ReviewPharmaceuticals (Basel, Switzerland)2026
Protein Therapeutic Quality Control Using Multi-Attribute Method (MAM): Challenges and Current Practice in cGMP Environments.
Review in Pharmaceuticals (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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8 authors.
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Abstract
The increasing complexity of modern protein therapeutics and the demand for faster development of new therapeutics require not only advanced analytical tools that provide in-depth understanding of the product quality attributes (PQAs) that are crucial for safety and efficacy but also the implementation of a control strategy to ensure that the released drug product meets the desired quality profile. The multi-attribute method (MAM), a liquid chromatography-mass spectrometry (LC-MS) approach, has emerged as a transformative solution that provides site-specific monitoring of multiple critical quality attributes (CQAs) in a single workflow, replacing several conventional profile-based assays. The MAM achieves comprehensive quality oversight through two primary mechanisms: targeted attribute quantitation (TAQ) for the simultaneous quantification of predefined known modifications, and new peak detection (NPD) for identifying unforeseen impurities, thereby establishing a robust, "double-layered" control strategy. This article reviews the practical challenges and current industry practices for successfully implementing the MAM within current good manufacturing practice (cGMP) environments. The successful transition of the MAM from a specialized characterization tool to a validated quality control (QC) cornerstone relies on a framework built upon four foundational pillars: stringent instrument qualification paired with compliance-ready informatics, proactive and strictly scheduled instrument maintenance, rigorous system suitability testing (SST), and phase-appropriate method validation and transfer. The challenges of global method transfer and the solutions to mitigate inter-laboratory variability are discussed. Finally, the review explores the emerging trends shaping the future of the MAM in QC and the critical role of the MAM in facilitating real-time release testing (RTRT) in next-generation autonomous manufacturing.
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