Multi-Parameter Optimization Guided by Explainable AI (Xai), Generative Chemistry & Physics-Based Ensemble Modeling: Shortening the Path from Hit-to-Lead Using Revenir

  • Uncover how the Revenir drug discovery platform integrates molecular dynamics, ensemble pocket discovery, and collects AI-driven analytics to accelerate structure function understanding
  • Using two case studies to demonstrate how an explainable ML framework identifies atomic drivers of potency and liabilities to guide medicinal chemistry optimization
  • Explore how generative design powered by Revenir data enables the rapid discovery of novel, experimentally validated small molecules