BACKGROUND: Accurate modelling of airflow and aerosol/particle dynamics within the human respiratory system is essential for improving inhalation-based drug delivery strategies and for evaluating the health risks associated with hazardous particulates. Owing to the complex geometry of the human airways, inter-individual anatomical variations, and variable breathing patterns, this process constitutes a highly complex multiphase flow problem. To address the constraints associated with in vivo and in vitro techniques, in silico approaches based on computational fluid dynamics (CFD) have been extensively utilized to examine respiratory airflow and aerosol dynamics at microscopic scales. OBJECTIVES: The aim of this study is to review recent CFD-based approaches for modeling airflow and aerosol behavior in the human respiratory system, summarize key modeling strategies and influential parameters, and identify future research directions. RESULTS: Recent studies indicate a transition of respiratory tract models toward more physiologically realistic and whole-lung representations. These studies demonstrate that coupling CFD with particle models enables reliable prediction of aerosol transport and deposition by accounting for the effects of geometric variations, breathing conditions, turbulence characteristics, and particle physical and chemical properties. CONCLUSION: CFD-based modeling, particularly when integrated with particle dynamics, provides a powerful and reliable framework for investigating airflow and aerosol behavior in the human respiratory system. Continued advancements toward realistic whole-lung models and improved representation of physiological and particle-related parameters are expected to further enhance predictive accuracy and support both clinical and environmental health applications.
Çiloğlu et al. (Mon,) studied this question.