0000000000415320

AUTHOR

Rachel Cavill

showing 2 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
researchProduct

High-throughput elucidation of thrombus formation reveals sources of platelet function variability

2019

In combination with microspotting, whole-blood microfluidics can provide high-throughput information on multiple platelet functions in thrombus formation. Based on assessment of the inter-and intra-subject variability in parameters of microspot-based thrombus formation, we aimed to determine the platelet factors contributing to this variation. Blood samples from 94 genotyped healthy subjects were analyzed for conventional platelet phenotyping: i.e. hematologic parameters, platelet glycoprotein (GP) expression levels and activation markers (24 parameters). Furthermore, platelets were activated by ADP, CRP-XL or TRAP. Parallel samples were investigated for whole-blood thrombus formation (6 mi…

Blood PlateletsPlatelet AggregationPlatelet Function TestsDISORDERSIntegrinPlatelet Membrane GlycoproteinsADHESIONPlatelet membrane glycoproteinArticleImmunophenotypingFlow cytometry03 medical and health sciences0302 clinical medicinePlatelet Biology & Its DisordersmedicineHumansPlateletPlatelet activationThrombuschemistry.chemical_classificationmedicine.diagnostic_testbiologyPlatelet CountThrombosisHematologyFlow CytometryPlatelet Activationmedicine.diseaseDIFFERENCEHigh-Throughput Screening AssaysCell biologychemistrybiology.proteinGPVIGlycoproteinBiomarkers030215 immunologyRESPONSESHaematologica-the Hematology Journal
researchProduct