Cambridge Healthtech Institute’s 2nd Annual

Machine Learning Approaches for Protein Engineering

Balancing Theory with Practice

May 18-19, 2023

The arrival of machine learning and AI tools promise to have a tremendous impact on the field of protein engineering. Drug discovery and development processes are fraught with inefficiencies due to the lack of predictive tools. For machine learning and AI to truly change the way drugs will get discovered, designed, and optimized in the future, there is much that needs to be learned about how to adapt them for use in antibody discovery, training set development, prediction, screening, simulation, and optimization. Join the esteemed faculty of the 2nd Annual Machine Learning Approaches for Protein Engineering conference at PEGS Boston to learn how to transform the process of antibody development and ultimately improve success rates.

Coverage will include, but is not limited to:

Adapting machine learning for antibody discovery and humanization
Developing rules and benchmarks for developability
Creating training sets for directed protein evolution
Predicting antibody developability from sequence using machine learning
Use cases of machine learning in protein engineering

The deadline for priority consideration is October 21, 2022.

All proposals are subject to review by session chairpersons and/or the Scientific Advisory Committee to ensure the overall quality of the conference program. Additionally, as per Cambridge Healthtech Institute’s policy, a select number of vendors and consultants who provide products and services will be offered opportunities for podium presentation slots based on a variety of Corporate Sponsorships.

Opportunities for Participation: