Introducing Benchling Biologics: AI Infrastructure for Modern Antibody Discovery

Antibody programs look nothing like they did ten years ago. Teams have moved from mostly IgGs to bispecifics, multispecifics, nanobodies, and fusion proteins, while AI has become central to the DBTL loop. Most antibody software hasn't kept pace, which leaves data siloed and the relationships between sequence, protein, and experiment missing.

In this session, originally broadcast with DDW, Michael Strerath, Senior Scientific Director of Digital Transformation at Bayer, shares why his team moved off legacy systems in early 2025 and rebuilt their registration foundation on Benchling. He covers what drove the decision, how Bayer now represents formats, domains, and relationships, and where automation and scientific sanity checks have changed how scientists work day to day.

Lily Helfrich, Product Manager at Benchling, frames the shifting antibody landscape and the scientific fundamentals behind a modern data foundation for complex biologics, from mAbs to multispecifics. She also demos Benchling Biologics: an antibody-aware data model, no-code format configuration, and automated registration that connects sequence to protein to experimental context.