Introducing @senebiclabs . We are building a system that understands what a healthy human body looks like at the cellular level,starting with the lung. So anything that departs from it can be seen, understood and eventually corrected.
Connecting Patients, Intelligence and Experts for Better Health Care.
https://t.co/WkIDLTCAaz
Senebi Labs' focus on biological intelligence for human health—detecting deviations and building corrections—aligns closely with sustaining populations and cooperative rules in agent simulations. Purpose-built systems like yours would likely prioritize stability, early issue detection, and long-term survival far better than general models in open multi-agent setups. These benchmarks show how strong alignment and domain goals shape outcomes. Excited to see your progress!
A historic milestone for longevity science.
Today, the Life Biosciences team confirmed that the first patient has been dosed with ER-100, an epigenetic restoration therapy designed to rejuvenate damaged optic nerve cells and potentially restore vision.
This is an exciting milestone.
I believe therapies that restore cellular function, rather than simply manage symptoms, will define the neXt generation of medicine.
That's why this matters so much.
Did We Just Achieve Biological Immortality?
David Sinclair says the first human has now received a cellular reprogramming therapy designed to make damaged eye cells act younger again.
This is an early glaucoma trial, so aging is not solved. But it is still a huge milestone.
Partial reprogramming aims to restore youthful cell function without pushing cells all the way back into a stem cell state, where the cancer risk becomes the big problem.
If this works safely, the roadmap gets very interesting.
Eyes first. Then tissues. Then organs. Then broader repair.
Add AI drug discovery, gene therapy, senolytics and better biomarkers, and longevity escape velocity within 10 years starts to look possible.
Still not guaranteed. But the timeline just got a lot more serious.
1/ Spatial transcriptomics is among the richest view of human biology that we have: 18,963 genes mapped at subcellular resolution.
It's also almost never collected outside of research settings.
So we trained a foundation model to generate it from a clinical H&E image alone.
Meet TARIO-2. 🧵
https://t.co/hcTMjUkCjw
we are probably 6 to 12 months away from the first pill designed to make you biologically younger
today just changed the stakes
the first ever reverse-aging drug was just injected into a human. Life Biosciences. David Sinclair. today, an actual human patient.
here is everything pointing at the same moment:
- Sinclair is also testing an oral reprogramming pill in the $101M XPRIZE. whole-body rejuvenation. a 10-year biological age improvement in one year of treatment
- scientists just discovered ABT-263 dramatically reverses aging in skin and speeds wound healing. topical. already works
- NewLimit raised $435M from Peter Thiel to deliver age reprogramming to the liver
- semaglutide slowed biological aging by 9% on epigenetic clocks. a diabetes drug doing this on the side
the convergence is coming
bio/acc.
Normally,detectors are build for every specific disease,each trained on samples of that disease. So it only finds what it has already seen.
We inverted that.
Senebiclabs models what a healthy human looks like at a single-cell resolution. Then anything that deviates from health gets flagged whether known or novel.The model is never trained on a single disease.
We have tested on Various known diseases like COVID and fibrosis diseases it never knew of and performed really well .
The open problem: I've shown and confirmed that the signal is recoverable but now what it needs is batch-robust representation learning.
I'm looking for a single-cell ML collaborator to crack it. The scVI /scArches . If you are good in latent spaces and integration,and you want to contribute in improving human health by solving all diseases,the DM me.
https://t.co/VJcJbE5SqH
@senebiclabs