Beyond Screens: AI & Active Learning for Smarter Target Identification in Proximity Drug Discovery
Time: 8:00 am
day: Day One
Details:
- How to use AI-driven modeling to uncover and validate novel drug targets, including historically undruggable proteins like transcription factors?
- How to apply active learning to prioritize the most promising targets by continuously refining biological insights through iterative prototype-test cycles, to accelerate the discovery of clinically viable drug targets?
- How to integrate multimodal machine learning to identify high-value targets by analyzing structural, sequence, and functional data simultaneously?
- How to enhance target identification by embedding real-world biological constraints, ensuring AI-generated targets are clinically relevant and actionable?