Pharma moves too slow.
Now it's our turn.
Accelerating a cure for Long Covid with Silicon Valley speed.
Built by scientists and engineers from Google DeepMind, UCSF, and Mayo Clinic.
The Problem
This isn't a scientific mystery. It's an infrastructure failure.
The biology is increasingly understood, but nothing is reaching patients. Data is siloed across platforms, trials aren't getting funded, and there's no diagnostic biomarker. Pharma has no economic reason to move fast on a disease it can't yet define with a blood test.
All Tasks
Waiting for approval
The Problem
We acquired the largest long COVID patient dataset in existence
Millions of patients across multiple platforms. Treatments, symptoms, labs, biomarkers, and outcomes tracked longitudinally and structured for machine learning. This data existed in fragments across patient communities, EHR systems, and research cohorts. We combined it. Everything downstream starts here.
100M+ Affected
0 Approved Treatments
The Dataset
Our models rank which existing treatments actually work.
Patients are already recovering on off-label drugs, but nobody is systematically measuring which ones, for whom, or why. We run our models against the full dataset to rank therapeutics by real-world patient outcomes, stratified by symptom profile and severity. Not case reports. Not anecdotes. Signal at scale.
Longitudinal Outcomes
Largest Patient Dataset
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Treatment Discovery
We fund clinical trials to get those treatments formally approved
A drug can work and doctors can know it works, but without an approved indication for long COVID, most physicians won't prescribe it and insurance won't cover it. We're funding trials to re-indicate the highest-signal candidates. The compounds exist. The safety data exists. What's missing is the trial funding.
Off-Label Analysis
Real-World Efficacy
Clinical Trials
We're funding the development of the first long COVID diagnostic biomarker
There is no blood test or objective measure for long COVID today. That makes trials harder to run, treatments harder to evaluate, and patients harder to believe. We're deploying capital to research institutions to build validated diagnostic biomarkers. You can't treat what you can't measure.
Trial Funding
Drug Re-indication
Hey David!
Here is your Custom project & schedule
On going project :
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10:00 am to 10:30 am
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06:00 pm to 06:30 pm
Our Approach
Why Now
The science exists. The patients exist. The funding doesn't
Fragmented Data
Silos kill discovery.
Misaligned Incentives
Wrong problems get funded.
No Central Coordination
Thousands of dead ends.
We raised $20M because the bottleneck was never knowledge, but capital and infrastructure. Our team spans ML, computational biology, and clinical research. We're based in San Francisco and we're moving fast