can be evaluated based on multiple SSPs. Certain SSPs may be more important than others when evaluating column performance and deciding whether to replace the column. The importance of SSPs in evaluating column performance can be ranked as provided in Table 1 below. [Table 1]

[0134] The method can include replacing the column or repacking the stationary phase particles of the column. The method can include replacing the column or repacking the stationary phase particles of the column after about 500 runs, 600 runs, 700 runs, 800 runs, 900 runs, 1000 runs, 1100 runs, 1150 runs, 1200 runs, 1250 runs, 1300 runs, 1350 runs, 1400 runs, 1450 runs, or 1500 runs. The column can be replaced or repacked after 500 to 1000 runs. The column can be replaced or repacked after about 1000 runs.

[0135] 2. Chromatography column The methods provided herein are applicable to media containing silica-based and polymer-based particles, including those with chemically modified surfaces. The chromatography columns can be used in chromatographic methods such as size-exclusion chromatography (SEC), reversed-phase liquid chromatography (RPLC), hydrophilic interaction liquid chromatography (HILIC), hydrophobic liquid chromatography (HIC), ion-exchange chromatography (IEX) (e.g., anion-exchange chromatography (AEX) and cation-exchange chromatography (CEX)), and affinity chromatography (AC).

[0136] Size exclusion chromatography (SEC) refers to a chromatographic method in which molecules in a solution are separated by their size, and sometimes molecular weight. This method is typically applied to large molecules or macromolecular complexes, such as proteins and industrial polymers. The stationary phase of a typical SEC column contains spherical beads with pores of specific sizes. Separation occurs when molecules of different sizes are included in or excluded from the pores within the matrix. Small molecules are able to enter the pores and thus slow their flow through the column, while large molecules do not enter the pores and elute in the void volume of the column. Two common types of separations performed by SEC are fractionation and desalting. In desalting, molecules of interest are larger than the size limit of the beads and elute in the void volume, while smaller molecules are retained in the pores. In fractionation, molecules of various molecular weights are separated within the stationary phase of the column.

[0137] Normal-phase chromatography historically uses unmodified silica-alumina resin; therefore, the stationary phase packed in the chromatography column is hydrophilic. The stationary phase particles can also be resins containing polar organic moieties, such as cyano and amino functional groups. Hydrophilic molecules in the mobile phase have a high affinity for the hydrophilic stationary phase and adsorb to the column packing. Elution of hydrophilic molecules adsorbed to the column packing requires the use of a more hydrophilic or polar solvent to move the adsorbed molecules toward the mobile phase.

[0138] Reversed-phase chromatography (RPC), also known as reversed-phase liquid chromatography (RPLC), is a method that uses a hydrophobic stationary phase to adsorb hydrophobic molecules from a polar (e.g., aqueous) mobile phase, allowing hydrophilic molecules to pass through first. A more hydrophobic solvent (e.g., a water-miscible organic solvent) is then used to elute the adsorbed molecules. Reversed-phase chromatography is essentially the reverse of normal-phase chromatography. A common type of resin for RPLC is a particle (also called a "solid support") covalently bonded to alkyl chains (such as octadecyl (C18), octadecyl (C8), and butyl (C4)), which form a hydrophobic surface for adsorbing hydrophobic molecules.

[0139] Hydrophilic interaction liquid chromatography (HILIC) is a method for separating polar compounds under high-performance liquid chromatography (RPLC). High-performance liquid chromatography (HPLC), also known as high-pressure liquid chromatography, is a technique that relies on a pump to pass a pressurized liquid solvent containing the sample mixture through a chromatography column filled with a solid stationary phase. Like normal-phase liquid chromatography, HILIC uses a conventional polar stationary phase, such as silica or resin bearing amino or cyano groups, but the mobile phase is typically a water-miscible polar organic solvent, which is more similar to that used in RPLC.

[0140] Hydrophobic liquid chromatography (HIC) is a chromatographic technique that separates mixtures based on hydrophobicity but operates under relatively mild conditions compared to RPLC. HIC stationary phases have weaker hydrophobic properties than RPLC, and the reduced polarity of the mobile phase for eluting adsorbed analytes is due to a reduced salt concentration. HIC is typically applied to protein separations because the milder mobile phase reduces the likelihood of protein unfolding and loss of biological activity.

[0141] Ion exchange chromatography (IEX) is a commonly used method for separating ions and polar molecules. It is often applied to discretely charged molecules, including proteins, nucleotides, and amino acids. The equilibrated stationary phase consists of ionizable functional groups to which molecules of interest in a mixture can bind as they pass through the column. The bound molecules are then eluted using an eluent containing a higher concentration of ions or an eluent that changes the pH of the column.

[0142] Anion exchange and cation exchange are two types of IEX. Cation exchange chromatography is used when the molecule of interest is positively charged (which is made possible by a pH lower than the molecule's isoelectric point) and the stationary phase is negatively charged. Anion exchange is used when the molecule of interest is negatively charged (which is made possible by a pH higher than the molecule's isoelectric point) and the stationary phase is positively charged.

[0143] Affinity chromatography (AC) is a method for separating biomolecules from a mixture based on highly specific binding interactions between the biomolecule and another substance. The binding partner (also called a "ligand") of a biomolecule of interest in the mixture is immobilized on a solid stationary phase, capturing the biomolecule of interest as the mobile phase moves through the column. A wash buffer is then applied to remove non-target biomolecules by disrupting weaker interactions with the stationary phase, while the biomolecule of interest remains bound. The target biomolecule can then be removed by applying an elution buffer that disrupts the interaction between the bound target biomolecule and the ligand.

[0144] The chromatography column is packed with a type of stationary phase particle selected from the group consisting of anion exchange chromatography stationary phase, cation exchange chromatography stationary phase, affinity or pseudo-affinity chromatography stationary phase, hydrophilic interaction liquid chromatography stationary phase, hydrophobic liquid chromatography stationary phase, reversed-phase liquid chromatography stationary phase, and size exclusion chromatography stationary phase (or any combination thereof). The chromatography stationary phase can be a multimodal (e.g., bimodal) chromatography stationary phase (e.g., a chromatography stationary phase having both anion exchange and hydrophobic interaction groups, or a chromatography stationary phase having both cation exchange and hydrophobic interaction groups).

[0145] Chromatography column particles are solid, insoluble particles modified with functional groups that have properties suitable for the intended chromatographic method. The functional groups are either covalently attached to the solid particles or are attached to the solid particles through non-covalent interactions.

