Co-founder of Gero. Doing my best to end aging. Physics-informed AI against aging and age related diseases. Preclinical stage, platform-based biotech company
Joined October 2015
- Tweets1.2K
- Following4.8K
- Followers3.3K
- Likes1.4K
Pinned Tweet
🚀 Thank you, @Nasdaq, for celebrating our potentially multi‑billion‑dollar partnership with Chugai (a member of the Roche Group)!
Why is this deal so important—for science, for the industry, for humanity?
👇 Find out in the comment.
Spoiler: The same tech behind this partnership is being used to design therapies to stop human aging. And now, it’s validated at the next level. Stay tuned—this is just the beginning.
“What can I do to help stop aging?”
People keep asking. Here’s the answer—and it’s never been easier:
👉 Investors who believe in this mission — DM me or tag someone who should see this.
👉 Scientists, engineers, drug hunters — we’re hiring. Let’s build the cure together.
👉 If you believe aging should be treated— share this now. Help spread the word.
Let’s make this decade the last one where aging is still considered “normal.”
#Longevity #Chugai #DrugDiscovery #AntiAging #Healthspan #DeepTech #NASDAQ
This week at Biomarkers, CDx & Precision Medicine Europe and NextGen Omics Tech & Data Europe 2026 in Basel, Gero’s Head of Translational AI and Target Discovery, Amir Feizi, PhD, presents how we combine longitudinal human health data, multi-omics, and human genetics to understand how disease progresses, identify therapeutic targets more likely to hold up in people, and test those hypotheses experimentally.
The session also includes a panel on bringing AI into R&D and clinical workflows, with speakers from Roche, AstraZeneca, the NHS, and RWTH Aachen University.
If you are attending, we would welcome the chance to meet.
October 13-14, 2026, Congress Centre Basel
On Sept. 22, Gero CEO Peter Fedichev joins the Forbes Middle East Healthcare Leaders Summit to discuss
how human data, AI and aging science can translate that biology into new medicines.
#TheForbesMiddleEastHealthcareLeadersSummit #ForbesME #LongevityScience
Introducing the minds driving healthcare forward.
Our speakers represent the full spectrum of the healthcare landscape, from precision medicine and AI to policy, community health, and next-generation technologies, bringing the insights shaping the future of care to the 5th Edition of the Forbes Middle East Healthcare Leaders Summit, held under the Patronage of H.E. Sheikh Nahyan bin Mubarak Al Nahyan, Minister of Tolerance and Coexistence, and presented by @PureHealthae , on September 22–23 at Emirates Palace Mandarin Oriental, Abu Dhabi.
Be in the room. Register now:
forbesmiddleeastevents.com/h…
@hacking_aging
Gero has been named to the Forbes Asia 100 to Watch 2026 list. Thank you, @Forbes
Gero combines longitudinal human data, AI, and a physics-based aging framework for therapeutic target identification and drug design. Gero's approach was born from a crucial but underappreciated observation: nature has already achieved dramatic slowing of aging and extremely long healthy life in several complex mammals. While in humans the risk of death roughly doubles every eight years after early adulthood, naked mole-rats, for example, can live about five times longer than expected for their size while showing essentially no increase in mortality risk with age. This observation led Gero to develop a physics-based framework that decodes the underlying physical laws of aging from human data to discover new medicines.
While most of aging-focused biotech pursues reversing or reprogramming aging to restore youthful cell function, Gero's framework identifies slowing aging itself as a more durable lever on healthspan, functional decline, and lifespan.
Gero’s thesis is that aging and age-related disease onset follow quantifiable physical laws that can be read in human data and turned into medicines. Gero trained AI world models of human health on approximately 10 million curated longitudinal medical records, selected from more than 100 million records and integrated with molecular, omics, and genetic data. The models distinguish reversible disease biology from deeper, long-timescale aging processes to identify "hub" targets that standard methods miss — single mechanisms shared across multiple chronic diseases. Under the Chugai collaboration, Chugai is developing drug candidates against targets identified by Gero; Gero also previously conducted a research collaboration with Pfizer in 2023.
