Multi-attribute method analysis of therapeutic monoclonal antibodies using an automated sample preparation system

Abstract

The multi-attribute method (MAM) has attracted increased attention as an alternative strategy for evaluating structural heterogeneity using conventional separation techniques such as ion-exchange chromatography and capillary electrophoresis of therapeutic monoclonal antibodies (mAbs). One of the remaining challenges for the practical use of the MAM is reliable and robust continuous monitoring. In this study, we successfully established an automated sample preparation system as a solution to this issue. Through method optimization, we confirmed that the peptide purification step using a solid-phase extraction column, which is usually performed after the digestion step, was not mandatory and that the addition of methionine as an oxidation inhibitor was able to significantly reduce artificial oxidation. Importantly, the use of our system enabled high-precision analysis for targeted peptide monitoring without relying on the operator’s knowledge and experience with peptide mapping using liquid chromatography/mass spectrometry (LC/MS). Our system could also be useful as a platform approach for targeted peptide monitoring in MAM workflow of traditional IgG-type mAbs. Furthermore, using common samples that were prepared using the automated system, we assessed the compatibility of LC/MS system in the targeted peptide monitoring via a collaborative study with MS vendors. The results showed that there was no significant difference in the mass accuracy, repeatability of the peak retention time and variations of intermediate precision of the measurement values among the four LC/MS systems, suggesting sufficient compatibility among the LC/MS systems. MAM system using our automated sample preparation method, which had high intermediate precision, will be useful for release and stability testing as well as characterization and manufacturing process development.