Multi-Attribute Method Development and Validation for Synthetic Peptide Impurity Monitoring toward GMP Release Testing

Synthetic peptide therapeutics exhibit highly heterogeneous impurity profiles containing numerous structural and sequence-related species that require stringent analytical control to ensure safety, efficacy, and manufacturing consistency. Conventional UV-based release methods and two-tier LC-UV/LC-MS workflows suffer from coelution ambiguities and cross-method inconsistencies, complicating impurity identification and quantitation. The multi-attribute method (MAM) comprises amino-acid-level impurity characterization, targeted quantitation of product quality attributes, and new peak detection (NPD) as a differential analysis against a reference standard to detect the presence, absence, or change in abundance of any species. Here, we present a multi-attribute method (MAM)-based approach specifically for synthetic peptide impurity monitoring, combining both targeted quantitation of specified impurities and new peak detection (NPD) for unspecified impurities within a single LC-MS workflow that was developed and validated for GMP release testing for a synthetic therapeutic peptide. The MAM workflow leveraged extracted ion chromatograms for specified impurity assignment and quantitation, while non-targeted MS processing enabled NPD-based detection of unspecified impurities exceeding method reporting thresholds. Development mode validation demonstrated satisfactory analytical performance across sensitivity, accuracy, precision, and specificity. Key technical considerations overcome in this workflow include reliable LC-MS discrimination of near-isobaric impurities and optimization of charge-state and isotope peak selection. By consolidating targeted and non-targeted impurity monitoring into a single workflow, this approach eliminates the cross-method inconsistencies inherent to conventional two-tier methods while improving analytical efficiency and specificity through orthogonal retention time and accurate mass discrimination. The workflow was demonstrated on a single synthetic peptide drug substance, with potential applicability to other synthetic modalities yet to be evaluated.