AIMC Topic: Torsades de Pointes

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Drug-induced torsadogenicity prediction model: An explainable machine learning-driven quantitative structure-toxicity relationship approach.

Computers in biology and medicine Sep 26, 2024
Drug-induced Torsade de Pointes (TdP), a life-threatening polymorphic ventricular tachyarrhythmia, emerges due to the cardiotoxic effects of pharmaceuticals. The need for precise mechanisms and clinical biomarkers to detect this adverse effect presen...
Humans Machine Learning Drug-Related Side Effects and Adverse Reactions Quantitative Structure-Activity Relationship Torsades de Pointes Algorithms Support Vector Machine Models, Biological
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A stacking ensemble machine learning model for evaluating cardiac toxicity of drugs based on in silico biomarkers.

CPT: pharmacometrics & systems pharmacology Aug 26, 2024
This study addresses the critical issue of drug-induced torsades de pointes (TdP) risk assessment, a vital aspect of new drug development due to its association with arrhythmia and sudden cardiac death. Existing methodologies, particularly those reli...
Torsades de Pointes Risk Assessment Support Vector Machine Cardiotoxicity Humans Machine Learning Neural Networks, Computer Biomarkers Computer Simulation
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A deep learning platform to assess drug proarrhythmia risk.

Cell stem cell Dec 22, 2022
Drug safety initiatives have endorsed human iPSC-derived cardiomyocytes (hiPSC-CMs) as an in vitro model for predicting drug-induced cardiac arrhythmia. However, the extent to which human-defined features of in vitro arrhythmia predict actual clinica...
Torsades de Pointes Arrhythmias, Cardiac Humans Myocytes, Cardiac Deep Learning Induced Pluripotent Stem Cells Action Potentials
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Sex-Specific Classification of Drug-Induced Torsade de Pointes Susceptibility Using Cardiac Simulations and Machine Learning.

Clinical pharmacology and therapeutics Apr 19, 2021
Torsade de Pointes (TdP), a rare but lethal ventricular arrhythmia, is a toxic side effect of many drugs. To assess TdP risk, safety regulatory guidelines require quantification of hERG channel block in vitro and QT interval prolongation in vivo for ...
Myocytes, Cardiac Torsades de Pointes Calcium Isotopes Risk Assessment Models, Biological Sex Factors Humans Machine Learning Computer Simulation Female Risk Factors Male
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Development of models for predicting Torsade de Pointes cardiac arrhythmias using perceptron neural networks.

BMC bioinformatics Dec 28, 2017
BACKGROUND: Blockage of some ion channels and in particular, the hERG (human Ether-a'-go-go-Related Gene) cardiac potassium channel delays cardiac repolarization and can induce arrhythmia. In some cases it leads to a potentially life-threatening arrh...
Electrocardiography Action Potentials Heart Ventricles Male Middle Aged Humans Models, Cardiovascular Long QT Syndrome ROC Curve Neural Networks, Computer Ether-A-Go-Go Potassium Channels Arrhythmias, Cardiac Torsades de Pointes Myocytes, Cardiac
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Response to "Complexity vs. Simplicity: The Winner Is?" Mechanism-Based Classifiers Provide More Than Just Classification.

Clinical pharmacology and therapeutics Nov 15, 2016
Machine Learning Algorithms Forecasting Humans Torsades de Pointes
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Improved Prediction of Drug-Induced Torsades de Pointes Through Simulations of Dynamics and Machine Learning Algorithms.

Clinical pharmacology and therapeutics May 20, 2016
The ventricular arrhythmia Torsades de Pointes (TdP) is a common form of drug-induced cardiotoxicity, but prediction of this arrhythmia remains an unresolved issue in drug development. Current assays to evaluate arrhythmia risk are limited by poor sp...
Risk Factors Humans Torsades de Pointes Machine Learning Algorithms
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Deep learning analysis of electrocardiogram for risk prediction of drug-induced arrhythmias and diagnosis of long QT syndrome.

European heart journal Oct 7, 2021
AIMS: Congenital long-QT syndromes (cLQTS) or drug-induced long-QT syndromes (diLQTS) can cause torsade de pointes (TdP), a life-threatening ventricular arrhythmia. The current strategy for the identification of drugs at the high risk of TdP relies o...
Pharmaceutical Preparations Long QT Syndrome Torsades de Pointes Humans Deep Learning Electrocardiography
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Emerging Concepts and Applied Machine Learning Research in Patients with Drug-Induced Repolarization Disorders.

Studies in health technology and informatics Jun 16, 2020
The paper presents a review of current research to develop predictive models for automated detection of drug-induced repolarization disorders and shows a feasibility study for developing machine learning tools trained on massive multimodal datasets o...
Long QT Syndrome Death, Sudden, Cardiac Torsades de Pointes Humans Machine Learning Electrocardiography
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Machine-Learning Prediction of Drug-Induced Cardiac Arrhythmia: Analysis of Gene Expression and Clustering.

Critical reviews in biomedical engineering Jan 1, 2018
A marked delay in the electrical repolarization of heart ventricles is characterized by prolongation of the Q-T wave (QT) interval on a surface electrocardiogram. Such a delay can lead to potentially life-threatening cardiac arrhythmia (torsades de p...
Male Drug Design Gene Expression Profiling Mice Rats Electrocardiography Reproducibility of Results Sensitivity and Specificity Animals Humans Machine Learning Female Arrhythmias, Cardiac Heart Clinical Trials as Topic Support Vector Machine MAP Kinase Signaling System Drug Evaluation, Preclinical Cluster Analysis Gene Expression Regulation False Positive Reactions Signal Processing, Computer-Assisted Heart Ventricles Torsades de Pointes
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