AIMC Topic: Blood-Brain Barrier

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Prediction of the Blood-Brain Barrier (BBB) Permeability of Chemicals Based on Machine-Learning and Ensemble Methods.

Chemical research in toxicology May 28, 2021
The ability of chemicals to enter the blood-brain barrier (BBB) is a key factor for central nervous system (CNS) drug development. Although many models for BBB permeability prediction have been developed, they have insufficient accuracy (ACC) and sen...
Humans Machine Learning Blood-Brain Barrier Organic Chemicals Permeability
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Direct Comparison of the Prediction of the Unbound Brain-to-Plasma Partitioning Utilizing Machine Learning Approach and Mechanistic Neuropharmacokinetic Model.

The AAPS journal May 18, 2021
The mechanistic neuropharmacokinetic (neuroPK) model was established to predict unbound brain-to-plasma partitioning (K) by considering in vitro efflux activities of multiple drug resistance 1 (MDR1) and breast cancer resistance protein (BCRP). Herei...
Rats Predictive Value of Tests Blood-Brain Barrier Dogs Models, Animal Machine Learning Animals ATP Binding Cassette Transporter, Subfamily B Models, Biological Male ATP Binding Cassette Transporter, Subfamily G, Member 2 Madin Darby Canine Kidney Cells Datasets as Topic
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Predicting Absorption-Distribution Properties of Neuroprotective Phosphine-Borane Compounds Using In Silico Modeling and Machine Learning.

Molecules (Basel, Switzerland) Apr 25, 2021
Phosphine-borane complexes are novel chemical entities with preclinical efficacy in neuronal and ophthalmic disease models. In vitro and in vivo studies showed that the metabolites of these compounds are capable of cleaving disulfide bonds implicated...
Machine Learning Computer Simulation Blood-Brain Barrier Humans Neuroprotection Protein Binding Phosphines Neuroprotective Agents Boranes
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Artificial neural network approach for predicting blood brain barrier permeability based on a group contribution method.

Computer methods and programs in biomedicine Jan 15, 2021
BACKGROUND AND OBJECTIVE: The purpose of this study was to develop a quantitative structure-activity relationship (QSAR) model for the prediction of blood brain barrier (BBB) permeability by using artificial neural networks (ANN) in combination with ...
Neural Networks, Computer Databases, Factual Blood-Brain Barrier Permeability Quantitative Structure-Activity Relationship
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Towards Deep Neural Network Models for the Prediction of the Blood-Brain Barrier Permeability for Diverse Organic Compounds.

Molecules (Basel, Switzerland) Dec 13, 2020
Permeation through the blood-brain barrier (BBB) is among the most important processes controlling the pharmacokinetic properties of drugs and other bioactive compounds. Using the fragmental (substructural) descriptors representing the occurrence num...
Biological Transport Permeability Blood-Brain Barrier Animals Organic Chemicals Molecular Structure Workflow Models, Biological Humans Neural Networks, Computer Algorithms
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A Recurrent Neural Network model to predict blood-brain barrier permeability.

Computational biology and chemistry Sep 24, 2020
The rapid development of computational methods and the increasing volume of chemical and biological data have contributed to an immense growth in chemical research. This field of study is known as "chemoinformatics," which is a discipline that uses m...
Quantitative Structure-Activity Relationship Cheminformatics Blood-Brain Barrier Algorithms Deep Learning Models, Biological Pharmaceutical Preparations Permeability Databases, Chemical
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Robotic fluidic coupling and interrogation of multiple vascularized organ chips.

Nature biomedical engineering Jan 27, 2020
Organ chips can recapitulate organ-level (patho)physiology, yet pharmacokinetic and pharmacodynamic analyses require multi-organ systems linked by vascular perfusion. Here, we describe an 'interrogator' that employs liquid-handling robotics, custom s...
Kidney Intestines Liver Cell Culture Techniques Brain Humans Robotics Heart Lab-On-A-Chip Devices Equipment Design Blood-Brain Barrier Microfluidics Skin Lung Calibration
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Finding Needles in a Haystack: Determining Key Molecular Descriptors Associated with the Blood-brain Barrier Entry of Chemical Compounds Using Machine Learning.

Molecular informatics Jul 19, 2019
In this paper we used two sets of calculated molecular descriptors to predict blood-brain barrier (BBB) entry of a collection of 415 chemicals. The set of 579 descriptors were calculated by Schrodinger and TopoCluj software. Polly and Triplet softwar...
Quantitative Structure-Activity Relationship Blood-Brain Barrier Organic Chemicals Models, Molecular Machine Learning Software Algorithms
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Improved Classification of Blood-Brain-Barrier Drugs Using Deep Learning.

Scientific reports Jun 19, 2019
Blood-Brain-Barrier (BBB) is a strict permeability barrier for maintaining the Central Nervous System (CNS) homeostasis. One of the most important conditions to judge a CNS drug is to figure out whether it has BBB permeability or not. In the past 20 ...
Support Vector Machine Pharmaceutical Preparations Databases as Topic Deep Learning Humans ROC Curve Reproducibility of Results Blood-Brain Barrier
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In Silico Prediction of Blood-Brain Barrier Permeability of Compounds by Machine Learning and Resampling Methods.

ChemMedChem Sep 21, 2018
The blood-brain barrier (BBB) as a part of absorption protects the central nervous system by separating the brain tissue from the bloodstream. In recent years, BBB permeability has become a critical issue in chemical ADMET prediction, but almost all ...
Models, Chemical Blood-Brain Barrier Algorithms Permeability Organic Chemicals Computer Simulation Databases, Chemical Support Vector Machine
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