Using machine learning to find targeted cancer treatments
Official title: A visible machine learning system to discover targeted treatment solutions in cancer
Funded at Broad Institute, INC. · NIH-11042739 · Data updated 2026-11-12
This study is looking at how certain genes work together in cancer cells to find new ways to treat cancer, so that doctors can create personalized therapies that are more effective for each patient.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Broad Institute, INC. NIH-funded |
| Lab location | 1 site (Cambridge, United States) |
| Project start | March 1, 2023 |
| Project end | February 28, 2027 |
| Funding year | 2025 |
| Award (this year) | $100,527 |
| NIH project number | 5K00CA264422-05 |
| Project ID | NIH-11042739 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are cancer patients whose tumors have specific genetic mutations that could be targeted by the proposed therapies.
✕Less likely to help
Patients with cancers that do not have identifiable genetic vulnerabilities or those who are not eligible for targeted therapies may not benefit from this research.
What this research studies
This research aims to improve cancer treatment by understanding how different genes interact within cancer cells. By identifying specific gene pairs that, when disrupted together, can lead to the death of cancer cells, the project seeks to develop targeted therapies tailored to individual patients' genetic profiles. The approach involves creating a machine learning framework that integrates various types of biological data to map out cancer pathways and identify potential treatment strategies. This innovative method could help in designing more effective and personalized cancer therapies.
Why it matters
Potential benefit: If successful, this research could lead to more effective and personalized cancer treatments for patients based on their unique genetic vulnerabilities.
How similar studies have gone: Other research has shown promise in using machine learning and genetic interaction analysis to develop targeted cancer therapies, indicating that this approach has potential for success.
Where this research is happening
-
Broad Institute, INC.
Cambridge, United States Active
Researchers
- Principal investigator: Qin, Yue — Broad Institute, INC.
- Study coordinator: Qin, Yue
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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.