Using AI to improve treatment planning for prostate cancer
Official title: Deep Learning-Based Treatment Planning for PSMA RPT
Funded at Yale University · NIH-11027895 · Data updated 2026-11-12
This study is looking to make prostate cancer treatment better by using advanced technology to personalize radiation therapy for patients with advanced cancer, so they can get the most effective care with fewer side effects.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Yale University NIH-funded |
| Lab location | 1 site (New Haven, United States) |
| Project start | January 1, 2025 |
| Project end | December 31, 2029 |
| Funding year | 2025 |
| Award (this year) | $602,361 |
| NIH project number | 1R01CA296305-01 |
| Project ID | NIH-11027895 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are men diagnosed with metastatic castration-resistant prostate cancer who are eligible for radiopharmaceutical therapy.
✕Less likely to help
Patients with early-stage prostate cancer or those not eligible for radiopharmaceutical therapy may not benefit from this research.
What this research studies
This research focuses on enhancing treatment planning for prostate cancer by utilizing advanced deep learning techniques. It aims to optimize the dosing of radiopharmaceutical therapy (RPT) for patients with metastatic castration-resistant prostate cancer (mCRPC) by analyzing imaging data from PSMA-PET and SPECT/CT scans. By tailoring treatment based on individual patient characteristics and the biodistribution of the therapeutic agent, the goal is to improve treatment efficacy and minimize side effects. Patients undergoing this therapy will benefit from a more personalized approach to their treatment.
Why it matters
Potential benefit: If successful, this research could lead to more effective and personalized treatment plans for patients with advanced prostate cancer.
How similar studies have gone: Previous research has shown promising results in using AI for treatment planning in oncology, indicating potential success for this novel approach.
Where this research is happening
-
Yale University
New Haven, United States Active
Researchers
- Principal investigator: El Fakhri, Georges — Yale University
- Study coordinator: El Fakhri, Georges
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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.