Computational tools to predict human T-cell epitopes across people
Official title: Development of computational tools for accounting for host variability in predicting T-cell epitopes
Funded at Georgia Institute of Technology · NIH-11404004 · Data updated 2026-11-12
A new computational toolkit aims to better predict which parts of pathogens will trigger T-cell responses in different people, helping plan vaccines and therapies.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Georgia Institute of Technology NIH-funded |
| Lab location | 1 site (Atlanta, United States) |
| Project start | September 1, 2022 |
| Project end | August 31, 2027 |
| Funding year | 2026 |
| Award (this year) | $370,174 |
| NIH project number | 5R35GM147164-06 |
| Project ID | NIH-11404004 on NIH RePORTER |
Who could benefit from this research
✓Could help
Patients with infectious diseases, cancer, or allergies who may benefit from personalized epitope-based approaches.
✕Less likely to help
Patients seeking general, non-personalized treatments may not directly benefit.
What this research studies
This grant develops computer methods to predict how proteins are processed and which epitopes are recognized by T-cells, considering differences between individuals. It addresses the challenge that animal models don’t always forecast human responses, by focusing on human-specific immune processing. The project leverages genetic information to account for variability between pathogens and people, with the goal of improving epitope-based strategies for cancer and allergy treatment as well as infectious diseases. Researchers will combine immunology knowledge with computing methodologies to create robust predictive tools that can guide future experiments and therapies. The work is centered at Georgia Tech and aims to translate computational predictions into more precise immune targets.
Why it matters
Potential benefit: If successful, patients could benefit from more accurate vaccine designs and personalized immunotherapies.
How similar studies have gone: Similar computational approaches have shown promise in predicting immune targets, but human-specific prediction remains challenging and this project seeks to improve accuracy.
Where this research is happening
-
Georgia Institute of Technology
Atlanta, United States Active
Researchers
- Principal investigator: Kieslich, Chris a. — Georgia Institute of Technology
- Study coordinator: Kieslich, Chris a.
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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.