Methods of detecting host cell proteins

Abstract

The disclosure relates to methods of detecting Host Cell Proteins (HCPs) in biopharmaceutical samples containing a drug product. More specifically, the disclosure relates to methods of assaying HCPs in biopharmaceutical samples using enzymatic digestion protocols, liquid chromatography (LC) gradients, immunoaffinity capture protocols, and High-Resolution Mass Spectrometry (HRMS) to enhance the recovery, detection, and profiling of HCPs, which can impact the efficacy, shelf-life, and therapeutic response of drug products.

Description

METHODS OF DETECTING HOST CELL PROTEINSCROSS-REFERENCE TO RELATED APPLICATION

[0001] This application claims the benefit of priority of Indian Provisional Application No. 202421090896, filed November 22, 2024, which is incorporated herein by reference in its entirety.FIELD OF THE DISCLOSURE

[0002] The disclosure relates to methods of detecting Host Cell Proteins (HCPs) in biopharmaceutical samples containing a drug product. More specifically, the disclosure relates to methods of assaying HCPs in biopharmaceutical samples using enzymatic digestion protocols, liquid chromatography (LC) gradients, immunoaffinity capture protocols, and High-Resolution Mass Spectrometry (HRMS) to enhance the recovery, detection, and profiling of HCPs, which can impact the efficacy, shelf-life, and therapeutic response of drug products.BACKGROUND OF THE DISCLOSURE

[0003] Recombinant DNA technology is used to produce proteins in amounts that allow for use in a spectrum of therapeutic applications. Host Cell Proteins (HCPs) are impurities derived from the expression system used in production of recombinant therapeutic proteins and have diverse physicochemical properties. Typically originating from the host organism (e.g., bacteria, yeast, or mammalian cells), these proteins are byproducts of cellular processes and are often retained at low levels in the final biologic product.

[0004] Some HCPs are considered high-risk HCPs and include those that are immunogenic and enzymatically active with the potential to degrade either product molecules or excipients used in formulation. Additionally, certain HCPs may interact directly with the therapeutic protein, leading to aggregation or other modifications such as proteolytic degradation that reduce efficacy and increase immunogenicity risks. Hence, HCPs are considered as a critical quality attribute (CQA) and therefore need to be monitored while making protein manufacturing process changes.

[0005] Improvements in antibody purity can be achieved by culture condition optimizations. A change in sample analysis can have an adverse impact on high-risk HCP profile, e.g., changes in HCP screening workflow detection and elimination of reactive HCPs while reducing aggregates tothe therapeutic antibody product. Hence, it is important to develop a process with the objective to eliminate high-risk HCPs.

[0006] The pharmaceutical industry has a need for improved methods of recovering, detecting, and profiling HCPs in biopharmaceutical samples containing a drug product.SUMMARY

[0007] The disclosure relates to methods of analyzing Host Cell Proteins (HCPs) in biopharmaceutical samples containing a drug product. In general, the disclosure relates to methods of assaying HCPs in biopharmaceutical samples using enzymatic digestion protocols, liquid chromatography (LC) gradients, immunoaffinity capture protocols, and High-Resolution Mass Spectrometry (HRMS) to enhance the recovery, detection, and profiling of HCPs, which can impact the efficacy, shelf-life, and therapeutic response of drug products.

[0008] Provided herein is a method of detecting host cell proteins (HCPs) in a biopharmaceutical sample, the method comprising: (a) subjecting proteins in the biopharmaceutical sample to enzymatic digestion; (b) eluting HCPs from the biopharmaceutical sample using a liquid chromatography (LC) gradient; (c) concentrating the eluted HCPs by immunoaffinity capture to produce an enriched HCP fraction; and (d) detecting HCPs in the enriched HCP fraction using High-Resolution Mass Spectrometry (HRMS).

[0009] These and other features and advantages of the present disclosure will be more fully understood from the following detailed description taken together with the accompanying claims. It is noted that the scope of the claims is defined by the recitations therein and not by the specific discussion of features and advantages set forth in the present description.BRIEF DESCRIPTIONS OF THE DRAWINGS

[0010] FIG. 1 is a bar graph comparing the number of HCPs detected using the standard digestion versus native digestive approach.

[0011] FIG. 2 is a bar graph comparing the number of HCPs detected using standard digestion with a 2 hour liquid chromatography (LC) gradient program versus native digestion with either 2 hour or 4 hour LC gradient program.

[0012] FIG. 3 is a bar graph comparing the impact of acetonitrile on HCPs detected using the standard digestion versus native digestion approach.

[0013] FIGs. 4A-C depict broader HCP coverage (cumulative HCP detection) in drug substance lots (batches) 1, 2, and 3 using parallel MS / MS approach; FIG. 4A, FIG. 4B, and FIG. 4C show HCP observed in drug substance lots 1, 2, and 3, respectively.

