Lungs In Silico

In many of the world’s developing regions, air pollution is sky high and rising. Severe health problems in local populations are the result. Inhalers are one way to treat symptoms, but they are far from perfect. That’s why Suvash Saha and his team of scientists stepped in, using simulations in computational models to single out where medical devices fail in their delivery of medicine to the lungs.

Tell us about your background… 

When I was a high school student, I dreamed of studying medicine. For reasons beyond my control, I couldn’t fulfil that dream and ended up in mathematics instead. Then, during my Master’s, I met a professor who supervised my first project in computational fluid dynamics – an experience that inspired me to undertake further research.

Today, I am a senior lecturer at the University of Technology Sydney (UTS), where I have developed a lung modeling research group. We collect CT scan data and develop lung geometries using various image processing techniques. The outcomes of these geometries differ greatly from those obtained using idealized lung geometry, which can affect the treatment outcomes. My focus is on the deposition of both air pollution and drug particles in the lungs’ surfaces. I am also working on gold nanoparticle interaction with lung surfactants using a molecular dynamics (MD) simulation technique.

What drives your work?

I was motivated to work on drug delivery via inhalers when my young daughter was diagnosed with mild asthma. I found that the inhalers available on the market were not optimized for drug delivery.

The drug dispersion from currently available devices and formulations varies from 12 to 40 percent of the load dose and, worse, most of the drug particles are deposited on upper airways due to their large size. With this in mind, my Motilal Nehru National Institute of Technology research partner and I began designing DPI inhalers and visualizing particle deposition in realistic lung surfaces.

Tell us how your computational model could reveal potential improvements… 

Conducting in vivo experiments for inhaled drugs is extremely difficult. In vitro and in situ experiments are possible, but they can’t properly explain local deposition. This leaves in silico (computer modeling) as the best option for visualizing local deposition and related phenomena.

This is where my team and I step in, investigating the effect of realistic inhalation rates and drug particle size on targeted drug delivery in a lifelike human lung model. The aim is to improve understanding of airflow and drug deposition in the human respiratory tract. In our work (1), we found that more drug particles enter and are deposited in the right bronchi than the left due to the position of the heart. This suggests that drugs should contain smaller, finer particles to enable contact with the distal bronchi.

Were there any surprises during the research?

When we conducted our study using the device’s available particle size and flow rate, we found that most particles are deposited in the upper airways. To find out how to send the particle into the deeper airways, we performed parametric studies and obtained the optimum particle size and flow rate for a realistic breathing pattern.

Where do you hope to see your findings applied? 

Recently, we have developed additional geometries to simulate lungs of different ages. Now, we intend to perform simulations using those geometries. Our ultimate aim is to translate our research into clinical applications.