Dr. Freddy Nguyen, a physician-scientist-entrepreneur and Director of MIT’s Catalyst Scholars Program, discusses his work at the frontier of translational research, diagnostics, precision medicine and healthcare innovation with Pit HexAI host Jordan Gass-Poore' and his involvement in co-founding Nine Diagnostics, a startup spun out of Memorial Sloan Kettering Cancer Center.

Focusing on innovation in precision medicine, Dr. Nguyen traces his path through initiatives like MIT Hacking Medicine and the MIT Catalyst Scholars Program and his work helping teams identify and turn real clinical problems into projects designed to reach patients. Emphasizing patient‑first and science‑first approaches to innovation, Dr. Nguyen encourages students and collaborators to ask why things work the way they do and to build solutions that can move quickly from lab to clinic. That same mindset underpins Nine Diagnostics, which uses a high‑throughput nanosensor platform to generate molecular “fingerprints” of disease. Instead of tracking a few isolated biomarkers, these fingerprints capture complex patterns across thousands of molecules, reflecting both tumor biology and the broader physiological context of each patient. This shift from genomics alone to “functional precision medicine” enables clinicians and researchers to see what is happening in real time inside the body, monitor treatment response faster and tailor therapies more precisely to each patient.

Touching on how AI and machine learning are making these technologies clinically useful, Dr. Nguyen discusses how advanced algorithms integrate multimodal data streams to discover patterns that would be impossible to detect by eye. These models not only improve sensitivity and specificity when predicting treatment response, but also support emerging “digital twin” computational representations of patient health that can be used to simulate and optimize care. At the same time, he emphasizes that more data is not automatically better, and that explainable AI in healthcare must focus on which signals truly matter for a specific clinical decision and how to close the loop between model outputs and underlying biology.

For students and early‑career researchers, Dr. Nguyen shares practical guidance on getting involved in leveraging AI to advance precision medicine and designing research with translation in mind from day one so that innovations reach patients faster, rather than staying trapped in academic silos.