scholarly journals Human iPSC‐Derived Blood‐Brain Barrier Models: Valuable Tools for Preclinical Drug Discovery and Development?

2020 ◽  
Vol 55 (1) ◽  
Author(s):  
Antje Appelt‐Menzel ◽  
Sabrina Oerter ◽  
Sanjana Mathew ◽  
Undine Haferkamp ◽  
Carla Hartmann ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Blood Brain Barrier ◽  
Brain Barrier ◽  
Drug Discovery And Development ◽  
Blood Brain ◽  
Human Ipsc

Modelling of the blood–brain barrier in drug discovery and development

2007 ◽  
Vol 6 (8) ◽  
pp. 650-661 ◽  
Author(s):  
Romeo Cecchelli ◽  
Vincent Berezowski ◽  
Stefan Lundquist ◽  
Maxime Culot ◽  
Mila Renftel ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Blood Brain Barrier ◽  
Brain Barrier ◽  
Drug Discovery And Development ◽  
Blood Brain

scholarly journals Miniaturization and Automation of a Human In Vitro Blood–Brain Barrier Model for the High-Throughput Screening of Compounds in the Early Stage of Drug Discovery

Pharmaceutics ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 892
Author(s):  
Elisa L. J. Moya ◽  
Elodie Vandenhaute ◽  
Eleonora Rizzi ◽  
Marie-Christine Boucau ◽  
Johan Hachani ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Blood Brain Barrier ◽  
Early Stage ◽  
Molecular Transport ◽  
Brain Barrier ◽  
Blood Brain ◽  
Cns Drugs ◽  
The Impact ◽  
The Brain

Central nervous system (CNS) diseases are one of the top causes of death worldwide. As there is a difficulty of drug penetration into the brain due to the blood–brain barrier (BBB), many CNS drugs treatments fail in clinical trials. Hence, there is a need to develop effective CNS drugs following strategies for delivery to the brain by better selecting them as early as possible during the drug discovery process. The use of in vitro BBB models has proved useful to evaluate the impact of drugs/compounds toxicity, BBB permeation rates and molecular transport mechanisms within the brain cells in academic research and early-stage drug discovery. However, these studies that require biological material (animal brain or human cells) are time-consuming and involve costly amounts of materials and plastic wastes due to the format of the models. Hence, to adapt to the high yields needed in early-stage drug discoveries for compound screenings, a patented well-established human in vitro BBB model was miniaturized and automated into a 96-well format. This replicate met all the BBB model reliability criteria to get predictive results, allowing a significant reduction in biological materials, waste and a higher screening capacity for being extensively used during early-stage drug discovery studies.

scholarly journals Retraction Notice to: In Vitro Modeling of Blood-Brain Barrier with Human iPSC-Derived Endothelial Cells, Pericytes, Neurons, and Astrocytes via Notch Signaling

2018 ◽  
Vol 10 (2) ◽  
pp. 674
Author(s):  
Kohei Yamamizu ◽  
Mio Iwasaki ◽  
Hitomi Takakubo ◽  
Takumi Sakamoto ◽  
Takeshi Ikuno ◽  
...  
Keyword(s):  
Endothelial Cells ◽  
Notch Signaling ◽  
Blood Brain Barrier ◽  
Brain Barrier ◽  
In Vitro Modeling ◽  
Blood Brain ◽  
Retraction Notice ◽  
Human Ipsc

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

2016 ◽  
Vol 34 (5) ◽  
pp. 382-393 ◽  
Author(s):  
S. Aday ◽  
R. Cecchelli ◽  
D. Hallier-Vanuxeem ◽  
M.P. Dehouck ◽  
L. Ferreira
Keyword(s):  
Stem Cell ◽  
Drug Discovery ◽  
Blood Brain Barrier ◽  
Human Blood ◽  
Brain Barrier ◽  
Blood Brain

A Simplified Protocol Employing Elacridar in Rodents: A Screening Model in Drug Discovery to Assess P-gp Mediated Efflux at the Blood Brain Barrier

2012 ◽  
Vol 6 (2) ◽  
pp. 134-144 ◽  
Author(s):  
Rajareddy Kallem ◽  
Chetan P. Kulkarni ◽  
Dakshay Patel ◽  
Megha Thakur ◽  
Michael Sinz ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Blood Brain Barrier ◽  
Brain Barrier ◽  
Screening Model ◽  
Blood Brain

LightBBB: computational prediction model of blood–brain-barrier penetration based on LightGBM

2020 ◽  
Author(s):  
Bilal Shaker ◽  
Myeong-Sang Yu ◽  
Jin Sook Song ◽  
Sunjoo Ahn ◽  
Jae Yong Ryu ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Prediction Model ◽  
Blood Brain Barrier ◽  
Prediction Models ◽  
Chemical Diversity ◽  
Brain Barrier ◽  
Permeability Prediction ◽  
Light Gradient ◽  
Blood Brain ◽  
Bbb Permeability

Abstract Motivation Identification of blood–brain barrier (BBB) permeability of a compound is a major challenge in neurotherapeutic drug discovery. Conventional approaches for BBB permeability measurement are expensive, time-consuming and labor-intensive. BBB permeability is associated with diverse chemical properties of compounds. However, BBB permeability prediction models have been developed using small datasets and limited features, which are usually not practical due to their low coverage of chemical diversity of compounds. Aim of this study is to develop a BBB permeability prediction model using a large dataset for practical applications. This model can be used for facilitated compound screening in the early stage of brain drug discovery. Results A dataset of 7162 compounds with BBB permeability (5453 BBB+ and 1709 BBB-) was compiled from the literature, where BBB+ and BBB- denote BBB-permeable and non-permeable compounds, respectively. We trained a machine learning model based on Light Gradient Boosting Machine (LightGBM) algorithm and achieved an overall accuracy of 89%, an area under the curve (AUC) of 0.93, specificity of 0.77 and sensitivity of 0.93, when 10-fold cross-validation was performed. The model was further evaluated using 74 central nerve system compounds (39 BBB+ and 35 BBB-) obtained from the literature and showed an accuracy of 90%, sensitivity of 0.85 and specificity of 0.94. Our model outperforms over existing BBB permeability prediction models. Availabilityand implementation The prediction server is available at http://ssbio.cau.ac.kr/software/bbb.

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