Tan Jifu, Thomas Antony, Liu Yaling
Department of Mechanical Engineering and Mechanics, Lehigh University, Bethlehem, PA 18015, USA.
Soft Matter. 2011 Dec 22;8:1934-1946. doi: 10.1039/C2SM06391C.
Multifunctional nanomedicine holds considerable promise as the next generation of medicine that allows for targeted therapy with minimal toxicity. Most current studies on Nanoparticle (NP) drug delivery consider a Newtonian fluid with suspending NPs. However, blood is a complex biological fluid composed of deformable cells, proteins, platelets, and plasma. For blood flow in capillaries, arterioles and venules, the particulate nature of the blood needs to be considered in the delivery process. The existence of the cell-free-layer and NP-cell interaction will largely influence both the dispersion and binding rates, thus impact targeted delivery efficacy. In this paper, a particle-cell hybrid model is developed to model NP transport, dispersion, and binding dynamics in blood suspension. The motion and deformation of red blood cells is captured through the Immersed Finite Element Method. The motion and adhesion of individual NPs are tracked through Brownian adhesion dynamics. A mapping algorithm and an interaction potential function are introduced to consider the cell-particle collision. NP dispersion and binding rates are derived from the developed model under various rheology conditions. The influence of red blood cells, vascular flow rate, and particle size on NP distribution and delivery efficacy is characterized. A non-uniform NP distribution profile with higher particle concentration near the vessel wall is observed. Such distribution leads to over 50% higher particle binding rate compared to the case without RBC considered. The tumbling motion of RBCs in the core region of the capillary is found to enhance NP dispersion, with dispersion rate increases as shear rate increases. Results from this study contribute to the fundamental understanding and knowledge on how the particulate nature of blood influences NP delivery, which will provide mechanistic insights on the nanomedicine design for targeted drug delivery applications.
多功能纳米药物作为下一代药物具有巨大的潜力,它能够以最小的毒性实现靶向治疗。目前大多数关于纳米颗粒(NP)药物递送的研究都将含有悬浮NP的流体视为牛顿流体。然而,血液是一种复杂的生物流体,由可变形的细胞、蛋白质、血小板和血浆组成。对于毛细血管、小动脉和小静脉中的血流,在递送过程中需要考虑血液的颗粒性质。无细胞层的存在以及NP与细胞的相互作用将在很大程度上影响分散和结合速率,从而影响靶向递送效果。在本文中,开发了一种颗粒 - 细胞混合模型来模拟NP在血液悬浮液中的运输、分散和结合动力学。通过浸入式有限元方法捕捉红细胞的运动和变形。通过布朗粘附动力学跟踪单个NP的运动和粘附。引入映射算法和相互作用势函数来考虑细胞 - 颗粒碰撞。在各种流变学条件下,从所开发的模型中推导NP的分散和结合速率。表征了红细胞、血管流速和颗粒大小对NP分布和递送效果的影响。观察到在血管壁附近具有较高颗粒浓度的非均匀NP分布轮廓。与不考虑红细胞的情况相比,这种分布导致颗粒结合率提高了50%以上。发现红细胞在毛细血管核心区域的翻滚运动增强了NP的分散,并且分散速率随着剪切速率的增加而增加。本研究的结果有助于从根本上理解血液的颗粒性质如何影响NP递送,这将为靶向药物递送应用的纳米药物设计提供机理见解。