Back to search

Article

Assessing the Anticholinergic Cognitive Burden Classification of Putative Anticholinergic Drugs Using ADME Properties

2024-06-22

Abstract excerpt

<h4>Aim: </h4> This study evaluated the use of machine learning in leveraging drug ADME data to develop a novel anticholinergic burden (AB) scale and compared its performance to previously published scales. <h4>Methods:</h4> Experimental and in silico ADME data were collected for antimuscarinic activity, blood-brain barrier penetration, bioavailability, chemical structure and P-gp substrate profile. These five ADM...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
24078b95-279d-5f62-a4ed-d27aa0399f6a
DOI
10.22541/au.171905180.04430862/v1
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Assessing the Anticholinergic Cognitive Burden Classification of Putative Anticholinergic Drugs Using ADME PropertiesDOI 10.22541/au.171905180.04430862/v1
Predicting neurological Adverse Drug Reactions based on biological, chemical and phenotypic properties of drugs using machine learning models.Semantic proximity
Cognitive function in the context of pharmacogenetic CYP2D6 variability and anticholinergic burden in older adults - results from the ActiFE study.Semantic proximity
Prediction and Classification of the Uptake and Disposition of Antidepressants and New CNS-Active Drugs in the Human Brain using the ANDROMEDA by Prosilico Software and Brainavailability-MatrixSemantic proximity
Anticholinergic Drug Burden and Risk of Incident MCI and Dementia: A Population-based Study.Semantic proximity
Analysis and Mining of Baloxavir Marboxil Adverse Event Signals in Elderly Patients Based on the FAERS DatabaseSemantic proximity
Predicting Antiseizure Medication Outcomes in Early Diagnosed Epilepsy: A Multimodal Framework Using EEG, MRI, and Clinical DataSemantic proximity
Analysis and Mining of Baloxavir Marboxil Adverse Event Signals in Elderly Patients Based on the FAERS DatabaseSemantic proximity
Escitalopram Adverse Events in Real-World Databases: Signal Detection, Prediction Modeling, and Network ToxicologySemantic proximity
A Multiscale Structural, Pharmacokinetic–Pharmacodynamic and Systems Pharmacology Framework Exploring a Plausible Interaction Between Cenobamate and Low-Dose Clobazam in Drug-Resistant EpilepsySemantic proximity
Prescribing of antiepileptic drugs for the treatment of painSemantic proximity
Exploring Advanced Applications of Artificial Intelligence in Neuropharmacology: A Comprehensive OverviewSemantic proximity
Artificial Intelligence for Post-Marketing Pharmacovigilance of Herbal and Botanical Medicines: A Scoping Review and the MIAHPV FrameworkSemantic proximity
Select a neighboring publication to make it the new centre.