[0014] FIG. 5 depicts HCPs detected across individual lots with cumulative profile representing process-specific HCPs for lots 1 -4.

[0015] FIG. 6 represents a comparison of cumulative HCPs in drug substance batches between Process 1 and Process 2, showing common and unique HCPs detected with Processes 1 and 2.

[0016] FIG. 7 depicts the removal of high-risk HCPs at each unit operation of Process 1 and Process 2.

[0017] FIG. 8 is a comparison between cumulative HCPs in drug product batches of a Reference biologic product and a Biosimilar candidate product.DETAILED DESCRIPTION

[0018] The disclosure relates to methods of detecting and quantifying Host Cell Proteins (HCPs) in biopharmaceutical samples containing a drug product. More specifically, the disclosure relates to methods of assaying HCPs in biopharmaceutical samples using enzymatic digestion protocols, liquid chromatography (LC) gradients, immunoaffinity capture protocols, and High- Resolution Mass Spectrometry (HRMS) to enhance the recovery, detection, and profiling of HCPs, which can impact the efficacy, shelf-life, and therapeutic response of drug product.

[0019] More specifically, the disclosure relates to improved methods for identifying HCPs in drug products. Removal of HCPs is essential to ensuring patient safety, increasing drug stability and shelf-life, and preventing biochemical processes that reduce efficacy and increase immunogenicity risk of drug products. The disclosure provides improved methods for detecting and identifying HCPs in biopharmaceutical samples containing a drug product.

[0020] As utilized in accordance with the present disclosure, unless otherwise indicated or defined, all technical and scientific terms used herein shall be understood to have the meaning commonly understood by a person skilled in the art to which this disclosure belongs. The following references provide one of skill with a general definition of many of the terms used in this disclosure: Singleton et al., Dictionary of Microbiology and Molecular Biology (2nd ed. 1994);The Cambridge Dictionary of Science and Technology (Walker ed., 1988); The Glossary of Genetics, 5th Ed., R. Rieger et al. (eds.), Springer Verlag (1991); and Hale & Marham, The HarperCollins Dictionary of Biology (1991). As used herein, the following terms have the meanings ascribed to them below, unless specified otherwise.

[0021] Unless otherwise required by context, singular terms shall include pluralities and plural terms shall include the singular. For example, the terms "a," "an," and "the," as used herein, are understood to be singular or plural unless the context clearly dictates otherwise. It should be understood that the terms "a" and "an" as used herein refer to "one or more" of the enumerated components unless otherwise indicated or dictated by its context. The use of the alternative (e.g., "or") should be understood to mean either one, both, or any combination thereof of the alternatives unless otherwise indicated. Thus, unless specifically stated or apparent from context, the term "or" as used herein is understood to be inclusive.

[0022] The terms "comprises" and "comprising," as used herein, can have the meaning ascribed to them in U.S. patent law and can mean "includes," "including," "containing," "having," and the like. Thus, unless expressly specified otherwise, the terms "comprises" and "comprising," as used herein, indicate that further components or members may optionally be present in addition to the components or members of the list introduced by "comprising." The terms "consisting essentially of' or "consists essentially," as used herein, likewise have the meaning ascribed in U.S. patent law, and allow for the presence of more than that which is recited so long as basic or novel characteristics of that which is recited are not changed by the presence of more than that which is recited.

[0023] Any of the methods or compositions provided herein can be combined with one or more of any of the other methods or compositions provided herein.

[0024] In the present disclosure, any concentration range, percentage range, ratio range, or integer range is to be understood to include the value of any integer within the recited range and, when appropriate, fractions thereof (such as one tenth and one hundredth of an integer), unless otherwise indicated. Ranges provided herein are understood to be shorthand for all of the values within the range. For example, a range of 1 to 50 is understood to include any number, combination of numbers, or sub-range 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.

[0025] Unless specifically stated or apparent from context, the terms "about" and "approximately," as used herein, are understood as meaning within a range of normal tolerance inthe art, for example within 2 standard deviations of the mean, or to mean within an acceptable error range for the particular value as determined by one of ordinary skill in the art, which will depend in part on how the value is measured or determined, i.e., the limitations of the measurement system. "About" can be understood as meaning within 10%, 9%, 8%, 7%, 6%, 5%, 4%, 3%, 2%, 1%, 0.5%, 0.1%, 0.05%, or 0.01% of the stated value. Unless otherwise clear from context, all numerical values provided herein are modified by the term about.

[0026] It is noted that terms like "preferably," "commonly," and "typically" are not utilized herein to limit the scope of the claimed subject matter or to imply that certain features are critical, essential, or even important to the structure or function of the claimed subject matter. Rather, these terms are merely intended to highlight alternative or additional features that can or cannot be utilized in a particular embodiment of the present disclosure.

