Experimental and numerical investigation of drug delivery and aerosol deposition in the mouth-throat airway using a pressurized metered dose inhaler (pMDI)

Abstract

Inhalation therapy is a widely used and effective method for treating respiratory diseases such as asthma and chronic obstructive pulmonary disease (COPD). Among the various inhalation devices, pressurized metered-dose inhalers (pMDIs) are the most commonly utilized due to their portability and rapid onset of action. However, despite their popularity, challenges remain in ensuring efficient and targeted drug delivery to the lungs. Factors such as airflow dynamics, inhalation profiles, device actuation, and anatomical variations can significantly impact drug deposition, particularly in the mouth-throat (MT) region, where substantial particle loss is often observed. This study aimed to improve the performance of inhalation therapy devices by leveraging insights gained from experimental in vitro studies and computational fluid dynamics (CFD) simulations. The thesis combines experimental measurements with CFD simulations (including USP-IP, COPD, and CF inhalation, pediatric geometry, and mucus modeling) to investigate the transport and deposition behavior of pharmaceutical aerosols delivered by pMDI devices. The experimental studies utilized an eight-stage Next Generation Impactor (NGI) setup paired with an industrial induction port (IP) and three-dimensional (3D)-printed mouth-throat geometries to quantify the deposition fraction on each stage, allowing for the plotting of particle size distribution. To facilitate this research, the geometry of the mouth-throat region was constructed using 3D printing technology with Ultimaker S3 and S5 printers, employing tough polylactic acid (PLA) for precise and durable models. High-performance liquid chromatography (HPLC) was used at the inhaler, MT geometry, and collection cup of each stage of the NGI to accurately measure the deposition of the active pharmaceutical ingredient (API). Additionally, CFD models were developed using the Eulerian-Lagrangian framework, which included the Discrete Phase Model (DPM) and turbulence models such as low Reynolds number (LRN) k-ω and Large Eddy Simulation (LES) to simulate particle and airflow dynamics under realistic physiological conditions. These models were validated against experimental data to ensure their accuracy and reliability. The initial project examined how airflow rate and spray cone angle affect aerosol deposition in an adult model of the mouth and throat. It was found that recirculation zones at the 90˚ bend in the oropharynx caused larger particles to be selectively retained. As airflow rates increased, the aerodynamic size of the particles decreased, leading to better delivery to the distal airways. However, larger cone angles resulted in more deposition in the mouth, while an 8˚ cone angle was identified as optimal for minimizing particle loss in the upper airway. These findings emphasized the importance of understanding the relationship between device parameters and inhalation dynamics to enhance drug delivery efficiency. The second part of the study examined the effects of constant and COPD-specific breathing profiles under varying humidity levels, focusing on how these factors influence particle transport and deposition. At low flow rates (30 L/min), there was a 39% increase in the deposition of large particles on the airway walls. In contrast, high humidity levels (99%) allowed more large particles (>5 μm) to pass through the airway, thereby reducing deposition in the mouth and throat. The COPD breathing profiles caused a slowdown in the development of the aerosol plume, leading to an increase in the deposition of large particles. Interestingly, regions of high turbulence, when combined with humidity, resulted in a 4% reduction in the deposition of large particles. This finding indicates complex interactions between environmental conditions and inhalation profiles. The third study expanded the research to a pediatric mechanical ventilation model that simulates a cystic fibrosis (CF) breathing profile. A 3D-printed airway derived from a CT scan was integrated into an NGI to validate CFD simulations. The study focused on the mucus boundary conditions using the Eulerian Wall Film (EWF) model and introduced a shear-thinning, non-Newtonian mucus layer. The results indicated that transient airflow broadened the particle size distribution, and the shear-thinning mucus disrupted the secondary flow, causing a more than 60% increase in the minimum particle size exiting the trachea. Additionally, a synchronized actuation (t = 0 s) has the highest deposition efficiency at 45.6%. Flow rate emerged as the most influential factor affecting deposition patterns, as supported by a Morris sensitivity analysis.