Understanding and Predicting Peptide Activity Using Artificial Intelligence Approaches
Ewa Lis
Founder/CTO, Koliber Biosciences Inc.
Artificial Intelligence (AI) is becoming widely adopted for small molecule drug discovery, yet the methods for leveraging AI for peptide drug discovery are lagging far behind. These challenges are primarily driven by limited availability of peptide datasets, high dimensionality of the design space as well as poorly developed methods for encoding peptides for deep learning algorithms. In this presentation we will discuss the advances that were made in developing feature encodings for peptides to enable development of high performing models and efficient exploration of peptide design space. We will demonstrate how AI can be utilized to prioritize peptide variants for testing through in silico prediction of performance. Moreover, methods to explain the models and visualize feature importance will be presented. Lastly, results from wet-lab validation experiments will be presented in the areas of immunogenicity and antimicrobial peptide development.
Ewa Lis Ph.D. is currently CTO of Koliber Biosciences, a San Diego based start-up developing an Artificial Intelligence Platform for Peptide Drug Discovery. Ewa specializes in developing features, encodings, and deep learning architectures suitable for solving biological data problems with machine learning. Prior to founding Koliber in 2014, Ewa held leadership positions at several companies including Life Technologies, Genomatica and Reveal Biosciences, where she developed innovative technologies from algorithms for pathology tissue classification to genome engineering research tools and microbially derived renewable chemicals. Ewa holds a BA in Chemistry from Cornell University and a Ph.D. in Biological Sciences from The Scripps Research Institute.