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In this week’s newsletter

✅ “They reset their clock and are as young as if they had been born just days ago”. ✅ American Biostasis Foundation. ✅ Two new hallmarks of aging. ✅ One step closer for Verve Therapeutics. ✅ The FDA is beginning to phase out animal testing. ✅ The problem with trying to nuance AI hype.

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Three decades later C. elegans can still teach us a thing or two about aging

In 1993, Cynthia Kenyon transformed the field of aging biology when she showed that a single mutation in the daf-2 gene - the C. elegans equivalent of the insulin/IGF-1 receptor - could double the worm’s lifespan. This discovery overturned the long-standing assumption that aging was simply inevitable wear and tear, revealing instead that it could be genetically regulated.

Three decades later, research on C. elegans continues to deliver fresh insights. A new study from Björn Schumacher’s lab at the University of Cologne uncovers a naturally evolved program of age deceleration and reversal during the worm’s dauer* (diapause) stage - a stress-resistant, metabolically suppressed larval form that can survive harsh conditions for months.

* Wikipedia tells me that the german word dauer translates to “endurance”, “persistence” or “unlimited time“.

Remarkably, worms that exit dauer show no loss of reproductive capacity or lifespan, despite having spent up to several weeks in the dauer stage - far longer than the worm’s normal ~2–3-week lifespan - and accumulating substantial chronological time. In effect, dauer provides a model of suspended aging and rejuvenation without cell division, dedifferentiation, or pathological decline. In other words, it shows that an organism can dramatically slow biological time, maintain somatic integrity, and later resume full functionality - not by rewinding its cellular identity, but by preserving and repairing what’s already there.

The paper’s findings suggest that dauer worms deploy an orchestrated set of transcriptomic, metabolic, and DNA repair programs that both slow biological aging and restore youthful molecular states upon recovery. These include suppressed metabolic activity, heightened proteostasis, and transcription-coupled DNA repair that clears age-related lesions.

As Björn Schumacher put it in a LinkedIn post, “they reset their clock and are as young as if they had been born just days ago”. “How do they do it? Slowing metabolism and enhancing protein turnover to slow aging. Then, during diapause exit they reverse and repair their DNA to become biologically young again.”

For human aging research, these insights point to numerous possibilities. While humans have no dauer equivalent, the molecular strategies that sustain dauer survival - especially the balance between metabolic suppression, maintenance systems, and rejuvenation mechanisms - could inspire new approaches to slow or even reverse aspects of aging. Future interventions might aim to pharmacologically mimic dauer-like states: activating repair pathways, modulating metabolism, or enhancing proteostasis to extend healthspan and preserve function.

The enduring (no dauer pun intended) message from C. elegans is clear: aging is not just a passive drift toward decline - it is, at least in part, a regulated process. And this tiny roundworm, simple yet adaptable, keeps reminding us that nature has already solved many of the puzzles we are only beginning to understand.

News from around the longevity and health space.

Two new hallmarks of aging

Lo and behold, there are now 14 hallmarks of aging! Two new hallmarks have been sneakily introduced in the review paper From geroscience to precision geromedicine: Understanding and managing aging - authored by many of the same scientists behind the landmark Hallmarks of Aging papers.

The additions? Extracellular matrix changes (ECM)* and psychosocial isolation (highlighting the pathogenic effects of social disconnection and loneliness).

* I’ll very likely revisit ECM in an upcoming newsletter, but for now I can point you to this podcast interview with Alexander Fedintsev. Suffice it to say that its inclusion as a hallmark of aging was long overdue.

The paper then pivots to a vision of precision geromedicine, aiming to transform how we track and intervene in aging. Here are the key takeaways:

✅ A gene-centric framework is proposed, introducing “gerogenes” (aging accelerators) and “gerosuppressors” (aging brakes), akin to oncogenes and tumor suppressors in cancer.

✅ Multi-omics data - spanning genomics, epigenomics, proteomics, metabolomics, and microbiome profiles - are combined with clinical and digital biomarkers to create individualized biological aging profiles.

✅ AI is positioned as essential to integrate and interpret this “data tsunami,” transforming complex, multi-layered measurements into actionable clinical insights — not relying on a single aging clock but aiming for composite, personalized assessments.

✅ The ambition is not merely to slow aging but to detect, prevent, or even reverse early aging trajectories, moving beyond today’s preventive medicine.

However, Reason over at Fight Aging! offers a timely reminder that this version of geroscience remains modest in scope compared to the more ambitious damage repair approach: “It seeks only to modestly slow aging, and will likely only achieve that goal. In contrast, damage repair approaches aim at outright rejuvenation. These two approaches to aging are not in conflict in principle, are complimentary strategies - but they are in conflict when it comes to the space of ideas, funding, and the will to make progress”

The problem with trying to nuance AI hype

I read this article in The Atlantic after a recommendation from Insilico CEO Alex Zhavoronkov, who is also quoted in it. It explores the possibilities and limitations of AI in science, drawing a contrast between the bold claims of Big AI executives and the more grounded perspectives of scientists working on the front lines.