[0027] For the purposes of describing the methods of the disclosure, it is noted that the term "substantially" is utilized herein to represent the inherent degree of uncertainty that can be attributed to any quantitative comparison, value, measurement, or other representation. The term "substantially" is also utilized herein to represent the degree by which a quantitative representation can vary from a stated reference without resulting in a change in the basic function of the subject matter at issue.

[0028] In some embodiments, the methods of the disclosure can be used to detect HCPs in a biopharmaceutical sample, wherein the method comprises: (a) subjecting proteins in the biopharmaceutical sample to enzymatic digestion; (b) eluting HCPs from the biopharmaceutical sample using a liquid chromatography (LC) gradient; (c) concentrating the eluted HCPs by immunoaffinity capture to produce an enriched HCP fraction; and (d) detecting HCPs in the enriched HCP fraction using High-Resolution Mass Spectrometry (HRMS).

[0029] In some embodiments, the methods of the disclosure can be used to detect HCPs in a biologic matrix, wherein the method comprises digesting a protein sample using a native digestion approach; eluting proteins from the protein sample using an optimized liquid chromatography (LC) gradient; binding and concentrating HCPs; and detecting proteins using Liquid chromatography with tandem mass spectrometry (LC-MS / MS). The LC-MS / MS technique derives benefits from a liquid chromatography separation followed by use of a highly sensitive quadrupole mass spectrometry.

[0030] The terms "recombinant therapeutic protein" and "therapeutic protein," as used herein, refer to a class of medicines used to treat or prevent disease in humans. Recombinant therapeutic proteins are produced using recombinant DNA technology. Recombinant therapeutic proteins can be used to treat diseases and conditions, such as, but not limited to cancer, inflammation, and infectious agents. Therapeutic proteins include, but are not limited to, hormones, growth factors, antibodies, cytokines, interferons, drugs, peptide products, peptide precursors, and vaccines.

[0031] The terms "drug product," "drug substance," "product protein," and "biotherapeutic protein," are used interchangeably herein, and refer to a recombinant therapeutic protein or therapeutic protein.

[0032] The terms "host cell proteins" and "HCPs," as used herein, refer to impurities originating from or produced by a host organism during the manufacturing of recombinant therapeutics proteins or biopharmaceuticals. Typically originating from a host organism (e.g., bacteria, yeast, or mammalian cells), HCPs are by-products of cellular processes and are often retained at low levels in the final biologic product or therapeutic proteins despite purification steps designed to detect, recover, and eliminate HCPs. The presence of HCPs can have a negative impact on shelf life, drug quality, stability, and efficacy of a recombinant therapeutic protein. Furthermore, HCPs can stimulate immune responses in patients administered a recombinant therapeutic protein.A. HCP Monitoring

[0033] Regulatory guidelines mandate rigorous monitoring and quantification of HCPs. Despite rigorous purification processes, trace amounts of HCPs can remain in the final product. The presence of these impurities in therapeutic products is of significant clinical concern for several reasons. Clinically, residual HCPs can act as adjuvants, potentially stimulating an immune response to biotherapeutic that compromises patient safety. Some HCPs, such as lipases and proteases, also exhibit enzymatic activity, which can degrade or interact with excipients or the therapeutic drug, thereby impacting the stability and shelf life of the final product. Additionally, certain HCPs may interact directly with the therapeutic protein, leading to aggregation or other modifications such as proteolytic degradation that reduce efficacy and increase immunogenicity risks. Addressing HCPs is therefore essential to ensure patient safety and to comply with regulatory standards, making HCP quantification and characterization a key component in biosimilarity demonstrations and therapeutic protein development.

[0034] HCP mixtures contain a diverse array of proteins originating from the host organism, with varied physicochemical properties. This diversity complicates High-Resolution Mass Spectrometry (HRMS) analysis, as unique proteins may require different conditions for optimal detection and quantification, adding complexity to sample preparation and data interpretation.

[0035] In biopharmaceutical samples, HCPs are often present at very low concentrations compared to the product protein or drug substance. The concentration differences, sometimes spanning several orders of magnitude, present a significant challenge for HRMS. High-abundance proteins can mask or interfere with the detection of low-abundance HCPs, making it difficult to achieve accurate quantification and comprehensive profiling.B. HCP Analysis

[0036] Traditional methods for analyzing HCPs include Enzyme-Linked Immunosorbent Assay (ELISA), Two-Dimensional Polyacrylamide Gel Electrophoresis (2D-PAGE), Western blotting, and high-resolution mass spectrometry (HRMS).

[0037] ELISAs are widely used due to their high sensitivity and ability to quantify HCPs at low PPM concentrations. However, this technique can miss non- immunogenic HCPs. Further, polyclonal antibodies also pose challenges as they may fail to recognize fragments of HCPs.Additionally, ELISA analysis fails to provide any information regarding the molecular nature of the HCPs present. Another drawback concerns HCPs that are highly immunogenic, which can overshadow less immunogenic HCPs even when the latter are present at a higher level.

