Ron Alfa of NOETIK AI appears on theCUBE Research at NYSE Wired to discuss the application of artificial intelligence, AI, to oncology. Alfa explains how NOETIK AI constructs datasets from patient tumor specimens and trains models that function as tumor digital twins, bridging clinical pathology and drug discovery languages. They address model generalization integration into clinical workflows while hosts Gemma Allen of NYSE Wired and theCUBE analysts John Furrier and Dave Vellante probe the technical approach dataset design and partnership strategy. Key takeaways include NOETIK AI's focus on increasing clinical trial success probability by pretraining models on thousands of patient tumors to improve patient selection and reduce downstream failure rates. Alfa emphasizes reliance on sample-derived biological data rather than patient health records describes a licensing and subscription agreement with GSK and outlines a roadmap to extend model coverage across all solid tumor oncology and integrate models into clinical decision workflows. This conversation provides practical insights for researchers clinicians and industry leaders interested in precision oncology tumor digital twins and AI-driven drug discovery.