But I found it disappointing. The piece suffers from a kind of present-tense bias: it judges the credibility of ambitious long-term* visions by measuring them against the limitations of today’s AI models. That’s a false equivalence. When people like Sam Altman, Dario Amodei, or Demis Hassabis talk about curing disease, they’re clearly referring to what next-generation systems might enable - not what GPT-4 or AlphaFold can do right now. To imply otherwise is not a sober correction; it’s a distortion.

* In AI, “long-term” increasingly means anything from a few years to perhaps 15 or 20. That’s part of the backlash against perceived tech hype: many people still struggle to grasp what exponential progress actually looks like.

In fact, many of the article’s “tempering” points - like how expensive hypothesis testing is, how long trials take, and how AI still requires experimental validation - are precisely the kinds of bottlenecks being targeted by parallel revolutions in robotics and lab automation. These developments barely get a passing mention in the piece, even though they could arguably be more transformative in the short term than LLMs themselves. Insilico, which the article cites, has already built AI-integrated robotic labs. The feedback loop is starting to close: AI models won’t just propose ideas - they will increasingly be able to test them, physically, in semi-autonomous systems. That alone challenges the framing of AI as merely an overhyped research assistant.

There’s also a narrowness to the scope. The piece focuses almost entirely on drug discovery, ignoring how generative models and AI agents are already reshaping adjacent fields: materials science, synthetic biology, even experimental physics. Nor does it address the underlying shift in who can do science when AI tools lower the barrier to entry. Science is not just changing in speed, but in structure.

Finally, there’s a strange (but not uncommon) assumption running through the article that “real” scientific progress must come from human novelty, while AI-generated insights are inherently derivative. But that’s a misunderstanding of how science has always worked. The best human scientists also build on priors, remix existing ideas, and work within constraints. That a model can now surface a key hypothesis - sometimes the same one a human team took years to arrive at - is not a failure of creativity. It’s a signal that the tools are getting better at navigating complexity faster than we can.

In trying to inject caution, the piece ends up soft-pedaling what may be the most important transition in the history of science: when intelligence itself - disembodied or not - becomes a scalable resource.

Less animal testing, more AI

The move is both long awaited and deeply contested: the FDA is beginning to phase out animal testing for certain drug classes, turning instead to computational models (including AI), organoids, and human cell lines to assess safety and efficacy. But however intense the current debate around this will be, there’s no denying this marks a shift in the direction of drug development. It’s, simply put, the future.

The FDA’s move centers on monoclonal antibodies and select biologics, where robust human data from international use already exists. If successful, this shift could speed up drug development, reduce R&D costs, and improve patient access - all while marking a milestone for ethical reform in biomedical research.

But while advocacy groups like PETA applaud the change, many in the pharmaceutical and research sectors caution that alternative methods are still evolving and may not yet capture the full complexity of human biology. For now, the FDA is proceeding cautiously, using case-by-case waivers and a pilot program to guide broader policy changes.

The drugs DO work

Verve Therapeutics has become something of a regular feature in this newsletter over the past few months - and for good reason. This gene-editing treatment holds the promise of a future where a single dose could provide lifelong control of LDL-C, potentially transforming the way we treat heart disease.

Now, Verve has announced positive initial data from its Phase 1b clinical trial. According to the press release: ”Single infusion of VERVE-102 led to dose-dependent decreases in blood PCSK9 and LDL-C, with mean reduction in LDL-C of 53% and a maximum reduction of 69% observed in the 0.6 mg/kg dose cohort […] VERVE-102 was well-tolerated with no treatment-related serious adverse events.”

By the way, bonus point to you if you caught the reference in the headline.

Chilly season in the longevity field

The cryonics field has seen an unusual burst of momentum in recent weeks. Let’s take a look:

✅ Alex Zhavoronkov, CEO of Insilico Medicine (also mentioned above), announced his personal investment in Wake Bio, a new stealth startup founded by ex-Google Brain scientist Mark Woodward, aiming to help build a real cryonics industry.

✅ Meanwhile, CryoDAO revealed plans for the American Biostasis Foundation, a major new facility in Texas that will serve as a long-term storage site and in-house research lab for cryopreserved humans and pets — in partnership with European company (and my cryonics provider) Tomorrow Bio.

✅ And Tomorrow Bio itself just unveiled a next-gen perfusion system, integrating smart alarms and automated monitoring to make the preservation process safer and more reliable across ambulances, surgical rooms, and transport kits.

Hey, you’ve made it all the way here! Thank you so much for reading! 🫶🏼