0000000000415319

AUTHOR

Florian Wimmenauer

showing 1 related works from this author

Use of deep learning methods to translate drug-induced gene expression changes from rat to human primary hepatocytes

2020

In clinical trials, animal and cell line models are often used to evaluate the potential toxic effects of a novel compound or candidate drug before progressing to human trials. However, relating the results of animal and in vitro model exposures to relevant clinical outcomes in the human in vivo system still proves challenging, relying on often putative orthologs. In recent years, multiple studies have demonstrated that the repeated dose rodent bioassay, the current gold standard in the field, lacks sufficient sensitivity and specificity in predicting toxic effects of pharmaceuticals in humans. In this study, we evaluate the potential of deep learning techniques to translate the pattern of …

0301 basic medicineGene ExpressionGene Expression Regulation/drug effectsPathology and Laboratory MedicineConvolutional neural networkTOXICITYMachine LearningVoeding Metabolisme en GenomicaTime Measurement0302 clinical medicineGene expressionMedicine and Health SciencesMeasurementClinical Trials as TopicMultidisciplinaryArtificial neural networkPharmaceuticsQRMetabolism and GenomicsTOXICOGENOMICS030220 oncology & carcinogenesisMetabolisme en GenomicaMedicineEngineering and TechnologyNutrition Metabolism and GenomicsHepatocytes/drug effectsAlgorithmsResearch ArticleComputer and Information SciencesClinical Trials as Topic/statistics & numerical dataNeural NetworksGenetic ToxicologyTOXICOLOGYSciencePredictive ToxicologyComputational biologyBiologyComputer03 medical and health sciencesDose Prediction MethodsDeep LearningVoedingArtificial IntelligenceIn vivoGeneticsLife ScienceAnimalsHumansGeneNutritionbusiness.industryDeep learningBiology and Life SciencesGold standard (test)REPRESENTATIONSRats030104 developmental biologyGene Expression RegulationHepatocytesArtificial intelligenceNeural Networks ComputerToxicogenomicsbusinessNeuroscience
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