[0146] The column particles that make up the stationary phase matrix are selected from the group consisting of silica-based particles or polymers (eg, agarose, cellulose, and polyacrylamide).

[0147] The column particles are modified with hydrophobic functional groups, which are alkyl chains such as octadecyl (C18), octyl (C8), and butyl (C4).

[0148] The column particle is modified with polar and hydrophilic functional groups.The polar functional groups that can be used to modify the column particle are well known in the art (for example, see Buszewski and Noga, Anal Bioanal Chem (2012) 402 (1): 231-247).The hydrophilic functional group is diol, cyano, amino, carboxylic acid, alkyl amide, amide, succinimide, polyethylene glycol, β-cyclodextrin, sugar, dipeptide, zwitterion, or sulfobetaine.

[0149] Column particles are modified with a ligand that specifically binds to a biomolecule of interest for use in affinity chromatography. Several types of ligand-biomolecule interactions used in affinity chromatography are well known and commonly used in the field of chromatography. The ligand is a substrate or substrate analog for use in capturing an enzyme. The ligand is an antibody or antigen-binding fragment for use in capturing an antigen. The ligand is an antigen for use in capturing an antibody or antigen-binding fragment. The ligand is a lectin for use in capturing a polysaccharide. The ligand is a nucleic acid for use in capturing a complementary oligonucleotide. The ligand is a hormone for use in capturing a receptor. The ligand is avidin for use in capturing biotin or a biotin-conjugated molecule. The ligand is calmodulin for use in capturing a calmodulin-binding partner. The ligand is glutathione for use in capturing a GST fusion protein. The ligand is protein A or protein G for use in capturing an immunoglobulin. The ligand includes a metal ion (e.g., Ni) for use in capturing a tagged peptide (e.g., a His-tagged peptide).

[0150] 3. Sample The sample to be purified or analyzed by column chromatography can contain biomolecules (or biological molecules).

[0151] The molecule targeted for purification or analysis by column chromatography can be a biomolecule. The biomolecule can be a nucleic acid, peptide / polypeptide / protein, carbohydrate, and / or lipid. The biomolecule can be a natural molecule. The biomolecule can be a synthetic molecule. The biomolecule can consist of a single molecular unit. The biomolecule can be a complex consisting of multiple subunits.

[0152] The target biomolecules for purification or analysis by column chromatography can be peptides, polypeptides, or proteins. Chromatographic methods such as SEC, HILIC, IEX, and affinity chromatography are often used to purify peptides, polypeptides, and proteins because the mobile phase can be mild and does not denature the structure of peptides, polypeptides, and proteins, thus preserving the biological function of the molecules.

[0153] The peptide, polypeptide, or protein can be a therapeutic protein.

[0154] The peptide, polypeptide, or protein can be an enzyme, cytokine, growth factor, hormone, interferon, interleukin, or anticoagulant.

[0155] The peptide, polypeptide, or protein can be an antibody or an antigen-binding fragment thereof. The antibody can be a polyclonal antibody, a monoclonal antibody, a bispecific antibody, a Fab fragment, a F(ab')2 fragment, a monospecific F(ab')2 fragment, a bispecific F(ab')2 fragment, a trispecific F(ab')2 fragment, a monovalent antibody, an scFv fragment, a diabody, a bispecific diabody, a trispecific diabody, an scFv-Fc, a minibody, an IgNAR, a v-NAR, an hcIgG, or a vhH.

[0156] A peptide, polypeptide, or protein can be a monomer. A peptide, polypeptide, or protein can be a multimer, such as a dimer, trimer, tetramer, and pentamer.

[0157] The peptide, polypeptide, or protein may have a molecular weight of about 1 to 3,000 kDa. The peptide, polypeptide, or protein may have a molecular weight of about 1 to 500 kDa. The peptide, polypeptide, or protein may have a molecular weight of about 1 to 10 kDa, 10 to 25 kDa, 25 to 45 kDa, 45 to 60 kDa, 60 to 75 kDa, 75 to 100 kDa, 100 to 125 kDa, 125 to 150 kDa, 150 to 175 kDa, 175 to 200 kDa, 200 to 225 kDa, 225 to 250 kDa, 250 to 300 kDa, 300 to 350 kDa, 350 to 400 kDa, 400 to 450 kDa, or 45 to 500 kDa.

[0158] Purification or analysis of target biomolecules by column chromatography can be nucleic acids. Nucleic acids can be polynucleotides, which are polymeric forms of nucleotides of any length, either ribonucleotides or deoxyribonucleotides, single-stranded or double-stranded. Target biomolecules can be DNA or RNA, genomic DNA, cDNA, DNA-RNA hybrids, or polymers containing purine and pyrimidine bases, other natural nucleotide bases, chemically or biochemically modified non-natural nucleotide bases, or derivatized nucleotide bases. Target biomolecules can be oligonucleotides, which are generally polynucleotides of about 5 to about 100 nucleotides of single-stranded or double-stranded DNA. Oligonucleotides, also known as "oligomers" or "oligos," can be isolated from genes or chemically synthesized. [Example]

[0159] Example 1 Research, materials, and methods Size exclusion chromatography (SEC) is a high-throughput analytical method for quantifying aggregate levels in solution. It separates different oligomerization states of monoclonal antibodies (mAbs) in a chromatography column at a constant flow rate in an isocratic environment. The column is typically packed with particles containing pores distributed across its surface. These pores allow molecules with smaller hydrodynamic sizes to pass through but exclude larger molecules. As smaller molecules spend more time migrating through the pores, they become separated from larger molecules as the column elutes. As molecules migrate through the non-particle region (i.e., void volume), their shape directly affects their transport rate. Molecules with smaller friction coefficients (e.g., spheres) migrate faster than molecules with larger friction coefficients (e.g., ellipsoids). SEC allows for the separation of mAbs and any aggregates in solution based on their size and shape.

[0160] Silica-based particles are commonly used in SEC columns, and the particles can be modified. Surface modification of silica particles involves several chemical reactions to generate covalent bonds between functional groups on the silica surface and silanol groups. It has been reported that the efficiency of surface modification can vary, sometimes leaving unmodified, isolated silanol groups. This can be a potential problem. Due to the inherent fragility of large-pore particles and repeated exposure to various analytical conditions (e.g., changes in mobile phase, sample matrix, and pressure), the lifetime of an SEC column is typically limited to fewer than 500 injections (S. Fekete et al., "Critical evaluation of fast size exclusion chromatographic separations of protein aggregates, applying sub-2 μm particles." J. Pharm. Biomed. Anal. 78-79 (2013) 141-149).

