AI to detect immune-related side effects after cancer immunotherapy
Informatics strategies to improve immune-related adverse event detection in cancer patients
This project uses AI language models to find and flag immune-related side effects in medical records of people treated with immune checkpoint inhibitor cancer therapies.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Brigham and Women's Hospital NIH-funded |
| Lab location | 1 site (Boston, United States) |
| Project ID | NIH-11174438 on NIH RePORTER |
What this research studies
If you had cancer and received immune checkpoint inhibitor treatment, this project aims to read your medical records (notes and data) with AI to identify inflammatory or autoimmune side effects that can show up long after treatment. The team will build and test neural language models that combine free-text clinic notes with structured EHR data to pull out these events accurately. They will run a clinical trial of the AI-assisted approach to see if it helps clinicians register patients into an irAE biorepository (Alliance A151804) for further study. The goal is to validate the tool in real clinical settings so it can be used to improve follow-up and research for survivors living with these side effects.
Who could benefit from this research
Good fit: Ideal candidates are people with cancer who received immune checkpoint inhibitors and have electronic health records at Brigham and Women's Hospital or participating Alliance clinical sites.
Not a fit: Patients who never received checkpoint inhibitor therapy or who do not have accessible medical records at participating centers are unlikely to benefit directly from this project.
Why it matters
Potential benefit: If successful, this could help spot immune-related side effects earlier and make it easier for patients to be enrolled in research that improves long-term care.
How similar studies have performed: AI and NLP tools have been used to extract clinical events from EHRs before, but applying them specifically for irAE detection and using them to drive biorepository enrollment is relatively new.
Where this research is happening
Boston, United States
- Brigham and Women's Hospital — Boston, United States (Active)
Researchers
- Principal investigator: Bitterman, Danielle S — Brigham and Women's Hospital
- Study coordinator: Bitterman, Danielle S
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 below.