Multi-attribute methods in antibody-drug conjugate characterization and quality control: Opportunities, challenges,...

Antibody-drug conjugates (ADCs) are complex biotherapeutics that combine the selectivity of monoclonal antibodies with the potency of cytotoxic payloads. Their structural heterogeneity, arising from variable conjugation sites, drug-to-antibody ratios (DAR), linker stability, and post-translational modifications, presents significant challenges for characterization and quality control. Multi-Attribute Methods (MAM), based on high-resolution mass spectrometry, have emerged as powerful tools to simultaneously identify and quantify critical quality attributes at multiple levels of analysis, including intact protein, subunits, and peptides. Compared with traditional assays such as capillary electrophoresis-sodium dodecyl sulfate, hydrophobic interaction chromatography, and Ion exchange chromatography, MAM offers higher specificity, sensitivity, and the ability to detect unexpected modifications in a single workflow. This review summarizes recent advances in the application of MAM to ADC development, highlighting strategies for monitoring DAR distribution, conjugation site occupancy, and stability of linkers and payloads. We also discuss challenges in method qualification, data handling, and regulatory acceptance, along with the potential of automation and machine learning to support large-scale implementation. Finally, we explore the future outlook of MAM as an integrated platform method for ADCs characterization and quality control, with emphasis on its role in regulatory submissions and quality control release testing.