Development of optimised separative (SEC) methods for harmonising Quality Control of Monoclonal Antibodies: an exploratory journey

Biotechnological drugs are pharmaceutical products made using living cells or organisms to produce complex therapeutic molecules like proteins and antibodies. These molecules are particularly vulnerable to structural modifications induced by environmental stressors during manufacturing, formulation, and storage, which can impact their efficacy, safety, and immunogenicity. Comprehensive characterization using orthogonal analytical techniques is essential to monitor structural integrity, functional activity, and physicochemical parameters. Size-based separation techniques are particularly important as fragments and aggregates are often present in these large molecules. These product-related impurities are frequently assigned as being critical quality attributes (CQAs). Size exclusion chromatography (SEC) is a cornerstone analytical tool extensively utilized for biopharmaceutical characterization, particularly for monitoring aggregation and molecular size distribution in mAbs. SEC is routinely integrated into development workflows, stability assessments, and lot release testing to ensure product consistency, efficacy, and safety. Analytical Quality-by-Design (AQbD) provides a structured, systematic approach to analytical method development aimed at ensuring method fitness for intended use across its entire lifecycle. By integrating risk assessment, design of experiments (DoE), and thorough method understanding, AQbD enhances method robustness and facilitates regulatory compliance The aim of this study was the development of an analytical platform for the separation of mAbs size variants by SEC analysis applying AQbD approach. This presentation will detail the development of a robust SEC method guided by AQbD principles, including method risk assessment, experimental design strategies, and critical method attribute optimization. Challenges faced, methodological refinements, and resulting improvements in method robustness and reliability will be discussed.