In this episode, Dr. Peter Fedichev—founder of Gero, a company using AI to decode aging—discusses how aging should be understood as a process of functional decline rather than a collection of diseases. Drawing from physics, systems biology, and data science, he shares how resilience—the body’s ability to recover from stress—may be the most powerful indicator of health and longevity.

Key Points:

Dr. Peter Fedichev argues that aging is best understood as the body’s declining resilience, not a collection of diseases. His research at Gero uses AI and physics to measure how well the body recovers from stress, offering a new lens for predicting health outcomes. By focusing on maintaining resilience, he believes we can extend not just lifespan, but the quality of life itself.

• Aging as Loss of Resilience: Dr. Fedichev redefines aging as the gradual loss of the body’s ability to recover from stress, marking a shift from viewing aging as a series of diseases to a measurable decline in resilience.
• Physics Meets Biology: Using concepts from physics, he explains how biological systems can be modeled to predict when and how resilience fades—helping scientists quantify the biological “tipping point” of aging.
• Healthspan vs. Lifespan: The goal, he emphasizes, is not merely to extend years lived but to prolong healthspan—the period of life free from chronic disease and frailty—by maintaining functional stability.
• AI and Data-Driven Longevity Science: Gero’s AI models analyze vast biomedical data to track resilience and biological age, identifying biomarkers that can forecast future health risks long before symptoms appear.
• From Intervention to Prevention: Rather than waiting for diseases to emerge, Fedichev advocates using resilience-based measures to design early interventions that slow or even reverse biological decline.
• Hope for a Longer, Healthier Future: He envisions a world where personalized monitoring of resilience becomes routine, allowing individuals to take proactive steps toward longer, healthier lives—guided by continuous data and science.