Poster
in
Workshop: Generative AI and Biology (GenBio@NeurIPS2023)
Targeting tissues via dynamic human systems modeling in generative design
Zachary Fox · Nolan English · Belinda S Akpa
Keywords: [ genetic algorithms ] [ physiological modeling ] [ language models ] [ Drug Discovery ]
Drug discovery is a complex, costly process with high failure rates. A successful drug should bind to a target, be deliverable to an intended site of activity, and promote a desired pharmacological effect without causing toxicity. Typically, these factors are evaluated in series over the course of a pipeline where the number of candidates is reduced from a large initial pool. One promise of AI-driven discovery is the opportunity to evaluate multiple facets of drug performance in parallel. However, despite ML-driven advancements, current models for pharmacological property prediction are exclusively trained to predict molecular properties, ignoring important, dynamic biodistribution and bioactivity effects.