Ask The Pros — The Latest In HCP Monitoring
A conversation with analytical process experts from across industry
Assessing total host cell protein (HCP) levels is no longer enough. Clearing high-risk HCPs requires robust characterization to develop suitable strategies.
Established methods focused on counting all of them indiscriminately. Now, a new wave of sophisticated monitoring technology offers drugmakers a clearer picture of process-related impurities, helping them produce safer, more effective, and more stable products.
Earlier this year, Life Science Connect collaborated with CMC technical expert Gopinath Annathur to explore emerging technologies helping developers to mitigate HCPS. The endeavor revealed that, among other things, current approaches remain nascent, with significant gaps in validated methodologies. Annathur helped us develop a series of questions related to downstream techniques, upstream strategies, and monitoring and analytics to bring our communities up to speed.
We asked experts in our network to share their expertise. Here’s what they had to say about emerging monitoring and analytical methods. Answers have been edited for clarity.
Monitoring high-risk HCP populations for a given process is a key understanding needed to direct the later-stage development of a commercial process. What new tools are being used to help navigate and guide development?
High-risk HCPs are process-related impurities, which can impact product stability, safety, and efficacy. As such, they form part of the critical quality attributes (CQAs), which must be monitored and reported.
ELISA-based methods have been widely used to quantify HCPs due to their easy application and cost-effectiveness. However, while capable of quantifying the overall HCP level, these approaches lack the ability to differentiate between individual HCP species. Furthermore, the reliance of ELISAs on polyclonal antibodies can lead to incomplete HCP coverage and lot-to-lot variability.
Consequently, the use of orthogonal approaches such as mass spectrometry (MS) has gained traction. Due to their antibody-free approach, they enable the detection of HCPs that may be non-immunogenic or poorly recognized by ELISA reagents, increasing throughput. Historically, these approaches were labor-intensive, involved complex sample preparation, and their results were susceptible to bias introduced by the chosen sample enrichment method. Recent advancements in sensitivity, resolution, and speed have enabled more comprehensive profiling and identification of low-abundance HCPs, including those harboring additional risks like enzymatic activity or immunogenicity. For example, the HCP-AIMS (host cell protein-automated iterative MS) utilizes directly digested samples without enrichment or pretreatment.1 Furthermore, advanced data acquisition methods, such as BoxCar, further facilitate detailed characterization of HCPs following acquisition.2
Applying such techniques to upstream and downstream process samples allows manufacturers to closely monitor the levels of hundreds to thousands of HCPs. When coupled with a “targeted high risk” approach to HCP identification, i.e., monitoring specific HCPs known to pose a higher risk (e.g., proteases, lipases, and immunogenic proteins) via historic data integration and the use of computation tools, they can ensure time and resources are focused on efficiently directing development to ensure satisfactory elimination of such proteins.
Caraugh Albany, Autolus Therapeutics
How can LC-MS/MS-based methods help troubleshoot workflows when unexpected HCP levels are seen in the final product based on the ELISA assay?
The observation of unexpected HCP levels via ELISA can pose significant troubleshooting challenges. As ELISAs rely on polyclonal antibodies raised against a mixture of HCPs, they provide total HCP quantification rather than identifying the individual protein(s) and their contributions to overall HCP levels.
Therefore, the use of orthogonal, antibody-independent approaches such as LC-MS/MS enables the identity and contribution of the HCP(s) present to be elucidated. This addresses the key question of whether an individual or a subgroup of HCP(s) is contributing to the unexpected result or whether it’s a global modulation.
By addressing this question, hypotheses can be made and potential sources of contamination identified. This information can then be attributed to a given process step (upstream or downstream) by utilizing process knowledge. For example, high levels of a protease could indicate an issue with a specific chromatography column or a lysis event during cell culture.
Caraugh Albany, Autolus Therapeutics
What is a comprehensive approach to characterizing the mAb manufacturing process that integrates a deep understanding of both the entire bioproduction workflow and HCP clearance?
A comprehensive approach to characterizing mAb manufacturing for HCP clearance hinges on a strategic analytical framework integrated with process understanding and risk assessment(s). This requires use of orthogonal analytical techniques at strategically chosen sampling points throughout manufacture.
Speaking more specifically to the analytics, evidence would suggest that a combination of complementary methods is required to facilitate appropriate identification and quantification of HCPs. These would likely include: total HCP ELISA, LC-MS, and process-specific ELISA., the use of which should be modulated throughout development.
During early development, critical process stages should undergo initial HCP profiling using broad methods such as total HCP ELISA and initial LC-MS/MS surveys to help establish a baseline and identify abundant or potentially problematic HCPs. Utilizing a risk-based assessment at this stage enables identification of HCPs with known biological activity/immunogenicity that may impact the final product and may require additional monitoring and restricting. Using this baseline and process knowledge, clearance can be monitored and, wherever possible, optimized.
Caraugh Albany, Autolus Therapeutics
A comprehensive characterization approach integrates bioproduction and HCP clearance through the following principles:
- End-to-end process understanding:
- Map the entire workflow (upstream processing, downstream processing, formulation) to identify HCP sources and clearance points. Use process flow diagrams and mass balance calculations to track HCP reduction.
- Employ systems biology approaches (e.g., proteomics, metabolomics) to understand how upstream conditions influence HCP profiles and downstream clearance.
