Improving biomedical data integration and discovery for better research outcomes
Official title: DOGSLED: Data, Ontologies, and Graphs Supporting Learning and Enhanced Discovery
Funded at Univ of North Carolina Chapel Hill · NIH-11178965 · Data updated 2026-11-12
This study is working on making a tool that helps researchers combine different health data to find better treatments and solutions for patients, so everyone can benefit from faster scientific discoveries.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Univ of North Carolina Chapel Hill NIH-funded |
| Lab location | 1 site (Chapel Hill, United States) |
| Project start | December 24, 2024 |
| Project end | November 30, 2025 |
| Funding year | 2025 |
| Award (this year) | $2,685,210 |
| NIH project number | 1OT2TR005712-01 |
| Project ID | NIH-11178965 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for benefiting from this research include patients with conditions that require innovative treatment approaches informed by integrated biomedical data.
✕Less likely to help
Patients with conditions that are not addressed by the current biomedical data integration efforts may not receive direct benefits from this research.
What this research studies
This research focuses on enhancing a system called the Biomedical Data Translator, which integrates various biomedical data to help answer important clinical questions. By developing a new framework known as DOGSLED, the project aims to improve the efficiency and usability of this system, making it a more effective tool for researchers. Patients can benefit from this research as it seeks to accelerate scientific discoveries that could lead to better treatments and healthcare solutions. The project involves collaboration with various teams to ensure a comprehensive approach to data integration and discovery.
Why it matters
Potential benefit: If successful, this research could lead to faster and more effective treatments for patients by improving how biomedical data is utilized in clinical settings.
How similar studies have gone: Other research initiatives focused on data integration and AI in healthcare have shown promise, indicating that this approach could yield significant advancements.
Where this research is happening
-
Univ of North Carolina Chapel Hill
Chapel Hill, United States Active
Researchers
- Principal investigator: Bizon, Christopher — Univ of North Carolina Chapel Hill
- Study coordinator: Bizon, Christopher
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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.