Establishment of a highly precise multi-attribute method for the characterization and quality control of therapeutic monoclonal antibodies

This study focuses on optimizing sample preparation for the multi-attribute method (MAM), a critical quality control technique for therapeutic monoclonal antibodies (mAbs). The authors aimed to address challenges associated with artificial modifications during sample preparation, which can compromise the accuracy of MAM analysis. They compared five different sample preparation methods using trastuzumab as a model mAb, evaluating them based on sequence coverage, peptide redundancy, missed cleavage, and chemical deamidation. Key findings revealed that using a low pH buffer and a shorter digestion time significantly reduced artificial deamidation. Furthermore, a desalting step after carboxymethylation proved essential for achieving high sequence coverage with reduced digestion time. The generation of missed cleavage peptides was also improved by employing a trypsin/lysyl endopeptidase (Lys-C) mixture. The optimized method successfully monitored 17 glycopeptides, 2 deamidated peptides, and N- and C-terminal peptides of the heavy chain with acceptable mass accuracy and coefficient of variation. While some oxidized peptides showed slightly higher inter-assay variability due to instability in the MS sample solution, the overall method demonstrated reliability and applicability for MAM analysis, suggesting that modification type, rather than peptide amount, influences peak area variation. This research provides a robust and efficient sample preparation protocol that enhances the precision and reliability of MAM for mAb characterization and quality control.