TCR-Antigen Map
Discovery of TCR-based signatures across disease areas


Adaptive has partnered with Microsoft to map and decode the human immune system. Specialized cells of the adaptive immune system, T and B cells, are continuously responding to infections and cancer as well as playing a significant role in developing autoimmune disease. By reading these signatures, we can make significant advances in how we detect and treat disease. Together we are using immunosequencing, proprietary computational modeling, and machine learning to discover T-cell receptor (TCR) signatures of disease. Using this data, we aim to translate the natural diagnostic capability of the immune system into the clinic.
We are building a map that links trillions of TCRs with the millions of clinically relevant antigens that are specifically targeted to attack, making the diagnosis of disease far more efficient and precise. This will make it possible to read what an immune system has fought or is currently fighting, with the goal of creating a better diagnostic for all diseases—from infectious diseases to autoimmune conditions to cancer.
We are interested in utilizing sample sets that can be mined for disease-associated TCRs, on the scale of 100s to 1000s of samples, in infectious diseases, autoimmune diseases and cancer.
Learning to decode the immune system to diagnose disease

Blood sample
The immune system is nature’s most finely tuned diagnostic, providing a fingerprint of a person’s health in their blood

Immunosequencing
We sequence TCRs from each individual sample that store the diagnostic information

Machine learning
We discover disease-specific TCR signatures by comparing TCRs across disease-specific cases and controls

Empowering care
Disease-specific signatures may be used by doctors and researchers to improve disease diagnosis, treatment and vaccines

Blood sample
The immune system is nature’s most finely tuned diagnostic, providing a fingerprint of a person’s health in their blood

Immunosequencing
We sequence TCRs from each individual sample that store the diagnostic information

Machine learning
We discover disease-specific TCR signatures by comparing TCRs across disease-specific cases and controls

Empowering care
Disease-specific signatures may be used by doctors and researchers to improve disease diagnosis, treatment and vaccines
This landmark collaboration is a cornerstone of the Microsoft Healthcare NExT initiative, and the first and only biotech and tech effort focused on revealing and translating insights about the immune system into actionable tools for clinicians.

Infectious Disease

Autoimmune Disease

Oncology

And More
Other diseases with unmet need for a blood-based diagnostic
Ongoing Clinical Studies
