Chemomics: Turning Screening Data Into Discovery Direction

Chemomics brings computation and DEL-scale data together to give discovery teams immediate clarity on what a target favors, rejects, and tolerates. Instead of stopping at hit identification, this approach uses every datapoint—positive and negative—to generate predictive maps, pharmacophores, and early mechanism-of-action insights that traditionally take years of SAR work to achieve. Millions of datapoints from diverse, drug‑like libraries feed machine‑learning models that have already delivered new chemotypes and validated inhibitors across demanding targets such as ERα, DCAF1, and WDR91. The result is a strategy-first foundation: high-confidence hits, fewer false starts, and rapid progression toward optimized compounds.

Gain a deeper look at the predictive power behind this data-driven methodology