Creating a framework for collecting and studying sepsis samples using AI-driven alerts.
Official title: Scalable and Interoperable framework for a clinically diverse and generalizable sepsis Biorepository using Electronic alerts for Recruitment driven by Artificial Intelligence (short title: SIBER-AI)
Funded at Emory University · NIH-10755744 · Data updated 2026-11-12
This study is looking to better understand and treat sepsis by collecting samples from patients at different stages of their illness, using smart technology to quickly find and enroll participants from both ambulances and hospitals, so we can learn more about how sepsis works and how to improve care for everyone affected.
Quick facts
| Grant type | R21 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Emory University NIH-funded |
| Lab location | 1 site (Atlanta, United States) |
| Project start | January 1, 2023 |
| Project end | June 30, 2025 |
| Funding year | 2024 |
| Award (this year) | $184,487 |
| NIH project number | 5R21GM148931-02 |
| Project ID | NIH-10755744 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals diagnosed with sepsis, particularly those in critical care settings.
✕Less likely to help
Patients who are not diagnosed with sepsis or those who are not critically ill may not benefit from this research.
What this research studies
This research focuses on improving the understanding and treatment of sepsis, a life-threatening condition. It aims to develop a biorepository that collects biological samples from patients diagnosed with sepsis at various stages of their illness. By utilizing artificial intelligence to identify and recruit patients quickly, the study seeks to gather diverse data that can help uncover the different mechanisms of sepsis and improve treatment outcomes. Patients will be enrolled from both ambulance settings and hospitals to ensure a comprehensive approach to data collection.
Why it matters
Potential benefit: If successful, this research could lead to earlier and more effective treatments for sepsis, ultimately reducing mortality rates.
How similar studies have gone: Previous research has shown success in using biorepositories and AI-driven methods to enhance patient recruitment and data collection in critical care settings.
Where this research is happening
-
Emory University
Atlanta, United States Active
Researchers
- Principal investigator: Esper, Annette M. — Emory University
- Study coordinator: Esper, Annette M.
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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.