Creating a new way to generate and protect clinical data for better patient care
Official title: A novel platform for synthetic generation and statistical obfuscation of tabular clinical data, simulated images, and machine-generated text
Funded at Grayrain, LLC · NIH-10696488 · Data updated 2026-11-12
This study is working on a new way to create safe, fake medical data that keeps your personal information private, so researchers and healthcare providers can share important information to help improve patient care and health outcomes.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Grayrain, LLC NIH-funded |
| Lab location | 1 site (Ann Arbor, United States) |
| Project start | September 15, 2023 |
| Project end | September 14, 2025 |
| Funding year | 2023 |
| Award (this year) | $324,632 |
| NIH project number | 1R41TR004515-01 |
| Project ID | NIH-10696488 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are patients whose data could contribute to or benefit from enhanced analytics in clinical settings.
✕Less likely to help
Patients whose data is already fully de-identified or who are not involved in clinical research may not receive direct benefits from this research.
What this research studies
This research focuses on developing a novel platform that generates synthetic clinical data while ensuring privacy protection. By using advanced algorithms, the project aims to create de-identified data that can be shared among healthcare and research organizations without compromising sensitive patient information. This approach addresses the current barriers to data sharing caused by privacy regulations and aims to enhance the usability of medical data for research and patient care. Patients may benefit from improved healthcare outcomes as a result of better data analytics and insights derived from this shared information.
Why it matters
Potential benefit: If successful, this research could lead to enhanced data sharing practices that improve patient care and outcomes.
How similar studies have gone: While there have been efforts to improve data sharing in healthcare, this specific approach to synthetic data generation and privacy protection is relatively novel and untested.
Where this research is happening
-
Grayrain, LLC
Ann Arbor, United States Active
Researchers
- Principal investigator: Shetty, Ronak — Grayrain, LLC
- Study coordinator: Shetty, Ronak
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.