Validating AI/ML Models for Structural Biology Through Benchmarking & Experimental Validation to Separate Actionable Tools from Hype
9:00 am - Wednesday 3rd February 2027
- Benchmarking AI/ML models against relevant structural biology datasets to understand how performance varies across applications, targets, and data types
- Combining computational predictions with wet-lab validation to determine whether model outputs translate into experimentally meaningful improvements
- Establishing robust validation frameworks for AI adoption to give discovery teams greater confidence when selecting tools and investing them into SBDD workflows
