Prediction of nanoparticle (NP) distribution in a vasculature involves transport phenomena at various scales and is crucial for the evaluation of NP delivery efficiency. A combined particulate and continuum model is developed to model NP transport and delivery processes. In the particulate model ligand-receptor binding kinetics is coupled with Brownian dynamics to study NP binding on a microscale. An analytical formula is derived to link molecular level binding parameters to particulate level adhesion and detachment rates. The obtained NP adhesion rates are then coupled with a convection-diffusion-reaction model to study NP transport and delivery at macroscale. The binding results of the continuum model agree well with those from the particulate model. The effects of shear rate, particle size and vascular geometry on NP adhesion are investigated. Attachment rates predicted by the analytical formula also agree reasonably well with the experimental data reported in literature. The developed coupled model that links ligand-receptor binding dynamics to NP adhesion rate along with macroscale transport and delivery processes may serve as a faster evaluation and prediction tool to determine NP distribution in complex vascular networks.

中文翻译：

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用于纳米颗粒靶向递送的耦合颗粒和连续介质模型

脉管系统中纳米颗粒 (NP) 分布的预测涉及各种尺度的运输现象，对于评估 NP 递送效率至关重要。开发了一个组合的颗粒和连续介质模型来模拟 NP 传输和输送过程。在微粒模型中，配体-受体结合动力学与布朗动力学相结合，以研究微观尺度上的 NP 结合。推导出分析公式以将分子水平结合参数与颗粒水平粘附和脱离率联系起来。然后将获得的 NP 粘附率与对流-扩散-反应模型相结合，以研究宏观尺度的 NP 运输和递送。连续体模型的结合结果与颗粒模型的结果非常吻合。研究了剪切速率、粒径和血管几何形状对 NP 粘附的影响。由分析公式预测的附着率也与文献报道的实验数据相当吻合。开发的耦合模型将配体 - 受体结合动力学与 NP 粘附率以及宏观运输和递送过程联系起来，可以作为更快的评估和预测工具，以确定复杂血管网络中的 NP 分布。