Why Everything You’ve Heard About Longevity Is Too Small
My JPM 2026 talk on why the field is asking the wrong questions — and what physics reveals about the real problem
There’s a moment in any scientific field when the questions being asked are smaller than the problem itself. Longevity research, I’d argue, is living through that moment right now.
I’m a physicist by training. I got pulled into aging biology the way most people get pulled into obsessions — by a single, unsettling fact.
In 2006, a paper came out showing that the naked mole rat doesn’t age. Not “ages slowly.” Doesn’t age. Its probability of dying doesn’t increase with time. That paper wasn’t funded by NIH. It came from a daughter company of Google — because you apparently need to build a $10 billion revenue business first in order to spin off a $200,000 experiment to check whether a small burrowing mammal from Somalia experiences aging. That, to me, says everything about why this field is still where it is.
But things are changing. And I want to tell you exactly how — and why the change is more profound than most people in the industry are willing to admit.
The $500 Billion Data Point
A few years ago, if you said that a drug extending human life by one to two years could generate $100 billion in market capitalization, you’d have been dismissed as a dreamer. Sam Altman said something like that in 2018, and it was treated as an interesting thought experiment.
Then GLP-1 agonists happened.
You know this drug — it’s now selling at over $50 billion per year, with oral versions forecast to cross $100 billion. One company is on the verge of becoming the first trillion-dollar pharma firm. The original story was weight loss. But the real story emerging from multiple clinical trials is something else: these drugs appear to reduce the risk of other age-related diseases — cardiovascular, neurological, metabolic — by somewhere around 30% in certain cases. When you translate that into rescued years of life, you’re looking at roughly one to two years of additional lifespan.
So here’s the data point we now have: a drug that probably extended human life by about a year saw its issuing company’s market cap increase by approximately half a trillion dollars. The order of magnitude that was predicted was correct.
What does this mean for the industry? Everything.
If your drug is selling for $50 billion a year, you’re not going to pivot to another cancer drug with a $5 billion ceiling. The logic of commercial scale is now pointing in one direction only: the next drug that can be bigger than GLP-1 is a true longevity drug. Everything else is smaller. Nobody wants to develop a drug against aging — aging isn’t a disease, regulators don’t know what to do with it, investors get nervous. But the mathematics of market size will force the industry there anyway. That’s not ideology. That’s arithmetic.
We’re already seeing the early signs. Nearly every major pharmaceutical company now has a longevity project running quietly in the background. Alphabet has acquired aging assets. We at Gero just completed a deal with Chugai, the daughter company of Roche. This is a trend that will accelerate.
What Aging Actually Is (And Why You’re Probably Thinking About It Wrong)
Let me show you the two charts that scare me most.
The first is VO2 max — your body’s ability to consume and use oxygen, which is essentially a measure of how much energy you can generate. It declines linearly with age, even in people who have no diseases whatsoever. There’s a threshold below which you can’t breathe properly during sleep. That threshold is, effectively, a death sentence. And you approach it on a schedule that nothing we currently know how to do can meaningfully alter.
The second is cognitive performance. Most tests of fluid intelligence — the kind that measures real-time reasoning, not accumulated knowledge — decline steadily from your mid-20s onward. Crystallized intelligence (your ability to recall and articulate what you already know) stays relatively flat for longer. Which means, as I like to say, you can still talk eloquently long after you’ve stopped understanding what you’re talking about. Beware of articulate people.
These two trajectories are aging. Not cancer. Not diabetes. Not any particular disease. The continuous, linear degradation of your physical and cognitive function — independent of illness — that is what aging is. And here’s the uncomfortable truth: if you’re exercising, eating well, and have no chronic conditions, you are still aging. You are still on this curve.
This is not a disease model. It’s a physics problem.
The Naked Mole Rat and the Second Law
The naked mole rat lives in Somalia, in underground colonies, about the size of a mouse. It has a matriarchal social structure, a dominant breeding female, and — crucially — a mortality curve that is essentially flat with age. It doesn’t get more likely to die as it gets older. It is, by every biological definition, non-aging.
It is not alone. Nature is full of creatures that don’t age, or age negligibly. Hydra. Certain turtles. Some sharks. The existence of non-aging organisms in nature is now well established. Which means aging is not an inevitable property of living systems. It is a feature — one that evolution selected for in some lineages and not others.
This is why I think aging is ultimately a problem of physics, not just biology. The late Leonard Hayflick, one of the foundational figures in aging biology, proposed something similar: that aging is fundamentally a thermodynamic problem. I was trained in theoretical physics. When I encountered this framing, I couldn’t ignore it. It’s why a field now called “geroscience physics” or “gerophyics” has emerged, and why our work at Gero sits at that intersection.
