Building End-to-End Experimental Workflows for Predictive Drug Discovery by Fueling AI With High-Quality Biophysical Data
- Show how integrated biophysical and analytical platforms generate model-ready datasets across discovery and development
- Share strategies for combining NMR, SPR/BLI, solution-phase measurements, and developability profiling to power ML-driven cycles
- Discuss practical considerations for data quality, reproducibility, and workflow scalability in AI-enabled drug discovery