AI-powered signatures to predict flu severity in diverse patients
Official title: Identifying Influenza Virus Infection Severity and Outcome Signatures Through Artificial Intelligence-driven Analyses
Funded at J. Craig Venter Institute, INC. · NIH-11377192 · Data updated 2026-11-12
Aging adults and children with flu may get sicker or recover differently, and this project will use artificial intelligence to find patterns across many data types to predict who will have severe illness.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | J. Craig Venter Institute, INC. NIH-funded |
| Lab location | 1 site (San Diego, United States) |
| Project start | July 7, 2022 |
| Project end | June 30, 2028 |
| Funding year | 2026 |
| Award (this year) | $733,054 |
| NIH project number | 5R01AI170111-04 |
| Project ID | NIH-11377192 on NIH RePORTER |
Who could benefit from this research
✓Could help
Patients with influenza across age groups, especially children and adults 65+, whose data can be used to train and test the predictive model.
✕Less likely to help
Patients whose data do not contribute to finding generalizable patterns may receive no direct benefit.
What this research studies
This project aims to combine multiple kinds of patient information, such as clinical data, lab results, and other measurements, to create a single model that can forecast how severe influenza may become in different people. By studying data from diverse age groups, including children and older adults, the researchers hope to identify signatures that signal higher risk. The work will involve building and testing an AI-based framework that integrates multiple datasets to predict outcomes more accurately than single tests. The ultimate goal is to inform clinicians on which patients need closer monitoring or more aggressive treatment.
Why it matters
Potential benefit: If successful, doctors could predict severe cases earlier and tailor care to each patient’s risk profile.
How similar studies have gone: Similar AI-based approaches have shown promise in predicting disease trajectories using multimodal data, though validation in broader populations is ongoing.
Where this research is happening
-
J. Craig Venter Institute, INC.
San Diego, United States Active
Researchers
- Principal investigator: Dupont, Christopher L. — J. Craig Venter Institute, INC.
- Study coordinator: Dupont, Christopher L.
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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.