The Multi-Attribute Method (MAM), An Advanced LC-MS Approach for Protein A Resin Performance and Lifecycle Evaluation

Area of Science:

• Biopharmaceutical Manufacturing
• Analytical Chemistry
• Chromatography

Background:

• Protein A resins are critical for monoclonal antibody (mAb) production but lack direct, quantitative assessment methods.
• Current methods for evaluating Protein A resin condition are often indirect or qualitative.

Purpose of the Study:

• To adapt the multi-attribute method (MAM) as a unified liquid chromatography-mass spectrometry (LC-MS) platform for Protein A resin analysis.
• To establish a comprehensive strategy for Protein A resin lifecycle management.

Main Methods:

• Systematic adaptation of MAM for Protein A resin analysis using LC-MS.
• Evaluation of four Cytiva Protein A resins (MabSelect™, MabSelect SuRe™, MabSelect SuRe™ LX, MabSelect™ PrismA).
• Assessment of resin identity, Protein A ligand integrity, fouling, and cleaning performance.

Main Results:

• MAM enabled resin-specific peptide fingerprinting and quantitative monitoring of Protein A ligand post-translational modifications (PTMs).
• Analysis revealed ligand degradation and fouling in used resins, with MabSelect™ being most susceptible.
• Direct detection and quantification of residual mAbs and host cell proteins (HCPs) from the resin matrix were achieved.

Conclusions:

• MAM is established as a novel, sensitive, and comprehensive strategy for Protein A resin lifecycle management.
• The method provides actionable insights for resin selection, cleaning optimization, and downstream process development.
• MAM offers molecular-level assessment of resin cleaning effectiveness, surpassing conventional approaches.