In vitro assessment of dry powders for inhalation (DPIs) aerodynamic performance is an inevitable test in DPI development. However, contemporary trends in drug development also implicate the use of in silico methods, e.g., computational fluid dynamics (CFD) coupled with discrete phase modeling (DPM). The aim of this study was to compare the designed CFD-DPM outcomes with the results of three in vitro methods for aerodynamic assessment of solid lipid microparticle DPIs. The model was able to simulate particle-to-wall sticking and estimate fractions of particles that stick or bounce off the inhaler’s wall; however, we observed notable differences between the in silico and in vitro results. The predicted emitted fractions (EFs) were comparable to the in vitro determined EFs, whereas the predicted fine particle fractions (FPFs) were generally lower than the corresponding in vitro values. In addition, CFD-DPM predicted higher mass median aerodynamic diameter (MMAD) in comparison to the in vitro values. The outcomes of different in vitro methods also diverged, implying that these methods are not interchangeable. Overall, our results support the utility of CFD-DPM in the DPI development, but highlight the need for additional improvements in these models to capture all the key processes influencing aerodynamic performance of specific DPIs.

The development of novel dry powders for dry powder inhalers (DPIs) requires the in vitro assessment of DPI aerodynamic performance. As a potential complementary method, in silico numerical simulations can provide additional information about the mechanisms that guide the particles and their behavior inside DPIs. The aim of this study was to apply computational fluid dynamics (CFDs) coupled with a discrete phase model (DPM) to describe the forces and particle trajectories inside the RS01^® as a model DPI device. The methodology included standard fluid flow equations but also additional equations for the particle sticking mechanism, as well as particle behavior after contacting the DPI wall surface, including the particle detachment process. The results show that the coefficient of restitution between the particle and the impact surface does not have a high impact on the results, meaning that all tested combinations gave similar output efficiencies and particle behaviors. No sliding or rolling mechanisms were observed for the particle detachment process, meaning that simple bouncing off or deposition particle behavior is present inside DPIs. The developed methodology can serve as a basis for the additional understanding of the particles’ behavior inside DPIs, which is not possible using only in vitro experiments; this implies the possibility of increasing the efficiency of DPIs.

Computational fluid dynamics (CFD) coupled with discrete phase modeling (DPM) appeared as an alternative approach to the commonly used in vitro methods for the assessment of dry powders for inhalation (DPI) aerodynamic properties. The aim of this study was to compare the parameters that describe DPI aerodynamic performance, obtained computationally by CFD-DPM and in vitro by next generation impactor (NGI). The analyzed parameters included: emitted fraction (EF), fine particle fraction (FPF), mass median aerodynamic diameter (MMAD) and geometric standard deviation (GSD). The results showed that CFD-DPM simulated EF values were generally comparable to the NGI obtained values, but there were some differences between the results obtained by these two methods. On the other hand, CFD-DPM predicted MMAD values were almost twice bigger than the NGI determined values, while the predicted GSD values were lower than NGI obtained values. In addition, CFD-DPM predicted values indicated larger differences between MMAD for different formulations in comparison to the NGI results. The largest difference between CFD-DPM and NGI results was observed for FPF values. Namely, CFD-DPM predicted FPF values were markedly lower than the NGI determined values for four of five tested formulations. Overall, although the designed CFD-DPM model and NGI measurements provided comparable data on the DPI EF values, the other relevant parameters obtained by these two approaches largely diverged indicating the need for further refinement of computational models to fully capture DPI aerodynamic performance.