Using computer tools to speed up the discovery of new antibacterial drugs
Official title: Accelerating drug discovery via ML-guided iterative design and optimization
Funded at University of California-Irvine · NIH-11030803 · Data updated 2026-11-12
This study is working on new computer tools to help scientists find better antibacterial drugs faster and cheaper, making it easier for researchers to share their discoveries and get helpful suggestions for their next steps.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California-Irvine NIH-funded |
| Lab location | 1 site (Irvine, United States) |
| Project start | March 1, 2023 |
| Project end | February 29, 2028 |
| Funding year | 2025 |
| Award (this year) | $531,346 |
| NIH project number | 5R35GM148236-03 |
| Project ID | NIH-11030803 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for benefiting from this research include individuals suffering from bacterial infections that are resistant to current treatments.
✕Less likely to help
Patients with viral infections or those who do not have bacterial infections may not receive any benefit from this research.
What this research studies
This research focuses on developing advanced computational tools to enhance the process of discovering new antibacterial drugs. By utilizing machine learning and iterative design, the project aims to optimize drug candidates more efficiently, reducing the time and costs associated with traditional drug discovery methods. The approach involves creating a community resource where researchers can input their findings and receive prioritized suggestions for their next steps in drug development. This open science initiative aims to make drug discovery more accessible and effective for researchers across various fields.
Why it matters
Potential benefit: If successful, this research could lead to faster and more effective development of new antibacterial treatments for patients.
How similar studies have gone: Other research has shown success in using computational methods to accelerate drug discovery, indicating that this approach has potential for significant advancements.
Where this research is happening
-
University of California-Irvine
Irvine, United States Active
Researchers
- Principal investigator: Mobley, David Lowell — University of California-Irvine
- Study coordinator: Mobley, David Lowell
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.