Introduction: Dry powder inhalers (DPIs) are essential for pulmonary drug delivery, enabling efficient and precise deposition of drugs in the lungs. Optimizing DPI performance re-quires an in-depth understanding of the aerosolization process, including airflow dynamics and particle behavior, although patient variability remains a challenge in developing new inhaler types. This review examines the application of computational fluid dynamics (CFD) for analyz-ing and improving DPI function. Methods: A comprehensive literature review was conducted using PubMed, Scopus, and Web of Science, covering articles published from 2010 to 2025. Studies focusing on CFD modeling of airflow, particle dispersion, and deagglomeration in DPIs were selected based on predefined eli-gibility criteria. Screening was conducted at the title, abstract, and full-text stages. Results: The investigations indicate that CFD accurately models airflow patterns, pressure dif-ferentials, and particle trajectories in DPI devices. CFD methodologies vary in turbulence mod-els, boundary conditions, and particle tracking techniques. Significant findings include enhanced predictions of aerosol dispersion and insights into how device shape influences medication deliv-ery efficacy. Discussion: The findings underscore the growing significance of CFD in DPI research. CFD en-ables virtual prototyping, reduces the need for extensive experimental testing, and supports the optimization of inhaler design. Limitations include the complexity of precisely modeling particle and particle-wall interactions, as well as the requirement for experimental validation. Conclusion: CFD has proven to be an effective computational tool for examining the aerosoliza-tion mechanisms of DPIs. Its application facilitates the development of more efficient, patient-centric inhalation therapies by improving design accuracy and performance reliability.
Negi et al. (Fri,) studied this question.