Rewriting human aging with Physics and AI with Dr. Peter Fedichev of Gero (Part 1)

<p>Dr. Peter Fedichev is the co-founder and CEO of <strong>GERO</strong>, a Singapore-based biotech startup that uses physics-informed AI and massive human health datasets to discover drugs aimed at slowing down aging and treating age-related diseases.</p><p>In this episode, explains his transition from a decade in theoretical physics to longevity biotech, motivated by applying physics tools to complex living systems and discoveries like the naked mole rat’s lack of mortality acceleration. He contrasts biology’s case-control, fact-collecting culture with physics’ search for universal variables, arguing aging is a universal, chronic-process problem well suited to physics-style modeling. Peter describes Gero’s approach as building predictive, generative AI models from large-scale medical records and omics data to capture the “equations of motion” of health over time. He critiques hallmark-of-aging narratives and emphasizes “functional decline” (functional span) over healthspan, noting very old people can be disease-free yet severely impaired. Using thermodynamics as an analogy, he argues aging involves entropy-like, stochastic damage that is hard to reverse but potentially possible to slow or stop by targeting fundamental control variables.</p><p><br></p><p>Host: John Joson Ng</p><p>Editors: Dillon Chew, Chi Dam, Vasilina Gedzun</p><p><br></p><p>00:00 Meet Peter Fedichev</p><p>00:23 From Physics to Biology</p><p>02:30 Non Aging Animals Spark</p><p>04:27 Physics Lens on Aging</p><p>06:21 Why Gero Exists</p><p>09:46 Modeling Health Dynamics</p><p>10:49 Beyond Lifespan Healthspan</p><p>12:43 Functional Decline Focus</p><p>16:07 Thermodynamics Meets AI</p><p>18:56 Entropy Limits Reversal</p><p>22:02 Temperature and Lifespan</p><p>25:12 Modeling to Speed Drugs</p><p>27:20 Closing Why Aging First</p>