Directed Evolution (DE) is a method developed by Nobel laureate Frances Arnold to improve protein fitness for specific applications. However, DE can be less efficient when mutations show epistatic behavior, meaning the effect of one mutation depends on others. A newer approach, Active Learning-assisted Directed Evolution (ALDE), incorporates machine learning into the DE process to address this issue. ALDE uses uncertainty quantification to guide the protein search space exploration more efficiently than traditional DE.

In this GEN webinar, Ravi Goel Lal from the Arnold lab at Caltech will present the basics and applications of ALDE. He will be joined by Dr. Galit Meshulam-Simon, Associate Director of Commercial Applications at Elegen, who will discuss how next-generation DNA synthesis supports this research.