[0038] 2D-PAGE separates HCPs based on their molecular weight and isoelectric point, allowing for visualization of individual HCPs. However, 2D-PAGE has limited sensitivity, detecting only abundant proteins, and can fail to separate proteins with similar physical properties. Furthermore, 2D-PAGE provides no protein identification, making it unsuitable for comprehensive HCP profiling.

[0039] Western blotting enhances HCP detection sensitivity and specificity when combined with specific antibodies. Nonetheless, this technique suffers from similar limitations as ELISA and 2D-PAGE, including low sensitivity for low-abundance proteins and an inability to detect non- immunogenic HCPs.

[0040] HRMS has emerged as a preferred tool in biopharmaceutical development. HRMS addresses key limitations of ELISAs, 2D-PAGE, and Western blotting through its advancedsensitivity, specificity, and ability to provide in-depth analysis. Unlike ELISA or Western blotting, which rely on antibody detection and may miss non-immunogenic HCPs, HRMS does not depend on antibodies and can detect a broader range of proteins, including low-abundance HCPs and HCP fragments. Additionally, HRMS allows precise identification of individual HCPs by measuring their unique mass-to-charge ratios, offering comprehensive profiling and quantification without overshadowing the effects of prominent HCPs. This detailed insight ensures that even trace levels (less than 1PPM) of HCPs are identified, supporting regulatory compliance and enhancing product safety. Despite the advantages of HRMS in HCP analysis, several challenges including a diverse protein population, a wide dynamic range, and concentration differences persist due to the complex nature of biopharmaceutical samples.

[0041] HCP mixtures contain a diverse array of proteins originating from the host organism, with varied physicochemical properties. This diversity complicates HRMS analysis, as each protein may require different conditions for optimal detection and quantification, adding complexity to sample preparation and data interpretation. Biopharmaceutical samples present challenges as HCPs are often present at very low concentrations compared to the desired product protein, such as a drug substance. The concentration differences, sometimes spanning several orders of magnitude, present a significant challenge for HRMS. High-abundance proteins can mask or interfere with the detection of low-abundance HCPs, making it difficult to achieve accurate quantification and comprehensive profiling.

[0042] Provided herein are methods for addressing the challenges of HCP analysis. The highly sensitive workflow for the detection of HCPs in complex biologic matrices using HRMS, as disclosed herein, provides surprising technical effects that are improvements over current methods for detecting HCPs in complex samples such as those containing recombinant therapeutic proteins.

[0043] In one embodiment of the methods of the disclosure, HCPs in a biopharmaceutical sample are detected by: (a) subjecting proteins in the biopharmaceutical sample to enzymatic digestion; (b) eluting HCPs from the biopharmaceutical sample using a liquid chromatography (LC) gradient; (c) concentrating the eluted HCPs by immunoaffinity capture to produce an enriched HCP fraction; and (d) detecting HCPs in the enriched HCP fraction using High-Resolution Mass Spectrometry (HRMS).

[0044] Protein digestion can be achieved using a standard digestion protocol in which proteins are denatured, reduced, and alkylated to unfold proteins for downstream HCP recovery anddetection. The inventors of the methods of the disclosure determined that standard digestion protocols result in limited HCP recovery, impacting the overall sensitivity and comprehensiveness of the analysis. To overcome this limitation, the inventors digested proteins utilizing a native digestion approach, which involves preserving proteins in their near-native state during enzymatic digestion. The native digestion may include the use of acetonitrile to optimize and improve HCP detection in the downstream HRMS. In one embodiment of the methods of the disclosure, the addition of acetonitrile effectively reduces peptide-peptide interactions. A decrease in the peptidepeptide interactions results in proteins being more readily accessible for HRMS analysis, leading to a substantial increase in the depth of HCP coverage (FIG. 3). This optimized native digestion method with acetonitrile enhanced the detection sensitivity and comprehensiveness of HCP profiling of drug product or drug substance (FIG. 3), allowing for the technical advancement of a more thorough evaluation of residual impurities in biopharmaceutical products.

[0045] This shift in protein digestion and downstream analysis provided a technical improvement over traditional HCP detection methods as it enhanced HCP recovery and detection by preserving protein structure and enabling more complete digestion. The result was an increased number and diversity of identified HCPs. The native digestion method provides the superior technical effect of capturing a broader spectrum of low-abundance HCPs as compared to the standard digestion protocol, contributing to a more comprehensive and sensitive HCP profile in the final workflow as shown in FIG. 1. Further, the methods of the disclosure, which use a native digestion protocol, result in a more comprehensive and sensitive HCP profile than that obtained using a standard digestion protocol.

