Mona Mohammadkhani is a Ph.D. candidate in Chemical Engineering at Lakehead University, Canada. Her research in pharmaceutical aerosol science focuses on computational modelling of inhaled drug delivery and lung aerosol transport, with particular interest in patient-specific aerosol behavior and inhaler design strategies. During her Ph.D., she has authored seven first-author peer-reviewed papers in this field.
A key theme in her doctoral research is the development of advanced numerical and experimental frameworks to study aerosol transport and deposition in the human respiratory system. Her work links inhaler plume generation with regional and deep-lung delivery across platforms such as pressurized metered-dose inhalers (pMDIs) and soft mist inhalers (SMIs). These frameworks incorporate airway wall motion, mucus-coated airway surfaces, atomization-physics-informed plume behavior, and in vitro validation to better represent clinically relevant respiratory conditions.
Her current interests center on targeted drug delivery and the use of machine learning and AI-assisted modelling to connect computational fluid dynamics-generated deposition data with patient-specific clinical information. This work supports the development of tools for optimized inhaler selection, regional targeting, and personalized respiratory therapy.