No abstract

The multi-attribute method (MAM), a liquid chromatography-mass spectrometry (LC-MS)-based peptide mapping method, has gained increased interest and applications in the biopharmaceutical industry. MAM can, in one method, provide targeted quantitation of multiple site-specific product quality attributes, as well as new peak detection. In this review, we focus on the scientific and regulatory considerations of using MAM in product quality attribute monitoring and quality control (QC) of therapeutic proteins. We highlight MAM implementation challenges and solutions with several case studies, and provide our perspective on the opportunities to use MS in QC for applications other than standard peptide mapping-based MAM.

New peak detection (NPD), as part of the LC–MS-based multi-attribute method (MAM), allows for sensitive and unbiased detection of new or changing site-specific attributes between a sample and reference that is not possible with conventional UV or fluorescence detection-based methods. MAM with NPD can serve as a purity test that can establish whether a sample and the reference are similar. The broad implementation of NPD in the biopharmaceutical industry has been limited by the potential presence of false positives or artifacts, which increase the analysis time and can trigger unnecessary investigations of product quality. Our novel contributions to the success of NPD are the curation of false positives, use of the known peak list concept, pairwise analysis approach, and the development of a NPD system suitability control strategy. In this report, we also introduce a unique experimental design utilizing sequence variant co-mixes to measure NPD performance. We show that NPD has superior performance relative to conventional control system methods in the detection of an unexpected change as compared with the reference. NPD is a new frontier in purity testing that reduces subjectivity, need for analyst intervention, and potential for missing unexpected product quality changes.