CASSS AT Europe 2020
November 2, 2020
The presence of sequence variants (SVs)—protein species that contain unintended changes to the target amino acid sequence—can adversely affect the safety and efficacy of biopharmaceuticals. An analytical method that enables sensitive detection of SVs in biopharmaceuticals would represent an important component of product quality monitoring processes. Current MS-based approaches to identifying SVs have the drawback of creating large numbers of false-positive identifications that require time-consuming validation by expert users.
We present an effective strategy for minimizing false positive and false negative identifications within the framework of an automated processing workflow for LC-MS/MS data that delivers comprehensive characterization and sensitive quantification of sequence variants.