Developing a quick test to identify bacteria and their antibiotic resistance directly from urine samples
Point-of-care antimicrobial susceptibility testing based on simultaneous tracking of multi-phenotypic features of single bacterial cells
['FUNDING_R01'] · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · NIH-10426291
This study is working on a new tool that helps doctors quickly find out if you have a urinary tract infection and which antibiotics will work best for you, so you can get the right treatment faster.
Quick facts
| Phase | ['FUNDING_R01'] |
|---|---|
| Study type | Nih_funding |
| Sex | All |
| Sponsor | ARIZONA STATE UNIVERSITY-TEMPE CAMPUS (nih funded) |
| Locations | 1 site (TEMPE, UNITED STATES) |
| Trial ID | NIH-10426291 on ClinicalTrials.gov |
What this research studies
This research focuses on creating a new technology that can quickly identify bacterial infections and determine which antibiotics will be effective against them, specifically for urinary tract infections (UTIs). By using advanced microscopy techniques and machine learning, the project aims to analyze individual bacterial cells in urine samples without the need for lengthy culturing processes. This approach allows for faster diagnosis and treatment decisions in healthcare settings, potentially improving patient outcomes significantly. The technology is designed to be used at the point of care, making it accessible for immediate clinical use.
Who could benefit from this research
Good fit: Ideal candidates for this research are individuals experiencing symptoms of urinary tract infections.
Not a fit: Patients with infections not related to urinary tract 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 lead to faster and more accurate treatment of bacterial infections, reducing the impact of antibiotic resistance.
How similar studies have performed: Other research has shown promise in rapid pathogen identification and susceptibility testing, but this specific approach using large-image-volume microscopy and machine learning is relatively novel.
Where this research is happening
TEMPE, UNITED STATES
- ARIZONA STATE UNIVERSITY-TEMPE CAMPUS — TEMPE, UNITED STATES (ACTIVE)
Researchers
- Principal investigator: WANG, SHAOPENG — ARIZONA STATE UNIVERSITY-TEMPE CAMPUS
- Study coordinator: WANG, SHAOPENG
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.
Conditions: Bacterial Infections, bacteria infection, bacterial disease