Advanced Computational Core supports smarter phage therapy design
Official title: Advanced Computational Core
Funded at J. David Gladstone Institutes · NIH-11265554 · Data updated 2026-11-12
A research center will use AI and high-throughput tests to design phage therapies against multi-drug resistant bacteria like Klebsiella pneumoniae, aiming to speed up precise matching of phages to bacterial strains.
Quick facts
| Grant type | P01 program project |
|---|---|
| Study type | NIH-funded research |
| Funding institution | J. David Gladstone Institutes NIH-funded |
| Lab location | 1 site (San Francisco, United States) |
| Project start | May 11, 2026 |
| Project end | April 30, 2031 |
| Funding year | 2026 |
| Award (this year) | $324,500 |
| NIH project number | 1P01AI195327-01 |
| Project ID | NIH-11265554 on NIH RePORTER |
Who could benefit from this research
✓Could help
Patients with infections due to multi-drug resistant Klebsiella pneumoniae or related pathogens may benefit from future phage-based treatments.
✕Less likely to help
Patients without access to phage therapy or those infected with non-target organisms may not benefit directly.
What this research studies
This grant funds an Advanced Computational Core that uses AI, bioinformatics, and modeling to predict how phage therapies interact with bacteria. It focuses on high-throughput assays to quantify each step of the phage infection cycle and to match phage genes to bacterial strains. Human lung organoids will be used to capture interactions that ordinary lab tests miss, helping ensure relevance to human disease. The work aims to produce open-source models and code to accelerate phage therapy development for resistant pathogens and beyond.
Why it matters
Potential benefit: If successful, patients with infections caused by resistant bacteria could benefit from faster, more effective phage therapies.
How similar studies have gone: Previous phage therapy research has shown promise, and this project builds on that by integrating AI and high-throughput assays to improve predictability.
Where this research is happening
-
J. David Gladstone Institutes
San Francisco, United States Active
Researchers
- Principal investigator: Pollard, Katherine S. — J. David Gladstone Institutes
- Study coordinator: Pollard, Katherine S.
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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.