What Machine Learning Taught Us About Aging
We feed medical histories — across tens of millions of people — into dynamic machine learning models. These models try to predict what happens to a person’s health over the full arc of their life. And when you train these systems on enough data, something interesting happens: they learn to separate aging from disease.
Not because we told them to. Because the signal is there in the data.
The models pull aging out as a distinct process, independent of specific disease trajectories. They identify genetic targets that are controlling the rate of aging in humans — not just predisposing people to particular diseases, but governing the underlying aging process itself. We’ve licensed one of these targets to a major pharmaceutical company. We expect there will be more.
This kind of analysis also lets us do something that was previously very difficult: measure maximum human lifespan in clinical data. It’s about 120 years. We know how to rejuvenate aging in mice. And we’ve arrived at a conclusion that not everyone likes:
In humans, you can stop aging. You cannot reverse it.
Most of human aging is thermodynamically irreversible. This is not what people want to hear at a longevity conference. But I think it’s one of the most important and actionable statements in the field — because it means the goal is not rejuvenation. The goal is stopping the clock.
Three Ways to Extend Human Life
Two hundred years ago, Benjamin Gompertz discovered the law of exponential aging — the observation that the probability of dying doubles roughly every eight years after maturity. He described aging as a combination of two processes: linear damage accumulation, and physiological noise (random biological fluctuation). This framing from 1825 maps almost exactly onto what our machine learning models are recovering from modern electronic health records.
Which means you can extend human life in three fundamentally different ways:
1. Cure diseases. This is what most of medicine does. It works, but the effect sizes are small. Even if you cured all cancers tomorrow, average lifespan would increase by about three years. Cure all diseases, and you might get ten years. That’s not nothing. But it’s not transformation.
2. Reduce the rate of damage accumulation. This goes after the linear deterioration component. If you could meaningfully slow the rate at which damage builds up in your cells and tissues, you could extend lifespan substantially — potentially far beyond what disease treatment can achieve.
3. Reduce physiological noise. This is what I find most interesting and most neglected. Noise — random biological fluctuation — is what separates the average human lifespan (around 80) from the maximum (around 120). The gap between average and maximum lifespan in humans is roughly 40 years. If you could reduce the noise, you could bridge that gap. Drugs that act on noise would produce large effects. This is where we are focused.
The vast majority of the longevity industry is working on option one. A newer generation of companies is working on option two — organ replacement, senolytics, epigenetic reprogramming. Very few are working on option three. That’s where the largest untapped leverage is.
Why “Reversing Aging” Is the Wrong Goal
There’s a fault line running through the longevity world right now, and it’s worth making explicit.
On one side are companies that believe aging is reversible — that you can take an 80-year-old and make them biologically 20. These companies tend to have large capital, large ambitions, and a belief in epigenetic reprogramming as the mechanism. On the other side is pharma — largely dismissive of the aging-reversal thesis, but quietly extending life one disease indication at a time.
And then there are a few of us who occupy a different position: we believe aging is not reversible in any deep thermodynamic sense, but it can be stopped. And we think that’s actually the bigger prize, because it’s achievable within the coming years rather than decades, and because stopping aging is the intervention with the largest population-level effect.
I’ll put it plainly: everyone who currently believes aging is fully reversible will either fail, or eventually become a conventional pharma company targeting disease indications. The second law of thermodynamics is not a recommendation. It’s a law.
Consider how we recognize age in a human face. You can see roughly how old someone is. You can also see whether they look healthy for their age — and that variation, roughly plus or minus five years, reflects reversible biological fluctuation. Sleep well and you look younger. Get sick and you look older. That variation is real and tractable.
But look at the size of someone’s nose. Their ears. These structures grow continuously with age, driven by irreversible collagen changes. No diet, no drug, no epigenetic intervention changes your nose size. That’s the second law of thermodynamics. The irreversible component is real, it’s large, and it’s currently being systematically underestimated by the field.
What You Should Actually Do (And When)
The most uncomfortable finding from our data analysis is this: the functional decline curve is largely set by your early adult peak.
Think of your body as a glider. It climbs to a certain altitude between roughly age 20 and 30, and then glides downward at a relatively fixed rate from there. The higher you climb — the better your physical and cognitive shape at your peak — the longer your glide path. The rate of descent is broadly similar for everyone. The starting height determines everything.
This means that for most people currently in midlife or beyond, the most important intervention is maintaining trajectory, not trying to reverse it. The reversible fluctuations around the trend are real and worth addressing. Metabolic health is the largest single accelerator of decline — diabetes can steal six or more years of healthy function. Managing metabolic health is the highest-ROI intervention available right now.
But no amount of current intervention brings a healthy 90-year-old back to their functional state at 50. That’s what the data shows. And it’s why so many people, when asked if they want to live to 250, say no. They’ve intuited the trap: more years in functional decline is not a gift.