By pairing a validated discovery engine with non-dilutive partnership revenue, Gero is positioned to advance a portfolio of both disease-modifying and aging-slowing programs in parallel, with proceeds supporting preclinical development of its pipeline and continued expansion of pharmaceutical partnerships.
Maxim Kholin retweeted
João Pedro de Magalhães has published a history of the hyperfunction theory of aging, arguing that aging is “programmatic” — developmental programs that keep running past their usefulness, with molecular damage demoted to a downstream symptom. It is a careful piece and worth reading (@jpsenescence on X). I also think its central inference is the most instructive mistake in the field, because nearly everyone makes it, including people who would never call themselves programmed-aging theorists.
The inference rests on six observations, and all six are real. Individuals of a species go through the same changes in roughly the same order, on a timetable characteristic of that species and sharply different between species — a mouse gets three years, we get eighty. The hallmarks move together, across tissues and across systems. Single genes have outsized effects; daf-2 doubles a worm’s lifespan. Aging runs continuously out of development, with no seam between them. And some of it reverses, under parabiosis, reprogramming, restored youthful factors.
Damage does none of that. Damage is random, unsynchronised, and does not care what species it is in. So: aging is not damage; aging is program.
The premises are correct. The conclusion does not follow. Read more on my Substack (peterfedichev.substack.com/p… <- please subscribe!). Help with likes, follow and repost here please!
aging. program without program
John Archibald Wheeler — Feynman's doctoral advisor at Princeton, and the man who named the black hole and the wormhole — had a habit of naming things by what they lacked: mass without mass, charge without charge, law without law. Each was a case where some familiar quantity turned out to be produced by something that did not contain it. Wheeler's suggestion was that regularity itself might emerge from underlying randomness, so that what looks like a law requires no law behind it.
Aging is program without program. See another sacred caw slayed on my Substack (peterfedichev.substack.com/p… <- please subscribe). As always, please like, repost or follow to see more like this.
Alan Tomusiak has written one of the better surveys of aging theories (“The Great Landscape of Aging Theories”) @fedichev comments
Alan Tomusiak has written one of the better surveys of aging theories (“The Great Landscape of Aging Theories”) I have seen — honest about falsification history, generous to positions he does not hold, and admirably explicit about the limits of his own map. I recommend it (see the link by @alantomusiak in the first comment).
The confusion is the word theory. The sixteen objects on Alan’s landscape are not sixteen answers to one question. They are answers to at least three different questions — why aging exists, what aging is, and how aging works — and these questions live at different levels of description.
For a complex system, a theory can be one of at least two types.
A phenomenological theory is a minimal set of variables and their relations that compresses a large corpus of observations. It classifies and explains without attempting microscopic reduction. Landau-Ginzburg theory of superconductivity is the canonical example: an order parameter, a free energy, a handful of coefficients — and an enormous range of phenomena falls out. Such theories are compressed representations of what happens.
A microscopic theory explains how it happens mechanistically — and, crucially, it earns that status only by being shown to recover the phenomenology in the macroscopic limit. BCS theory is not the theory of superconductivity because it involves electrons and phonons; it is the theory because Gor’kov demonstrated that Landau-Ginzburg emerges from it. The derivation is the price of admission.
The phenomenological theories of aging are the ones with equations: Gompertz mortality kinetics, Strehler-Mildvan, Uri Alon’s saturating removal (yes, it’s a phenomenological effective theory, though the authors confront such classification!), and our own resilience-loss (actually a lot more complete recent work with Jan Gruber) models at Gero. Few effective variables, explicit dynamics, compression of mortality curves and biomarker trajectories. These are the Landau-Ginzburg candidates.
The Hallmarks of Aging — the most cited framework in the field — is the interesting failure case: it is neither. No dynamics, no compression, no recovered macroscopic law. It is a parts inventory. Which is exactly why it feels simultaneously comprehensive and inert: everything is on the list, and the list explains nothing.
Follow, like and repost — read the full argument on Substack this week peterfedichev.substack.com/p… and subscribe.
There are 100+ drugs in development for erectile dysfunction.
There are 0 for menopause beyond symptom management.
Only 4% of women even use the one hormone therapy that exists.
