New smart methods to compare diabetes treatments using complex data
Official title: Novel and Rigorous Statistical Learning and Inference for Comparative Effectiveness Research with Complex Data
Funded at Rutgers, the State Univ of N.j. · NIH-11404068 · Data updated 2026-11-12
A scientist team at Rutgers is developing new, user-friendly statistical methods to compare different diabetes drugs and their safety in real-world data.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Rutgers, the State Univ of N.j. NIH-funded |
| Lab location | 1 site (Piscataway, United States) |
| Project start | September 1, 2023 |
| Project end | August 31, 2027 |
| Funding year | 2026 |
| Award (this year) | $339,523 |
| NIH project number | 5R01LM014257-04 |
| Project ID | NIH-11404068 on NIH RePORTER |
Who could benefit from this research
✓Could help
Adults with diabetes who are treated with different drugs and have rich health data available could benefit.
✕Less likely to help
Patients treated with a single drug in very simple data settings or without access to detailed medical information may see limited benefit.
What this research studies
If you have adult-onset diabetes, this project aims to make it easier for doctors to understand which treatments work best for different people by using advanced data methods. The researchers will create and test automated, reliable approaches to measure how well medications perform when lots of patient information is available. They will focus on high-dimensional data to uncover true treatment effects while controlling for confounding factors. The results will be shared so clinicians can apply them in everyday care and improve patient outcomes.
Why it matters
Potential benefit: If successful, the methods could help doctors choose safer and more effective diabetes treatments for individual patients.
How similar studies have gone: Previous CER work shows that robust statistical methods can improve treatment effect estimation in complex data, but this project aims to advance automated and rigorous approaches.
Where this research is happening
-
Rutgers, the State Univ of N.j.
Piscataway, United States Active
Researchers
- Principal investigator: Tan, Zhiqiang — Rutgers, the State Univ of N.j.
- Study coordinator: Tan, Zhiqiang
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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.