From Models to Medicine

In this episode, we sit down with Dr. Freddy Nguyen, CEO and co-founder of Nine Diagnostics, whose background spans medicine, pathology, optics, and nanotechnology. Freddy shares how Nine Diagnostics is building a multiomics platform that helps cancer patients find out within days whether their treatment is actually working. We dig into why AI's real power in medicine lies in its ability to connect siloed data across molecular readouts, imaging, and clinical context, and why treating patients as more than just their diagnosis is the only way to build tools that actually hold up in the real world. We also get into the harder conversation: where AI in clinical workflows breaks down. It's a candid, technically grounded conversation about what equitable AI in medicine actually requires.

What does it actually take to make AI work inside a pharmaceutical company and why do so many efforts stall after the model is built? Pranay Mohanty, from J&J Innovative Medicine, joins us to talk about how building the model is only one part of the work and what can happen when you try to apply that model to messy, real-world data.We dig into how teams are starting to use digital twins to simulate patients and rethink trial design, what it looks like to work alongside regulators like the U.S. Food and Drug Administration, and why keeping a human in the loop isn’t optional. Along the way, we share how AI is actually shaping portfolio decisions today and where the limits still are.

What does emergency medicine have to do with large-scale knowledge systems? Jason Grafft joins us to talk about his non-linear path from EMS and simulation education to knowledge engineering and why the structured, fact-bound thinking that medicine demands is one of the most undervalued assets in the AI era. We dig into how he uses graph-based models to bridge clinical experts and technical systems, where LLMs are actually helping in entity resolution, and the practical advice he gives every clinician trying to break into tech.

As pathology labs digitize, how do skilled practitioners learn to trust AI with patient diagnoses? Michael Rivers discusses the critical importance of "explainable AI," keeping the human pathologist in the loop with the ability to override algorithms, and how these powerful new technologies will help address the global shortage of pathologists, ultimately bringing equitable, expert care to patients worldwide.

Welcome to From Model to Medicine, a podcast from KAMI Think Tank exploring how artificial intelligence is actually being applied across the life sciences industry.Each episode, we speak with scientists, operators, and leaders working at the intersection of AI and biology, from drug discovery and clinical development to regulatory operations and beyond.KAMI Think Tank is an educational organization that helps life science professionals learn how to use AI practically in their day-to-day work.This podcast is about moving past the hype and understanding what it actually takes to bring AI from promising models to real impact in medicine.We’re your hosts, Kamayani Gupta and Michelle Yi. This is From Model to Medicine.