We're trying to fix that @hacking_aging & @athenabiorg
In most long-lived species, evolution strongly selects for longevity because more years = more offspring. But in humans, menopause breaks that link. It’s rare in nature and may have evolved through the “grandmother hypothesis” — older females stopping reproduction to invest in grandchildren, especially useful in species with long childhoods.
Using our AI platform on massive human datasets, we can now study both the shared aging mechanisms and the ones unique to reproductive aging. Menopause affects every woman in modern societies and has a massive impact on healthspan. The scientific, commercial, and humanitarian case is exceptionally clear.
It’s a perfect example of how cracking aging biology can deliver therapies that are both deeply fundamental and immediately life-changing.
Thank you, @athenabiorg, for the conversation. Friends, learn more below about how we’re working toward treating menopause as an aging problem.
Maxim Kholin retweeted
Our longevity biotech deep dive for Social Capital crossed 350k views (way more than we anticipated). The full report is private. For investors looking at longevity biotech, here are two bets worth understanding:
1) The overcrowded bet: cellular reprogramming. Bezos, Altman, and Brian Armstrong went in early, and NewLimit just raised $435M from tier-1 VCs and Eli Lilly - a genuinely bullish signal. Still, only two studies show a lifespan gain in normal mice (7-12%), so don't expect systemic rejuvenation from the first generation of epigenetic reprogramming therapies, but they'll very likely show efficacy against specific diseases. It might not be too late to enter the field, but it's definitely not early: three companies with only preclinical data are already at unicorn valuations.
2) The asymmetric bet: growing and preserving organs. Today up to 75% of donated hearts and lungs are wasted because they last only hours outside the body, and globally just ~10% of the need is met. The companies fixing that, building new organ sources and learning to bank them long-term, are early, and many are still in stealth. We personally know who's building what, and it's still possible to get in at low valuations. That's where the alpha is hidden.
For the @chamath's @socialcapital deep dive, we assembled a group of 17 leading scientists, founders, and experts. Much of the useful signal is offline: who’s building in stealth, which founders can actually deliver, and which science is real versus merely well-promoted.
With that work finished, we now have capacity for the next longevity biotech project for a family office, fund, private banking team, or private investor looking at the field. Beyond deep dives, we can help you source stealth deals, run due diligence, build custom intel tools, or launch client-facing longevity products.
Know someone who runs a family office or fund and is into longevity? Share this with them.
Want details? Let's jump on a quick call - DM.
Naked mole rats defy the laws of aging. We can too. #Science youtube.com/shorts/OSzMSv6PX… @YouTube
Lecture by Peter Fedichev @fedichev
This may become one of the defining scientific debates in longevity.
Billions of dollars, renowned scientists, visionary investors, and dozens of biotech companies are betting that biological rejuvenation will unlock radical life extension.
Peter Fedichev and Gero @hacking_aging making a different bet.
Reset is not enough.
The greatest gains in lifespan may come from slowing the accumulation of irreversible aging, not simply reversing its reversible component.
At the very least, this hypothesis deserves serious consideration. It is grounded in more than a decade of research, published scientific work, the application of physics to large-scale human longitudinal data, and a drug discovery platform that has already generated pharma partnerships.
It is also inspired by nature itself. Many of the best-studied negligibly senescent animals appear to achieve exceptional longevity not by repeatedly becoming young again, but by aging extraordinarily slowly in the first place.
When the stakes are measured in decades of healthy life, and billions of dollars are being invested, it may be wiser to pursue more than one scientific path.
A reply to @ydeigin regarding my take on why epigenetic rejuvenation won't give us radical life extension: Yuri argues that serial cloning (one cell → trillions → one cell, repeated 57 times) is an extraordinarily harsh mutational stress-test — far tougher than a normal lifetime — yet the cloned mice maintained normal lifespans for decades of generations.
This, he says, suggests somatic mutation load isn’t the primary limit on lifespan and weakens the idea that unrepaired damage caps what epigenetic rejuvenation can achieve.
Fair point on the severity of the bottleneck. But let’s look at what the experiment actually falsifies. The stronger claim (often bundled with “information theory of aging”) is that a full epigenetic reset — complete nuclear reprogramming + embryogenesis — returns biological age to zero with essentially no irreversible residue. Serial cloning is about as rigorous a real-world test of that exact claim as exists: every single generation receives a total reset, repeated across 57 generations, with full developmental selection. Yet the damage accumulated monotonically anyway, until the lineage failed at generation 58.
