Using AI to understand lupus nephritis progression in humans and mice
Official title: Using artificial intelligence to bridge human and murine studies of lupus nephritis progression
Funded at University of Chicago · NIH-10981178 · Data updated 2026-11-12
This study is exploring how artificial intelligence can help us understand lupus nephritis better by comparing tissue samples from people and mice, with the goal of finding new ways to predict and improve treatments for this serious kidney condition.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Chicago NIH-funded |
| Lab location | 1 site (Chicago, United States) |
| Project start | August 15, 2024 |
| Project end | July 31, 2029 |
| Funding year | 2024 |
| Award (this year) | $752,511 |
| NIH project number | 1R01AI180222-01A1 |
| Project ID | NIH-10981178 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals diagnosed with lupus nephritis who are experiencing challenges in treatment response.
✕Less likely to help
Patients with lupus nephritis who are not actively seeking treatment or those with other unrelated kidney conditions may not benefit from this research.
What this research studies
This research investigates how artificial intelligence can help bridge the gap between human and mouse studies of lupus nephritis, a severe kidney condition associated with systemic lupus erythematosus. By analyzing tissue samples from both humans and mice, the study aims to identify specific immune states that contribute to disease progression. The approach involves advanced imaging techniques and AI-driven analysis to better understand the mechanisms of the disease and predict treatment responses. This could lead to more effective therapies tailored to individual patient needs.
Why it matters
Potential benefit: If successful, this research could lead to improved prediction of treatment responses and better management of lupus nephritis for patients.
How similar studies have gone: Other research has shown promise in using AI and advanced imaging techniques to enhance understanding of autoimmune diseases, suggesting potential for success in this novel approach.
Where this research is happening
-
University of Chicago
Chicago, United States Active
Researchers
- Principal investigator: Clark, Marcus Ramsay — University of Chicago
- Study coordinator: Clark, Marcus Ramsay
Related research
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Objective classification of lupus nephritis using computer vision
A new computer vision tool uses deep learning to classify lupus nephritis from kidney tissue images to help doctors predict outcomes for patients with lupus.
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AI-powered look at lupus nephritis in humans and mice
Researchers will use artificial intelligence to compare kidney tissue from people with lupus nephritis to tissue from mouse models, aiming to understand why treatments work differently in humans.
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.