AIMC Topic: Central Nervous System Agents

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Development of Simplified in Vitro P-Glycoprotein Substrate Assay and in Silico Prediction Models To Evaluate Transport Potential of P-Glycoprotein.

Molecular pharmaceutics Apr 16, 2019
For efficient drug discovery and screening, it is necessary to simplify P-glycoprotein (P-gp) substrate assays and to provide in silico models that predict the transport potential of P-gp. In this study, we developed a simplified in vitro screening m...
Swine ATP Binding Cassette Transporter, Subfamily B, Member 1 Animals Drug Discovery Transfection Biological Availability Drug Evaluation, Preclinical Central Nervous System Agents Machine Learning Computer Simulation Reproducibility of Results Intestinal Absorption ATP Binding Cassette Transporter, Subfamily B LLC-PK1 Cells Cell Membrane Permeability Protein Transport Data Accuracy
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Physicochemical property profile for brain permeability: comparative study by different approaches.

Journal of drug targeting Feb 6, 2016
A comparative study of classification models of brain penetration by different approaches was carried out on a training set of 1000 chemicals and drugs, and an external test set of 100 drugs. Ten approaches were applied in this work: seven medicinal ...
Models, Theoretical Machine Learning Structure-Activity Relationship Pharmaceutical Preparations Computer Simulation Central Nervous System Agents Permeability Brain Drug Discovery
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A method to predict different mechanisms for blood-brain barrier permeability of CNS activity compounds in Chinese herbs using support vector machine.

Journal of bioinformatics and computational biology Oct 27, 2015
The blood-brain barrier (BBB), a highly selective barrier between central nervous system (CNS) and the blood stream, restricts and regulates the penetration of compounds from the blood into the brain. Drugs that affect the CNS interact with the BBB p...
Drug Evaluation, Preclinical Blood-Brain Barrier Molecular Targeted Therapy Central Nervous System Agents Algorithms ATP Binding Cassette Transporter, Subfamily B, Member 1 Models, Theoretical Permeability Reproducibility of Results Humans Support Vector Machine Plants, Medicinal Medicine, Chinese Traditional
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Adverse Outcome Pathway and Machine Learning to Predict Drug Induced Seizure Liability.

ACS chemical neuroscience Jun 4, 2025
Central nervous system (CNS) drugs have the highest clinical attrition, often due to CNS-related toxicities such as drug-induced seizures (DIS). Early prediction of DIS risk could reduce failure rates and optimize drug development by prioritizing tes...
Seizures Central Nervous System Agents Humans Machine Learning
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A merged molecular representation deep learning method for blood-brain barrier permeability prediction.

Briefings in bioinformatics Sep 20, 2022
The ability of a compound to permeate across the blood-brain barrier (BBB) is a significant factor for central nervous system drug development. Thus, for speeding up the drug discovery process, it is crucial to perform high-throughput screenings to p...
Central Nervous System Agents Permeability Deep Learning Biological Transport Blood-Brain Barrier
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[Challenges to Improve the Prediction Accuracy of the Non-clinical Tests for Human CNS Adverse Effects: Potentials of Artificial Intelligence and Human ESC/iPSC-derived Neurons].

Yakugaku zasshi : Journal of the Pharmaceutical Society of Japan Jan 1, 2018
Human Embryonic Stem Cells Animal Testing Alternatives Induced Pluripotent Stem Cells Neuroimaging Cell Differentiation Artificial Intelligence Drug Evaluation, Preclinical Neurons Drug Discovery Central Nervous System Agents Humans
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