[0161] There are limited reports of monitoring the performance of SEC columns using biological molecules. The work described herein used an in-house generated immunoglobulin G1 (IgG1) mAb (mAb-1) to study column aging and develop a robust method for monitoring column performance.

[0162] material All chemicals used were analytical or sequencing-grade. Sodium phosphate monobasic monohydrate (NaH2PO4·H2O), sodium phosphate dibasic heptahydrate (Na2HPO4·7H2O), and sodium chloride crystals (NaCl) were purchased from VWR International (Radnor, PA, USA). Water purified by a Milli-Q Advantage A10 water purification system (Millipore, MA, USA) was used in all experiments. mAb-1 (IgG1 mAb) manufactured by Regeneron was used in this study.

[0163] Instruments and columns An ACQUITY UPLC Protein BEH SEC column (200 Å, 1.7 μm, 4.6 mm × 300 mm) and an ACQUITY UPLC Protein BEH SEC Guard column (200 Å, 1.7 μm, 4.6 mm × 30 mm) were purchased from Waters Corporation (Milford, MA, USA). A Waters ACQUITY UPLC H-Class PLUS system (Waters; MA, USA) was used for SEC separation. Seven lots of SEC columns (19 columns total) and two UPLC H-class systems were evaluated throughout the study. New columns were equilibrated with at least 10 column volumes of mobile phase or until a stable backpressure was achieved.

[0164] procedure The SEC mobile phase consisted of sodium phosphate buffer at pH 7.0 and sodium chloride. An isocratic elution mode was applied at a constant flow rate of 0.3 mL / min and ambient column temperature (23 ± 3 °C). Data were collected by UV absorbance at 280 nm. All samples had an injection volume of 0.2 μL. Each data set was collected from four consecutive injections and automatically integrated by Waters Empower 3 software without manual integration. SSPs, including USP resolution, USP theoretical plate count, USP tailing factor, asymmetry factor, retention time, peak height, peak area, area %, and peak width, were automatically obtained from Waters Empower 3 software. The data and generated models were analyzed using JMP15 software. The SSP equations are explained in the Results and Discussion section.

[0165] Example 2 Results and Discussion Experimental design and current control strategy A sample of mAb-1 was loaded onto the SEC column in four replicate injections once a week, and the resulting chromatograms were monitored for resolution, tailing factor, theoretical plate number, asymmetry factor, peak width, peak height, peak area, area %, and elution time. All new columns used in this study were adjusted to the desired flow rate and equilibrated to ensure stable chromatographic conditions. SSP was analyzed using monomeric mAb-1, which eluted between 8.0 and 8.8 min. Aggregates (i.e., high molecular weight species, HMWS) and fragments (i.e., low molecular weight species, LMWS) eluted between 6.5 and 8.0 min and between 8.6 and 11.0 min, respectively (Figure 2A). After 1,250 injections, the SEC chromatograms showed deterioration in column performance, including changes in the peak shape and retention time of the monomer, as well as a loss of resolution (Figure 2B).

[0166] To assess how the SSP changes over time, control charts for each SSP were generated using the average values ​​from four replicate injections over time (Figures 3A-3G). Two thresholds, designated the upper and lower control limits, were calculated from the average and moving range between data subgroups. For routine column maintenance, monitoring changes in area% typically determines column performance. Data outside the control limits indicates poor column performance and prompts the user to replace the SEC column. While monitoring area% on a control chart is a good technique for tracking column performance, it has low sensitivity for detecting gradual changes in the column over time.

[0167] Evaluation of the data collected during this study indicates that control charts based on area % can provide misleading interpretations of column performance. Figure 3A shows that the average area % over time was 97.7%, with all data falling within ±3 standard deviations of the mean and showing no trend. Meanwhile, other SSPs (e.g., resolution, tailing factor, number of theoretical plates, asymmetry factor, peak width, and elution time) show a steady increase or decrease in data from each successive time point over time, indicating column degradation. The SSP window, which determines the range of control limits, is a convenient tool for determining acceptable column performance criteria. Additionally, routine monitoring of indicators of column degradation, such as injection number and operating conditions (e.g., pH, buffer, temperature, particulates, flow rate), can help identify the underlying causes of column degradation over time.

[0168] Correlation between SSP and SEC column time course Monitoring selected SSPs on the control charts revealed that several parameters showed a clear correlation with the SEC column time course. For example, on a given column, the elution time of mAb-1 monomer consistently increased over time. To investigate this correlation, nine monitored SSPs were plotted against the injection number for each SEC column. Of the nine SSPs, seven were found to have a linear correlation with injection number, a measure or surrogate measure of column time course. The coefficients of determination (R) for the seven SSPs that showed correlation were: 2) values ​​were greater than 0.7. The analysis and implications of these SSPs are described below.

[0169] retention time Retention time is a measure of the time required for a molecule to pass through a separation system, from injection to detection. This simple and easily measured SSP tracks the column's consistency for each analytical run. Small changes in retention time are expected and are often due to slight changes in mobile phase composition or instrument settings. However, a steady trend of increasing retention time over time suggests column degradation. In Figure 4A, the monomer peak became later in retention time as the number of injections on the column increased. This is likely due to increased interactions between the eluting molecule and the column stationary phase. A strong, positive, linear correlation was observed between retention time and injection number.

[0170] Peak width and peak height As a column ages, the functional groups or silica-containing core of the stationary phase can deteriorate, increasing the level of nonspecific interactions with eluting molecules. This deterioration can alter the peak tailing and overall peak width of a given peak. In this study, the peak width at 5% of the monomer peak height was monitored for mAb-1. Figure 4B shows that the overall peak width increased with the number of injections. Peak height is the distance from the baseline of a peak to its apex. Figure 4C shows that peak height exhibits a negative linear relationship with the number of column injections. At a constant injection column load, the change in peak height can be attributed to the broadened peaks and asymmetric shape shown in Figure 2B.

