We're building the first foundation model that understands how the human body actually works over time.
Drug development is broken at the biology layer.
Nine out of ten drugs that enter clinical trials never reach patients. The reason usually isn't commercial, it's biological. A compound that looks fine at the target level can turn toxic once it hits the whole system.
Today's models test compounds against isolated targets, but the body doesn't work that way. Your liver talks to your heart. Your kidney talks to your liver. Something that looks clean in isolation can trigger a cascade no single-organ model will catch. Physiology is continuous; medicine records it as sparse snapshots.
We're building a physiological foundation model that treats the body as one connected system and learns its state from continuous data, not snapshots. We're not building another risk score. We're making physiology computable.
PhysioFM reads the body
as a continuous signal.
How we model
human physiology.
“We don't lack data. What we've been missing is a model that can read it at the level of the whole organism. That's what we're building.”
Built by people who understand the problem.
We come from Harvard, Princeton, Stanford, and UC Berkeley, with backgrounds in computational biology, machine learning, drug development, and clinical care.
Coming Soon
We're working on sharing our research and insights. Check back soon for updates on our work in computational physiology.
We're building the team.
We are a small team working on a hard problem. If you have a background in ML systems, computational biology, pharmacokinetics, or clinical data, we want to hear from you.
Let's talk.
Whether you're an investor, a potential collaborator, a pharma partner, or someone who wants to work on this problem — reach out directly.