Stem Cell-Based Human Blood–Brain Barrier Models for Drug Discovery and Delivery.

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Title: Stem Cell-Based Human Blood–Brain Barrier Models for Drug Discovery and Delivery.
Authors: Aday, S.1,2,3, Cecchelli, R.4 romeo.cecchelli@univ-artois.fr, Hallier-Vanuxeem, D.4, Dehouck, M.P.4, Ferreira, L.1,2,3 lino@biocant.pt
Source: Trends in Biotechnology. May2016, Vol. 34 Issue 5, p382-393. 12p.
Subjects: Stem cells, Blood-brain barrier, Drug development, Drug delivery systems, Drug toxicity, Permeability (Biology)
Abstract: The development of novel neuropharmaceuticals requires the evaluation of blood–brain barrier (BBB) permeability and toxicity. Recent studies have highlighted differences in the BBB among different species, with the most important differences involving the expression of P-glycoprotein (P-gp), multidrug resistance-associated proteins, transporters, and claudins. In addition, functional studies have shown that brain pharmacokinetics of P-glycoprotein substrates are different in humans and rodents. Therefore, human BBB models may be an important platform for initial drug screening before in vivo studies. This strategy might help to reduce costs in drug development and failures in clinical studies. We review the differences in the BBB among species, recent advances in the generation of human BBB models, and their applications in drug discovery and delivery. [ABSTRACT FROM AUTHOR]
Copyright of Trends in Biotechnology is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Stem Cell-Based Human Blood–Brain Barrier Models for Drug Discovery and Delivery.
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  Data: <searchLink fieldCode="DE" term="%22Stem+cells%22">Stem cells</searchLink><br /><searchLink fieldCode="DE" term="%22Blood-brain+barrier%22">Blood-brain barrier</searchLink><br /><searchLink fieldCode="DE" term="%22Drug+development%22">Drug development</searchLink><br /><searchLink fieldCode="DE" term="%22Drug+delivery+systems%22">Drug delivery systems</searchLink><br /><searchLink fieldCode="DE" term="%22Drug+toxicity%22">Drug toxicity</searchLink><br /><searchLink fieldCode="DE" term="%22Permeability+%28Biology%29%22">Permeability (Biology)</searchLink>
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  Data: The development of novel neuropharmaceuticals requires the evaluation of blood–brain barrier (BBB) permeability and toxicity. Recent studies have highlighted differences in the BBB among different species, with the most important differences involving the expression of P-glycoprotein (P-gp), multidrug resistance-associated proteins, transporters, and claudins. In addition, functional studies have shown that brain pharmacokinetics of P-glycoprotein substrates are different in humans and rodents. Therefore, human BBB models may be an important platform for initial drug screening before in vivo studies. This strategy might help to reduce costs in drug development and failures in clinical studies. We review the differences in the BBB among species, recent advances in the generation of human BBB models, and their applications in drug discovery and delivery. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Trends in Biotechnology is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1016/j.tibtech.2016.01.001
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        Text: English
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