[0171] Tailing Factor The tailing factor is calculated based on the USP tailing factor (T f ) is a measurement of peak tailing using

number

[0172] An ideal chromatographic peak on a new column has a Gaussian distribution with b slightly larger than a. As the column ages, the peak typically broadens at the tail end due to increased interactions between the eluting molecules and the column stationary phase, resulting in a T f Indeed, we observed such an increase in tailing on the monomer peak of mAb-1, resulting in an increase in T f There was a positive linear correlation between the number of injections and the number of injections (Fig. 4D).

[0173] Asymmetry coefficient Similar to the tailing factor, the asymmetry factor is a general measure of peak distortion. s ) can be used to assess peak tailing and peak fronting as an indicator of loss of column quality and is defined in Equation 2:

number

[0174] As a result, an aged column that causes peak tailing is s is greater than 1, but an aged column that causes peak fronting is A s is less than 1. Consistent with the trend of tailing coefficients, the A of mAb-1 monomer s gradually increased with the number of injections (Fig. 4E).

[0175] degree of separation Resolution is a measure for distinguishing two eluting peaks based on their retention time and peak width in a chromatogram. USP resolution (R s ) applied in this study and defined in Eq.

number

[0176] Figure 4F shows that the USP resolution decreased with increasing injection number, suggesting that the quality of the separation between the mAb-1 monomer and the LMWS decreases with column aging.

[0177] Theoretical Plate Number The number of theoretical plates is considered an important indicator of column efficiency. The USP number of theoretical plates (N) is applied in this study and is defined as Equation 4:

number

[0178] The USP theoretical plate numbers (Figure 4G) showed a decreasing trend across most columns as the number of injections increased. Generally, the lower the theoretical plate number of a column, the less efficient the separation.

[0179] This section described linear trends among SSPs and injection times across several columns. However, analysis of these relationships revealed that each column exhibited a unique slope and y-intercept. Therefore, a statistical model is needed to summarize the intercepts and slopes from all columns to shorten the analysis period and make it applicable to routine evaluation processes. Once established, this model can be used to efficiently classify SSPs and be utilized for screening and long-term control monitoring of column performance.

[0180] Example 3 Evaluation of column performance by statistically defined SSP In this study, 19 SEC columns were evaluated over a 48-week period. In Figures 4A-4G, each column is represented by a dashed or dotted line.

[0181] Seven SSPs (resolution, tailing factor, number of theoretical plates, asymmetry factor, peak width, peak height, and elution time) were tracked and found to be highly correlated with the number of injections, which can serve as indicators for estimating column performance and lifetime. A generalized linear model (GLM) was applied to analyze these SSPs collected from multiple columns. Instead of sequentially injecting the same sample onto a single column, multiple studies were performed to evaluate the impact of variability between column lots and provide more general conclusions regarding column lifetime. The proposed model is as follows:

number

number

[0182] The four models reveal increasing trends (indicated by solid lines) in the four SSPs, including elution time, peak width, asymmetry factor, and tailing factor (Figure 4A, Figure 4B, Figure 4D, Figure 4E). As the column ages, the stationary phase may lose functional groups, increasing the risk of exposing mAb-1 to silanol groups on the particle surface and thus increasing nonspecific interactions between the stationary phase and eluting molecules. The net result is that molecules move more slowly through the stationary phase, resulting in longer elution times. Furthermore, peak tailing and broadening occur when undesired interactions occur, making integration and quantification more difficult. As expected, increasing the number of injections leads to increases in elution time, tailing factor, asymmetry factor, and peak width. In Table 1, the number of injections and grouped column lots explained 94%, 81%, 83%, and 79% of the variance in retention time, peak width (at 5%), tailing factor, and asymmetry factor, respectively. [Table 2]

[0183] Based on data collected with GLM, mAb-1 elutes at approximately 8.2 minutes, with a tailing factor of 1.17 and an asymmetry factor of 1.27 at the beginning of the column's life. It is noteworthy that perfectly symmetrical peak shapes are rarely observed, and some degree of peak asymmetry is generally considered acceptable (e.g., tailing factor <1.3 and asymmetry factor <1.2). The rate of change (slope) of the tailing factor is 10.2% per 1000 injections (Figure 5). This means that a new column with an initial tailing factor of 1.16 is expected to reach a value of 1.3 in approximately 1100 injections, based on the model. Once the column reaches 1000 injections, the retention time and peak width are expected to increase by 2.3% and 12.2%, respectively (see Figures 4A, 4B, and 5).

[0184] In contrast to the four SSP parameters mentioned in the previous paragraph, peak height, resolution, and theoretical plate number show a decreasing trend with column aging (Figure 4C, Figure 4F, Figure 4G). As the column aged, the resolution between the monomer peak and the LMWS peak decreased, which may ultimately lead to inaccurate peak integration. Linear regression analysis showed an average 11.3% decrease in resolution per 1000 injections for the SEC column (Figure 5). Considering that the change in retention time (approximately 1 s per 1000 injections) was negligible, the decrease in theoretical plate number can be primarily attributed to an increase in peak width. As a result, the theoretical plate number (Table 1) showed a decreasing trend across most of the columns evaluated, decreasing by an average of 19.2% per 1000 injections (Figure 5). The decrease in theoretical plate number suggests that peak broadening is caused by a decrease in column efficiency. [Table 3] [Table 4] [Table 5] [Table 6] [Table 7] [Table 8] [Table 9] [Table 10]

[0185] Example 4 Biologics Manufacturing Careful examination of SSPs using control charts and general linear models before and throughout routine analysis has revealed that SSPs are important tools for detecting column degradation over time. Monitoring SSP changes over time helps establish realistic, historically based acceptance criteria for determining when a column should be replaced. Another approach is to use the percent change and estimated intercept obtained from a linear regression between SSP and injection number to predict column degradation rates over time or to screen and evaluate the initial performance of new columns. Replicate injections of in-house test standards onto multiple columns and the establishment of long-term internal control criteria for SSPs ensure consistent analytical results, leading to faster identification of column failures and higher data quality.

[0186] The above methods can be used to monitor column performance for the production of a range of biologics, including, but not limited to, protein-based therapeutics (e.g., monoclonal antibody-based therapeutics and receptor Fc fusion proteins), oligonucleotide-based therapeutics (e.g., antisense, small interfering RNA, aptamers), carbohydrate-based therapeutics (e.g., heparin), and lipid-based drug delivery products.