[0046] In one embodiment of the methods of the disclosure, a tailored liquid chromatography (LC) gradient optimization is used to minimize the masking effects of co-eluting peptides, which is a common challenge in processing complex protein samples. The inventors of the methods of the disclosure found that the standard LC gradient program limited HCP detection due to co-eluting peptides, as product proteins and high-abundance peptides frequently co-elute with HCPs, reducing analytical sensitivity and depth of coverage. To address this challenge, in one embodiment of the methods of the disclosure, an optimized LC gradient program was used to enhance separation efficiency as compared to a standard LC gradient.

[0047] The term "optimized LC gradient," as used herein, refers to a customized gradient in which the elution conditions are gradually increased. The use of an optimized LC gradient allowsfor the enhanced separation of HCP peptides from more abundant product proteins or peptides. In one embodiment of the methods of the disclosure, the optimized LC gradient significantly reduced peptide interference, enhancing HCP detection by maximizing the exposure of individual HCP peptides for mass spectrometric analysis. This tailored LC gradient strategy has the surprising technical effect of improving HCP coverage as shown in FIG. 2. The increased coverage allows for a more comprehensive HCP profile by increasing the number of unique HCPs detected and quantified across complex biologic samples. In one embodiment of the methods of the disclosure, the optimized LC gradient reduces the quantity of co-eluting peptides, including high abundance proteins and product proteins, as compared to a standard LC gradient.

[0048] In one embodiment of the methods of the disclosure, immunoaffinity capture is utilized to bind and concentrate HCPs that are copurified with the drug product followed by separation of the enriched HCP fraction from the drug product. The enriched HCP fraction is then analyzed using high-resolution mass spectrometry (HRMS).

[0049] In one embodiment of the methods of the disclosure, the depth of coverage and sensitivity of the HCP analysis is enhanced by using a parallel LC-MS / MS approach. The LC- MS / MS technique yields benefits from a liquid chromatography separation followed by use of a highly sensitive quadrupole mass spectrometry (LC-MS / MS). This configuration allows for the same sample to be analyzed in duplicate or triplicate, significantly increasing the detection capacity for HCPs and improving overall method sensitivity. Parallel LC-MS / MS runs allow for the simultaneous processing of multiple analyses from same sample. This approach maximizes HCP detection by ensuring that any variability in detection due to sample preparation or instrument sensitivity is minimized. Further, each replicate can be subjected to slightly different conditions or can be analyzed at different times to ensure comprehensive coverage of the HCP profile. For example, when analyzing a complex biologic sample, conducting parallel LC-MS / MS runs enables a thorough evaluation of HCPs present in various concentrations. Each replicate captures a unique snapshot of the sample, allowing for more robust identification and quantification of low- abundance HCPs that might otherwise be missed in a single analysis (FIGs. 4A-C).

[0050] Each replicate can be subjected to different liquid chromatography systems (e.g., UPLC, HPLC, and MPLC), and separation conditions to ensure comprehensive coverage of the HCPs. These conditions can include different column chemistry (e.g., Cl 8, C8, or HILIC columns), different mobile phase, and different gradient conditions. Additional impact can also be achievedusing different ion- pairing reagents (e.g., trifluoroacetic acid or heptafluorobutyric acid). Adjustments to these parameters can significantly impact peptide retention, separation efficiency, and sensitivity.

[0051] In addition to LC conditions, to improve the ionization of peptides and proteins that have inherently poor ionization potential in LC-MS runs can be enhanced by the addition of ionization enhancers to the mobile phase (e.g., m-Nitrobenzyl Alcohol, Glycerol, or Propylene Glycol, Dimethyl Sulfoxide, Formic Acid, Acetic Acid, Trifluoroacetic Acid and Ammonium Acetate or format).

[0052] Different ionization source, such as electrospray ionization (ESI) and atmospheric pressure chemical ionization (APCI), as well as optimization of parameters in the mass spectrometer (e.g., tube temperatures and spray voltages) can be used to enhance peptide ionization and sensitivity. Analyzing each replicate under these varied conditions or at different times helps mitigate potential biases and ensures a more robust and comprehensive analysis of the HCPs.

[0053] The advanced parallel LC-MS / MS analysis enhances the sensitivity of the detection method and allows for a more detailed exploration of the diverse protein population present in a sample. The integration of parallel LC-MS / MS into the methods of the disclosure increases the robustness and reliability of HCP analysis, ensuring compliance with regulatory requirements and supporting the safety and efficacy of therapeutic proteins.

[0054] In addition to enhancing sensitivity through parallel LC-MS / MS runs, the methods of the disclosure can incorporate an analysis of multiple batches of drug products or drug substances manufactured using a single process. This multi-batch analysis approach can be used to develop a comprehensive process-specific Host Cell Protein profile (PHCPP). For example, the PHCPP can be used to determine the drug product impurity profile or assess the safety of the drug product.

