Department of Pharmaceutics, Institute of Pharmacy, University of Bonn, Bonn, Germany; Department of Pharmaceutics and Pharmaceutical Technology, Faculty of Pharmacy, Pharos University in Alexandria, Alexandria, Egypt.
Department of Neurosurgery, University Hospital Bonn, Bonn, Germany.
Adv Drug Deliv Rev. 2021 Sep;176:113859. doi: 10.1016/j.addr.2021.113859. Epub 2021 Jul 9.
Brain delivery is a broad research area, the outcomes of which are far hindered by the limited permeability of the blood-brain barrier (BBB). Over the last century, research has been revealing the BBB complexity and the crosstalk between its cellular and molecular components. Pathologically, BBB alterations may precede as well as be concomitant or lead to brain diseases. To simulate the BBB and investigate options for drug delivery, several in vitro, in vivo, ex vivo, in situ and in silico models are used. Hundreds of drug delivery vehicles successfully pass preclinical trials but fail in clinical settings. Inadequate selection of BBB models is believed to remarkably impact the data reliability leading to unsatisfactory results in clinical trials. In this review, we suggest a rationale for BBB model selection with respect to the addressed research question and downstream applications. The essential considerations of an optimal BBB model are discussed.
脑内递药是一个广泛的研究领域,其研究结果受到血脑屏障(BBB)通透性有限的极大阻碍。在上个世纪,研究已经揭示了 BBB 的复杂性及其细胞和分子成分之间的串扰。病理性的 BBB 改变可能先于、同时或导致脑部疾病。为了模拟 BBB 并研究药物递药的选择,人们使用了几种体外、体内、离体、原位和计算模型。数以百计的药物递送载体成功通过了临床前试验,但在临床环境中失败。人们认为,BBB 模型选择不当会显著影响数据的可靠性,导致临床试验结果不理想。在这篇综述中,我们根据研究问题和下游应用,提出了 BBB 模型选择的基本原理。讨论了最优 BBB 模型的基本考虑因素。