A Practical Roadmap for Implementing the LC-MS-Based Multi-Attribute Method for Analysis of Therapeutic Proteins

Background/Objectives: The mass spectrometry-based multi-attribute method (MAM) enables site-specific monitoring of multiple product quality attributes (PQAs) within a single LC-MS peptide mapping assay and is increasingly being adopted in biopharmaceutical development and quality control (QC). However, its analytical and operational complexities necessitate a structured approach to method development, qualification, system readiness, and assay transfer. This study presents a practical roadmap for implementing LC-MS-based MAM, aligned with USP-NF General Chapter ⟨1060⟩. Methods: Sample preparation and LC-MS acquisition parameters were optimized to minimize analytical artifacts and support robust workflow performance. System readiness was established using a publicly available monoclonal antibody reference standard. Adalimumab and etanercept were then used as representative biotherapeutics to evaluate key elements of MAM implementation, including qualification and interlaboratory transfer. Results: The refined workflow provided consistent digestion performance, chromatographic stability, mass accuracy, and reliable data processing across both molecules. Qualification studies demonstrated acceptable specificity, precision, sensitivity, and quantitative performance for targeted PQA monitoring, while new peak detection (NPD) assessments supported the detection of emerging or changing species. Interlaboratory transfer studies demonstrated successful transfer of the standardized workflow across laboratories and LC-MS platforms. Conclusions: These results establish a technical and operational foundation for MAM implementation, including system readiness, qualification, and assay transfer. The proposed implementation framework provides a robust and broadly applicable roadmap for MAM deployment across diverse biopharmaceutical programs while supporting subsequent product-specific refinement and validation for routine QC applications.