[0187] Protein-based therapeutics include, but are not limited to, the production of biologics and pharmaceuticals. Protein-based therapeutics can include any protein, polypeptide, or peptide with any amino acid sequence desired to be produced. These include, but are not limited to, viral proteins, bacterial proteins, fungal proteins, plant proteins, and animal (including human) proteins. Protein types can include, but are not limited to, antibodies, receptors, Fc-containing proteins, trap proteins, enzymes, factors, inhibitors, activators, ligands, reporter proteins, selection proteins, protein hormones, protein toxins, structural proteins, storage proteins, transport proteins, neurotransmitters, and contractile proteins. Derivatives, components, chains, and fragments of the above are also included. Sequences can be natural, semisynthetic, or synthetic.

[0188] Nucleic acid and nuclease therapeutics, such as RNAi, siRNA, and CRISPR / Cas9, are also biological therapeutics, including the C5 siRNA therapeutic cemdisiran, the RNAi ALN-APP for early-onset Alzheimer's disease, RNAi for nonalcoholic steatohepatitis, and CRISPR / Cas9 for transthyretin amyloidosis.

[0189] For example, for antibody production, the present invention is amendable for research and production applications for diagnostics and therapeutics based on all major antibody classes: IgG, IgA, IgM, IgD, and IgE. IgG is a preferred class, including IgG1 (including IgG1λ and IgG1κ), IgG2, IgG3, and IgG4. Further examples of antibodies include human antibodies, humanized antibodies, chimeric antibodies, monoclonal antibodies, multispecific antibodies, bispecific antibodies, antigen-binding antibody fragments, single-chain antibodies, diabodies, triabodies, or tetrabodies, Fab or F(ab')2 fragments, IgD antibodies, IgE antibodies, IgM antibodies, IgG antibodies, IgG1 antibodies, IgG2 antibodies, IgG3 antibodies, or IgG4 antibodies. The antibody can be an IgG1 antibody. The antibody can be an IgG2 antibody. The antibody can be an IgG4 antibody. The antibody can be a chimeric IgG2 / IgG4 antibody. The antibody can be a chimeric IgG2 / IgG1 antibody. The antibody can be a chimeric IgG2 / IgG1 / IgG4 antibody. Derivatives, components, domains, chains, and fragments of the above are also included. Further examples of antibodies include human antibodies, humanized antibodies, chimeric antibodies, monoclonal antibodies, multispecific antibodies, bispecific antibodies, antigen-binding antibody fragments, single-chain antibodies, diabodies, triabodies, or tetrabodies, Fab or F(ab')2 fragments, IgD antibodies, IgE antibodies, IgM antibodies, IgG antibodies, IgG1 antibodies, IgG2 antibodies, IgG3 antibodies, or IgG4 antibodies. The antibody can be an IgG1 antibody. The antibody can be an IgG2 antibody. The antibody can be an IgG4 antibody. The antibody can be a chimeric IgG2 / IgG4 antibody. The antibody can be a chimeric IgG2 / IgG1 antibody. The antibody can be a chimeric IgG2 / IgG1 / IgG4 antibody.

[0190] The antibody may be an anti-programmed cell death 1 antibody (e.g., an anti-PD1 antibody described in U.S. Patent Application Publication No. US2015 / 0203579A1), an anti-programmed cell death ligand-1 antibody (e.g., an anti-PD-L1 antibody described in U.S. Patent Application Publication No. US2015 / 0203580A1), an anti-Dll4 antibody, an anti-angiopoietin-2 antibody (e.g., an anti-ANG2 antibody described in U.S. Patent No. 9,402,898), an anti-angiopoietin-like 3 antibody (e.g., an anti-AngP antibody described in U.S. Patent No. 9,018,356), or an anti-programmed cell death ligand-1 antibody (e.g., an anti-PD-L1 antibody described in U.S. Patent Application Publication No. US2015 / 0203580A1). tl3 antibody), anti-platelet derived growth factor receptor antibody (e.g., anti-PDGFR antibody described in U.S. Pat. No. 9,265,827), anti-Erb3 antibody, anti-prolactin receptor antibody (e.g., anti-PRLR antibody described in U.S. Pat. No. 9,302,015), anti-complement 5 antibody (e.g., anti-C5 antibody described in U.S. Patent Application Publication No. US2015 / 0313194A1), anti-TNF antibody, anti-epidermal growth factor receptor antibody (e.g., anti-EGFR antibody described in U.S. Pat. No. 9,132,192 or U.S. Pat. No. Antibodies such as anti-EGFRvIII antibodies described in U.S. Patent Application Publication No. US2015 / 0259423A1, anti-proprotein convertase subtilisin kexin-9 antibodies (e.g., anti-PCSK9 antibodies described in U.S. Patent Application Publication No. US2014 / 0044730A1), anti-growth differentiation factor-8 antibodies (e.g., anti-GDF8 antibodies, also known as anti-myostatin antibodies, described in U.S. Patent Application Publication No. US8,871,209 or U.S. Patent Application Publication No. US2014 / 0044730A1), anti-glucagon receptor (e.g., anti-EGFRvIII antibodies described in U.S. Patent Application Publication No. US2015 / 0259423A1), ... Anti-GCGR antibodies described in U.S. Patent Application Publication No. US2015 / 0337045A1 or U.S. Patent Application Publication No. US2016 / 0075778A1), anti-VEGF antibodies, anti-IL1R antibodies, interleukin 4 receptor antibodies (e.g., anti-IL4R antibodies described in U.S. Patent Application Publication No. US2014 / 0271681A1 or U.S. Patent No. 8,735,095 or U.S. Patent No. 8,945,559), anti-interleukin 6 receptor antibodies (e.g., U.S. Patent No. 7,582,298, U.S. Patent No. 8,043,617, U.S. Patent No. 9,173,880), anti-IL1 antibodies, anti-IL2 antibodies, anti-IL3 antibodies, anti-IL4 antibodies, anti-IL5 antibodies, anti-IL6 antibodies, anti-IL7 antibodies, anti-interleukin 33 (e.g., the anti-IL33 antibodies described in U.S. Patent Application Publication No. US2014 / 0271658A1 or US2014 / 0271642A1), anti-respiratory syncytial virus antibodies (e.g., the anti-RSV antibodies described in U.S. Patent Application Publication No. US2014 / 0271653A1), anti-surface antigen cluster 3 antibodies (e.g., the anti-IL6R antibodies described in U.S. Patent Application Publication No. US2014 / 0271658A1 or US2014 / 0271642A1), anti-IL6R ...), anti-IL6R antibodies (e.g., the anti-IL6R antibodies described in U.S. Patent Application Publication No. US2014 / 0271658A1), anti-IL6R antibodies (e.g., the anti-IL6R antibodies described in U.S. Patent Application Publication No. US2014 / 0271658A1), anti-IL6R antibodies (e.g., the anti-IL6R antibodies described in U.S. Patent Application Publication No. US2014 / 0271642A1), anti-IL6R antibodies (e.g., the anti-IL6R antibodies described in U.S. Patent Application Publication No. US2014 / 02 Nos. 014 / 0088295A1 and 0266966A1, and U.S. Application No. 62 / 222,605), anti-Cluster of Differentiation (C20) antibodies (e.g., anti-CD20 antibodies described in U.S. Patent Application Publication Nos. US2014 / 0088295A1 and 0266966A1, and U.S. Patent No. 7,879,984), anti-CD19 antibodies, anti-CD28 antibodies, anti-Cluster of Differentiation (C48) antibodies (e.g., anti-CD48 antibodies described in U.S. Patent No. 9,228,014), anti-Fel d1 antibodies (e.g., as described in U.S. Patent Application Publication No. US2015 / 0337029A1), anti-Middle East respiratory syndrome virus (e.g., anti-MERS antibodies described in U.S. Patent Application Publication No. US2015 / 0337029A1), anti-Ebola virus antibodies (e.g., as described in U.S. Patent Application Publication No. US2016 / 0215040), anti-Zika virus antibodies, anti-lymphocyte activation gene 3 antibodies (e.g., anti-LAG3 antibodies or anti-CD223 antibodies), anti-nerve growth factor antibodies (e.g., as described in U.S. Patent Application Publication No. US2016 / 0017029, and U.S. Patent Nos. 8,309,088 and 9,353,176), and anti-activin A antibodies. In some embodiments, the bispecific antibody is selected from the group consisting of anti-CD3 x anti-CD20 bispecific antibodies (as described in U.S. Patent Application Publication Nos. US2014 / 0088295A1 and US2015 / 0266966A1), anti-CD3 x anti-mucin 16 bispecific antibodies (e.g., anti-CD3 x anti-Muc16 bispecific antibodies), and anti-CD3 x anti-prostate specific membrane antigen bispecific antibodies (e.g., anti-CD3 x anti-PSMA bispecific antibodies). See also U.S. Patent Publication No. US2019 / 0285580A1. Also included are MetxMet antibodies, agonist antibodies against NPR1, LepR agonist antibodies, BCMAxCD3 antibodies, MUC16xCD28 antibodies, GITR antibodies, IL-2Rg antibodies, EGFRxCD28 antibodies, Factor XI antibodies, antibodies against SARS-CoC-2 variants, Fel d 1 multi-antibody therapy, and Bet v 1 multi-antibody therapy. Derivatives, components, domains, chains, and fragments of the above are also included.

