Multi-attribute method (MAM) to assess analytical comparability of adalimumab biosimilars

Abstract

Adalimumab drug product (Humira ®), the first fully human monoclonal antibody (mAb) approved by FDA in 2002, led the top ten list of best-selling mAbs in 2018 and has been the most profitable drug in the world. With the expiration of patent protection in Europe in 2018 and in United States by 2023, the landscape is changing as up to 10 adalimumab biosimilars are expected to enter the market in the US. Biosimilars offer the potential to lower costs on health care systems and increase patient accessibility. The analytical similarity of seven different adalimumab biosimilars was accomplished in the present study using the multi-attribute method (MAM), a LC-MS based peptide mapping technique that allows for primary sequence assessment and evaluation of multiple quality attributes including deamidation, oxidation, succinimide formation, N- and C- terminal composition and detailed N-glycosylation analysis. In the first step, characterization of the most relevant post-translational modifications of a reference product was attained during the discovery phase of MAM. During the second step, as part of the MAM targeted monitoring phase, adalimumab batch-to batch variability was evaluated to define statistical intervals for the establishment of similarity ranges. The third step describes biosimilarity evaluation of predefined quality attributes and new peak detection for the assessment of any new or modified peak compared to the reference product. This study highlights a new perspective of the MAM approach and its underlying power for biotherapeutic comparability exercises in addition to analytical characterization. MAM offers a streamlined comparability assessment workflow based on high-confidence quality attribute analysis using high-resolution accurate mass mass spectrometry (HRAM MS) and the capability to detect any new or modified peak compared to the reference product.

Keywords: Adalimumab; Biosimilars; Biotherapeutics; Critical quality attributes; HRAM MS; MAM.