Using machine learning to improve safety in stimulant therapy for adults
Official title: Using machine learning to analyze integrated clinical and geo-social data to inform the design of a decision support system to reduce the risk of stimulant therapy
Funded at Pennsylvania State Univ Hershey Med Ctr · NIH-10984771 · Data updated 2026-11-12
This study is looking at how technology can help doctors understand the risks of using stimulant medications in adults by analyzing both medical and social information, so they can make safer choices for their patients.
Quick facts
| Grant type | Career grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Pennsylvania State Univ Hershey Med Ctr NIH-funded |
| Lab location | 1 site (Hershey, United States) |
| Project start | July 15, 2024 |
| Project end | June 30, 2029 |
| Funding year | 2024 |
| Award (this year) | $180,896 |
| NIH project number | 1K01DA059606-01A1 |
| Project ID | NIH-10984771 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are adults under 21 years old who are being considered for stimulant therapy or are currently using stimulant medications.
✕Less likely to help
Patients who do not use stimulant medications or are over the age of 21 may not benefit from this research.
What this research studies
This research investigates how machine learning can analyze clinical and social data to identify risks associated with stimulant therapy in adults. By examining large datasets, the project aims to uncover personalized risk factors for stimulant use disorder and overdose. The goal is to develop a decision support system that helps healthcare providers make informed choices about prescribing stimulants, ultimately reducing the risk of harm to patients. This approach combines clinical data with social determinants of health to create a comprehensive understanding of patient risk.
Why it matters
Potential benefit: If successful, this research could lead to safer prescribing practices for stimulant medications, reducing the risk of misuse and overdose among patients.
How similar studies have gone: Other research has shown promise in using machine learning for clinical decision support, indicating that this approach could be effective.
Where this research is happening
-
Pennsylvania State Univ Hershey Med Ctr
Hershey, United States Active
Researchers
- Principal investigator: Tuan, Wen-Jan — Pennsylvania State Univ Hershey Med Ctr
- Study coordinator: Tuan, Wen-Jan
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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.