A Robust and Sensitive New Peak Detection and Identification Method for Mass Spectrometry-Based Differential Analysis in Biologics Characterization

Abstract

New peak detection (NPD) is a significant component of the multiattribute method (MAM) for MS use to facilitate the detection of quality attributes exhibiting abnormal ratio changes, vanishing attributes, or newly emerging attributes. However, challenges remain to get a balanced sensitivity and minimize false positives in NPD. In this study, we have developed a robust NPD and identification method to enhance sensitivity 10-fold (0.5% spike-in) compared to previously reported work while maintaining controlled false positives via a statistics-driven experimental design utilizing three control samples and a product-specific peptide library. This method not only enables MAM to replace conventional analytical methods for quality attribute control, but also provides a new and objective way of performing differential analysis of LC-MS-based experiments at different stages of the biopharmaceutics process development.