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用于中枢神经系统药物递送的体外血脑屏障实验模型:一个进化的视角。

Experimental Models of In Vitro Blood-Brain Barrier for CNS Drug Delivery: An Evolutionary Perspective.

机构信息

Department of Pharmaceutical Sciences, School of Pharmacy, College of Health Professions, North Dakota State University, Fargo, ND 58105, USA.

出版信息

Int J Mol Sci. 2023 Jan 31;24(3):2710. doi: 10.3390/ijms24032710.

Abstract

Central nervous system (CNS) disorders represent one of the leading causes of global health burden. Nonetheless, new therapies approved against these disorders are among the lowest compared to their counterparts. The absence of reliable and efficient in vitro blood-brain barrier (BBB) models resembling in vivo barrier properties stands out as a significant roadblock in developing successful therapy for CNS disorders. Therefore, advancement in the creation of robust and sensitive in vitro BBB models for drug screening might allow us to expedite neurological drug development. This review discusses the major in vitro BBB models developed as of now for exploring the barrier properties of the cerebral vasculature. Our main focus is describing existing in vitro models, including the 2D transwell models covering both single-layer and co-culture models, 3D organoid models, and microfluidic models with their construction, permeability measurement, applications, and limitations. Although microfluidic models are better at recapitulating the in vivo properties of BBB than other models, significant gaps still exist for their use in predicting the performance of neurotherapeutics. However, this comprehensive account of in vitro BBB models can be useful for researchers to create improved models in the future.

摘要

中枢神经系统 (CNS) 疾病是全球健康负担的主要原因之一。尽管如此,获批用于治疗这些疾病的新疗法在同类药物中属于最少的。缺乏类似于体内屏障特性的可靠且高效的体外血脑屏障 (BBB) 模型是开发 CNS 疾病治疗方法的重大障碍。因此,为药物筛选开发稳健且灵敏的体外 BBB 模型的进展可能使我们能够加速神经药物的开发。本综述讨论了迄今为止为探索脑血管屏障特性而开发的主要体外 BBB 模型。我们的主要重点是描述现有的体外模型,包括 2D Transwell 模型(涵盖单层和共培养模型)、3D 类器官模型以及具有其构建、渗透性测量、应用和局限性的微流控模型。尽管微流控模型在再现 BBB 的体内特性方面优于其他模型,但在预测神经治疗药物的性能方面仍存在很大差距。然而,本综述全面介绍了体外 BBB 模型,这对研究人员将来创建改进的模型可能会很有用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e133/9916529/6e66849a0552/ijms-24-02710-g004.jpg

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