Personalized Treatment Selection

This application area focuses on selecting the most effective therapy regimen for an individual patient based on their unique clinical, molecular, and functional data, rather than relying on population‑level protocols. It encompasses both predicting disease risk and progression, and—critically—matching each patient to the drugs or combinations most likely to work for them while minimizing toxicity. In functional precision medicine, this can include testing many therapies directly on patient‑derived cells and using computational models to interpret the results. It matters because traditional one‑size‑fits‑all treatment approaches lead to trial‑and‑error care, delayed or missed diagnoses, unnecessary side effects, and poor outcomes for complex, rare, or relapsed conditions like pediatric cancers. By integrating large‑scale clinical records, omics data, imaging, and ex vivo drug response profiles, advanced analytics can quickly surface optimal, personalized treatment options at scale, improving survival rates, reducing adverse events, and shortening time to effective care.