Using deep learning to understand how pediatric cancer cells respond to drugs
Official title: Deep learning of drug sensitivity and genetic dependency of pediatric cancer cells
Funded at University of Pittsburgh at Pittsburgh · NIH-10871858 · Data updated 2026-11-12
This study is exploring new ways to treat childhood cancers by using smart computer techniques to see how cancer cells from kids react to different medicines, hoping to find better treatments for young patients.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Pittsburgh at Pittsburgh NIH-funded |
| Lab location | 1 site (Pittsburgh, United States) |
| Project start | March 1, 2020 |
| Project end | June 30, 2026 |
| Funding year | 2024 |
| Award (this year) | $249,000 |
| NIH project number | 5R00CA248944-05 |
| Project ID | NIH-10871858 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include children diagnosed with various types of pediatric cancers who may benefit from new therapeutic approaches.
✕Less likely to help
Patients with adult cancers or those whose cancers are not represented in the pediatric cell lines being studied may not receive benefits from this research.
What this research studies
This research focuses on developing new therapies for pediatric cancers by utilizing advanced deep learning techniques to analyze how pediatric cancer cells respond to various drugs. The approach involves creating models that can predict drug sensitivity and genetic dependencies based on genomic data from both pediatric and adult cancer cells. By leveraging existing knowledge from adult cancers, the research aims to identify effective treatments for children with cancer, which is currently a challenging area due to limited resources. The findings will be validated through laboratory experiments and patient-derived models.
Why it matters
Potential benefit: If successful, this research could lead to more effective and personalized treatment options for children with cancer.
How similar studies have gone: Other research has shown success in using deep learning to predict drug responses in adult cancers, making this approach promising for pediatric applications.
Where this research is happening
-
University of Pittsburgh at Pittsburgh
Pittsburgh, United States Active
Researchers
- Principal investigator: Chiu, Yu-Chiao — University of Pittsburgh at Pittsburgh
- Study coordinator: Chiu, Yu-Chiao
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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.