Brown Tyler D, Habibi Nahal, Wu Debra, Lahann Joerg, Mitragotri Samir
School of Engineering and Applied Sciences, Harvard University, 29 Oxford Street, Cambridge, Massachusetts 02318, United States.
Wyss Institute of Biologically Inspired Engineering, Harvard University, 3 Blackfan Circle, Boston, Massachusetts 02115, United States.
ACS Biomater Sci Eng. 2020 Sep 14;6(9):4916-4928. doi: 10.1021/acsbiomaterials.0c00743. Epub 2020 Aug 31.
The delivery of therapeutics to the brain in an efficient, noninvasive manner continues to be a major unmet need in the field of drug delivery. One significant impediment to brain delivery results from the existence of the physical yet dynamic blood-brain barrier (BBB). Despite the many, often complex strategies that currently exist to breach the BBB, adequate delivery of effective therapeutics from the bloodstream continues to remain quite low. Nanotechnology has emerged as a promising tool for brain delivery, but little is known about the important particle parameters that influence delivery. Here, we synthesized and characterized a library of nanoparticles with distinct properties ranging from size, shape, stiffness, and composition to investigate and identify the key attributes influencing particle uptake and transport for brain delivery. To accomplish this task, an human BBB model was developed and validated using human cerebral microvascular endothelial cells (hCMEC/D3). Particle uptake and apparent permeability coefficients () were then determined for each particle group. To elucidate the roles of different parameters on particle uptake and transport across the BBB, the predominant mechanisms of endocytosis were also investigated. Our results show that particle composition yielded the greatest impact on penetration across the BBB model. This work lays the foundation and provides new insights into the role of particle parameters on penetration across the BBB.
以高效、非侵入性的方式将治疗药物输送到大脑仍然是药物输送领域一个尚未满足的主要需求。大脑药物输送的一个重大障碍是存在物理性但动态的血脑屏障（BBB）。尽管目前存在许多往往很复杂的突破血脑屏障的策略，但从血流中充分输送有效的治疗药物的效率仍然很低。纳米技术已成为一种有前景的大脑药物输送工具，但对于影响药物输送的重要颗粒参数却知之甚少。在此，我们合成并表征了一系列具有不同性质（从尺寸、形状、硬度和组成等方面）的纳米颗粒库，以研究和确定影响大脑药物输送中颗粒摄取和转运的关键属性。为完成这项任务，使用人脑血管内皮细胞（hCMEC/D3）建立并验证了一种人血脑屏障模型。然后测定每个颗粒组的颗粒摄取和表观渗透系数（）。为阐明不同参数对颗粒摄取和跨血脑屏障转运的作用，还研究了内吞作用的主要机制。我们的结果表明，颗粒组成对跨血脑屏障模型的渗透影响最大。这项工作为颗粒参数在跨血脑屏障渗透中的作用奠定了基础并提供了新的见解。