- QbD-driven development:
- Define a quality target product profile (QTPP) that includes HCP limits as a key specification (e.g., <100 ppm for mAbs).
- Use DoE and statistical modeling to establish design spaces for critical process parameters that ensure robust HCP clearance while maintaining yield and purity.
- Analytical platform integration:
- Combine orthogonal analytical methods (ELISA, LC-MS/MS, 2D-DIGE) to provide a complete picture of HCP dynamics. For example, ELISA monitors total HCP trends, while LC-MS/MS identifies specific HCPs co-purifying with the mAb.
- Implement process analytical technology (PAT) tools for real-time HCP monitoring, such as at-line LC-MS or rapid ELISA.
- Risk-based decision-making:
- Use risk assessment tools (e.g., BPDG’s HCP risk-ranking framework) to prioritize HCP control efforts based on process stage, HCP type, and clinical impact.
- Continuously update the control strategy with data from process development, scale-up, and clinical studies.
- Regulatory alignment:
- Ensure characterization studies meet FDA, EMA, and ICH expectations for HCP control (e.g., ICH Q6B, Q11). Provide detailed documentation of HCP profiling, clearance validation, and risk assessments in regulatory submissions.
- Justify HCP limits based on process capability, preclinical/clinical data, and patient safety considerations.
Characterizing the mAb manufacturing process requires a deep understanding of the bioproduction workflow with robust HCP clearance strategies. This involves end-to-end process mapping, QbD-driven optimization, orthogonal analytical methods (ELISA, LC-MS/MS), and risk-based control strategies. By addressing HCP risks at each stage — cell line development, USP, DSP, and formulation — while aligning with regulatory guidelines (ICH Q8–Q11), manufacturers can ensure product quality and patient safety. Advances in analytics, in silico tools, and industry collaboration continue to enhance HCP management, making this approach both practical and forward-looking.
Diana Colleluori and Michelle Tseng, Biologics Consulting Group
How are HCP ELISA methods impacted by mAb co-purifying HCPs? What strategy would one follow to detect and counter this problem?
Co-purification of HCPs with mAbs is a common challenge. While protein A affinity chromatography is widely used for initial capture of mAbs, it doesn't completely remove HCPs, leading to impurities in the final product. Two main mechanisms contribute to HCP co-purification: (i) product association and (ii) co-elution. Both present challenges for HCP ELISAs, which typically utilize polyclonal antibodies to detect a heterogeneous HCP population. These antibodies are often developed using host cell culture fluid (HCCF) from non-transfected cells, resulting in their potential inability to recognize HCPs that have been co-purified. Furthermore, if they are recognized, the antibody's affinity or avidity may be reduced for these co-purifying HCPs, leading to underestimation of their concentration and potential downstream impacts on risk assessment and, therefore, product purity and safety.
Complementary antibody-free methods can be utilized to detect and overcome this challenge by both analyzing the coverage of the selected HCP ELSISA and providing a better understanding of the interactions between HCPs and the mAb. For example, MS has been instrumental in identifying individual HCPs that co-purify with/piggyback on mABs throughout the manufacturing process. In some cases, it can demonstrate that mAbs bind to or interact with a conserved set of HCPs. As a developer, identifying which particular HCPs are likely to be co-eluted with your mABs enables tailoring of the process control strategy. For example, this can be accomplished through the development of a process-specific ELISA that incorporates antibodies specifically targeting these problematic HCPs. This can provide a more accurate measurement for these critical impurities.
Caraugh Albany, Autolus Therapeutics
What rational approaches do you follow to arrive at final HCP limits or criteria for products, considering the type of drug, the concentration of the product, the frequency of dose, and the routes of administration that would make it severe or low risk? Are there special requirements for high-risk HCPs?
For biologics, acceptable HCP levels are product and risk dependent, rather than fixed numerical limits. For monoclonal antibodies or mAb derivatives, where large and frequent doses are administered parenterally, limits are typically expected to be in the low nanogram to picogram range per dose, justified by exposure due to dose concentration and frequency, rather than a universal value. For vaccines or viral vector-based products, which are often given once or twice at much lower doses, higher residual HCP levels may be scientifically and clinically acceptable. In some enveloped viral vector systems, recombinant host proteins can co-purify or become intrinsic to the product through budding from the host membrane, so the emphasis is on identifying and monitoring those components rather than applying an arbitrary total HCP threshold.
Lee Smith, GreyRigge Associates Ltd
References:
- Huang Y, Molden R, Hu M, Qiu H, Li N. Toward unbiased identification and comparative quantification of host cell protein impurities by automated iterative LC-MS/MS (HCP-AIMS) for therapeutic protein development. J Pharm Biomed Anal. 2021 Jun 5;200:114069. doi: 10.1016/j.jpba.2021.114069. Epub 2021 Apr 20. PMID: 33901758.
- Nie S, Greer T, O’Brien Johnson R, Zheng X, Torri A, Li N. Simple and sensitive method for deep profiling of host cell proteins in therapeutic antibodies by combining ultra-low trypsin concentration digestion, long chromatographic gradients, and boxcar mass spectrometry acquisition. Anal Chem. 2021;93(10):4383–90. doi: 10.1021/acs.analchem.0c03931.