[0055] Analyzing multiple batches allows for a more thorough understanding of the variability in HCP content across different production runs. This is advantageous in accounting for the unique HCPs in each batch of products and varying levels of specific HCPs due to inherent differences in manufacturing conditions, raw materials, or biological variability. The methods disclosed herein are advantageous over single batch analyses that may be characterized by specific HCPs that are absent, leading to an incomplete or biased assessment of HCPs in the biopharmaceutical sample.

[0056] In contrast, evaluating HCP profiles across several batches ensures that the analysis captures the full spectrum of process-specific HCPs, leading to a more accurate representation ofthe potential impurities present in the final product (FIG. 5). This comprehensive profiling not only enhances the reliability of safety assessments, but also supports regulatory compliance by demonstrating a thorough understanding of the product's impurity profile. Moreover, this multibatch analysis helps identify trends or patterns in HCP content, enabling proactive measures to be taken in process optimization, quality control, and purification of drug products.Embodiments

[0057] Embodiment 1 : A method of detecting host cell proteins (HCPs) in a biopharmaceutical sample, the method comprising:(a) subjecting proteins in the biopharmaceutical sample to enzymatic digestion;(b) eluting HCPs from the biopharmaceutical sample using a liquid chromatography (LC) gradient;(c) concentrating the eluted HCPs by immunoaffinity capture to produce an enriched HCP fraction; and(d) detecting HCPs in the enriched HCP fraction using High-Resolution Mass Spectrometry (HRMS).

[0058] Embodiment 2: The method of embodiment 1, wherein the proteins in the biopharmaceutical sample are denatured, reduced, and alkylated during enzymatic digestion.

[0059] Embodiment 3 : The method of embodiment 1 , wherein the proteins in the biopharmaceutical sample are maintained in a near-native state during enzymatic digestion.

[0060] Embodiment 4: The method of embodiment 3, wherein the structures of the proteins in the biopharmaceutical sample are preserved.

[0061] Embodiment 5: The method of embodiment 3, wherein the proteins in the biopharmaceutical sample are more completely digested.

[0062] Embodiment 6: The method of embodiment 3, wherein proteins in the biopharmaceutical sample are subjected to enzymatic digestion in the presence of acetonitrile.

[0063] Embodiment 7 : The method of embodiment 4, wherein an amount of acetonitrile sufficient to reduce peptide-to-peptide interactions is used.

[0064] Embodiment 8: The method of embodiment 3, wherein the recovery and detection of HCPs is enhanced as compared with enzymatic digestion that denatures, reduces, and alkylates proteins in the biopharmaceutical sample.

[0065] Embodiment 9: The method of embodiment 2, wherein a broader spectrum of low abundance HCPs are recovered as compared with enzymatic digestion that denatures, reduces, and alkylates proteins in the biopharmaceutical sample.

[0066] Embodiment 10: The method of embodiment 1, wherein a standard LC gradient program is used to elute HCPs from the biopharmaceutical sample.

[0067] Embodiment 11 : The method of embodiment 1 , wherein an optimized LC gradient program is used to elute HCPs from the biopharmaceutical sample.

[0068] Embodiment 12: The method of embodiment 11, wherein the optimized LC gradient program comprises gradually increasing elution conditions.

[0069] Embodiment 13 : The method of embodiment 11 , wherein the optimized LC gradient program has enhanced separation efficiency as compared to a standard LC gradient program.

[0070] Embodiment 14: The method of embodiment 11, wherein the optimized LC gradient program reduces the quantity of co-eluting peptides as compared to a standard LC gradient program.

[0071] Embodiment 15: The method of embodiment 11 , wherein the co-eluting peptides are high abundance proteins.

[0072] Embodiment 16: The method of embodiment 11, wherein the co-eluting peptides are drug products.

[0073] Embodiment 17: The method of embodiment 11, wherein the co-eluting peptides are drug products and high abundance proteins.

[0074] Embodiment 18: The method of embodiment 11 , wherein the optimized LC gradient program enhances elution of HCPs from abundant proteins in the biopharmaceutical sample.

[0075] Embodiment 19: The method of embodiment 11, wherein the optimized LC gradient program reduces peptide interference.

[0076] Embodiment 20: The method of embodiment 11 , wherein the optimized LC gradient program increases exposure of HCPs for HRMS as compared to a standard LC gradient program.

[0077] Embodiment 21 : The method of embodiment 1, wherein the concentrated HCPs in the enriched HCP fraction are selectively bound from one or more drug products in the biopharmaceutical sample.

[0078] Embodiment 22: The method of embodiment 1, wherein two or more rounds of detecting HCPs in the biopharmaceutical sample are conducted (i.e., parallel LC-MS / MS).

[0079] Embodiment 23 : The method of embodiment 22, wherein the biopharmaceutical samples analyzed by parallel LC-MS / MS are obtained from two or more drug product Batches (or lots) manufactured using the same process.

