MATCHMAKERS: AI tools to predict TCR binding and design
Official title: MATCHMAKERS - Creating and training AI tools for TCR binding prediction and design
Funded at Massachusetts Institute of Technology · NIH-11514453 · Data updated 2026-11-12
Researchers are building AI tools to predict how T cell receptors recognize tumor antigens, with aims to help improve targeted immunotherapies.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Massachusetts Institute of Technology NIH-funded |
| Lab location | 1 site (Cambridge, United States) |
| Project start | May 1, 2024 |
| Project end | April 30, 2027 |
| Funding year | 2026 |
| Award (this year) | $1,209,684 |
| NIH project number | 3OT2CA297463-01S2 |
| Project ID | NIH-11514453 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates are patients with cancer or immune-related conditions whose tumor antigens could be targeted by TCR-based therapies.
✕Less likely to help
Patients not eligible for TCR-targeted therapies or without tumor antigens suitable for TCR recognition may see limited direct benefit.
What this research studies
This grant brings together immunology, structural biology, and computational experts to create large datasets of TCR-pMHC pairs and develop ultra-fast AI methods to predict recognition. The work is designed to generate generalized models that can guide design of TCRs and their targets, using human and mouse data from cancer and immunity contexts. By combining sequencing, structural insights, and machine learning, the team hopes to accelerate understanding of TCR-antigen interactions relevant to cancer therapy. The project is organized into four work packages focusing on data generation, high-throughput matching, model development, and validation.
Why it matters
Potential benefit: If successful, patients could see faster development of personalized or more effective T cell-based immunotherapies.
How similar studies have gone: Preliminary work in TCR-antigen prediction and high-throughput data generation has shown promise, but robust generalized predictors remain an area of active development.
Where this research is happening
-
Massachusetts Institute of Technology
Cambridge, United States Active
Researchers
- Principal investigator: Birnbaum, Michael — Massachusetts Institute of Technology
- Study coordinator: Birnbaum, Michael
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.