Article

Deep Learning Predicts Patterns of Cardiotoxicity in a High-Content Screen Using Induced Pluripotent Stem Cell–Derived Cardiomyocytes

2021-03-24

Abstract excerpt

<h4>ABSTRACT</h4> Drug-induced cardiotoxicity and hepatotoxicity are major causes of drug attrition. To decrease late-stage drug attrition, pharmaceutical and biotechnology industries need to establish biologically relevant models that use phenotypic screening to predict drug-induced toxicity. In this study, we sought to rapidly detect patterns of cardiotoxicity using high-content image analysis with deep learnin...

Topics

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

Identifiers and source

Literature Corpus work: 1d482348-30d6-542d-bea6-45b7a590e8aa
DOI: 10.1101/2021.03.23.436666

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Deep Learning Predicts Patterns of Cardiotoxicity in a High-Content Screen Using Induced Pluripotent Stem Cell–Derived CardiomyocytesDOI 10.1101/2021.03.23.436666Read

A Deep Learning-Based Scoring Framework for Large-Scale Multi-Donor Cardiotoxicity ScreeningSemantic proximity Read

MORE IS DIFFERENT: DRUG PROPERTY ANALYSIS ON CELLULAR HIGH-CONTENT IMAGES USING DEEP LEARNINGSemantic proximity Read

A machine learning platform for genotype-specific cardiotoxicity risk prediction using patient-derived iPSC-CMs.Semantic proximity Read

predicTox: An integrated database of clinical risk frequencies and human gene expression signatures for cardiotoxic drugsSemantic proximity Read

Clinical Trial in a Dish: Using Patient-Derived Induced Pluripotent Stem Cells to Identify Risks of Drug-Induced Cardiotoxicity.Semantic proximity Read

Assessment of beating parameters in human induced pluripotent stem cells enables quantitative in vitro screening for cardiotoxicity.Semantic proximity Read

Drug screening using a library of human induced pluripotent stem cell-derived cardiomyocytes reveals disease-specific patterns of cardiotoxicity.Semantic proximity Read

A Machine Learning Approach Predicts Tissue-Specific Drug Adverse EventsSemantic proximity Read

Predictive Modeling of Multiplex Chemical Phenomics for Novel Cells and Patients: Applied to Personalized Alzheimer’s Disease Drug RepurposingSemantic proximity Read

Predicting individual-specific cardiotoxicity responses induced by tyrosine kinase inhibitorsSemantic proximity Read

Deep learning prediction of chemical-induced dose-dependent and context-specific multiplex phenotype responses and its application to personalized alzheimer's disease drug repurposing.Semantic proximity Read

Multiscale mapping of transcriptomic signatures for cardiotoxic drugsSemantic proximity Read