Using advanced imaging and data analysis to predict treatment responses in lung cancer patients
Official title: Prospective validation of a radiomics-based multi-modal predictive model for metastatic non-small cell lung cancer patients treated with PD-1 immunotherapy
Funded at Onc.ai, INC. · NIH-11007396 · Data updated 2026-11-12
This study is looking to create a smarter way to predict which patients with advanced lung cancer will benefit from a specific immunotherapy treatment, using a mix of advanced imaging and lab tests to help doctors make better choices for their patients.
Quick facts
| Grant type | Sbir 2 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Onc.ai, INC. NIH-funded |
| Lab location | 1 site (San Carlos, United States) |
| Project start | September 13, 2024 |
| Project end | August 31, 2026 |
| Funding year | 2024 |
| Award (this year) | $1,625,000 |
| NIH project number | 1R44CA291456-01A1 |
| Project ID | NIH-11007396 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are patients diagnosed with metastatic non-small cell lung cancer who are considering or currently undergoing PD-1 immunotherapy.
✕Less likely to help
Patients with other types of cancer or those not eligible for PD-1 immunotherapy may not benefit from this research.
What this research studies
This research aims to develop a new predictive model that combines advanced imaging techniques with clinical and genomic data to better identify which patients with metastatic non-small cell lung cancer will respond to PD-1 immunotherapy. By utilizing machine learning and computer vision on CT scans, alongside routine lab tests, the study seeks to improve patient selection for this treatment, which currently has low response rates. The goal is to create a more effective and personalized approach to cancer therapy, potentially leading to better outcomes for patients.
Why it matters
Potential benefit: If successful, this research could significantly enhance the ability to predict which patients will benefit from PD-1 immunotherapy, leading to improved treatment outcomes and reduced unnecessary costs and side effects.
How similar studies have gone: While there have been various attempts to predict responses to PD-1 immunotherapy, this radiomics-based approach is novel and has not been extensively tested in this context.
Where this research is happening
-
Onc.ai, INC.
San Carlos, United States Active
Researchers
- Principal investigator: Jordan, Petr — Onc.ai, INC.
- Study coordinator: Jordan, Petr
Related research
Other NIH-funded projects on the same topics.
-
Targeting GARP-TGFβ to Improve Immunotherapy in NSCLC
A new antibody approach aims to block a key TGFβ-related pathway in the tumor environment to help people with non-small cell lung cancer respond better to therapy.
-
Targeting DHX9 to boost viral-like immune response in Small Cell Lung Cancer
A scientist team is testing whether blocking a protein called DHX9 can make aggressive small cell lung cancer more visible to the immune system and more responsive to immunotherapy.
-
Integrated blood and radiomics to guide immunotherapy in metastatic NSCLC
A research project aims to use blood tests and advanced imaging patterns to personalize first-line immunotherapy choices for people with metastatic non-small cell lung cancer.
-
Blocking a tumor pathway to boost immunotherapy for non-small cell lung cancer
This project will see if adding a drug that blocks the Hedgehog pathway to immune checkpoint therapy helps people with non-small cell lung cancer by restoring the immune system's CD8 T cells inside tumors.
-
Improving Immunotherapy for Lung Cancer with CT Scans
This work aims to find new ways to predict which non-small cell lung cancer patients will respond best to immunotherapy using information from their routine CT scans.
-
Using CT scans and patient tests to predict who will benefit from PD‑1 immunotherapy
A computer tool combines CT scan features, blood and tumor markers, and clinical data to predict which people with advanced lung or bladder cancer are likely to benefit from PD‑1 immunotherapy.
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.