AIMC Topic: Blood-Brain Barrier
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Predicting blood-brain barrier permeability of molecules with a large language model and machine learning.
Scientific reports
Jul 9, 2024
Predicting the blood-brain barrier (BBB) permeability of small-molecule compounds using a novel artificial intelligence platform is necessary for drug discovery. Machine learning and a large language model on artificial intelligence (AI) tools improv...
Glycocalyx shedding patterns identifies antipsychotic-naïve patients with first-episode psychosis.
Psychiatry research
Jun 21, 2024
Psychotic disorders have been linked to immune-system abnormalities, increased inflammatory markers, and subtle neuroinflammation. Studies further suggest a dysfunctional blood brain barrier (BBB). The endothelial Glycocalyx (GLX) functions as a prot...
Prediction of blood-brain barrier permeability using machine learning approaches based on various molecular representation.
Molecular informatics
Jun 12, 2024
The assessment of compound blood-brain barrier (BBB) permeability poses a significant challenge in the discovery of drugs targeting the central nervous system. Conventional experimental approaches to measure BBB permeability are labor-intensive, cost...
Assessing the anticholinergic cognitive burden classification of putative anticholinergic drugs using drug properties.
British journal of clinical pharmacology
Jun 11, 2024
AIMS: This study evaluated the use of machine learning to leverage drug absorption, distribution, metabolism and excretion (ADME) data together with physicochemical and pharmacological data to develop a novel anticholinergic burden scale and compare ...
Nose-to-Brain Drug Delivery and Physico-Chemical Properties of Nanosystems: Analysis and Correlation Studies of Data from Scientific Literature.
International journal of nanomedicine
Jun 11, 2024
BACKGROUND: In the last few decades, nose-to-brain delivery has been investigated as an alternative route to deliver molecules to the Central Nervous System (CNS), bypassing the Blood-Brain Barrier. The use of nanotechnological carriers to promote dr...
Identifying Substructures That Facilitate Compounds to Penetrate the Blood-Brain Barrier via Passive Transport Using Machine Learning Explainer Models.
ACS chemical neuroscience
May 9, 2024
The local interpretable model-agnostic explanation (LIME) method was used to interpret two machine learning models of compounds penetrating the blood-brain barrier. The classification models, Random Forest, ExtraTrees, and Deep Residual Network, were...
Breaking the Barriers: Machine-Learning-Based c-RASAR Approach for Accurate Blood-Brain Barrier Permeability Prediction.
Journal of chemical information and modeling
May 3, 2024
The intricate nature of the blood-brain barrier (BBB) poses a significant challenge in predicting drug permeability, which is crucial for assessing central nervous system (CNS) drug efficacy and safety. This research utilizes an innovative approach, ...
Application of parallel artificial membrane permeability assay technique and chemometric modeling for blood-brain barrier permeability prediction of protein kinase inhibitors.
Future medicinal chemistry
Apr 19, 2024
This study aims to investigate the passive diffusion of protein kinase inhibitors through the blood-brain barrier (BBB) and to develop a model for their permeability prediction. We used the parallel artificial membrane permeability assay to obtain ...
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).
Deep Learning-Driven Exploration of Pyrroloquinoline Quinone Neuroprotective Activity in Alzheimer's Disease.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Mar 7, 2024
Alzheimer's disease (AD) is a pressing concern in neurodegenerative research. To address the challenges in AD drug development, especially those targeting Aβ, this study uses deep learning and a pharmacological approach to elucidate the potential of ...
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