The impact of age-related diseases happen sooner than you think. Welcome to the Thalion Initiative...

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.

The biology is ready? ...to be studied, sure. That's why we need funding. Nice proof-of-concept grant opportunity for repro aging

Are biophysical constraints biology's underrated variable? We focus mostly on signalling molecules but this new paper from @PetrovaLab shows that a physical constraint like osmotic pressure can block lymphatic vessel growth even when growth factors are abundant. So it's not controlling it instead of signalling but alongside it like an independent gate. If we remove AQP1 (might have heard of this water channel, Nobel-winning discovery, etc) , gut lymphatics shorten, fat absorption fails, mice gain less weight on a high-fat diet. The physical microenvironment is a co-determinant in the process. Another curious thing is the context-specificity: AQP1 marks stress-adaptive lymphangiogenesis in the gut, lymphedema, and inflammation but not in normal embryonic development. We see different programs, depending on physical context. Maybe biology is more mechanical than the dominant frameworks suggest.

Great piece on comparative biology and what it can teach us about aging by @Aria_Babu . Humans are already outliers. Most mammals get 1 billion heartbeats, we get 2 billion; we live decades past reproduction and way longer than animals our size. Yet there's so much more to learn from other species that can repair DNA, avoid cancer, or regenerate. worksinprogress.co/isue/the-…

Did they just discover cellular bombs? Biology is so much fun

A great snapshot of the field, and good to see the recognition of comparative and evolutionary biology in this report - we're betting a lot on it @TTIScience.

In this latest Lifespan Interview @DToddWhite discusses @TTIScience: applying a first-principles approach to aging biology, and building tools and datasets needed to accelerate longevity research. 👉 Read more: lifespan.io/the-thalion-init…

Everyone being excited that Bryan Johnson might “fix women’s health” in itself shows how dire the situation is. It's been so underfunded and under-researched that a wealthy man publicly funding a high-touch diagnostic workup for his girlfriend can look to some as one of the most ambitious efforts in the space. But let's not confuse personalized medicine with research infrastructure. Bryan is not funding women’s reproductive health research here. He is funding a very comprehensive clinical investigation for one woman. Great for Kate. But that is not the same as producing generalizable knowledge for women. It can't: -answer population level questions -tell us how endometriosis varies by age, genetics, immune state, hormonal history, metabolic health, parity, environmental exposures, or lesion location -validate a diagnostic pathway -determine sensitivity and specificity of ultrasound or MRI across disease stages -compare treatments -capture recurrence -explain mechanisms -build standards of care. We need real infrastructure - cohorts, mechanistic studies, better imaging, biomarkers, longitudinal datasets, trials and funding models that treat women’s health as core biology. That said, visibility is not nothing. If this gets people asking why endometriosis is still so poorly understood, why diagnosis is so slow, why women’s pain is normalized, and why reproductive biology has not received the seriousness it deserves, then it can be valuable

Cats aren’t worms. You don’t casually double the lifespan of a mammal. What we have is evidence of a large 1-year survival benefit in a tiny group of cats already suffering from advanced kidney disease. The 30-year claim is based on nothing. It's still exciting but for a different reason. The comparative biology angle is more interesting: cats may have a species-specific AIM vulnerability that makes kidney failure a major lifespan bottleneck and fixing that could matter a lot. But “doubling lifespan” is doing far more work than the data support.

Eggcelent work from Colossal 🥚 Artificial eggs for avian development are a genuinely eggciting step - not just for de-extinction, but for rethinking developmental environments. From incubation to ex utero systems and artificial wombs… a very fertile direction. I worked in an egg lab for 4 years, so excuse the puns. I have a lot in reserve. No need to eggsaggerate, but this is big.

Really impressive work! MouseMapper feels like a glimpse into the future of biology: whole-body, cell-level perturbation mapping, powered by deep learning and paired with spatial proteomics. And of course we love a paper with pretty pictures

