Using machine learning to determine antibiotic resistance in bacteria
Antibiotic Resistance Determination Utilizing Machine Learning
This study is working on a smart computer program that can quickly figure out which antibiotics will work best for bacterial infections, helping doctors treat patients faster and more effectively.
Quick facts
| Grant type | U01 cooperative agreement |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Ut Southwestern Medical Center NIH-funded |
| Lab location | 1 site (Dallas, United States) |
| Project ID | NIH-10818431 on NIH RePORTER |
What this research studies
This research aims to develop advanced machine learning models that can accurately predict antibiotic resistance in bacterial infections. By utilizing whole-genome sequencing data, the project seeks to eliminate the lengthy process of culturing pathogens and performing phenotypic tests, which can take days. Instead, the team will create a deep-learning prediction model that can quickly identify the most effective antibiotics for various bacterial species and combinations. The ultimate goal is to enhance patient care by speeding up the diagnosis and treatment of bacterial infections.
Who could benefit from this research
Good fit: Ideal candidates for this research include patients suffering from bacterial infections, particularly those with chronic infections or those who have experienced antibiotic resistance.
Not a fit: Patients with viral infections or those who do not have bacterial infections may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could significantly reduce the time it takes to identify effective antibiotics for patients with bacterial infections, leading to faster and more effective treatment.
How similar studies have performed: Other research has shown promise in using machine learning for predicting antibiotic resistance, indicating that this approach has potential for success.
Where this research is happening
Dallas, United States
- Ut Southwestern Medical Center — Dallas, United States (Active)
Researchers
- Principal investigator: Zhan, Xiaowei — Ut Southwestern Medical Center
- Study coordinator: Zhan, Xiaowei
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.