Revealing Airflow-Particle Dynamics in Dry Powder Inhalers

Dry powder inhalers (DPIs) are essential for pulmonary drug delivery, yet how adhesive formulation powders are converted into well-dispersed aerosols remains poorly resolved, which is highly device- and formulation-dependent. Here we integrate device and formulation characterization, theoretical analysis, numerical simulations, and machine learning to map airflow-particle dynamics across DPIs. Device geometry sets internal flow fields, which modulate drag, swirl, and impact, thereby mobilizing powders and driving transient deagglomeration. For fine particle-dominated DPI formulations, gravity acting on fines is negligible, whereas adhesive force dominates in static powder beds and decays as agglomerates break up, driven by aerodynamic interactions and particle impacts. Highly adhesive carrier-free agglomerates disperse via strong swirl and frequent particle-wall impacts, while carrier-based blends with moderate adhesion rely on aerodynamic drag and high-energy carrier impacts. Further assisted by machine learning, we identify flow rate, drag, and particle-wall impacts as primary contributors to dispersion, whereas particle-particle impacts are a principal inhibitor. This integrated work reveals how devices and formulations shape airflow-particle dynamics and aerodynamic performance, providing mechanism-based guidance for next-generation DPI design.