Intranasal administration of drugs serves as a promising, noninvasive option for the treatment of various disorders of the central nervous system and upper respiratory tract. Predictive, ie, realistic and accurate, particle tracking in the human nasal cavities is an essential step to achieve these goals. The major factors affecting aerosol transport and deposition are the inhalation flowrate, the particle characteristics, and the nasal airway geometry. In vivo and in vitro studies using nasal cavity casts provide realistic images regarding particle-deposition pattern. Computational Fluid-Particle Dynamics (CF-PD) studies can offer a flexible, detailed and cost effective solution to the problem of direct drug delivery. The open-source software OpenFOAM was employed to conduct, after model validation, laminar and turbulent fluid-particle dynamics simulations for representative nasal cavities. Specifically, micron particles and nanoparticles were both individually tracked for different steady airflow rates to determine sectional deposition efficiencies. For micron particles, inertial forces were found to be the dominating factor, resulting in higher deposition for larger particles, mainly due to impaction. In contrast, diffusional effects are more important for nanoparticles. With a focus on the olfactory region, the detailed analysis of sectional deposition concentrations, considering a wide range of particle diameters, provide new physical insight to the particle dynamics inside human nasal cavities. The laminar/turbulent Euler-Lagrange modelling approach for simulating the fate of nanoparticles form a foundation for future studies focusing on targeted drug delivery. A major application would be direct nanodrug delivery to the olfactory region to achieve large local concentrations for possible migration across the blood-brain-barrier.
Copyright © 2020. Published by Elsevier Ltd.

References

PubMed