[0191] Exemplary antibodies produced according to the present invention include alirocumab, atortivimab, maftivimab, odesivimab, odesivimab-ebgn, casirivimab, imdevimab, cemiplimab, semprimab-rwlc, dupilumab, evinacumab, evinacumab-dgnb, fasinumab, fianlimab, galetusumab, itepekimab, nesbacumab, odrononextamab, pozelimab, sarilumab, trevoglumab, and linucumab.

[0192] Additional exemplary antibodies include ravulizumab-cwvz, abciximab, adalimumab, adalimumab-atto, ado-trastuzumab, alemtuzumab, atezolizumab, avelumab, basiliximab, belimumab, benralizumab, bevacizumab, bezlotoxumab, blinatumomab, brentuximab vedotin, brodalumab, canakinumab, capromab pendetide, certolizumab pegol, cetuximab, denosumab, dinutuximab, durvalumab, eculizumab, elotuzumab, emicizumab-kxwh, entansin alirocumab, evolocumab, golimumab, gsel These include cumab, ibritumomab tiuxetan, idarucizumab, infliximab, infliximab-abda, infliximab-dyyb, ipilimumab, ixekizumab, mepolizumab, necitumumab, nivolumab, obilutoxaximab, obinutuzumab, ocrelizumab, ofatumumab, olaratumab, omalizumab, panitumumab, pembrolizumab, pertuzumab, ramucirumab, ranibizumab, raxibacumab, reslizumab, rinucumab, rituximab, secukinumab, siltuximab, tocilizumab, trastuzumab, ustekinumab, and vedolizumab.

[0193] The present invention is also suitable for producing other molecules, including fusion proteins. Preferred fusion proteins include receptor-Fc fusion proteins, such as certain trap proteins. The protein of interest can be a recombinant protein (e.g., an Fc fusion protein) containing an Fc portion and another domain. The Fc fusion protein can be a receptor-Fc fusion protein containing one or more extracellular domains of a receptor linked to the Fc portion. The Fc portion includes a hinge region followed by the CH2 and CH3 domains of IgG. Receptor-Fc fusion proteins contain two or more different receptor chains that bind to either a single ligand or multiple ligands. For example, the Fc fusion protein is a TRAP protein, such as IL-1 TRAP (e.g., rilonacept, comprising the IL-1RAcP ligand binding domain fused to the IL-1R1 extracellular domain fused to the Fc of hIgG1; see U.S. Patent No. 6,927,044), or VEGF TRAP (e.g., aflibercept or div-aflibercept, comprising the Ig domain 2 of the VEGF receptor Flt1 fused to the Ig domain 3 of the VEGF receptor Flk1 fused to the Fc of hIgG1; see U.S. Patent Nos. 7,087,411 and 7,279,159).The Fc fusion protein can also be an ScFv-Fc fusion protein, which comprises one or more antigen-binding domains of an antibody, such as a variable heavy chain fragment and a variable light chain fragment, bound to an Fc portion.The above-mentioned derivatives, components, domains, chains, and fragments are also included.

[0194] Other proteins lacking the Fc portion, such as recombinantly produced enzymes and mini-traps, can also be produced according to the present invention. Mini-traps are trap proteins that use a multimerization component (MC) instead of the Fc portion, as disclosed in U.S. Patent Nos. 7,279,159 and 7,087,411. Derivatives, components, domains, chains, and fragments of the above are also included.

[0195] The present invention can also be employed in the production of recombinantly produced proteins, such as viral proteins (e.g., adenovirus and adeno-associated virus (AAV) proteins), bacterial proteins, and eukaryotic proteins. Additionally, the present invention can be employed in the production of viruses and viral vectors, such as parvoviruses, dependoviruses, lentiviruses, herpesviruses, adenoviruses, AAVs, and poxviruses.

