Using artificial intelligence to improve chemotherapy decisions for brain tumor patients
Official title: Artificial Intelligence-based decision support for chemotherapy-response assessment in Brain Tumors
Funded at Wm S. Middleton Memorial Veterans Hosp · NIH-10862550 · Data updated 2026-11-12
This study is testing a new AI system that helps doctors figure out which glioblastoma patients, especially veterans, might not benefit from standard chemotherapy, so they can find better treatment options and avoid unnecessary costs and procedures.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Wm S. Middleton Memorial Veterans Hosp NIH-funded |
| Lab location | 1 site (Madison, United States) |
| Project start | July 1, 2023 |
| Project end | March 31, 2028 |
| Funding year | 2024 |
| NIH project number | 5I01BX005842-02 |
| Project ID | NIH-10862550 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include veterans diagnosed with glioblastoma who are undergoing or considering chemotherapy.
✕Less likely to help
Patients with brain tumors other than glioblastoma or those not receiving chemotherapy may not benefit from this research.
What this research studies
This research focuses on developing an artificial intelligence system to assess how well patients with glioblastoma respond to chemotherapy. By analyzing patient data, the AI aims to identify those who are unlikely to benefit from standard chemotherapy treatments, allowing for more personalized and effective treatment options. The goal is to reduce unnecessary procedures and costs associated with ineffective therapies, particularly for veterans who may face unique challenges. The study will also explore how to differentiate between tumor recurrence and treatment effects using advanced imaging techniques.
Why it matters
Potential benefit: If successful, this research could lead to more tailored treatment plans for brain tumor patients, improving outcomes and reducing unnecessary procedures.
How similar studies have gone: Other research has shown promise in using AI for treatment decision-making in oncology, indicating potential success for this approach.
Where this research is happening
-
Wm S. Middleton Memorial Veterans Hosp
Madison, United States Active
Researchers
- Principal investigator: Tiwari, Pallavi — Wm S. Middleton Memorial Veterans Hosp
- Study coordinator: Tiwari, Pallavi
Related research
Other NIH-funded projects on the same topics.
-
AI tool to predict chemotherapy response for brain tumors
This project will build an AI tool to help doctors predict which people with glioblastoma are unlikely to benefit from chemotherapy.
-
Using localized chemotherapy to boost the immune response against brain tumors
This study is looking at how giving chemotherapy directly to the brain tumor can help boost the immune system's ability to fight glioblastoma, and it’s designed for patients with this type of brain cancer who want to explore new treatment options that might have fewer side effects.
-
Photodynamic lipids to boost chemotherapy for metastatic ovarian cancer
A patient-friendly approach tests a light-activated method to make ovarian cancer metastases more sensitive to chemotherapy.
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Dual targeting of heart cell receptors to prevent chemotherapy heart damage
Atrial patients receiving the chemotherapy drug doxorubicin may be protected from heart damage by targeting two heart cell receptors at once.
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A 3D ultrasound scanner to see early chemotherapy response in breast cancer
A new 3D ultrasound imaging method will be tested to see if it can quickly show whether breast cancer is responding to chemotherapy.
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ONC206 for children with brain tumors: a first-in-children trial
A first-in-children trial will test the safety and early signs of effectiveness of ONC206, taken by mouth, in kids with malignant brain tumors like diffuse midline gliomas.
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.