Development of a mathematical correlation for polydisperse non-spherical drug particle deposition in the human upper respiratory system

IF 0.7 Q4 ENGINEERING, BIOMEDICAL
Sanaz Aghaei, Hassan Khaleghi
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引用次数: 0

Abstract

Estimating the drug particle deposition in the upper respiratory system is essential to provide more effective treatment for respiratory diseases. This study numerically investigates the effect of both particle size distribution and particle shape on the total deposition efficiency in the human upper respiratory system. To investigate the effect of particle size distribution, spherical monodisperse and polydisperse particles are compared. Non-spherical polydisperse particles are also studied to investigate the effect of sphericity. It is concluded that by decreasing particle size and increasing particle sphericity, the total deposition efficiency decreases. This means that more particles escape from the upper airways to the bronchi and bronchioles. Therefore, for lung disease treatment, finer particles with higher sphericity are more suitable. Furthermore, a mathematical correlation is developed to represent the total deposition efficiency as a function of Stokes number and sphericity. This correlation estimates the deposition of both spherical and non-spherical polydisperse particles.
多分散非球形药物颗粒在人体上呼吸道沉积的数学相关性研究
了解药物颗粒在上呼吸道系统的沉积情况,对于提供更有效的呼吸系统疾病治疗至关重要。本文通过数值模拟研究了颗粒大小分布和颗粒形状对人体上呼吸道总沉积效率的影响。为考察粒径分布的影响,对球形单分散颗粒和多分散颗粒进行了比较。对非球形多分散颗粒也进行了研究,探讨了球形度的影响。结果表明,减小颗粒尺寸和增大颗粒球形度会降低总沉积效率。这意味着更多的颗粒从上呼吸道逃逸到支气管和细支气管。因此,对于肺部疾病的治疗,更适合球度较高的细颗粒。此外,还建立了总沉积效率与Stokes数和球度的数学关系。这种相关性估计了球形和非球形多分散颗粒的沉积。
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来源期刊
CiteScore
1.60
自引率
0.00%
发文量
73
期刊介绍: IJBET addresses cutting-edge research in the multi-disciplinary area of biomedical engineering and technology. Medical science incorporates scientific/technological advances combining to produce more accurate diagnoses, effective treatments with fewer side effects, and improved ability to prevent disease and provide superior-quality healthcare. A key field here is biomedical engineering/technology, offering a synthesis of physical, chemical, mathematical and computational sciences combined with engineering principles to enhance R&D in biology, medicine, behaviour, and health. Topics covered include Artificial organs Automated patient monitoring Advanced therapeutic and surgical devices Application of expert systems and AI to clinical decision making Biomaterials design Biomechanics of injury and wound healing Blood chemistry sensors Computer modelling of physiologic systems Design of optimal clinical laboratories Medical imaging systems Sports medicine.
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