Improving the effectiveness of inhalers for patients using machine learning.
Official title: ML-CFD-DEM Based Reduced Order Models (ROM) to Quantify Variability in Inhalers, Drugs, and Users for Evaluating Comparability of Generic OIDP Complex Products
Funded at Oklahoma State University Stillwater · NIH-11064450 · Data updated 2026-11-12
This study is looking to improve how well dry powder inhalers work by using smart technology to predict how well the medicine gets to your lungs, taking into account things like the inhaler's design and how you use it, so that everyone can get the best results from their inhalers, whether they are brand-name or generic.
Quick facts
| Grant type | U01 cooperative agreement |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Oklahoma State University Stillwater NIH-funded |
| Lab location | 1 site (Stillwater, United States) |
| Project start | September 1, 2024 |
| Project end | August 31, 2026 |
| Funding year | 2024 |
| Award (this year) | $300,000 |
| NIH project number | 1U01FD008379-01 |
| Project ID | NIH-11064450 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are patients who use dry powder inhalers for respiratory conditions.
✕Less likely to help
Patients who do not use inhalers or have conditions that do not require inhaled medications may not benefit from this research.
What this research studies
This research focuses on enhancing the performance of dry powder inhalers (DPIs) by developing advanced machine learning models that can predict how well inhaled medications reach the lungs. It takes into account various factors such as inhaler design, drug formulation, and individual patient characteristics, including specific lung conditions and how well patients use the devices. By creating more efficient models, the research aims to better understand the variability in inhaler performance and ensure that generic inhalers are as effective as their brand-name counterparts.
Why it matters
Potential benefit: If successful, this research could lead to more effective inhalers that improve medication delivery for patients with respiratory conditions.
How similar studies have gone: Other research has shown promise in using machine learning to improve medical devices, indicating potential success for this approach.
Where this research is happening
-
Oklahoma State University Stillwater
Stillwater, United States Active
Researchers
- Principal investigator: Feng, Yu — Oklahoma State University Stillwater
- Study coordinator: Feng, Yu
Related research
Other NIH-funded projects on the same topics.
-
Iron and scar-forming cells in the lungs (IPF)
Researchers are exploring how iron in the lungs may drive the scarring seen in idiopathic pulmonary fibrosis and whether this could lead to new therapies.
-
Understanding how a calcium sensor helps Pseudomonas infections resist the immune system
This project looks at how the bacteria Pseudomonas aeruginosa uses a calcium sensor to survive and cause infections in people with conditions like cystic fibrosis.
-
ERK1/2 signaling and SARS-CoV-2 immune dysregulation in the lung
Aims to see if blocking ERK1/2 in immune cells can reduce dangerous lung inflammation from SARS-CoV-2 and boost antiviral defenses.
-
OADDL Testing Support for Vet-LIRN (Veterinary Network)
A veterinary diagnostic lab in Oklahoma will support national animal health surveillance and testing programs by handling clinical samples, animal feeds, environmental samples, and necropsies to help keep animal health and food safety safer.
-
How social life affects cognitive health in older adults in rural and urban areas
A study following older adults in rural and urban areas to see how social networks and daily activities relate to thinking skills over time.
-
Biophysical view of how enzymes work to help fight cancer
A scientist is studying how enzymes work on a deep, molecular level to help design better cancer drugs with fewer side effects.
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.