Muno builds novel blood tests that predict what your immune system is fighting.
Your immune system already knows what's wrong. Antibodies bind to everything: pathogens, tumors, even your own proteins. The pattern of what they target is a map of disease. Today, diagnostics read that map 10–15 antigens at a time. Like finding a needle in a haystack. We use machine learning to predict how antibodies bind to antigens — turning months of wet-lab screening into hours of computation. We're building towards a future where you can screen thousands of antigens at once — in silico. We're starting where diagnostics fail most: autoimmune and post-infectious disease, conditions where millions wait years for answers. Our goal is to map every antibody to every disease in every patient. The map was always there, and we're building the technology to finally read it.
Current diagnostics rely on sequential, expensive wet-lab tests. For post-infectious conditions like long COVID, no subtyping test exists — leaving millions without answers.
The first diagnostic that classifies long COVID patients by their immune signature. We screen against a panel of hundreds of autoantigens to find the ones that matter.
Our computational engine generalizes across any condition where antibodies play a role.
Lupus, rheumatoid arthritis, type 1 diabetes — our engine identifies the specific autoantibody-antigen pairs driving each patient’s disease.
Long COVID, post-Lyme, ME/CFS — conditions where infection triggers immune dysregulation. We find the signature.
We identify common antigen targets across patients and sequence the autoantibodies that bind them — enabling decoy development and targeted immunomodulatory therapies.
Immunologists, computational biologists, and ML engineers working at the intersection of immunity, precision medicine and computation.
Join our waitlist to be among the first to experience immune-driven diagnostics.