Abstract
A rapid data-driven method for determining regional deposition of inhaled medication aerosols in human airways is presented, which is patient specific. Inhalation patterns, device characteristics, and aerodynamic particle size distribution of medications are considered. The method is developed using dimensional analysis and Buckingham Pi theorem, and provides total, regional, and lobar distributions of aerosol deposition. 34 dimensionless quantities are selected, of which 22 encode features of the airway trees and segmented lobes, 14 pertain to the device and the drug formulation, and 13 the inhalation profile of the subject. The dimensionless correlations are obtained using a large database of computational fluid dynamics results on patient specific airways. The intraclass correlation coefficient between the current method and its training dataset is 0.92. The difference between the predicted average lobar deposition in the six asthma patients and the in-vivo data is 1.3%. The model has the potential to offer insights into the effectiveness of personalized drug delivery in clinical settings and can aid in drug development cycles.