AI-powered dosing helper for vancomycin in ICU patients
Official title: Advancing Scalable AI-Powered Clinical Decision Support for AUC-Guided Vancomycin Dosing in ICU Patients
Funded at Loyola University Chicago · NIH-11357888 · Data updated 2026-11-12
A lightweight AI-assisted tool helps doctors estimate the right vancomycin dose for ICU patients to keep drug levels safe and effective.
Quick facts
| Grant type | R03 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Loyola University Chicago NIH-funded |
| Lab location | 1 site (Maywood, United States) |
| Project start | September 15, 2026 |
| Project end | August 31, 2028 |
| Funding year | 2026 |
| Award (this year) | $154,000 |
| NIH project number | 1R03TR006291-01 |
| Project ID | NIH-11357888 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates are ICU patients with serious gram-positive infections, such as MRSA, who are treated with vancomycin and for whom dosing decisions are critical.
✕Less likely to help
Patients not on vancomycin or not in ICU settings may not benefit from this specific dosing tool.
What this research studies
This project aims to turn an AI clinical decision support system into a scalable, evidence-based tool that suggests patient-specific vancomycin dosing based on the 24-hour AUC. It will use a data-sniffer to estimate AUC24 from electronic health records without full pharmacokinetic profiles and train explainable AI models with data from multiple hospitals. The effort includes building a modular prescriptive engine to guide dosing and creating a public-facing demonstration to involve clinicians and other stakeholders. By focusing on safe, effective antibiotic use in the ICU, the project seeks to support antibiotic stewardship and improve patient outcomes.
Why it matters
Potential benefit: If successful, the tool could help ICU clinicians dose vancomycin more accurately, potentially reducing kidney injury and treatment failure.
How similar studies have gone: Prior foundational work and related AI-CDSS efforts suggest that AI-assisted dosing can improve decision-making in critical care settings.
Where this research is happening
-
Loyola University Chicago
Maywood, United States Active
Researchers
- Principal investigator: Tootooni, Samie — Loyola University Chicago
- Study coordinator: Tootooni, Samie
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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.