Therapeutic proteins exhibit complex structural heterogeneity arising from glycosylation, post-translational modifications, sequence variants, and product-related impurities. This project will develop computational methods for interpretation of high-resolution mass spectrometry data to characterize these critical quality attributes. The research will integrate machine learning, statistical analysis, and computational mass spectrometry to enable robust and scalable analytical workflows for biopharmaceutical development.