# Virtual Patient Cohorts to Illuminate Immunologic Drivers of Influenza Severity

> **NIH NIH R01** · UNIVERSITY OF TENNESSEE HEALTH SCI CTR · 2022 · $528,515

## Abstract

Project Summary
Influenza viruses result in a significant number of illnesses and deaths each year highlighting its health and
economic burden. Management of this disease is difficult, and little is known about how different host factor
contribute to heterogenous outcomes. To advance the goals of understanding the diverse immune responses to
influenza and predict risk, it is essential to develop new tools that can define individualized immune trajectories,
simultaneously account for multiple sources of heterogeneity, and accurately predict dynamics that drive disease
progression. This project addresses gaps in identifying the impact that host factors have disease outcome and
gaps in developing computational methods for respiratory infections that accurately predict inflammation and
disease severity. The studies will develop and exploit new predictive systemic immune models and simulate
human populations using virtual patient cohorts aims at differentiating clinical outcomes and identify downstream
effects of varying levels of basal immunity.

## Key facts

- **NIH application ID:** 10485704
- **Project number:** 1R01AI170115-01
- **Recipient organization:** UNIVERSITY OF TENNESSEE HEALTH SCI CTR
- **Principal Investigator:** Morgan Craig
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $528,515
- **Award type:** 1
- **Project period:** 2022-06-01 → 2027-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10485704

## Citation

> US National Institutes of Health, RePORTER application 10485704, Virtual Patient Cohorts to Illuminate Immunologic Drivers of Influenza Severity (1R01AI170115-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10485704. Licensed CC0.

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