Predicting how antibodies fight the flu to guide better vaccines
Multiscale Modeling of Influenza Neutralizing Antibody and Fc Effector Biology
Building computer models that use real vaccine and infection data to predict the kinds of antibodies people make against influenza so vaccines can be designed to give broader protection.
Quick facts
| Grant type | U01 cooperative agreement |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Duke University NIH-funded |
| Lab location | 1 site (Durham, United States) |
| Project ID | NIH-11249581 on NIH RePORTER |
What this research studies
This project will use large datasets from past influenza infections and vaccinations to train generative computer models that predict antibody sequences people produce. Researchers will combine those repertoire models with mechanistic simulations of antibody neutralization and Fc-effector functions to estimate how mixed antibody responses protect against flu. The models will be calibrated on human-derived infection and vaccination data and used to suggest vaccine designs, including mRNA approaches, that aim to elicit diverse but coordinated antibody responses. While the work is computational, its outputs are intended to guide future vaccine testing in people.
Who could benefit from this research
Good fit: Ideal participants would be people who have received flu vaccines or had influenza infections and are willing to share blood samples or vaccination/infection histories for model calibration.
Not a fit: People seeking immediate treatment for influenza are unlikely to receive direct clinical benefit from this primarily computational project.
Why it matters
Potential benefit: If successful, the work could help create flu vaccines that give broader, more durable protection, including against novel pandemic strains.
How similar studies have performed: Related AI and modeling efforts have shown promise at predicting antibody features and informing vaccine ideas, but translating these models into vaccines that protect people remains largely unproven.
Where this research is happening
Durham, United States
- Duke University — Durham, United States (Active)
Researchers
- Principal investigator: Chan, Cliburn C — Duke University
- Study coordinator: Chan, Cliburn C
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 below.