One clear counter-example is sufficient to reject the universal “reset erases everything, zero leftover” assertion. I’m not claiming mutation load is the dominant driver of normal mouse lifespan, nor that 58 generations is a hard biological ceiling. Only that even the most powerful reset conceivable left a residue it could not eliminate.
This fits a broader pattern. Dose-ramped in vivo OSKM plateaued far short of top longevity interventions and raised cancer risk. Caloric restriction and heterochronic parabiosis both improve the reversible (regulatory noise) component but leave the entropic/irreversible trajectory flat. Four structurally unrelated interventions — full genetic reset, transcription-factor overexpression, dietary, and circulatory — all hit a similar floor.
That convergence points toward a thermodynamic flavor: stress drives regulatory noise, which over time seeds irreversible entropic drift. We can slow the process. We cannot simply rewind it.
Great job!
Part 2 of the deep dive I've been working on with @socialcapital (@chamath's investment vehicle) is out.
The series is a two-part introduction to Longevity Biotech and Aging Research, written for readers with no background in biology, medicine, or biotech.
Part 1 covered the biology of aging and the state of the field. Part 2 gets into the strategies researchers, companies, and investors are pursuing to slow or reverse aging, and where each approach stands today.
Thank you again to @chamath, the @socialcapital team, and every contributor who helped shaping this: @Andrei_Tarkhov, @elimohamad, @fedichev, @KarlPfleger, @MarkHamalainen, @MartinBJensen, @MaxUnfried, @mkaeberlein, @omri_drory, @RaianyRomanni, @realnathancheng, @sebastiangiwa, @shappiron, @shoylev, @statto, @strygah, @ydeigin
If any errors are to be found in this deep dive, I own them.
Following a Chugai (Roche Group) collaboration with up to $250M in milestones in addition to royalties, and inspired by mammals that defy the rules of aging, Gero uses physics-first AI and human longitudinal data to develop medicines that substantially slow aging and treat age-related diseases.
SINGAPORE & SAN FRANCISCO--(BUSINESS WIRE)--Gero, which previously secured a collaboration with Chugai Pharmaceutical, a member of the Roche Group, including an upfront payment and up to $250M in milestones in addition to royalties, today announced $17M in new financing, bringing total equity funding to $34M.
Backed by a collaboration with Chugai Pharmaceutical, a Roche Group member, worth up to $250M in milestones plus royalties, Gero uses physics-first AI and human longitudinal data to develop medicines that slow aging and treat age-related diseases.
Share
Gero combines longitudinal human data, AI, and a physics-based aging framework for therapeutic target identification and drug design. Gero's approach was born from a crucial but underappreciated observation: nature has already achieved dramatic slowing of aging and extremely long healthy life in several complex mammals. While in humans the risk of death roughly doubles every eight years after early adulthood, naked mole-rats, for example, can live about five times longer than expected for their size while showing essentially no increase in mortality risk with age. This observation led Gero to develop a physics-based framework that decodes the underlying physical laws of aging from human data to discover new medicines.
While most of aging-focused biotech pursues reversing or reprogramming aging to restore youthful cell function, Gero's framework identifies slowing aging itself as a more durable lever on healthspan, functional decline, and lifespan.
Gero’s thesis is that aging and age-related disease onset follow quantifiable physical laws that can be read in human data and turned into medicines. Gero trained AI world models of human health on approximately 10 million curated longitudinal medical records, selected from more than 100 million records and integrated with molecular, omics, and genetic data. The models distinguish reversible disease biology from deeper, long-timescale aging processes to identify "hub" targets that standard methods miss — single mechanisms shared across multiple chronic diseases. Under the Chugai collaboration, Chugai is developing drug candidates against targets identified by Gero; Gero also previously conducted a research collaboration with Pfizer in 2023.
By pairing a validated discovery engine with non-dilutive partnership revenue, Gero is positioned to advance a portfolio of both disease-modifying and aging-slowing programs in parallel, with proceeds supporting preclinical development of its pipeline and continued expansion of pharmaceutical partnerships. The financing comes as pharma increasingly seeks mechanisms that act across many diseases at once, the same cross-disease property that made GLP-1 medicines a more-than-$50-billion category.
