AI to predict and improve CAR T cell cancer therapy
Multimodal AI modeling of T cell therapies to predict patient response and nominate advanced cell design strategies
This project builds AI tools to predict how people will respond to CAR T cell cancer treatments and to suggest molecular changes to make the cells safer and more effective.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Stanford University NIH-funded |
| Lab location | 1 site (Stanford, United States) |
| Project ID | NIH-11467177 on NIH RePORTER |
What this research studies
You will be hearing about AI systems that learn from detailed cell-level data, tumor images, and clinical records to forecast who will benefit from CAR T cell therapy and who might have side effects. One model (tcellGPT) uses single-cell and molecular profiles of the infused CAR T product, and another (tnicheAI) analyzes tumor images to find suppressive areas in the tumor environment. The two models are combined into tcellAI so doctors and researchers can see a fuller picture that includes the infusion product, the tumor, and patient health details. Clinicians and bioethicists are involved throughout to help protect privacy and fairness as the tools are developed.
Who could benefit from this research
Good fit: Ideal candidates are people with cancers being considered for or already scheduled to receive CAR T cell therapy at participating medical centers.
Not a fit: People without cancer or those who are not eligible for CAR T cell therapy are unlikely to benefit directly from this work.
Why it matters
Potential benefit: If successful, these tools could help clinicians personalize CAR T treatments, reduce toxic side effects, and speed development of better engineered cell therapies.
How similar studies have performed: Some prior studies have used machine learning to find predictors of CAR T outcomes, but combining single-cell, spatial pathology, and clinical data to also nominate cell-engineering strategies is a newer, less-tested approach.
Where this research is happening
Stanford, United States
- Stanford University — Stanford, United States (Active)
Researchers
- Principal investigator: Mackall, Crystal — Stanford University
- Study coordinator: Mackall, Crystal
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.