Tuğba Ören Varol

Closing the Translational Gap: Closed‐Loop AI Discovery Frameworks for Experimental Validation and Clinical Implementation in Cancer Therapeutics

It is proposed that the translational potential of AI in oncology is substantially shaped by the rigor of the experimental feedback loops that constrain and refine it, thereby accelerating the delivery of more effective, personalized therapies validated through the complete hierarchy of in vitro assays, in vivo PDX models, and prospective clinical trials to patients.