Accurate and realistic predictions of the fate of nasally inhaled drugs help to understand the complex fluid-particle dynamics in the nasal cavity. Key elements of such a comprehensive numerical analysis include: (i) inhaled drug-aerosol transport and deposition with air-particle-mucus interactions; and (ii) mucociliary clearance (MCC) dynamics, including drug transport, dissolution and absorption for different nasal inlet conditions.

The open-source computational fluid dynamics (CFD) toolbox, OpenFOAM, has been employed for the development of the computer simulation model. As part of the design, a novel 3D meshing technique allows for the smooth capture of both the relatively large flow domain as well as the micron-size mucus layer. This efficient meshing strategy drastically reduces the overall meshing time from hours to a matter of minutes. The effect of pharmacokinetic characteristics of drugs on dissolution, subsequent uptake and clearance were analyzed. A method to impose a boundary-driven flow velocity was introduced in order to mimic the beating of the cilia. Several drug specific parameters, such as solubility, partition coefficient and particle size, were considered. The effects of particle distribution on MCC and uptake were simulated as well. The CFD predictions show that drugs with a high partition coefficient are absorbed rapidly. Similarly, drugs with higher solubility show an appreciable increase in cumulative uptake in the epithelium. Particle size, however, plays a more nuanced role in drug uptake. Specifically, smaller particles with their relatively large surface areas, tend to dissolve quicker and are absorbed more rapidly when compared to larger particles. However, after the initial steeper increase in cumulative uptake of the smaller particles, the difference in the uptake values for the two cases is negligible. Furthermore, the initial deposition locations in the nasal cavity play an important role in overall drug uptake. Particles deposited closer to the ciliated portion of the nasal cavity (i.e. the posterior region) were more readily absorbed when compared to particles deposited closer to the unciliated nasal vestibule.

准确和现实地预测鼻吸入药物的命运有助于了解鼻腔中复杂的流体颗粒动力学。这种全面的数值分析的关键要素包括：（i）吸入的药物-气溶胶的运输和沉积与空气-颗粒-黏液的相互作用；（ii）粘膜纤毛清除（MCC）动态，包括不同鼻腔入口情况下的药物运输，溶解和吸收。

开源计算流体动力学（CFD）工具箱OpenFOAM已用于开发计算机仿真模型。作为设计的一部分，一种新颖的3D网格技术可以平滑捕获相对较大的流域以及微米大小的粘液层。这种有效的网格划分策略将总体网格划分时间从数小时减少到数分钟。分析了药物的药代动力学特征对溶解，随后的摄取和清除的影响。为了模拟纤毛的跳动，引入了施加边界驱动流速的方法。考虑了几种药物特异性参数，例如溶解度，分配系数和粒径。还模拟了颗粒分布对MCC和摄取的影响。CFD预测表明，具有高分配系数的药物会被迅速吸收。类似地，具有较高溶解度的药物在上皮中的累积摄取量显示明显增加。然而，粒径在药物吸收中起着更细微的作用。具体地，与较大的颗粒相比，具有相对较大的表面积的较小的颗粒倾向于更快地溶解并且被更快地吸收。但是，在较小颗粒的累积吸收量开始急剧增加之后，两种情况的吸收值差异可以忽略不计。此外，鼻腔中的初始沉积位置在总体药物吸收中起重要作用。颗粒沉积更靠近鼻腔的纤毛部分（即