Abstract：
OBJECTIVE: Drug inhalation is generally accepted as the preferred administration method for treating respiratory diseases. To achieve effective inhaled drug delivery for an individual, it is necessary to use an interdisciplinary approach that can cope with inter-individual differences. The paper aims to present an individualised pulmonary drug deposition model based on Computational Fluid and Particle Dynamics simulations within a time frame acceptable for clinical use.
METHODS: We propose a model that can analyse the inhaled drug delivery efficiency based on the patient\'s airway geometry as well as breathing pattern, which has the potential to also serve as a tool for a sub-regional diagnosis of respiratory diseases. The particle properties and size distribution are taken for the case of drug inhalation by using nebulisers, as they are independent of the patient\'s breathing pattern. Finally, the inhaled drug doses that reach the deep airways of different lobe regions of the patient are studied.
RESULTS: The numerical accuracy of the proposed model is verified by comparison with experimental results. The difference in total drug deposition fractions between the simulation and experimental results is smaller than 4.44% and 1.43% for flow rates of 60 l/min and 15 l/min, respectively. A case study involving a COVID-19 patient is conducted to illustrate the potential clinical use of the model. The study analyses the drug deposition fractions in relation to the breathing pattern, aerosol size distribution, and different lobe regions.
CONCLUSIONS: The entire process of the proposed model can be completed within 48 h, allowing an evaluation of the deposition of the inhaled drug in an individual patient\'s lung within a time frame acceptable for clinical use. Achieving a 48-hour time window for a single evaluation of patient-specific drug delivery enables the physician to monitor the patient\'s changing conditions and potentially adjust the drug administration accordingly. Furthermore, we show that the proposed methodology also offers a possibility to be extended to a detection approach for some respiratory diseases.
METHODS: We propose a model that can analyse the inhaled drug delivery efficiency based on the patient\'s airway geometry as well as breathing pattern, which has the potential to also serve as a tool for a sub-regional diagnosis of respiratory diseases. The particle properties and size distribution are taken for the case of drug inhalation by using nebulisers, as they are independent of the patient\'s breathing pattern. Finally, the inhaled drug doses that reach the deep airways of different lobe regions of the patient are studied.
RESULTS: The numerical accuracy of the proposed model is verified by comparison with experimental results. The difference in total drug deposition fractions between the simulation and experimental results is smaller than 4.44% and 1.43% for flow rates of 60 l/min and 15 l/min, respectively. A case study involving a COVID-19 patient is conducted to illustrate the potential clinical use of the model. The study analyses the drug deposition fractions in relation to the breathing pattern, aerosol size distribution, and different lobe regions.
CONCLUSIONS: The entire process of the proposed model can be completed within 48 h, allowing an evaluation of the deposition of the inhaled drug in an individual patient\'s lung within a time frame acceptable for clinical use. Achieving a 48-hour time window for a single evaluation of patient-specific drug delivery enables the physician to monitor the patient\'s changing conditions and potentially adjust the drug administration accordingly. Furthermore, we show that the proposed methodology also offers a possibility to be extended to a detection approach for some respiratory diseases.
摘要：
目的：药物吸入是治疗呼吸系统疾病的首选给药方式。为了实现对个体的有效吸入药物递送,有必要使用能够应对个体间差异的跨学科方法。本文旨在在临床可接受的时间范围内提出基于计算流体和粒子动力学模拟的个性化肺部药物沉积模型。
方法：我们提出了一个模型，该模型可以根据患者的气道几何形状和呼吸模式来分析吸入给药效率。这也有可能作为一个子区域的呼吸系统疾病诊断的工具。颗粒性质和尺寸分布是通过使用雾化器吸入药物的情况下，因为它们与病人的呼吸模式无关。最后,研究了到达患者不同肺叶区域深气道的吸入药物剂量。
结果：通过与实验结果的比较，验证了所提出模型的数值准确性。对于60l/min和15l/min的流速，模拟结果与实验结果之间的总药物沉积分数差异小于4.44％和1.43％，分别。进行了一项涉及COVID-19患者的案例研究，以说明该模型的潜在临床用途。该研究分析了与呼吸模式相关的药物沉积分数，气溶胶尺寸分布，和不同的叶区域。
结论：所提出的模型的整个过程可以在48小时内完成，允许在临床使用可接受的时间范围内评估吸入药物在个体患者肺部的沉积。为患者特异性药物递送的单一评估实现48小时的时间窗口使医师能够监测患者的变化状况并可能相应地调整药物施用。此外，我们表明，所提出的方法也提供了一种可能性，可以扩展到一些呼吸道疾病的检测方法。
方法：我们提出了一个模型，该模型可以根据患者的气道几何形状和呼吸模式来分析吸入给药效率。这也有可能作为一个子区域的呼吸系统疾病诊断的工具。颗粒性质和尺寸分布是通过使用雾化器吸入药物的情况下，因为它们与病人的呼吸模式无关。最后,研究了到达患者不同肺叶区域深气道的吸入药物剂量。
结果：通过与实验结果的比较，验证了所提出模型的数值准确性。对于60l/min和15l/min的流速，模拟结果与实验结果之间的总药物沉积分数差异小于4.44％和1.43％，分别。进行了一项涉及COVID-19患者的案例研究，以说明该模型的潜在临床用途。该研究分析了与呼吸模式相关的药物沉积分数，气溶胶尺寸分布，和不同的叶区域。
结论：所提出的模型的整个过程可以在48小时内完成，允许在临床使用可接受的时间范围内评估吸入药物在个体患者肺部的沉积。为患者特异性药物递送的单一评估实现48小时的时间窗口使医师能够监测患者的变化状况并可能相应地调整药物施用。此外，我们表明，所提出的方法也提供了一种可能性，可以扩展到一些呼吸道疾病的检测方法。
