DATA INDEPENDENT LC-MS ASSAYS FOR IDENTIFICATION, QUANTIFICATION AND MONITORING OF HOST CELL PROTEINS IN MONOCLONAL ANTIBODIES
Posters | 2024 | Waters | ASMSInstrumentation
The accurate identification and quantification of host cell proteins (HCPs) in monoclonal antibody (mAb) preparations is critical for ensuring drug safety, efficacy and regulatory compliance. Data-independent acquisition (DIA) LC-MS methods offer comprehensive peptide coverage, high sensitivity and robust quantification, enabling reliable HCP monitoring at low parts-per-million levels.
This work presents two complementary LC-MS workflows for HCP analysis in mAb digests: a discovery assay for broad identification of HCP contaminants, and a high-throughput monitoring assay for GMP-compatible quantification. The goal is to achieve a lower limit of quantification (LLOQ) of 5 ppm while maintaining data integrity and assay speed.
The NIST mAb Reference Material 8671 was precipitated to deplete the antibody, digested overnight with RapiZyme trypsin, reduced with DTT and acidified. For discovery, a 90 min gradient on the Xevo G3 QTof acquired alternating low- and high-energy scans (400–2000 Da). For monitoring, a 30 min gradient on BioAccord captured MSE scans (50–2000 Da). Data processing employed Progenesis QI and Byonic for peptide identification, waters_connect for screening, and Hi3 quantification using spiked standards.
The discovery assay detected seven endogenous HCPs in two of three replicates and two spiked proteins (yeast alcohol dehydrogenase and rabbit glycogen phosphorylase) at 5 ppm LLOQ. The monitoring assay consistently quantified four spiked proteins over a range of concentrations, matching the 5 ppm sensitivity, and identified endogenous HCP peptides at 13–19 ppm. Chromatographic performance remained stable under sample overloading conditions.
Advances may include expanded HCP peptide libraries, targeted MRM/PRM workflows for known impurities, integration of automation for sample prep, and AI-driven data analysis for rapid results interpretation. Implementation in continuous bioprocessing and real-time release testing represents further application potential.
The combined discovery and monitoring DIA LC-MS assays deliver robust, sensitive and high-throughput solutions for HCP analysis in mAb products, supporting both research and GMP-grade quality control with an LLOQ of 5 ppm.
LC/HRMS, LC/MS, LC/MS/MS, LC/TOF
IndustriesPharma & Biopharma
ManufacturerWaters
Summary
Significance of the Topic
The accurate identification and quantification of host cell proteins (HCPs) in monoclonal antibody (mAb) preparations is critical for ensuring drug safety, efficacy and regulatory compliance. Data-independent acquisition (DIA) LC-MS methods offer comprehensive peptide coverage, high sensitivity and robust quantification, enabling reliable HCP monitoring at low parts-per-million levels.
Objectives and Study Overview
This work presents two complementary LC-MS workflows for HCP analysis in mAb digests: a discovery assay for broad identification of HCP contaminants, and a high-throughput monitoring assay for GMP-compatible quantification. The goal is to achieve a lower limit of quantification (LLOQ) of 5 ppm while maintaining data integrity and assay speed.
Applied Instrumentation
- Waters Xevo G3 QTof operated in MSE mode (30 000 resolution)
- Waters BioAccord LC-MS System with Accurate Mass Screening workflow
- ACQUITY UPLC Premier with Premier CSH C18 column (2.1 × 150 mm, 1.7 µm)
- RapiZyme trypsin enzyme for optimized protein digestion
Methodology
The NIST mAb Reference Material 8671 was precipitated to deplete the antibody, digested overnight with RapiZyme trypsin, reduced with DTT and acidified. For discovery, a 90 min gradient on the Xevo G3 QTof acquired alternating low- and high-energy scans (400–2000 Da). For monitoring, a 30 min gradient on BioAccord captured MSE scans (50–2000 Da). Data processing employed Progenesis QI and Byonic for peptide identification, waters_connect for screening, and Hi3 quantification using spiked standards.
Main Results and Discussion
The discovery assay detected seven endogenous HCPs in two of three replicates and two spiked proteins (yeast alcohol dehydrogenase and rabbit glycogen phosphorylase) at 5 ppm LLOQ. The monitoring assay consistently quantified four spiked proteins over a range of concentrations, matching the 5 ppm sensitivity, and identified endogenous HCP peptides at 13–19 ppm. Chromatographic performance remained stable under sample overloading conditions.
Benefits and Practical Applications
- High sensitivity enables detection of HCPs at regulatory thresholds
- Data-independent approach ensures reproducible identification and quantification
- Shorter gradients and streamlined workflows support higher sample throughput
- Compliant monitoring assay suitable for GMP QC environments
Future Trends and Opportunities
Advances may include expanded HCP peptide libraries, targeted MRM/PRM workflows for known impurities, integration of automation for sample prep, and AI-driven data analysis for rapid results interpretation. Implementation in continuous bioprocessing and real-time release testing represents further application potential.
Conclusion
The combined discovery and monitoring DIA LC-MS assays deliver robust, sensitive and high-throughput solutions for HCP analysis in mAb products, supporting both research and GMP-grade quality control with an LLOQ of 5 ppm.
References
- Doneanu CE; Anderson M; Williams BJ; Lauber MA; Chakraborty A; Chen W. Anal Chem. 2015;87:10283–10291.
- Huang L; Wang N; Mitchell CE; Brownlee T; Maple SR; De Felippis MR. Anal Chem. 2017;89:5436–5444.
- Chen IH; Xiao H; Daly T; Ning L. Anal Chem. 2020;92:3751–3757.
- Wang Q; Slaney TR; Wu W; Ludwig R; Li T; Leone A. Anal Chem. 2020;92:10327–10335.
- Yang F; Li D; Kufer R; Cadang L; Zhang J; Dai L; Gu J; Wohlrab S; Greenwood-Goodwin M; Shen A; Duan D; Li H; Yuk IH. Anal Chem. 2021;93:723–731.
- Ippoliti S; Zampa N; Yu YQ; Lauber MA. Waters Application Note 2023;P/N 720007840.
- Silva JC; Gorenstein MV; Li GZ; Vissers JP; Geromanos SJ. Mol Cell Proteomics. 2006;5:144–156.
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