In this episode of Global Trial Accelerators, we speak with Daniel S. Chen, MD, PhD, Founder and CEO of Synthetic Design Lab and former Global Head of Cancer Immunotherapy Development at Genentech/Roche.

Daniel shares insights from his pioneering work in cancer immunotherapy, the development of breakthrough therapies such as atezolizumab, and the future of oncology innovation. We also discuss the Cancer-Immunity Cycle, translational science, and what it takes to accelerate the path from discovery to patient impact.

Shareef Mahdavi joins the podcast to discuss how patient experience directly impacts practice growth, referrals, and retention. He shares the strategies that helped transform Laser Eye Center of Silicon Valley by improving how patients felt throughout their journey — leading to stronger reviews, increased leads, and long-term growth.

In this episode, we sit down with Dr. Joseph Geraci — mathematical physicist, medical scientist, and AI innovator — to explore how artificial intelligence is transforming the future of medicine and clinical research.

Dr. Geraci began his career in quantum computing and mathematical physics, earning his PhD under renowned scientist Dr. Daniel Lidar with research supported by DARPA and the U.S. Army’s Disruptive Technology Office. He later expanded his work into artificial intelligence for medicine, oncology, and neuroscience, where he uncovered a critical problem in modern healthcare: traditional disease labels often fail to capture the true complexity and diversity of patients.

This realization led him to found NetraMark and develop NetraAI, a groundbreaking AI platform designed to learn from small, noisy clinical datasets. Using a novel mathematically-augmented framework and long-range memory mechanisms, NetraAI can identify hidden and explainable patient subpopulations with extraordinary precision — helping pharmaceutical companies improve clinical trial outcomes and better match treatments to the patients most likely to benefit.

In this conversation, Dr. Geraci shares insights on quantum algorithms, machine learning, the limitations of modern clinical trials, and how explainable AI could redefine our understanding of disease, health, and intelligence itself.