Strategies and Use Cases of ML/AI Across Biopharmaceutical R&D

The 2027 PEGS Machine Learning Stream offers three programs focusing on practical applications of the use of ML/AI tools in the research and development of biologic drugs. The first track looks at how labs are using automation and machine learning in analytical and CMC development, from high-throughput mass spec to real-time release testing, and what it takes to validate these tools against real results. Midweek, the second track explores computational approaches to predicting immunogenicity, including structure-based methods and models built for regulatory scrutiny. And the third track focuses on the discovery and engineering stages, where generative models and improved developability metrics are changing how molecules get designed and screened. Collectively, this stream charts the rapidly expanding role of AI/ML, simulation, and computational design in accelerating biologic drug development.

Conferences Include:

May 10-11

ML and Digital Integration in Biotherapeutic Analytics