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| Authority control databases: Academics |
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Peter Fedichev | |
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| Born | Peter Olegovich Fedichev |
| Alma mater | Moscow Institute of Physics and Technology (M.S.); University of Amsterdam (Ph.D.) |
| Occupations | Physicist, biotechnologist, entrepreneur |
| Known for | Research on quantitative models of ageing; co-founding Gero.ai |
| Scientific career | |
| Institutions | Gero.ai |
Peter Fedichev is a physicist and biotechnologist. He worked on ultracold quantum systems before moving into computational drug design and later longevity research. [1] [2]
He is the co-founder and chief executive officer of Gero.ai, a biotechnology company based in Singapore that applies physics-based and machine-learning methods to ageing and disease research. [3] [4]
Fedichev received an M.Sc. in theoretical physics from the Moscow Institute of Physics and Technology while conducting research at the Kurchatov Institute. [5] In 1994 he joined the University of Amsterdam and the AMOLF institute, completing a Ph.D. cum laude in theoretical physics. He later worked at the University of Innsbruck on condensed-matter and quantum-gas systems. [6] [7] [8]
During the 2000s Fedichev co-founded Quantum Pharmaceuticals, an early company exploring computational drug design. [9] Since 2015 he has led Gero.ai, whose studies use large health datasets and mathematical models to analyse ageing dynamics. [10] [2] In a 2021 study published in Nature Communications , Fedichev and co‑authors analysed longitudinal blood biomarker data and step‑count records to propose that human resilience declines with age and may limit maximum lifespan. [11] [12] Scientific American cited him noting that the convergence of blood and activity data suggests a “real pace-of-aging factor”. [2]
Fedichev has written on the use of physical and mathematical approaches to describe biological ageing. He and co-authors have proposed that the progression of ageing can be treated as a problem in non-equilibrium thermodynamics and complex-systems dynamics. Fedichev and collaborators have published models describing how variability in health indicators increases with age and may predict lifespan limits. [13] [14] Subsequent studies extended this framework to distinguish between processes that might be reversible through intervention and those that appear thermodynamically irreversible. [15] [16] Nature gathered these developments in its 2024 “Gerophysics” article collection, co-edited by Fedichev and biologist Brian K. Kennedy, describing the field as an emerging interdisciplinary area linking statistical physics and biogerontology. [17] [3]
Gero.ai, co-founded in 2018 by Fedichev and Maxim Kholin in Singapore, develops physics-informed AI models trained on electronic medical records and molecular-level data to predict health trajectories and identify potential therapeutic targets for ageing-related conditions. [3] [4] [18] In January 2023 Gero entered a research collaboration with Pfizer to identify therapeutic targets for fibrotic diseases. [19] In July 2025 Gero signed a joint research and licence agreement with Chugai Pharmaceutical (a member of the Roche Group) to develop antibody therapies against targets identified by its AI models. [20]
| Authority control databases: Academics |
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