How do you predict the future of disease - and what happens when the most important variables aren’t the ones we assume matter most?

On this episode of The Emerging Scholar Podcast, host John McGavock sits down with Dr. Navdeep Tangri, nephrologist, clinician scientist, and creator of the Kidney Failure Risk Equation (KFRE), one of the world’s most widely used tools for predicting kidney failure.

What began as a deceptively simple question from patients, became a global scientific challenge. In a field driven by diabetes and hypertension, Dr. Tangri made a bold and counter-intuitive decision: leave both out of the prediction model. Why? Because in predictive epidemiology, causation is not the same as prediction—and variables that cannot be measured reliably may not belong in the equation at all.

From a math-minded medical student experimenting with neural networks in 2001 to publishing a landmark paper in JAMA, Dr. Tangri shares the story behind KFRE: how it was built, validated across 30 countries, integrated into global electronic medical records, and took 13 years to reach clinical practice guidelines.

Along the way, this episode becomes something bigger than kidney disease. It’s a masterclass in predictive epidemiology, implementation science, mentorship, and what it really takes to move research from paper to practice. Dr. Tangri also looks ahead to the future of AI in medicine, why lab-based prediction may outperform intuition, and how new technologies could make kidney disease remission - not just slowing progression - the new standard of care.

For emerging scholars, this is also a story about curiosity, persistence, and the long road between discovery and impact - and why, as Dr. Tangri puts it, great researchers are ultimately trying to bring tomorrow’s care, today.