This Perspective reviews how AI is moving drug discovery from long, costly experimental pipelines toward earlier clinical translation, with an AI-designed TNIK inhibitor trial serving as an important proof-of-feasibility reference point. It argues that precision oncology could benefit from AI-driven integration of multi-omics, federated learning, and adaptive trial design, but only if validation, fairness, interpretability, and regulatory alignment improve.
To continue reading click here
