Predicting how gene therapy spreads in glioblastoma after surgery to improve treatment coverage
Official title: Quantitative imaging and computational modeling to predict gene therapy coverage in glioma following resection
Funded at University of Florida · NIH-11453740 · Data updated 2026-11-12
This project uses a gene therapy that helps radiation work better against glioblastoma and builds computer models to predict where the therapy reaches after surgical tumor removal.
Quick facts
| Grant type | R21 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Florida NIH-funded |
| Lab location | 1 site (Gainesville, United States) |
| Project start | September 18, 2026 |
| Project end | August 31, 2028 |
| Funding year | 2026 |
| Award (this year) | $416,401 |
| NIH project number | 1R21CA307416-01A1 |
| Project ID | NIH-11453740 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates are patients with glioblastoma who have undergone surgical resection and are eligible for gene-therapy–based approaches in the research continuum.
✕Less likely to help
Patients with glioblastoma who cannot receive gene therapy or MRI-based modeling as part of their care may not benefit.
What this research studies
Glioblastoma is a dangerous brain cancer with limited survival even with current treatments. The research combines an oncolytic adenovirus, prodrugs, and radiotherapy to increase tumor cell kill, aiming to understand why the therapy may not reach all tumor areas. Using computational modeling and imaging data, the team will predict AdV distribution and identify regions with insufficient coverage to guide dose planning. Validation will occur in patient-derived glioblastoma models in animals, with plans to translate findings toward patient-specific treatment strategies aided by MRI data. This work could help tailor therapies to individual patients and improve local tumor control after surgery.
Why it matters
Potential benefit: If successful, the approach could lead to personalized dosing and improved tumor coverage, potentially extending survival for glioblastoma patients.
How similar studies have gone: Previous studies show that modeling AdV distribution can inform dosing, but this exact integrative approach with DCE-MRI–driven personalization is still being explored.
Where this research is happening
-
University of Florida
Gainesville, United States Active
Researchers
- Principal investigator: Sarntinoranont, Malisa — University of Florida
- Study coordinator: Sarntinoranont, Malisa
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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.