Towards Quantitative Prediction of the Performance of Dry Powder Inhalers by Multi-Scale Simulations and Experiments.

This work demonstrates the use of multi-scale simulations coupled with experiments to build a quantitative prediction tool for the performance of adhesive mixtures in a dry powder inhaler (DPI). Using discrete element model (DEM), the behaviour of fine-carrier particle assemblies upon different mechanisms encountered during dose entrainment and dispersion can be described at the individual particle level. Combining these results with computational fluid dynamics (CFD) simulations, the complete dosing event from a DPI can be captured and key performance measures can be extracted. A concept of apparent surface energy, ASE, was introduced to overcome challenges associated with the complex particle properties, e.g. irregular particle shapes and surface roughness. This approach correctly predicts trends observed experimentally regarding API adhesivity, flow rate and device geometry. By incorporating the effects of drug load, critical adhesion and surface energy distributions to the simulation tool, the fine particle fraction could be predicted with good agreement to experiments for two different formulations in two different devices at two flow rates. It is concluded that multi-scale simulations provide a useful tool to support device and formulation development, as well as to gain further insight into the physical mechanisms governing dispersion from DPIs.