College of

Engineering, Architecture and Technology

Two OSU professors in the College of Engineering, Architecture and Technology received an NSF award in the amount of $549,999 for their research in developing a first-of-its-kind, user-friendly and trustworthy virtual human testing platform that can quantify the inhaler performance in a low-risk, time-saving, disease-specific, and patient-specific fashion, thereby accelerating inhaler innovation with enhanced drug delivery efficiency to designated lung sites.  

 

Dr. Yu Feng, an associate professor in the School of Chemical Engineering is the PI for this project and Dr. Chenang Liu, an assistant professor in the School of Industrial Engineering and Management is the Co-PI.  

 

"This innovation is of great importance to pharmaceutical companies and medical device design companies, especially for the chronic obstructive pulmonary disease (COPD) treatment as well as other chronic lung diseases", said Liu.  "By providing a reliable and comprehensive virtual testing environment, this all-in-one virtual human testing platform stands to accelerate the development and refinement of inhaler technology, ultimately benefiting patients suffering from respiratory conditions, since it can potentially achieve targeted drug delivery to the deeply undertreated small airways with optimal therapeutic outcomes and minimized side effects."

 

The proposed project will develop a virtual human testing platform by: (1) integrating disease-specific representative whole-lung geometries with the assistance of artificial intelligence (AI) and computational lung aerosol dynamics; (2) enabling droplet-vapor interaction simulation for multiple types of inhalers; and (3) designing an easy-to-navigate web-based user interface (UI) for this platform, enabling a widely-accessible way to input desired drug formulation and inhaler design parameters, and downloading bioequivalence data predicted by the virtual human testing platform for evaluating and optimizing inhaler design without the need for expertise in computational fluid-particle dynamics. The project will also advance the scientific knowledge in inhaler innovation by developing an AI-assisted approach to construct representative disease-specific chronic obstructive pulmonary disease (COPD) whole-lung models, which will help pharmaceutical companies understand how inhalers can deliver accurate doses into the disease-specific lung environment. The project will also serve as a non-invasive and cost-effective alternative tool for the comparative bioequivalence study of inhaler engineering and design on population groups with different lung diseases.

 

To read more about the award visit the NSF website.