Main Article Content
Abstract
Biopharmaceuticals have revolutionized the treatment of many diseases especially monoclonal antibodies (mAbs). Nevertheless, their very structural complexity poses great problems of analytical characterization and quality control (QC). The old fashion method, based on a big panel of single attribute measurements, is frequently both labour-intensive, time consuming and offers an oblique perspective of a product quality. Multi-Attribute Method (MAM) has become an innovative mass spectrometry (MS)-based platform, which can determine and measure dozens of care-giving quality attributes (CQAs) in an individual, centralized test. In this review I have described the fundamentals of MAM, preparation of the samples, analysis using LC-MS and data processing. We discuss the whole spectrum of CQAs that can be further thorough and comprehensively, such as product identity, post-translational changes (PTMs) such as deamidation, oxidation, and glycosylation and process related impurities. Moreover, we talk about the feasible aspects of the application and experimental validation of the MAM in a regulated cGMP facility and clarify its benefits in comparison to the traditional ones and the present-day view held by regulatory bodies. Lastly, we discuss potential opportunities and challenges that stand out and wait in the future, where automation, machine learning, and expansion into new modalities will reinforce MAM even more as a staple of current biopharmaceutical development and QC.