[0196] The present invention is also applicable to the manufacture of biosimilar products. Biosimilar products, often referred to as follow-on products, are defined in various ways depending on the jurisdiction but typically share common characteristics compared to a previously approved biological product in that jurisdiction, referred to as the "reference product." According to the World Health Organization, a biosimilar product ("biosimilar") is a biotherapy product that is similar in quality, safety, and effectiveness to an already approved reference biotherapy product and is currently used in many countries, including the Philippines.

[0197] In the United States, biosimilars are currently defined as: (A) biological products that are highly similar to the reference product, despite minor variations in clinically inactive ingredients, and (B) there are no clinically meaningful differences between the biological product and the reference product in terms of product safety, purity, and efficacy. In the United States, biosimilars are interchangeable products or products that can be substituted for the previous product without the intervention of the healthcare professional who prescribed the previous product. In the European Union, biosimilars are currently defined as biological products that are highly similar to another biological product already approved in the EU (called the "reference product") in terms of structure, biological activity and efficacy, safety, and immunogenicity profile (the inherent ability of proteins and other biological products to elicit an immune response). Russia follows these guidelines. In China, biosimilars currently refer to biological products that contain the same active substances as the original biological drug, are similar in quality, safety, and efficacy to the original biological drug, and have no clinically meaningful differences. In Japan, biosimilars are currently defined as products that are bioequivalent / equivalent in quality, safety, and efficacy to the reference product already approved in Japan. In India, biosimilars are currently referred to as "similar biological products," which are similar in quality, safety, and efficacy to an approved reference biological product based on comparability. In Australia, biosimilar medicines are currently very similar versions of reference biological products. In Mexico, Colombia, and Brazil, biosimilars are currently biotherapeutic products similar in quality, safety, and efficacy to an already approved reference product. In Argentina, biosimilars are currently derived from an original product (comparator) with common characteristics. In Singapore, biosimilars are currently biotherapeutic products similar in physicochemical properties, biological activity, safety, and efficacy to an existing biologic product registered in Singapore. In Malaysia, biosimilars are currently new biologic medicines developed to be similar in quality, safety, and efficacy to an already registered, established drug product.In Canada, a biosimilar is a biological drug that is highly similar to a biological drug already approved for sale. In South Africa, a biosimilar is a biological drug developed to be similar to a biological drug already approved for human use. Biosimilars and their synonyms under these and any revised definitions are within the scope of this invention.

[0198] It should be understood that the description, specific examples, and data are given by way of illustration and are not intended to limit the invention. Various changes and modifications within the invention, including combinations of features both in whole and in part, will become apparent to those skilled in the art from the discussion, disclosure, and data contained herein and are therefore considered part of the invention.

Claims

1. 1. A method of operating a chromatography column, comprising: running a generalized linear model (GLM) on a set of values ​​of system suitability parameters (SSPs), the set of values ​​of the SSPs being obtained from an initial run of an analyte through the column and one or more subsequent runs.

2. 2. The method of claim 1, wherein the slope of the linear regression line generated by the GLM indicates the performance of the column compared to the initial state of the column during the first run.

3. 10. A method according to any one of the preceding claims, wherein the method comprises measuring the value of the SSP in the first run and in subsequent runs.

4. 10. The method of any one of the preceding claims, wherein the slope of the linear regression line indicates the rate of column degradation or column aging.

5. The SSP is a) retention time; b) peak height and / or peak width; c) the tailing factor; d) asymmetry coefficient; e) degree of separation; f) number of theoretical plates; 10. The method of any one of the preceding claims, selected from the group consisting of:

6. 10. A method according to any one of the preceding claims, comprising making a determination that the performance of the column is acceptable if the set of values ​​of the SSP fits a linear model.

7. 6. The method of any one of claims 1 to 5, comprising making a determination that the performance of the column is unacceptable if the set of values ​​of the SSP does not fit a linear model.

8. The method of claim 7 , wherein the set of values ​​of the SSP is better fitted to an exponential model than a linear model.

9. The generalized linear model has the following formula: [Equation 1] wherein x １ is the number of runs, [Equation 2] is x １ is the estimated SSP value for the th run, and β ０ is the estimated mean intercept, and β １ is the estimated slope of the linear regression line, and β ２ x ２ is the estimated correction for variation between columns from different lots, and β ０ and β １ are regression coefficients calculated to minimize the sum of squared residuals, and optionally, the term β ２ x ２ 10. The method of any one of the preceding claims, wherein is removed from the GLM equation.

10. R-squared (R ２ 10. The method of claim 9, further comprising determining a .times. ...

11. The R ２ 11. The method of claim 10, comprising making a determination that the performance of the column is unacceptable if the value is less than a predetermined threshold.

12. The method of claim 11 , wherein the predetermined threshold is 0.

7.

13. 10. The method of any one of the preceding claims, further comprising replacing the column or repacking the stationary phase particles of the column.

14. 1. A method for monitoring a column, comprising: running a generalized linear model (GLM) on a set of values ​​of system suitability parameters (SSPs), the set of values ​​of the SSPs being obtained from an initial run of an analyte through the column and one or more subsequent runs.

15. 15. The method of claim 14, wherein the slope of the linear regression line generated by the GLM indicates the performance of the column compared to the initial state of the column during the first run.

16. 16. The method of claim 14 or 15, wherein the method comprises measuring the value of the SSP in the initial run and in subsequent runs.

17. 17. The method of any one of claims 14 to 16, wherein the slope of the linear regression line indicates the rate of column degradation or the rate of column aging.

18. The SSP is a) retention time; b) peak height and / or peak width; c) the tailing factor; d) asymmetry coefficient; e) degree of separation; f) number of theoretical plates; or any combination thereof.

19. 19. The method of any one of claims 14 to 18, comprising making a determination that the performance of the column is acceptable if the set of values ​​of the SSP fits a linear model.

20. 19. The method of any one of claims 14 to 18, comprising making a determination that the performance of the column is unacceptable if the set of values ​​of the SSP does not fit a linear model.

21. 21. The method of claim 20, wherein the set of values ​​of the SSP is better fitted to an exponential model than a linear model.