[0080] Embodiment 24: The method of embodiment 23, wherein the analysis of two or more drug products yields a comprehensive process-specific Host Cell Protein profile (PHCPP).

[0081] Embodiment 25: The method of embodiment 24, wherein the PHCPP is used to determine a drug product impurity profile.

[0082] Embodiment 26: The method of embodiment 24, wherein the PHCPP is used to assess drug product safety

[0083] Embodiment 27: The method of embodiment 24, wherein HCPs are detecting in the biopharmaceutical sample at each unit operation of a drug product manufacturing process.

[0084] Embodiment 28: The method of claim 1, wherein the method allows for optimization of purification conditions in a drug product manufacturing process.EXAMPLES1. HRMS-Based Workflow / Application of HRMS-based workflow:

[0085] An HRMS-based workflow for HCP detection provides several critical applications in the characterization and quality control of biotherapeutics proteins. Such methods enable comprehensive profiling and quantifications of HCPs, addressing key challenges in biopharmaceutical development. The following applications are central to ensuring product safety, consistency, and regulatory compliance, while also potentially reducing the scope of clinical trials.2. Process Comparison:

[0086] HRMS-based methods allow for detailed HCP profiling across different manufacturing processes, enabling a direct comparison of HCP profiles. Sample analysis from different process stages or alternative production processes via HRMS can reveal variations in HCP content and composition (FIG. 6). This is critical for assessing process consistency and understanding the impact of process modifications on HCP levels, which ultimately influence product quality and safety. For example, HRMS can detect subtle differences in low-abundance HCPs that may be missed by other methods, helping to ensure that process changes do not inadvertently introduce new HCP risks.3. Monitoring HCPs Removal Across Downstream Processing Steps:

[0087] HRMS-based analysis can be applied at each unit operation in downstream processing to track the removal or persistence of specific HCPs throughout purification. By measuring HCP levels after each purification step, HRMS provides insights into the effectiveness of each unit operation, such as Clarified harvest protein A chromatography, ion exchange, and ultrafiltration, in reducing HCP burden. This allows for optimization of purification conditions, as it helps identify steps where HCPs may be insufficiently removed and informs adjustments to improve process purity and overall product quality (Table 1; FIG. 7).Table 1: HCP Removal Across Downstream Processing Steps of Monoclonal Antibody.4. Evaluation of Generic HCP ELISA Kits:

[0088] Generic HCP ELISA kits often fail to detect all HCPs present in a specific sample, due to the limited coverage of available antibodies. HRMS can be used to evaluate the effectiveness of these kits by identifying undetected HCPs that are missed due to insufficient antibody coverage.One approach involves the addition of protein product samples in a 96-well plate and incubating the sample. Following incubation, the product and bound HCPs are removed from the well, and HRMS is used to analyze any remaining, undetected HCPs. This reveals gaps in ELISA coverage, ensuring a more accurate assessment of HCP risk by uncovering HCPs not captured by the ELISA.5. Comparative Analysis for Biosimilars:

[0089] HRMS plays a critical role in comparing HCP profiles between biosimilar products and their reference counterparts. By thoroughly profiling HCPs in both biosimilar and reference products, HRMS helps identify any differences in HCP content that may impact product safety, efficacy, or immunogenicity (FIG. 8). This is crucial for demonstrating biosimilarity, as regulatory agencies often require comprehensive evidence showing that the biosimilar's impurity profile, including HCPs, closely matches that of the reference product. HRMS provides the sensitivity and specificity needed to detect low-abundance HCPs that might contribute to subtle differences in immunogenicity risk.6. Assessment of Antibody Coverage in Generic HCP ELISA Kits Using HRMS:

[0090] Generic HCP ELISA kits are commonly used to quantify host cell proteins (HCPs) during process development; however, their suitability for accurate process-specific HCP quantification remains questionable and regulators usually prefer process specific HCPs assay or a sound justification for accepting kit based method. High-resolution mass spectrometry (HRMS) can be employed to assess the effectiveness of these kits by identifying HCPs that remain undetected. One approach involves incubating drug substance (DS), or Harvest Cell Culture Fluid (HCCF), or process intermediate sample in a 96-well ELISA plate coated with commercially available anti-HCP antibodies. After incubation, unbound material is washed away, leaving antibody-bound HCPs in the wells. These bound HCPs are then digested using suitable proteolytic enzymes such as trypsin, Lys-C, chymotrypsin, or Glu-C. The resulting peptide mixture is analyzed by HRMS. A control sample, processed without antibody capture, is also digested and analyzed. If the control sample exhibits a similar HCP profile to the captured sample, it indicates complete antibody coverage, confirming the suitability of the ELISA kit for accurate HCP quantification and eliminating the need for process-specific kit development.7. Evaluation of Immunogenicity Risk of HCPs in Drug Substance or Drug Product

