Modifying harmful oral microbes with smart peptides guided by machine learning
Official title: Modifying microbial dysbiosis by machine learning guided species-biased antimicrobial peptides
Funded at University of Kansas Lawrence · NIH-11305025 · Data updated 2026-11-12
A study aims to use machine learning to guide the design of targeted antimicrobial peptides that reshape the oral microbiome to help treat periodontitis in teens and adults.
Quick facts
| Grant type | R21 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Kansas Lawrence NIH-funded |
| Lab location | 1 site (Lawrence, United States) |
| Project start | September 4, 2026 |
| Project end | August 31, 2028 |
| Funding year | 2026 |
| Award (this year) | $252,275 |
| NIH project number | 1R21DE034950-01A1 |
| Project ID | NIH-11305025 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates are adolescents or adults with periodontitis who consent to participate and provide oral samples for analysis.
✕Less likely to help
Patients without periodontal disease or those unwilling to share samples may not benefit.
What this research studies
This project focuses on periodontitis, an inflammatory gum disease linked to harmful bacteria in the mouth. Researchers will use machine learning to identify species-biased peptides that selectively target dysbiotic microbes while preserving beneficial ones. The work combines computational design with laboratory testing to steer the mouth’s microbial community back toward a healthy balance. If successful, it could reduce relapse and lessen the need for broad antibiotics or surgery. Participants would be adults or adolescents with periodontal disease, potentially contributing samples or data to refine the approach.
Why it matters
Potential benefit: If successful, this approach could lead to more precise, less disruptive treatments for periodontitis and reduce relapse risk.
How similar studies have gone: Previous work shows promise in targeting specific oral bacteria; this project extends those concepts with machine learning-guided, species-specific peptides.
Where this research is happening
-
University of Kansas Lawrence
Lawrence, United States Active
Researchers
- Principal investigator: Tamerler-Behar, Candan — University of Kansas Lawrence
- Study coordinator: Tamerler-Behar, Candan
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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.