Using machine learning to improve understanding of drug interactions and genetic factors
Official title: Machine learning drives translational research from drug interactions to pharmacogenetics
Funded at Ohio State University · NIH-11038036 · Data updated 2026-11-12
This study is exploring how advanced computer technology can help us understand how different medications interact with each other and how your genes might affect how you respond to those drugs, all to make sure you stay safe and get the best treatment possible.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Ohio State University NIH-funded |
| Lab location | 1 site (Columbus, UNITED STATES) |
| Project start | May 1, 2023 |
| Project end | February 29, 2028 |
| Funding year | 2025 |
| Award (this year) | $634,590 |
| NIH project number | 5R01LM014199-03 |
| Project ID | NIH-11038036 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include patients who are taking multiple medications or those with specific genetic variations that affect drug metabolism.
✕Less likely to help
Patients who are not on any medications or those without relevant genetic variations may not benefit from this research.
What this research studies
This research investigates how machine learning and artificial intelligence can enhance our understanding of drug-drug interactions (DDIs) and pharmacogenetics (PG), which are significant causes of adverse drug events. By analyzing vast amounts of medical literature, the team aims to identify connections between DDIs and PG, ultimately leading to better patient safety and personalized medicine. The study will develop new methods to extract and analyze information from existing research, focusing on specific genetic variations that may affect drug responses.
Why it matters
Potential benefit: If successful, this research could lead to safer medication practices and more personalized treatment plans for patients based on their genetic profiles.
How similar studies have gone: Previous research has shown promise in using machine learning for drug interaction studies, indicating a potential for success in this novel approach.
Where this research is happening
-
Ohio State University
Columbus, United States Active
Researchers
- Principal investigator: Li, Lang — Ohio State University
- Study coordinator: Li, Lang
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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.