Study of DPI Carriers Design Parameters for Dry Powder Inhalation through Artificial Neural Network Modeling

Carriers are commonly used in dry powder inhalation to enhance the flowability, aerosolization and drug delivery efficiency of fine drug particles. The properties of carriers such as, size, shape, density, surface roughness, as well as carrier-to-drug ratio, inhalation flow rate, type of dry powder inhalers have important impacts on the drug delivery efficiency. However, there are contradictory reports in the literature on the effects of individual parameters on drug delivery efficiency. In this study, the effect of carrier properties, carrier-to-drug ratio, and inhalation flow rate on drug delivery efficiency in terms of emitted dose (ED) and fine particle fraction (FPF) are examined using artificial neural network (ANN) modeling. Image analysis is performed on scanning electron microscopy (SEM) images of carriers to determine the surface properties. Sensitivity analysis is carried out to determine important parameters that have the most impact on ED and FPF. Genetic algorithm (GA) is applied to determine the ANN modeling parameters. The effects and interactions of various factors on ED and FPF are revealed.