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What if the future of medicine is not about what is “normal” for everyone, but what is normal for you?
In Episode 35 of Decoding Longevity, Raghav Sehgal sits down with Dr. Nathan Price to explore how AI, systems biology, and longitudinal health data could transform personalized medicine and the way we understand aging.
They discuss the N-of-1 approach, personal data clouds, multi-omics, genetic gap analysis, and how AI could help interpret the thousands of biological signals generated by a single person.
Nathan also explains the concept of digital twins in healthcare, why healthspan should become “measurable, predictable, and modifiable,” and how future AI systems could help us predict and continuously update individual health trajectories.
The conversation also covers health data privacy, scientific wellness, translating research into real-world products, and what the next 5–10 years could bring for longevity research and personalized health.
