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<p>Pressurized metered dose inhalers (pMDIs) are among the most commonly prescribed inhalation devices; yet their performance often remains suboptimal. Although the inefficiencies of these inhalers have been recognized for a long time, the absence of a comprehensive numerical model that spans the entire process—from propellant injection to aerosol plume formation—has hindered efforts to identify the underlying causes of these issues. This study presents a novel multiphase framework based on the volume of fluid (VOF) approach, which captures key internal flow phenomena in pMDIs, including cavitation, flash boiling, and atomization. The model was validated using plume visualization data obtained via high-speed imaging, complemented by high-resolution X-ray imaging from prior <i>in vitro</i> studies. The proposed numerical framework demonstrates predictive capability by reproducing key plume characteristics in close agreement with multiple independent experimental datasets. It yields a mass median diameter of approximately 2.7&#xa0;μm, which closely aligns with the experimental value of 3&#xa0;μm. Additionally, the model captures the dynamics of the spray, predicting an initial velocity of around 110&#xa0;m/s and a cone angle of approximately 21°. These predictions are in excellent agreement with the high-speed imaging data obtained in this study. By moving beyond one-size-fits-all approaches, this platform enables the optimization and adaptation of inhaler configurations based on formulation-specific performance criteria, offering a promising tool to support the development of pMDIs tailored to a broad range of therapeutic applications.</p> Graphical Abstract <p></p>

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A Novel End-to-End Simulation Framework for Internal Flow in pMDIs: Coupled Modeling of Cavitation, Flash Boiling, and Atomization

  • 期刊论文

  • 发表日期：

    2025年11月6日

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  • Mona Mohammadkhani,
  • Janusz Kozinski,
  • Leila Pakzad

摘要

Pressurized metered dose inhalers (pMDIs) are among the most commonly prescribed inhalation devices; yet their performance often remains suboptimal. Although the inefficiencies of these inhalers have been recognized for a long time, the absence of a comprehensive numerical model that spans the entire process—from propellant injection to aerosol plume formation—has hindered efforts to identify the underlying causes of these issues. This study presents a novel multiphase framework based on the volume of fluid (VOF) approach, which captures key internal flow phenomena in pMDIs, including cavitation, flash boiling, and atomization. The model was validated using plume visualization data obtained via high-speed imaging, complemented by high-resolution X-ray imaging from prior in vitro studies. The proposed numerical framework demonstrates predictive capability by reproducing key plume characteristics in close agreement with multiple independent experimental datasets. It yields a mass median diameter of approximately 2.7 μm, which closely aligns with the experimental value of 3 μm. Additionally, the model captures the dynamics of the spray, predicting an initial velocity of around 110 m/s and a cone angle of approximately 21°. These predictions are in excellent agreement with the high-speed imaging data obtained in this study. By moving beyond one-size-fits-all approaches, this platform enables the optimization and adaptation of inhaler configurations based on formulation-specific performance criteria, offering a promising tool to support the development of pMDIs tailored to a broad range of therapeutic applications.

Graphical Abstract