The financing included participation from Melnichek Investments, an AI-focused investment firm whose founder was behind AIMatter, acquired by Google and multiple other AI startups acquired by major tech companies; an early backer of a company acquired by Facebook, now Meta; the co-founder of NYSE-listed EPAM Systems; and senior operators from the pharmaceutical and technology sectors.
"Target selection is the critical bottleneck in translating aging biology into medicines, and the field has not lacked ideas, it has lacked human-evidence-grounded targets that pharma is ready to develop," said Brian K. Kennedy, PhD, Distinguished Professor at the National University of Singapore, former President and CEO of the Buck Institute for Research on Aging, and Independent Director of Gero.
Gero is one of the few groups bringing published aging theory, longitudinal human data, and pharmaceutical-partner validation into a single discovery engine."
"Gero stands out for grounding discovery in a published, physics-based framework and real human data, and for turning that science into a working platform, which is why I invested," said Anita Cosgrove, former Senior Vice-President, Strategic Business Development at Human Longevity, Inc., and an investor in Gero.
"Countless molecular events happen every second, both in a naked mole-rat and in us — yet over decades our risk of death doubles every eight years while theirs stays almost flat. That gap is a physics problem. We've spent a decade building the theory. What's changed is that we now have the data — tens of millions of longitudinal health records — and generative AI that can extract the mathematics of aging directly from that data, the way physics has always worked but at a scale and complexity no analytical theory could reach. In aerospace, that level of modelling transformed engineering outcomes. We expect the same in medicine. And aging is the place to start: it's the shared engine behind virtually every chronic disease, which means slowing it is the highest-leverage intervention in human health," said Peter Fedichev, PhD, Co-Founder and CEO of Gero.
The framework underlying the platform was originated by Co-Founder and CEO Peter Fedichev, PhD, and developed across leading journals including Nature Communications over more than a decade, more recently with Jan Gruber, PhD, of the National University of Singapore. The work shaped gerophysics, the application of physics to aging, now recognized in a dedicated Nature Portfolio (npj Aging) collection co-edited by Fedichev, Kennedy, and Gruber among others.
About Gero
Gero is a physics-first AI drug discovery and development company focused on age-related diseases and the biology of aging. The platform builds AI models of human health from large-scale longitudinal real-world data, combining clinical, molecular, omics, and genetic data with physics-based modeling and AI-enabled target discovery, paired with ProtoBind-Diff, a generative AI model for small-molecule design directly from protein sequence. Gero partners with pharmaceutical companies on age-related disease and advances proprietary programs aimed at intervention in aging itself. Gero's scientific work has been published in Science, Nature Communications, and other leading journals. The company is headquartered in Singapore, with a U.S. subsidiary in San Francisco. To learn more, visit gero.ai and follow Gero on LinkedIn and X at @hacking_aging.
Gero has been named a 2026 Technology Pioneer by the World Economic Forum (WEF) for Advancing the Physics of Aging in Drug Discovery
Gero’s physics-first AI drug discovery platform is transforming breakthroughs in the physics of aging into a pipeline of medicines designed to treat age-related diseases and slow the aging process itself.
We're especially glad that the World Economic Forum and Davos platform will help us educate the community and lead the conversation on a question we believe defines the next decade of medicine: treating aging as a new pharmaceutical category, one we are working to define.
Gero has just been selected as a 2026 Technology Pioneer by the World Economic Forum (@wef).
For over a decade I've approached #aging as a physicist: not as a collection of isolated diseases to treat after they appear, but as a macroscopic process driven by the accumulation of entropic damage and the loss of resilience in a complex system. That framework is what led us to found @hacking_aging.
At Gero, we use physics-informed models on large-scale clinical data to separate aging itself from specific disease trajectories. Our goal is straightforward: identify ways to slow the underlying rate of functional decline before reversible stress turns into irreversible collapse. Stop the clock where it matters most — on the processes that erode healthspan.
This recognition from the WEF is a strong validation of that direction. Looking forward to connecting with the other pioneers and pushing these ideas further.
➡️Read the full announcement: businesswire.com/news/home/2…
