Machine Learning Approaches for Protein Engineering: Part 1 banner

Part 1 of the PEGS Europe machine learning program delves into essential strategies and best practices small and large research groups need to employ as they strive to use machine learning tools to accelerate and optimize biologics drug discovery and development. We will explore the pros and cons of different approaches for developing and accessing high quality training data and then consider ways of using methods for “out of set” predictions that present new opportunities for ML-based studies arising out of known antigens, structures and successful campaigns. And to empower smaller companies working to compete with the substantial resources of major research organizations, a session will showcase the workflows, capabilities and successes of a set of emerging biopharma companies structured around the use of ML/AI tools as a primary R&D paradigm.

Recommended Short Course*
Monday, 4 November, 14:00 – 17:00
SC4: In silico and Machine Learning Tools for Antibody Design and Developability Predictions
*Separate registration required. See short courses page for details. All short courses take place in-person only.





For more details on the conference, please contact:

Kent Simmons
Senior Conference Director
Cambridge Healthtech Institute
Phone: (+1) 207-329-2964
Email: ksimmons@healthtech.com

For sponsorship information, please contact:

Companies A-K
Jason Gerardi
Sr. Manager, Business Development
Cambridge Healthtech Institute
Phone: (+1) 781-972-5452
Email: jgerardi@healthtech.com

Companies L-Z
Ashley Parsons
Manager, Business Development
Cambridge Healthtech Institute
Phone: (+1) 781-972-1340
Email: ashleyparsons@healthtech.com