Immunomatics raises $100K from GenDx co-founder for AI transplant tool
What's the deal? ImmunomaticsDealroom has a profile for this one. Try Dealroom →, a San Marcos, California healthtech startup building AI tools to assess transplant donor-recipient risk, has raised a $100,000 early-stage investment from Myosotis Investments B.V.Dealroom has a profile for this one. Try Dealroom →, the Netherlands-based life sciences firm founded by biotech entrepreneur Wietse Mulder.
The hire: Mulder has also joined Immunomatics as strategic advisor. He co-founded GenDxDealroom has a profile for this one. Try Dealroom →, a transplant diagnostics firm acquired by Eurobio Scientific in 2022, and spent nearly two decades in HLA and transplantation. He will guide the company as it validates its technology and prepares for commercialisation.
What's the endgame? Immunomatics is developing AI to improve transplant compatibility assessment beyond counting HLA mismatches. Using outcomes data, HLA typing, and machine learning, it aims to better estimate donor-recipient risks and support clinical decisions.
Founder and chief executive officer Lidio Meireles, a computational biologist, started the company after facing donor-selection uncertainty as a blood stem cell recipient, with limited tools to choose the lowest-risk donor.
Why now? The company is raising capital to accelerate validation and commercialisation. Alongside the Myosotis investment, it is running an equity crowdfunding campaign on Wefunder to let individual investors participate.
Immunomatics has received a $207,740 NIHDealroom has a profile for this one. Try Dealroom → SBIR Phase I award and is collaborating with the UC San Diego Transplantation Lab. It is now working to expand its clinical data, validate its models, and advance its regulatory strategy.
What they're saying: "He understands the science, the clinical environment, and what it takes to bring new transplant technologies to market," Meireles said of Mulder. Mulder said Meireles "brings a rare combination of computational expertise, scientific understanding, and personal experience as a transplant recipient."
The signal: The round is small, but the backing of a proven transplant diagnostics operator signals confidence in applying machine learning to donor matching — a field still largely reliant on simpler mismatch counting.
Read more: prnewswire.com
Image credit: Ken Lund
