A living watch-list
AI is moving fast in health — some genuinely useful today, much of it years away, and plenty of it hype. Here's how we sort it, with a bias toward what helps you make better decisions now, and honest attribution for the bold claims.
Every major wearable and lab has layered AI on its numbers. The shift is from raw data to interpreted insight: not just seeing your HRV drop, but being told what it might mean and what to do.
AI on WHOOP’s strain, recovery, and sleep data — turns HRV and sleep debt into plain-language guidance you can act on.
Oura’s AI reads your readiness, sleep, and activity trends and suggests concrete, personal adjustments.
100+ biomarker blood panels with AI-assisted interpretation. Powerful — but it can raise more questions than it answers, so bring results to a clinician.
A capable thinking partner: understand a lab result, prep questions before an appointment, sanity-check a plan. Not a doctor — verify anything that drives a real decision.
Two figures shape most of the AI-longevity conversation. We cite them as proponents — read their ambition with interest and their timelines with a pinch of salt.
Where the big money and the big claims are. Genuinely exciting, mostly not yet something you can buy. We track it so you can tell real progress from press releases.
The frontier is shifting from cutting DNA (permanent, off-target risk) to epigenetic silencing. Scribe Therapeutics’ ELXR platform switches genes off without altering the code — its lead STX-1150 drove durable LDL-cholesterol lowering in primates for ~18 months and is projected to enter human trials in 2026. Meanwhile CRISPR-GPT (Stanford, Princeton, Google DeepMind) is an AI “co-pilot” that designs editing experiments — in tests, non-specialists hit 90%+ efficiency on their first try.
Beyond gene therapy, labs use AI to virtually screen vast chemical space for “reprogramming cocktails” that nudge cells toward a younger state — the small-molecule cousin of Sinclair’s reprogramming work. AI-first drug shops like Insilico Medicine aim these methods squarely at aging, compressing early discovery from years toward months.
“Deep aging clocks” use AI across genomics, proteomics, and metabolomics to estimate biological vs. chronological age. Researchers are also mining the biology of long-lived species — bats, whales, naked mole-rats — for age-resistance pathways to borrow for humans.
Go deeper with the people shaping the field.
Further reading
This is a living page — the field changes monthly. Take the pledge and we'll flag what actually matters in the field note.