Predicting treatment failure in patients with lung disease related to connective tissue disorders
Official title: A Multi-Dimensional Signature to Predict Treatment Failure in Patients with Connective Tissue Disease-Associated Interstitial Lung Disease
Funded at University of Michigan at Ann Arbor · NIH-11051661 · Data updated 2026-11-12
This study is looking to find ways to predict which patients with lung problems related to connective tissue diseases might not respond well to treatment, so that doctors can make better decisions and help patients get the right care sooner.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Michigan at Ann Arbor NIH-funded |
| Lab location | 1 site (Ann Arbor, United States) |
| Project start | January 15, 2025 |
| Project end | December 31, 2029 |
| Funding year | 2025 |
| Award (this year) | $196,245 |
| NIH project number | 1K23HL171871-01A1 |
| Project ID | NIH-11051661 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are patients diagnosed with connective tissue disease who are experiencing interstitial lung disease and are currently receiving immunosuppressive therapy.
✕Less likely to help
Patients with interstitial lung disease not associated with connective tissue diseases or those who are not receiving immunosuppressive therapy may not benefit from this research.
What this research studies
This research aims to develop predictive biomarkers that can identify patients with connective tissue disease-associated interstitial lung disease (CTD-ILD) who are at risk of treatment failure. By analyzing patient data, the study will assess lung function decline and other clinical outcomes to create a model that can guide treatment decisions. If successful, this approach could lead to earlier interventions, such as stronger immunosuppressive therapies or antifibrotic treatments, and timely referrals for lung transplantation. The principal investigator, Dr. Janelle Pugashetti, is focused on improving patient outcomes through better predictive tools.
Why it matters
Potential benefit: If successful, this research could significantly improve treatment outcomes for patients with CTD-ILD by enabling personalized therapy based on predicted treatment responses.
How similar studies have gone: While predictive models in similar contexts have shown promise, this specific approach to CTD-ILD treatment failure prediction is novel and has not been extensively tested.
Where this research is happening
-
University of Michigan at Ann Arbor
Ann Arbor, United States Active
Researchers
- Principal investigator: Pugashetti, Janelle Vu — University of Michigan at Ann Arbor
- Study coordinator: Pugashetti, Janelle Vu
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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.