Cancer immunotherapy has transformed oncology, yet many patients still don't respond or develop resistance to these treatments. Meanwhile, AI has generated unprecedented libraries of potential targets, but the ecosystem has become siloed. Discovery teams excel at identifying promising mechanisms but struggle with clinical prioritization, while drug developers want novel assets but lack visibility in the AI platform rationale. The result? Promising targets are left unused, clinical programs pursue the wrong targets, and money is wasted. The missing piece isn't more AI; it's multidisciplinary collaboration across the entire development continuum. This panel convenes leaders spanning discovery, development, diagnostics, business development, and investment to address a fundamental question - how do we build teams and partnerships that enable true end-to-end AI-driven drug development?