Using real-world patient data to make clinical trials faster and fairer
Methods to improve efficiency and robustness of clinical trials using information from real-world data with hidden bias
This project creates methods to help clinical trials safely use real-world patient data so new treatments can be tested faster and more fairly.
Quick facts
| Grant type | U01 cooperative agreement |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Duke University NIH-funded |
| Lab location | 1 site (Durham, United States) |
| Project ID | NIH-11191394 on NIH RePORTER |
What this research studies
Researchers will develop statistical tools that combine randomized trial results with patients' medical records and registry data while guarding against hidden biases that can skew conclusions. They will build a sensitivity-analysis framework to show how robust trial findings are when external real-world controls are used, and design methods that selectively borrow and adjust information from those controls. The team will validate these methods using simulations and real-world datasets drawn from health systems and prior trials. There are no in-person visits for patients, though people whose records are in contributing databases may be indirectly involved.
Who could benefit from this research
Good fit: Patients with cancer, neurological disorders, or other conditions represented in participating electronic health records or registries would be the most relevant individuals for this work.
Not a fit: Patients without usable electronic health records in the contributing datasets or those seeking direct clinical treatment in the project will not receive a direct benefit from this methodological work.
Why it matters
Potential benefit: If successful, this could reduce the size and time of clinical trials and help effective treatments reach patients sooner with more reliable evidence.
How similar studies have performed: Some trials have used external real-world control groups to support approvals, but concerns about hidden bias have limited wider use, so this project builds on earlier examples while addressing unresolved gaps.
Where this research is happening
Durham, United States
- Duke University — Durham, United States (Active)
Researchers
- Principal investigator: Wang, Xiaofei — Duke University
- Study coordinator: Wang, Xiaofei
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 below.