Presented at ASMS 2019, Atlanta, GA, USA
Sequence variants (SVs) are protein species that contain unintended changes to the target amino acid sequence. Their presence can adversely affect the safety and efficacy of biopharmaceuticals, and consequently an analytical method that enables sensitive detection of SVs would represent an important component of product quality monitoring processes. Mass spectrometric methods enable identification of SVs, but current approaches create large numbers of false positive identifications. Here we present an automated processing workflow for LC-MS/MS data that delivers comprehensive characterization and sensitive quantification of sequence variants and an effective strategy for minimizing false positive and false negative identifications.