Aging follows a predictable pattern. That suggests it's not random damage—it's programmed. Dr. João Pedro de Magalhães @jpsenescence proposes an interesting perspective on the theoretical underpinning of aging: our DNA is the hardware, while the epigenome—the chemical tags that turn genes on or off—acts as software. Over time, this software may become maladaptive, driving aging rather than merely reacting to damage. Here's what you need to know. 👇 🔍 The Research In his paper "Ageing as a software design flaw," Dr. de Magalhães compares the epigenome to computer software executing genetic instructions. Early in life, this developmental program orchestrates growth from a single cell to a fully formed adult. But after reproductive prime, these same genetic scripts might start working against us—suggesting aging may be less about accumulated damage and more about developmental instructions gone awry. Key Concepts: • DNA as Hardware: Our genetic code remains mostly stable, like a computer's unchanging foundation. • Epigenome as Software: Chemical marks dynamically switch genes on and off, like software toggles. • Developmental Programs: These processes guide cell division and tissue formation but may later trigger deterioration. 📊 Core Findings 1️⃣ Epigenetic Clocks (Horvath Clock) • Dr. Steve Horvath's work reveals that roughly 400 genome sites can predict chronological age with remarkable accuracy. • This clock starts ticking almost from conception, suggesting aging isn't random—it follows an orderly pattern written into our developmental script. 2️⃣ Predictable, Not Random • Aging markers like grey hair or bone density loss unfold predictably, not chaotically. • Across species—from mice to humans—the pace of development correlates with lifespan. Mice live fast and die young because their growth software runs at breakneck speed. 3️⃣ Maladaptive Developmental Software • Presbyopia—the stiffening of the eye's lens—illustrates how growth processes beneficial in youth (lens expansion) become harmful in mid-to-later life. • Similar dynamics appear in other tissues through hormone changes and immune shifts past reproductive age. 📖 Why This Matters Traditional theories treat aging as a linear accumulation of damage. But if aging is part of a developmental program, wear and tear isn't the sole culprit. Instead, we're dealing with a quasi-programmed decline, where the very instructions ensuring reproductive success later drive degeneration. • Antagonistic Pleiotropy: Genes advantageous early in life (promoting growth, rapid cell division) can have detrimental effects later, once survival for reproduction is achieved. • Evolutionary Limitations: Natural selection strongly favors traits that help us pass on genes, but it's less concerned with what happens afterward—so flaws in the software persist. 🛠️ Interventions & Practical Applications If developmental software inadvertently fuels aging, slowing or resetting it could boost healthspan: 1️⃣ mTOR Inhibition (Rapamycin) • mTOR drives cell growth and metabolism—crucial for development early in life. Later, overactive mTOR can accelerate tissue damage. • Rapamycin, by dialing down mTOR, extends lifespan in yeast, worms, flies, and mice—and is being explored in humans. 2️⃣ GH/IGF-1 Modulation (Metformin, Caloric Restriction) • High GH/IGF-1 fosters rapid growth but can promote diseases in old age. • Metformin and calorie restriction both reduce IGF-1 levels, correlating with improved metabolic health and increased longevity in animal models. 3️⃣ Cellular Reprogramming (Yamanaka Factors) • Shinya Yamanaka's breakthrough showed that four transcription factors (Oct3/4, Sox2, Klf4, c-Myc) can revert adult cells to a stem-cell-like state, effectively resetting epigenetic age. • Full reprogramming poses cancer risks, but partial or cyclical approaches may offer a factory reset on aging without unchecked cell growth. 💡 Key Takeaway When we view aging as a continuation of developmental processes rather than random decay, a new frontier for intervention emerges. Rather than playing whack-a-mole with diseases as they appear, we can aim to modify genetic and epigenetic programs before pathology sets in. From targeting pathways like mTOR/GH/IGF-1 to exploring partial cellular reprogramming, the prospect of true anti-aging therapies may rest on hacking the same software that built us in the first place. 🔗 Read the Full Review Curious to dive deeper into the idea of aging as a developmental software flaw? Explore our analysis to learn how epigenetic clocks, cancer paradoxes, and species-wide comparisons all converge on one notion: aging might be a predictable, programmable process that we can slow—or even reset. gethealthspan.com/science/ar…

Very much so. That’s why in the first phase of @TTIScience we build large scale multiomic evolutionary and developmental atlases.

Always been fascinated with animals since I was a kid -that pure wonder is literally what pulled me into biology. Now I'm rediscovering it through comparative biology/evolutionary lens. The Amazon molly’s genetic trick letting an all-female species outlive evolutionary doom by 10× is the perfect reminder, and a good example of why we’re putting a big focus on the comparative biology vertical at @TTIScience , using cross-species insights to rethink aging trajectories at scale. Nature keeps teaching us resilience in the most unexpected ways.

Fantastic work on AI for biology. Understanding the fundamentals through specific AI usecases where data is available.

Splendid work! Now imagine how we could decipher evolution and its adaptations if we would have large-scale datasets across all building blocks of life for all species. Not only genomes, but transcriptomes, metabolmes, lipidomes, methylomes, etc. We could really understand why certain species do not develop diseases or have century long lifespans.

Can we use natures adaptations from other animals to extend healthy lifespan in humans? I believe so! But the missing ingredient is infrastructure at scale: a shared, standardized comparative biology dataset that de-risks discovery for everyone. And this is exactly the kind of “public good” philanthropy can catalyze, and we are building at @TTIScience. More in my article for @CFObyPostmedia in the comment.