Accelerating lead discovery via completion of DMTA cycles: multi-property optimization powered by ultra-large virtual libraries and generative AI

• Unité de recherche: INNOSUISSE
• Numéro de projet: 128.872 INT-ICT
• Titre du projet anglais: Accelerating lead discovery via completion of DMTA cycles: multi-property optimization powered by ultra-large virtual libraries and generative AI

Mots-clé (Anglais)

ICT, Machine learning, Chemical biology, Automation

Résumé des résultats (Abstract) (Anglais)

This project accelerates hit identification and lead optimization in drug design by integrating physics-inspired generative AI, multi-objective optimization, ultra-large virtual libraries, automated synthesis, and experimental validation in a closed-loop system.