#113 Why AI Could Add Decades to Your Lifespan | Dr. Derya Unutmaz

Rhonda Patrick (0:00)

Welcome back to the podcast. Today, I'm joined by Dr. Derya Unutmaz, an immunologist and aging researcher at the Jackson Laboratory. His work spans immune biology, chronic disease, cancer, aging, and increasingly artificial intelligence. Especially relevant to today's conversation, Derya is also a scientific collaborator with OpenAI.

He has co-authored research examining how AI could accelerate scientific discovery. He's received early access to OpenAI's models, and used the technology to help solve a three-year-old immunology mystery in his own laboratory.

More recently, he joined OpenAI's Builders Unscripted podcast to discuss building tools for biology with codex, and a future in which AI may help scientists simulate experiments before actually performing them in the lab. We began the podcast with one of Derya's most boldest predictions, that the next 10 to 15 years could represent a uniquely important window for longevity. He believes we may be approaching what is known as longevity escape velocity. This is a hypothetical point at which advances in medicine extend remaining life expectancy faster than time passes. It is a highly uncertain forecast, and we examine the scientific reasoning behind it. From there, we explore how AI is already beginning to change the way research is conducted, analyzing high-dimensional biological data, generating hypotheses, and helping scientists determine which experiments are most likely to produce meaningful answers. Derya also makes a provocative argument. If AI becomes sufficiently reliable at reducing diagnostic errors and detecting patterns that physicians miss, there may eventually come a point when choosing not to use AI becomes medically irresponsible.

We also discuss why cancer remains so difficult to cure and how AI could help personalize treatment by integrating a patient's genetics, immune function, medical history, tumor biology, and so many other layers of biological data. We then move into the biology of aging. Why aging may reflect a progressive loss of resilience and communication across cells and tissues? What unusual animals can teach us about cancer resistance and DNA repair?

What partial cellular reprogramming might make possible? And why the brain may be uniquely difficult to rejuvenate? Toward the end of the conversation, we make the discussion more practical. Derya explains how someone could begin constructing what he calls a simple mini digital twin. By organizing longitudinal health information, establishing personal baselines, and giving AI enough context to help evaluate what changed before and after a particular interventions. Derya brings an especially valuable perspective to this discussion because he approaches AI as a biologist first. He understands both the extraordinary potential of these tools and the complexity of the systems they are being asked to interpret. That complexity is one of the reasons this subject is so compelling to me. Aging is not the product of a single pathway or an isolated defect. It emerges from an immense network of cells and tissues communicating, repairing damage, adapting to stress, and gradually losing the ability to maintain those functions. We can now generate enormous amounts of biological data, but collecting data is not the same as understanding it. AI may not replace biological intuition or clinical judgment, but it could expand what scientists and physicians are able to see. It may help identify patterns across genetics, immune function, metabolism, protein, medical history, behavior, and even environmental exposures that would otherwise be impossible for any individual human to integrate all together. You don't have to agree with Derya's timelines to find this conversation valuable. What matters is the direction of the science and the questions it forces us to confront. Can medicine move beyond population averages and toward a deeper understanding of individual biology? Can we detect disease earlier, design more informative experiments, and reduce avoidable medical errors?

And can AI help us navigate biological complexity without de-placing the validation, the judgment, and the human responsibility that rigorous science requires? Derya approaches these questions with the curiosity of a working scientist and an optimism that is both refreshing and infectious. He gives an enormous and often intimidating subject a very human dimension, and I'm excited for you to hear his perspective. But before we begin, I want to mention two ways you can stay connected and support the show. First, if you're not already subscribed to my weekly newsletter, I encourage you to sign up right now. Stop what you're doing. Go sign up. Each week, I highlight new research that I find especially compelling and worth sharing. It has become one of the most popular things we publish, in part because we are willing to go beyond the headlines and examine what this science actually shows. So far this year, we have covered studies on microplastic and glass bottles, the relationship between red meat consumption and dementia risk, and most recently, whether fruits and vegetables contain as many polyphenols as we assume. We go deep into the research, but the goal is always to make the findings clear, useful, and relevant to your health. You can subscribe at foundmyfitness.com/newsletter.