To leverage AI in the transformation of the next-generation drug discovery technologies, the use of biologically relevant cell-based assays to generate high-quality data with fast turnaround is crucial. Identifying disease-relevant cell lines to use and pathways to measure as readouts is essential. Additionally, pinpointing specific pathogenic target isoforms is vital for each specific program. Besides, developing assays that maximize assay window, consistency, and reliability is also key, along with incorporating counter screen assays to eliminate false positives.
After a screening cascade or funnel is established upfront, it is iteratively utilized throughout target validation, compound screening, hit identification, hit-to-lead, and lead optimization stages. The quality and consistency of assay results can provide real-time feedback to AI algorithms, enabling fast and more accurate predictions of molecules with more and more improved efficacy, potency, specificity and safety. Faster data generation enhances the power of AI and machine learning, making the drug discovery process more efficient and sustainable with increased success rates at each step.