Machine Learning Approaches for Protein Engineering

The incorporation of machine learning, AI tools, and generative as well as protein language models will have a tremendous impact on the field of protein engineering but has also sparked a heated debate into which methods save time and money vs. have the opposite effect of adding inefficiencies and uncertainty to the process. Historically, drug discovery and development processes have been fraught with inefficiencies due to the lack of predictive tools. Machine learning and AI have the capacity to completely change the way protein structures and biologics will get predicted, discovered, designed, and optimized in the future, but it remains imperative to evolve and adapt them for use in antibody and protein engineering. Join the esteemed faculty of the 3rd Annual Machine Learning Approaches for Protein Engineering conference at PEGS Boston to transform the process of antibody development and improve success rates.