The goal of longevity medicine should not be to extend the period of decline. It should be to compress it — or eliminate it. More years of function, not more years of survival.
The Regulatory Trap That’s Killing the Field
Here is a structural problem that almost nobody talks about directly, but that shapes everything:
If you’re developing a longevity drug, regulators will push you toward a disease endpoint. Prove it reduces cardiovascular events. Prove it delays cognitive decline in an already-impaired population. Because aging isn’t a disease, you can’t run a trial against aging itself.
The problem is that a drug optimized to beat a specific disease will almost always be beaten, on that specific endpoint, by a drug designed specifically for that disease. So longevity drugs — tested against disease endpoints — will consistently look like inferior disease drugs. They’ll fail, or they’ll struggle for approval, or they’ll get approved with narrow labels that don’t capture their real value. This is a regulatory trap.
The company Loyal is doing something clever with dogs — they negotiated with the FDA to run trials against lifespan as a primary endpoint in dogs, rather than against a specific disease. That’s a preview of what needs to happen in human medicine.
What I’d advocate for: let longevity biotechs run Phase 2 trials against any biomarker they choose, as long as the trials are rigorous and nobody is being harmed. Then move to Phase 3 basket trials — where you enroll people who have one age-related disease and wait to see how long it takes them to develop a second one. That measures the underlying rate of aging in a practical, disease-independent way.
The regulatory system that enables this framework first will have a significant market advantage. It’s not just a scientific question — it’s a geopolitical one.
What a True Anti-Aging Drug Might Look Like
If I had to bet — and I should note I’m a physicist, not a clinician — I’d bet it looks like a vaccine.
Here’s the logic. Most of the damage that accumulates in aging tissues is supposed to be cleared by the immune system. Macrophages, the body’s cellular janitors, are responsible for removing cellular debris, senescent cells, misfolded proteins. Evolution has already spent millions of years optimizing this system. We are, already, remarkably long-lived mammals. Our immune system is already doing heroic work to get us to 80 or 90.
The question is whether we can fine-tune it to work a little harder. Not replace it with something synthetic. Not introduce a new scavenging mechanism from scratch. Just train what’s already there to be slightly better at the job it evolved to do.
A vaccine-like intervention that recalibrates immune surveillance toward damage clearance — that’s my best current guess for what the first true anti-aging therapeutic looks like. Not a pill. Not a gene therapy. A recalibration of an ancient biological system.
The Humanitarian Case
I want to end with something that often gets lost in the excitement about technology and capital.
Demographic transition is already happening. People are living longer and having fewer children. Nobody asked us whether we wanted this. Medicine has effectively made it harder to die young, and that’s mostly a good thing. But the downstream consequence — millions of people spending their final decade in a state of profound functional decline, surviving on medicine but not living — is a humanitarian crisis in slow motion.
Most people in their 30s and 40s today will live into their 90s, possibly beyond. The question is not whether they will live long. The question is whether those additional years will be years of capacity and engagement, or years of managed deterioration.
The current medical paradigm — focused almost entirely on treating disease while accepting functional decline as inevitable — is not a neutral choice. It’s a choice for the wrong version of the future. Every year we delay building the scientific and regulatory infrastructure for genuine anti-aging medicine is a year that compounds into millions of people’s lived experience.
This is not a matter of preference about which biology to fund. It is a humanitarian imperative to shift the field’s center of gravity from disease treatment to aging itself.
More people in this industry — scientists, investors, regulators — should be asking not “how do we cure more diseases?” but “how do we slow the underlying process that makes people vulnerable to all of them?”
That’s the only question whose answer is large enough to matter.
Peter Fedichev is co-founder of Gero, a longevity biotech company using AI and physics-based approaches to understand and target the aging process. This piece is adapted from remarks delivered at the J.P. Morgan Healthcare Conference.
Your discussion of physiological noise is particularly intriguing. One aspect that may deserve further consideration is the repeating transport architecture that surrounds virtually every cell: capillary → interstitium → cell membrane. This is where energy, oxygen, nutrients, and signals ultimately succeed or fail in reaching their destination.
From this perspective, physiological noise may partly reflect increasing transport delays across these interfaces. As exchange becomes less efficient, regulatory systems are forced into larger compensatory responses, making instability appear as noise at higher levels of organization.
This is why I remain cautious about narratives centered on finding the next molecule. The deeper challenge may be preserving permeability itself. Movement, circadian alignment, and metabolic flexibility are not merely lifestyle choices; they help maintain biological accessibility.
If this view is correct, longevity is not only a biomedical challenge but a societal one. We cannot expect pharmacology to fully compensate for schools, workplaces, and daily environments that systematically disconnect human biology from the conditions under which it evolved.
8.5/10