Department of Chemical and Biochemical Engineering, Missouri University of Science and Technology, 1101 North State Street, 110 Bertelsmeyer Hall, Rolla, MO 65401, USA
J R Soc Interface. 2018 Mar;15(140). doi: 10.1098/rsif.2017.0787.
Tissue targeting is a critical challenge for systemic delivery of drug nanocarriers. To overcome this challenge, major research efforts have been undertaken to design ligand-conjugated nanoparticles. However, limited work has been done to quantitatively assess the effectiveness of such approach. In this work, using a mechanistic spatio-temporal model, I investigate the effectiveness of ligand-directed tissue targeting. By applying an approach from the colloidal filtration theory, I develop a Brownian dynamics model of nanoparticle-cell interaction. The model incorporates a single cell and its surrounding flow field. It considers both specific (receptor-mediated) and non-specific (bare cell surface-mediated) recognition of nanoparticles subject to convective and diffusive motion. Using the model, I investigate how the specific and non-specific interactions compare in determining the overall targeting efficacy. My analysis provides some interesting findings that contradict the general notion that effective targeting is possible based upon the differential receptor expression in cancer and non-cancer cells. I show that such strategy may yield only a marginal gain in the targeting efficacy. Moreover, non-specific interaction may have an important influence on particle recognition by cells even at high receptor expression levels.
组织靶向是药物纳米载体系统递送的一个关键挑战。为了克服这一挑战，人们进行了大量的研究工作来设计配体偶联的纳米颗粒。然而，定量评估这种方法的有效性的工作却很少。在这项工作中，我使用一种基于机制的时空模型来研究配体导向的组织靶向的有效性。通过应用胶体过滤理论中的一种方法，我开发了一种用于纳米颗粒-细胞相互作用的布朗动力学模型。该模型包含一个单细胞及其周围的流场。它考虑了在对流和扩散运动下，纳米颗粒的特异性（受体介导）和非特异性（裸细胞表面介导）识别。通过使用该模型，我研究了特异性和非特异性相互作用如何在确定整体靶向效率方面进行比较。我的分析提供了一些有趣的发现，这些发现与基于癌症和非癌细胞中差异受体表达而实现有效靶向的一般观点相矛盾。我表明，这种策略可能只会在靶向效率上产生微小的增益。此外，即使在高受体表达水平下，非特异性相互作用也可能对细胞对颗粒的识别产生重要影响。
