Opportunities to Harness AI and Machine Learning in Drug Discovery Toxicology
Tuesday, December 3, 2024
1:00 PM to 2:00 PM (US EST, UTC -5)
Hosted by: The SOT Regulatory and Safety Evaluation and Computational Toxicology Specialty Sections
Registration required for this free webinar.
Yodi Melnikov, PhD, is a principal data scientist in the safety assessment group at Genentech where he has focused on developing artificial intelligence and machine learning (AI/ML) models for early hazard identification in small molecule development. More recently, Yodi has been responsible for developing and optimizing bioinformatics pipelines for cross-species and cross-platform data inference in safety assessment, as well as data related data integrity and robust data inference work.
In this webinar, Dr. Melnikov will describe the various opportunities to leverage AI/ML in the drug discovery and development process to ultimately support decision making, improve efficiencies, and potentially reduce animal use. Case studies on modeling and practical application of toxicological endpoints ranging from simple single endpoint prioritization models like hERG, to more complex models combining data from multiple sources such as secondary pharmacology and drug induced liver injury, will be presented.
Speaker:
· Yodi Melnikov, PhD, Principal Data Scientist, Computational Toxicology, Genentech
Registration required for this free webinar.