When Spectra Speak: Letting AI Read the Fine Print of Biologics

Biologic characterisation has historically relied heavily on spectroscopy, which transforms chemical complexity into comprehensible fingerprints. Through the careful use of AI, supported by strict data procedures and scientific supervision, these fingerprints may be read more quickly & thoroughly.

- By Dr Anirban Mudi, Lead Platform Product Manager – Next Gen & AI, IDBS, Bangalore and Prof. Ashutosh Kumar, Department of Biosciences and Bioengineering, IIT Bombay

Biologics—complex therapeutic proteins such as monoclonal antibodies, peptide hormones, insulin & its analogs, and engineered enzymes—represent some of the greatest advances in modern medicine. Their ability to precisely target disease pathways has transformed treatments for cancer, autoimmune disorders, and metabolic conditions. Yet the very complexity that makes biologics so effective also makes them difficult to fully characterise and control. Unlike small-molecule drugs, whose chemical structures are relatively simple, reproducible, and easy to verify, biologics are produced inside living cells and therefore carry subtle variations. Small differences in protein folding, glycosylation patterns, or early signs of aggregation can meaningfully alter a drug's safety profile, half-life, or efficacy. Detecting these shifts is critical to ensuring that every batch released to patients meets rigorous quality standards.