Probably Genetic lands $12M Series A to turn rare disease data into drug targets
What's the deal? Probably Genetic has raised $12 million in a Series A round led by Threshold Ventures, with participation from Y Combinator and other existing investors. The AI platform diagnoses genetic diseases, and the round brings its total raised to $14 million.
What does it do? Its main product is a physician-ordered genetic test for undiagnosed rare disease patients, who typically wait seven years for answers. The company's AI converts self-reported symptoms, medical records, and biological data into phenotypic data to train precision medicine models. So far, it has collected data from 130,000 patients.
Where's the money going? Probably Genetic will use the capital to grow its core business, hire, and enter drug discovery. It plans to expand from saliva-based genetic testing to proteomic testing — which requires blood draws and is crucial for drug discovery — in 2027.
Why it matters: "The bottleneck in drug development isn't designing molecules anymore. It's knowing which targets are worth pursuing," said Emily Melton, managing partner and co-founder at ThresholdDealroom has a profile for this one. Try Dealroom → Ventures. She added that drugs backed by human genetic evidence are "roughly twice as likely to succeed," yet the data linking genes to real clinical outcomes "barely exists."
How the model works: Most patients pay nothing, as testing is covered by commercial and government plans. The rest face copays capped at $250 or get testing funded through pharma partnerships. Partners — including UCB, Biogen, Ultragenyx, ChiesiDealroom has a profile for this one. Try Dealroom →, BialDealroom has a profile for this one. Try Dealroom →, Mahzi TherapeuticsDealroom has a profile for this one. Try Dealroom →, and X4 Pharmaceuticals — want to identify patients for clinical trials or existing therapies.
Why now? In August, Probably Genetic was awarded up to $10 million from ARPA-HDealroom has a profile for this one. Try Dealroom →, an agency within the Department of Health and Human Services that funds high-risk research. It is participating in the agency's Rare Disease AI/ML for Precision Integrated Diagnostics program, using its dataset to find undiagnosed patients and supply drug developers with real-world data.
What's the endgame? "We can already train AI models that can cut that diagnostic delay short, but to train those models, you need really good data — and the data to train these models doesn't exist today," said co-founder and chief executive officer Lukas Lange. The idea took root when Lange, a genetics doctorate student at Oxford, spent hours sifting fragmented patient records to identify rare disease cases.
The signal: At $12 million, the round sits in the middle of the pack for its stage — modest by headline standards. But the structure hints at where health tech is heading: datasets built as a byproduct of patient care, then monetised through biopharma partnerships hunting the next generation of drug targets.
Read more: fiercehealthcare.com
Image credit: Probably Genetic
