Summary
Machine learning models predicted the likelihood of clinical and regulatory success for drug candidates early in development. The platform provided transparent, explainable insights to support portfolio, licensing, and R&D decisions. It helped biopharma organizations reduce clinical risk and prioritize high‑potential assets. Scalable cloud infrastructure enabled reliable, data‑driven decision support across development stages.