[0091] Residual host cell proteins (HCPs) present in biotherapeutic products can pose immunogenicity risks, potentially triggering adverse immune responses in patients. To assess this risk, an HRMS-based workflow can be integrated with immunoaffinity enrichment and T-cell assays. In this approach, HCPs present in the drug substance or drug product are first enriched using immunoaffinity capture using anti-HCP antibodies. The purified HCP fraction is thenintroduced into an in vitro T-cell assay, where antigen-presenting cells (APCs) process and present HCP-derived peptide fragments on their surface via MHC class II molecules. These presented peptides are subsequently identified using high-resolution mass spectrometry (HRMS). Detection of HCP-derived peptides on APCs indicates that these proteins can be processed and presented to T cells, suggesting a potential to elicit an immune response in humans. This workflow provides a direct, mechanistic evaluation of immunogenicity risk, complementing in silico epitope prediction and supporting regulatory safety assessments.

Claims

WHAT IS CLAIMED IS:Claim 1 : A method of detecting host cell proteins (HCPs) in a biopharmaceutical sample, the method comprising:(a) subjecting proteins in the biopharmaceutical sample to enzymatic digestion;(b) eluting HCPs from the biopharmaceutical sample using a liquid chromatography (LC) gradient;(c) concentrating the eluted HCPs by immunoaffinity capture to produce an enriched HCP fraction; and(d) detecting HCPs in the enriched HCP fraction using High-Resolution Mass Spectrometry (HRMS).Claim 2: The method of claim 1, wherein the proteins in the biopharmaceutical sample are denatured, reduced, and alkylated during enzymatic digestion.Claim 3: The method of claim 1, wherein the proteins in the biopharmaceutical sample are maintained in a near-native state during enzymatic digestion.Claim 4: The method of claim 3, wherein the structures of the proteins in the biopharmaceutical sample are preserved.Claim 5: The method of claim 3, wherein the proteins in the biopharmaceutical sample are more completely digested.Claim 6: The method of claim 3, wherein proteins in the biopharmaceutical sample are subjected to enzymatic digestion in the presence of acetonitrile.Claim 7: The method of claim 4, wherein an amount of acetonitrile sufficient to reduce peptide-to-peptide interactions is used.Claim 8: The method of claim 3, wherein the recovery and detection of HCPs is enhanced as compared with enzymatic digestion that denatures, reduces, and alkylates proteins in the biopharmaceutical sample.Claim 9: The method of claim 2, wherein a broader spectrum of low abundance HCPs are recovered as compared with enzymatic digestion that denatures, reduces, and alkylates proteins in the biopharmaceutical sample.Claim 10: The method of claim 1, wherein a standard LC gradient program is used to eluteHCPs from the biopharmaceutical sample.Claim 11 : The method of claim 1 , wherein an optimized LC gradient program is used to eluteHCPs from the biopharmaceutical sample.Claim 12: The method of claim 11, wherein the optimized LC gradient program comprises gradually increasing elution conditions.Claim 13: The method of claim 11, wherein the optimized LC gradient program has enhanced separation efficiency as compared to a standard LC gradient program.Claim 14: The method of claim 11, wherein the optimized LC gradient program reduces the quantity of co-eluting peptides as compared to a standard LC gradient program.Claim 15: The method of claim 11, wherein the co-eluting peptides are high abundance proteins.Claim 16: The method of claim 11, wherein the co-eluting peptides are drug products.Claim 17: The method of claim 11, wherein the co-eluting peptides are drug products and high abundance proteins.Claim 18: The method of claim 11, wherein the optimized LC gradient program enhances elution of HCPs from abundant proteins in the biopharmaceutical sample.Claim 19: The method of claim 11, wherein the optimized LC gradient program reduces peptide interference.Claim 20: The method of claim 11, wherein the optimized LC gradient program increases exposure of HCPs for HRMS as compared to a standard LC gradient program.Claim 21 : The method of claim 1, wherein the concentrated HCPs in the enriched HCP fraction are selectively bound from one or more drug products in the biopharmaceutical sample.Claim 22: The method of claim 1, wherein two or more rounds of detecting HCPs in the biopharmaceutical sample are conducted (i.e., parallel LC-MS / MS).Claim 23 : The method of claim 22, wherein the biopharmaceutical samples analyzed by parallel LC-MS / MS are obtained from two or more drug product Batches manufactured using the same process.Claim 24: The method of claim 23, wherein the analysis of two or more drug products yields a comprehensive process-specific Host Cell Protein profile (PHCPP).Claim 25: The method of claim 24, wherein the PHCPP is used to determine a drug product impurity profile.Claim 26: The method of claim 24, wherein the PHCPP is used to assess drug product safety.Claim 27: The method of claim 24, wherein HCPs are detecting in the biopharmaceutical sample at each unit operation of a drug product manufacturing process.Claim 28: The method of claim 1, wherein the method allows for optimization of purification conditions in a drug product manufacturing process.

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