22. The generalized linear model is [Equation 3] where x １ is the number of runs, [Equation 4] is x １ is the estimated SSP value for the th run, and β ０ is the estimated mean intercept, and β １ is the estimated slope of the linear regression line, and β ２ x ２ is the estimated correction for variation between columns from different lots, and β ０ and β １ are regression coefficients calculated to minimize the sum of squared residuals, and optionally, the term β ２ x ２ The method of any one of claims 14 to 21, wherein is removed from the GLM equation.

23. R-squared (R ２ 23. The method of claim 22, further comprising determining a .times. ...

24. The R ２ 24. The method of claim 23, comprising making a determination that the performance of the column is unacceptable if the value is less than a predetermined threshold.

25. 25. The method of claim 24, wherein the predetermined threshold is 0.

7.

26. The method of any one of claims 14 to 25, further comprising replacing the column or repacking the stationary phase particles of the column.

27. A method of operating a chromatography column, comprising determining the percent change in SSP between an initial run of an analyte through the column and a subsequent run.

28. The SSP is a) retention time; b) peak height and / or peak width; c) the tailing factor; d) asymmetry coefficient; e) degree of separation; f) number of theoretical plates; or any combination thereof.

29. 29. The method of claim 27 or 28, wherein a positive percent change in retention time, peak width, and / or tailing factor indicates a decrease in column performance.

30. 29. The method of claim 27 or 28, wherein a negative percent change in peak height, resolution, and / or number of theoretical plates indicates a decrease in column performance.

31. 31. The method of any one of claims 27 to 30, comprising making a determination that the performance of the column is unacceptable if the percent change in the SSP exceeds a reference level.

32. The percent change in the SSP over a reference level is: a) when the SSP is retention time, the percent change is greater than 2.3%; b) if the SSP is a peak width, the percent change is greater than 12%; c) if the SSP is a tailing factor, the percent change is greater than 10%; d) if the SSP is an asymmetry coefficient, the percent change is greater than 15.75%; e) if the SSP is a peak height, the percent change is less than −9.8%; f) if the SSP is a resolution, the percent change is less than −10.5%, and g) when the SSP is in theoretical plates, the percent change is less than -18.5%.

33. 31. The method of any one of claims 27 to 30, further comprising determining that the performance of the column is acceptable and continuing to use the column.

34. 34. The method of claim 33, wherein the determination that the performance of the column is acceptable is made if the percent change in the SSP is equal to or greater than a reference level.

35. the percent change in the SSP is greater than or equal to a reference level; a) when the SSP is retention time, the percent change is 2.3% or less; b) if the SSP is a peak width, the percent change is 12% or less; c) if the SSP is a tailing factor, the percent change is 10% or less; d) if the SSP is an asymmetry factor, the percent change is 15.75% or less; e) if the SSP is peak height, the percent change is -9.8% or greater; f) if the SSP is a resolution, the percent change is −10.5% or greater; and g) when the SSP is in theoretical plates, the percent change is -18.5% or greater.

36. 36. The method of any one of claims 27 to 35, further comprising replacing the column or repacking the stationary phase particles of the column.

37. A method of monitoring a chromatography column, comprising determining the percent change in SSP between an initial run of an analyte through the column and a subsequent run.

38. The SSP is a) retention time; b) peak height and / or peak width; c) the tailing factor; d) asymmetry coefficient; e) degree of separation; f) number of theoretical plates; or any combination thereof.

39. 39. The method of claim 37 or 38, wherein a positive percent change in retention time, peak width, and / or tailing factor indicates a decrease in column performance.

40. 39. The method of claim 37 or 38, wherein a negative percent change in peak height, resolution, and / or number of theoretical plates indicates a decrease in column performance.

41. 41. The method of any one of claims 37 to 40, comprising making a determination that the performance of the column is unacceptable if the percent change in the SSP exceeds a reference level.

42. The percent change in the SSP over a reference level is: a) when the SSP is retention time, the percent change is greater than 2.3%; b) if the SSP is a peak width, the percent change is greater than 12%; c) if the SSP is a tailing factor, the percent change is greater than 10%; d) if the SSP is an asymmetry coefficient, the percent change is greater than 15.75%; e) if the SSP is a peak height, the percent change is less than −9.8%; f) if the SSP is a resolution, the percent change is less than −10.5%, and g) when the SSP is in terms of theoretical plates, the percent change is less than -18.5%.

43. 41. The method of any one of claims 37 to 40, comprising making a determination that the performance of the column is acceptable and continuing to use the column.

44. 44. The method of claim 43, wherein the determination that the performance of the column is acceptable is made if the percent change in the SSP is greater than or equal to a reference level.

45. the percent change in the SSP is greater than or equal to a reference level; a) when the SSP is retention time, the percent change is 2.3% or less; b) if the SSP is a peak width, the percent change is 12% or less; c) if the SSP is a tailing factor, the percent change is 10% or less; d) if the SSP is an asymmetry factor, the percent change is 15.75% or less; e) if the SSP is peak height, the percent change is -9.8% or greater; f) if the SSP is a resolution, the percent change is −10.5% or greater; and g) when the SSP is in theoretical plates, the percent change is -18.5% or greater.

46. 46. ​​The method of any one of claims 37 to 45, further comprising replacing the column or repacking the stationary phase particles of the column.

47. 10. The method of any one of the preceding claims, wherein the column comprises silica-based particles or polymer-based materials.

48. 48. The method of claim 47, wherein the surface of the particle is chemically modified.

49. The chromatography a) Size Exclusion Chromatography (SEC); b) reversed-phase liquid chromatography (RPLC); c) Hydrophilic Interaction Liquid Chromatography (HILIC); d) Hydrophobic Liquid Chromatography (HIC); e) ion exchange chromatography (IEX), and 6. The method according to any one of the preceding claims, wherein the method is selected from the group consisting of: f) affinity chromatography (AC).

50. 50. The method of claim 49, wherein the ion exchange chromatography (IEX) is anion exchange chromatography (AEX) or cation exchange chromatography (CEX).

51. 10. The method of any one of the preceding claims, wherein the chromatography column is a silica-based SEC column.

52. 10. The method of any one of the preceding claims, wherein the analyte is a biomolecule.

53. 53. The method of claim 52, wherein the biomolecule is selected from the group consisting of a protein, a nucleic acid, a carbohydrate, and a lipid.

54. 54. The method of claim 53, wherein the protein is selected from the group consisting of an antibody, an enzyme, a cytokine, a growth factor, a hormone, an interferon, an interleukin, or an anticoagulant.

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