AIMC Topic: Central Nervous System Agents
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GCN-BBB: Deep Learning Blood-Brain Barrier (BBB) Permeability PharmacoAnalytics with Graph Convolutional Neural (GCN) Network.
The AAPS journal
Apr 3, 2025
The Blood-Brain Barrier (BBB) is a selective barrier between the Central Nervous System (CNS) and the peripheral system, regulating the distribution of molecules. BBB permeability has been crucial in CNS-targeting drug development, such as glioblasto...
Molecular Generation for CNS Drug Discovery and Design.
ACS chemical neuroscience
Mar 13, 2025
Computational drug design is a rapidly evolving field, especially the latest breakthroughs in generative artificial intelligence (GenAI) to create new compounds. However, the potential of GenAI to address the challenges in designing central nervous s...
Prediction of the Extent of Blood-Brain Barrier Transport Using Machine Learning and Integration into the LeiCNS-PK3.0 Model.
Pharmaceutical research
Feb 10, 2025
INTRODUCTION: The unbound brain-to-plasma partition coefficient (K) is an essential parameter for predicting central nervous system (CNS) drug disposition using physiologically-based pharmacokinetic (PBPK) modeling. K values for specific compounds ar...
A Practical Method for Predicting Compound Brain Concentration-Time Profiles: Combination of PK Modeling and Machine Learning.
Molecular pharmaceutics
Sep 26, 2024
Given the aging populations in advanced countries globally, many pharmaceutical companies have focused on developing central nervous system (CNS) drugs. However, due to the blood-brain barrier, drugs do not easily reach the target area in the brain. ...
A novel open-access artificial-intelligence-driven platform for CNS drug discovery utilizing adult zebrafish.
Journal of neuroscience methods
Aug 24, 2024
BACKGROUND: Although zebrafish are increasingly utilized in biomedicine for CNS disease modelling and drug discovery, this generates big data necessitating objective, precise and reproducible analyses. The artificial intelligence (AI) applications ha...
CNSMolGen: A Bidirectional Recurrent Neural Network-Based Generative Model for De Novo Central Nervous System Drug Design.
Journal of chemical information and modeling
May 13, 2024
Central nervous system (CNS) drugs have had a significant impact on treating a wide range of neurodegenerative and psychiatric disorders. In recent years, deep learning-based generative models have shown great potential for accelerating drug discover...
Machine Learning Exploration of the Relationship Between Drugs and the Blood-Brain Barrier: Guiding Molecular Modification.
Pharmaceutical research
Apr 11, 2024
OBJECTIVE: This study aimed to improve the efficiency of pharmacotherapy for CNS diseases by optimizing the ability of drug molecules to penetrate the Blood-Brain Barrier (BBB).
Leading consumption patterns of psychoactive substances in Colombia: A deep neural network-based clustering-oriented embedding approach.
PloS one
Aug 18, 2023
The number of health-related incidents caused using illegal and legal psychoactive substances (PAS) has dramatically increased over two decades worldwide. In Colombia, the use of illicit substances has increased up to 10.3%, while the consumption alc...
Determination of new psychoactive substances and other drugs in postmortem blood and urine by UHPLC-MS/MS: method validation and analysis of forensic samples.
Forensic toxicology
Oct 5, 2021
PURPOSE: This study aimed to validate a modified QuEChERS method followed by ultra-high performance liquid chromatography-tandem mass spectrometry to determine 79 new psychoactive substances (NPS) and other drugs in blood and urine.
Innovative approaches in CNS drug discovery.
Therapie
Dec 5, 2020
Central nervous system disorders remain the leading causes of mortality and morbidity worldwide, affecting more than 1 billion patients. This therapeutic area suffers from high unmet medical needs and the search for innovative approaches to identify ...
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