Creating new models to understand immune responses in viral infections
Official title: Novel Hybrid Computational Models to Disentangle Complex Immune Responses
Funded at University of Idaho · NIH-10935967 · Data updated 2026-11-12
This study is exploring new ways to use computer models to understand how our immune system fights off viruses like COVID-19, with the goal of finding better ways to help people recover from severe infections.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Idaho NIH-funded |
| Lab location | 1 site (Moscow, United States) |
| Project start | September 26, 2023 |
| Project end | August 31, 2026 |
| Funding year | 2024 |
| Award (this year) | $228,422 |
| NIH project number | 5R01GM152736-02 |
| Project ID | NIH-10935967 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals who have experienced severe respiratory viral infections, particularly those related to COVID-19.
✕Less likely to help
Patients with mild or asymptomatic COVID-19 infections may not receive direct benefits from this research.
What this research studies
This research aims to develop innovative computational models that combine traditional mathematical approaches with machine learning to better understand the immune system's response to viral infections, particularly COVID-19. By integrating mechanistic biological knowledge with advanced data analysis techniques, the study seeks to predict how immune responses can be modulated to reduce mortality during severe respiratory infections. The research will involve testing these models in a mouse viral coinfection system, providing insights that could translate to human health.
Why it matters
Potential benefit: If successful, this research could lead to improved strategies for managing immune responses in patients with severe viral infections, potentially reducing mortality rates.
How similar studies have gone: Preliminary studies combining traditional mathematical models with machine learning have shown promise, indicating that this approach could lead to significant advancements in understanding immune responses.
Where this research is happening
-
University of Idaho
Moscow, United States Active
Researchers
- Principal investigator: Hernandez Vargas, Esteban Abelardo — University of Idaho
- Study coordinator: Hernandez Vargas, Esteban Abelardo
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.