Machine learning is transforming how drugs are designed. Yet, nine out of ten drugs that enter human trials still fail. They are designed against aggregated patient data that captures static moments and largely misses the essential moments where human biology actually changes.
Lupus moves in flares. A flare is a discrete, datable event — and it is almost never the day of a scheduled appointment.
1 Sun et al., 2022 · 2 Derived from ~$300B annual pharma R&D
We believe every drug will one day be tested in a virtual patient before it is tested in a person.
Those models will need data no hospital record or biobank holds today. We are gathering it.
Per-timepoint costs roughly halved since 2024.
FHIR mandates let patients bring their own history.
Thousands of daily patient relationships at near-zero marginal cost.
Advanced therapies demand longitudinal molecular profiling.
We watch each patient closer than anyone — the engine funds itself.
EHR via FHIR, validated PROs, wearables, and an agent that initiates contact. No app to download — Gather reaches out first, morning and evening, over WhatsApp and SMS.
PRE / FLARE / POST. Mobile phlebotomy at home within 24–48 hours of a flare, then sequence or bank. Our ML decides which samples run next, so spend follows signal.
Select a layer for detail.
Sampled at every event — PRE (baseline), ON (the event), POST (resolution). The same patient before, during and after each event: a disease-state transition no other platform captures.
The record compounds with every month of watching. Patients share in it: the longer they stay, the more they earn.
One patient, every layer, every event: a dataset that has never existed.
Immunology recruits at the highest cost in medicine, from information that is weeks to months stale.
of trials reach planned enrollment3
of trials run behind schedule3
lupus patients enrolled per site per month4
what a lupus trial spends per patient, all-in
3 Enrollment-barriers review, 2020 — 31% is a shortfall, not a success rate · 4 Md Yusof et al., BILAG-BR, Rheumatology 2021
Live in patients today: 100+ patients waitlisted, 5+ pharma waitlisted, first paid pilots Q4 2026.
Repository protocol and consent model in place. 1M+ patient reach, 10+ collaborations.
First paid pilots, and the first event-resolved cohort at molecular depth.
Dataset at licensing scale. The first licensing conversation opens.
Co-founded Valinor ($13M raised).Harvard Medical School.
Worked on product at Enveda.McGill, Bioengineering and Economics.
Our team and advisors come from Lila, Tempus, Enveda, McGill, and Harvard Medical School.
Tell us the indication and the protocol window you are trying to fill. We will tell you who qualifies today — and what the event-resolved record can show you.
Zhanel replies to partnering enquiries herself, usually within two working days.
