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      In-vitro blood–brain barrier modeling: A review of modern and fast-advancing technologies

      1 , 1 , 2
      Journal of Cerebral Blood Flow & Metabolism
      SAGE Publications

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          Abstract

          The development of realistic in vitro blood-brain barrier (BBB) models that recapitulate the physiological parameters and molecular aspect of the neurovascular unit (NVU) is of fundamental importance not only in CNS drug discovery but also in translational research. Successful modeling of the NVU would provide an invaluable tool to aid in dissecting out the pathological factors, mechanism of action (and corresponding targets) prodromal to the onset of CNS disorders. The field of BBB in vitro modeling has seen many radical changes in the last few years with the introduction on novel technologies and methods to improve over existing models and develop new ones. Therefore, the goal of this review is to provide the readers with updated technical and operational details concerning current BBB platforms with special focus on stem cell technology used to establish a functional BBB model in vitro. Furthermore, we provide a detailed update on rapidly advancing 3D printing technologies used for engineering BBB models which use is now fast expanding among researchers.

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          Most cited references61

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          3D printing of polymer matrix composites: A review and prospective

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            Blood-brain barrier structure and function and the challenges for CNS drug delivery.

            N. Abbott (2013)
            The neurons of the central nervous system (CNS) require precise control of their bathing microenvironment for optimal function, and an important element in this control is the blood-brain barrier (BBB). The BBB is formed by the endothelial cells lining the brain microvessels, under the inductive influence of neighbouring cell types within the 'neurovascular unit' (NVU) including astrocytes and pericytes. The endothelium forms the major interface between the blood and the CNS, and by a combination of low passive permeability and presence of specific transport systems, enzymes and receptors regulates molecular and cellular traffic across the barrier layer. A number of methods and models are available for examining BBB permeation in vivo and in vitro, and can give valuable information on the mechanisms by which therapeutic agents and constructs permeate, ways to optimize permeation, and implications for drug discovery, delivery and toxicity. For treating lysosomal storage diseases (LSDs), models can be included that mimic aspects of the disease, including genetically-modified animals, and in vitro models can be used to examine the effects of cells of the NVU on the BBB under pathological conditions. For testing CNS drug delivery, several in vitro models now provide reliable prediction of penetration of drugs including large molecules and artificial constructs with promising potential in treating LSDs. For many of these diseases it is still not clear how best to deliver appropriate drugs to the CNS, and a concerted approach using a variety of models and methods can give critical insights and indicate practical solutions.
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              Additive manufacturing and its societal impact: a literature review

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                Author and article information

                Journal
                Journal of Cerebral Blood Flow & Metabolism
                J Cereb Blood Flow Metab
                SAGE Publications
                0271-678X
                1559-7016
                July 04 2017
                October 2018
                July 30 2018
                October 2018
                : 38
                : 10
                : 1667-1681
                Affiliations
                [1 ]Department of Pharmaceutical Sciences, Texas Tech University Health Sciences Center, Amarillo, TX, USA
                [2 ]Center for Blood Brain Barrier Research, Texas Tech University Health Sciences Center, Amarillo, TX, USA
                Article
                10.1177/0271678X18788769
                6168917
                30058456
                0274d672-1bdc-43b7-8810-9c6f40e19ed9
                © 2018

                http://journals.sagepub.com/page/policies/text-and-data-mining-license

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