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<p>The multi-attribute method (MAM), leveraging high-resolution mass spectrometry (HRMS), has become a revolutionary platform for the simultaneous assessment of multiple critical quality attributes (CQAs) in monoclonal antibodies (mAbs). By integrating peptide mapping with targeted and untargeted analyses, MAM facilitates accurate identification of product variants, post-translational modifications, and sequence variants, hence diminishing dependence on several orthogonal tests. This review analyzes recent advancements in MAM workflows, including automation, advanced data analytics, and hybrid methodologies that integrate orthogonal techniques like Raman spectroscopy and hydrogen–deuterium exchange mass spectrometry (HDX-MS). Regulatory perspectives from the U.S. Food and Drug Administration (FDA), European Medicines Agency (EMA), and International Council for Harmonisation (ICH) are examined concerning analytical validation, system suitability, and implementation in biopharmaceutical quality control. Key challenges, including data standardization, regulatory harmonization, and implementation in current good manufacturing practice (cGMP) environments, are critically evaluated. MAM represents a robust, scalable, and regulatory-compliant methodology that can enhance biopharmaceutical characterization, facilitate real-time release testing, and expedite the provision of high-quality monoclonal antibody therapies.</p> Graphical abstract <p></p>

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Multi-attribute method for simultaneous monitoring of critical quality attributes in monoclonal antibodies: advances, challenges, and regulatory perspectives

  • 期刊论文

  • 发表日期：

    2025年11月20日

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  • Sameer Kumar Singdevsachan,
  • Ravindra Singh Rawat,
  • Sanjay S. Gottipamula,
  • Sathyabalan Murugesan

摘要

The multi-attribute method (MAM), leveraging high-resolution mass spectrometry (HRMS), has become a revolutionary platform for the simultaneous assessment of multiple critical quality attributes (CQAs) in monoclonal antibodies (mAbs). By integrating peptide mapping with targeted and untargeted analyses, MAM facilitates accurate identification of product variants, post-translational modifications, and sequence variants, hence diminishing dependence on several orthogonal tests. This review analyzes recent advancements in MAM workflows, including automation, advanced data analytics, and hybrid methodologies that integrate orthogonal techniques like Raman spectroscopy and hydrogen–deuterium exchange mass spectrometry (HDX-MS). Regulatory perspectives from the U.S. Food and Drug Administration (FDA), European Medicines Agency (EMA), and International Council for Harmonisation (ICH) are examined concerning analytical validation, system suitability, and implementation in biopharmaceutical quality control. Key challenges, including data standardization, regulatory harmonization, and implementation in current good manufacturing practice (cGMP) environments, are critically evaluated. MAM represents a robust, scalable, and regulatory-compliant methodology that can enhance biopharmaceutical characterization, facilitate real-time release testing, and expedite the provision of high-quality monoclonal antibody therapies.

Graphical abstract