Charge variant analysis is a widely used tool to monitor changes in product quality during the manufacturing process of monoclonal antibodies (mAbs). Although it is a powerful technique for revealing mAb heterogeneity, an unexpected outcome, for example the appearance of previously undetected isoforms, requires further, time-consuming analysis. The process of identifying these unknowns can also result in unwanted changes to the molecule that are not attributable to the manufacturing process. To overcome this, we recently reported a method combining highly selective cation exchange chromatography-based charge variant analysis with on-line mass spectrometric (MS) detection. We further explored and adapted the chromatographic buffer system to expand the application range. Moreover, we observed no salt adducts on the native protein, also supported by the optimal choice of MS parameters, resulting in increased data quality and mass accuracy. Here, we demonstrate the utility of this improved method by performing an in-depth analysis of adalimumab before and after forced degradation. By combining molecular mass and retention time information, we were able to identify multiple modifications on adalimumab, including lysine truncation, glycation, deamidation, succinimide formation, isomerisation, N-terminal aspartic acid loss or C-terminal proline amidation and fragmentation along with the N-glycan distribution of each of these identified proteoforms. Host cell protein (HCP) analysis was performed using liquid chromatography-mass spectrometry that verified the presence of the protease Cathepsin L. Based on the presence of trace HCPs with catalytic activity, it can be questioned if fragmentation is solely driven by spontaneous hydrolysis or possibly also by enzymatic degradation.

Peptide mapping analysis is a regulatory expectation to verify the primary structure of a recombinant product sequence and to monitor post-translational modifications (PTMs). Although proteolytic digestion has been used for decades, it remains a labour-intensive procedure that can be challenging to accurately reproduce. Here, we describe a fast and reproducible protocol for protease digestion that is automated using immobilised trypsin on magnetic beads, which has been incorporated into an optimised peptide mapping workflow to show method transferability across laboratories. The complete workflow has the potential for use within a multi-attribute method (MAM) approach in drug development, production and QC laboratories. The sample preparation workflow is simple, ideally suited to inexperienced operators and has been extensively studied to show global applicability and robustness for mAbs by performing sample digestion and LC-MS analysis at four independent sites in Europe. LC-MS/MS along with database searching was used to characterise the protein and determine relevant product quality attributes (PQAs) for further testing. A list of relevant critical quality attributes (CQAs) was then established by creating a peptide workbook containing the specific mass-to-charge (m/z) ratios of the modified and unmodified peptides of the selected CQAs, to be monitored in a subsequent test using LC-MS analysis. Data is provided that shows robust digestion efficiency and low levels of protocol induced PTMs.

The multi-attribute method (MAM) is a liquid chromatography–mass spectrometry based method that is used to directly characterize and monitor many product quality attributes and impurities on biotherapeutics, most commonly at the peptide level. It utilizes high-resolution accurate mass spectral data which are analyzed in an automated fashion. MAM is a promising approach that is intended to replace or supplement several conventional assays with a single LC-MS analysis and can be implemented in a Current Good Manufacturing Practice environment. MAM provides accurate site-specific quantitation information on targeted attributes and the nontargeted new peak detection function allows to detect new peaks as impurities, modifications, or sequence variants when comparing to a reference sample. The high resolution MAM workflow was applied here for three independent case studies. First, to monitor the behavior of monoclonal antibody product quality attributes over the course of a 12-day cell culture experiment providing an insight into the behavior and dynamics of product attributes throughout the process. Second, the workflow was applied to test the purity and identity of a product through analysis of samples spiked with host cell proteins. Third, through the comparison of a drug product and a biosimilar with known sequence variants. The three case studies presented here, clearly demonstrate the robustness and accuracy of the MAM workflow that implies suitability for deployment in the regulated environment.