This episode features Peter Fedichev, a physicist-turned-biotech innovator who is redefining how we understand ageing. As founder and CEO of Gero, Fedichev brings a unique perspective to the longevity space, merging theoretical physics with advanced AI and systems biology. His approach challenges mainstream assumptions about age reversal, offering a thought-provoking view on the limits of human lifespan extension.

Key Points:

In this episode, Peter Fedichev, who challenges conventional ageing theories and presents a bold, physics-informed approach to understanding and potentially slowing human ageing. He argues that while ageing reversal is likely unachievable due to the fundamental laws of physics, slowing down the rate of ageing is a realistic and powerful goal.

• Physics Meets Biology: Fedichev applies statistical mechanics and physics principles to biology, particularly ageing. He believes that to tackle ageing effectively, we need to model biological systems the same way physicists study complex, multi-scale systems.
• Two Paths of Ageing: Ageing consists of two processes: irreversible, slow linear changes (like growing ears/nose) and dynamic, reversible changes (like fatigue or illness). Current anti-ageing drugs only target the reversible part, yielding limited impact on lifespan.
• Slowing Ageing > Reversing It: Fedichev likens reversing ageing to "unboiling an egg"—theoretically possible, but practically unachievable due to the immense precision required. Instead, slowing the rate of ageing (like reducing heat in the egg analogy) is both feasible and impactful.
• Gerophysics and Predictive Modeling: Gero, Fedichev’s company, develops models to predict how different biological factors influence ageing and lifespan. These models help identify interventions that can realistically slow ageing based on data and physics-based theories.
• The Role of "Effective Temperature": Fedichev introduces the idea of "effective temperature" as a metaphor for biological variability. Higher physiological fluctuations signal poor health and increased mortality risk—controlling these fluctuations is key to longevity.
• Hallmarks of Ageing: Too Fragmented: He critiques the “hallmarks of ageing” approach as overly reductionist. Instead, he advocates for systemic, universal models that can explain ageing across species, inspired by the example of non-ageing animals like the naked mole rat.
• AI and Ageing Research: AI plays a vital role in analysing massive biomedical datasets. Gero uses machine learning to identify patterns and predict which interventions might meaningfully impact ageing on a human scale.
• Lessons from the Naked Mole Rat: Fedichev emphasizes that animals like naked mole rats exhibit no increase in mortality with age, proving that extreme longevity is biologically possible. Studying these species offers a roadmap for reducing human ageing rates.