Understanding the different types of COPD using advanced technology
Official title: Linking endotype and phenotype to understand COPD heterogeneity via deep learning and network science
Funded at Brigham and Women's Hospital · NIH-11001158 · Data updated 2026-11-12
This study is looking at chronic obstructive pulmonary disease (COPD) to better understand the different ways it affects people, using advanced technology to create detailed profiles that could help doctors provide more personalized treatments and improve predictions about how the disease will progress.
Quick facts
| Grant type | Career grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Brigham and Women's Hospital NIH-funded |
| Lab location | 1 site (Boston, United States) |
| Project start | January 1, 2023 |
| Project end | December 31, 2027 |
| Funding year | 2025 |
| Award (this year) | $178,200 |
| NIH project number | 5K01HL166705-03 |
| Project ID | NIH-11001158 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals diagnosed with chronic obstructive pulmonary disease (COPD) who exhibit a range of symptoms and disease progression.
✕Less likely to help
Patients with mild or early-stage COPD who do not exhibit significant heterogeneity in their condition may not benefit from this research.
What this research studies
This research investigates chronic obstructive pulmonary disease (COPD), a complex condition with varying symptoms and progression among patients. By utilizing deep learning and network science, the study aims to combine clinical and genomic data to create detailed patient profiles. These profiles will help identify distinct subtypes of COPD, which can lead to more personalized treatment options and better predictions of disease outcomes. The approach focuses on integrating various data types to enhance our understanding of the disease's heterogeneity.
Why it matters
Potential benefit: If successful, this research could lead to more tailored treatments for COPD patients, improving their quality of life and disease management.
How similar studies have gone: Previous research has shown promise in using advanced data integration techniques to classify complex diseases, suggesting that this approach could yield valuable insights for COPD as well.
Where this research is happening
-
Brigham and Women's Hospital
Boston, United States Active
Researchers
- Principal investigator: Maiorino, Enrico — Brigham and Women's Hospital
- Study coordinator: Maiorino, Enrico
Related research
Other NIH-funded projects on the same topics.
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-
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-
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This study is looking at how certain genes might affect chronic obstructive pulmonary disease (COPD) by examining cells in the lungs, and it hopes to find new ways to improve treatments for people living with this condition.
-
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This study is creating a helpful tool that uses smart technology to predict when patients with COPD might need medical care, so doctors can better support them and improve their health.
-
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A multicenter trial will test whether adding omalizumab helps people with COPD who are allergic to common indoor allergens and are exposed to them.
-
Integrative histo-genomic analysis to guide cancer risk and targeted therapies with interpretable AI
Researchers are developing an advanced AI-powered approach to map genetic and cellular patterns across breast and cervical cancers to help tailor treatments.
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.