Accelerating Covalent Drug Design by Improving Prediction of Binding Reactivity & Reducing Experimental Iteration Through Physics-Based & Data-Driven Models
- Assessing strengths and limitations of QM informed, physics based and ML driven approaches for modelling covalent systems
- Comparing predictive performance for reaction feasibility, binding geometry and adduct stability
- Integrating computational predictions with experimental validation to reduce synthesis burden and cycle time