2019
A Time-Embedding Network Models the Ontogeny of 23 Hepatic Drug Metabolizing Enzymes
Matlock M, Tambe A, Elliott-Higgins J, Hines R, Miller G, Swamidass S. A Time-Embedding Network Models the Ontogeny of 23 Hepatic Drug Metabolizing Enzymes. Chemical Research In Toxicology 2019, 32: 1707-1721. PMID: 31304741, PMCID: PMC6933754, DOI: 10.1021/acs.chemrestox.9b00223.Peer-Reviewed Original ResearchConceptsAge-dependent changesHepatic Drug Metabolizing EnzymesAdverse drug reactionsValproic acid toxicityDrug metabolizing enzymesDrug metabolism enzymesElimination of drugsPediatric patientsPediatric populationMetabolite exposureDrug reactionsClinical dataElevated riskOverall clearanceDrug toxicityFunction of ageDrug safetyFetal periodMetabolizing enzymesDrug metabolismDrug toxicity risksPotential mechanismsAcid toxicityEnzyme expressionDemographic factors
2018
The Impact of Scaling Factor Variability on Risk-Relevant Pharmacokinetic Outcomes in Children: A Case Study Using Bromodichloromethane (BDCM)
Kenyon E, Lipscomb J, Pegram R, George B, Hines R. The Impact of Scaling Factor Variability on Risk-Relevant Pharmacokinetic Outcomes in Children: A Case Study Using Bromodichloromethane (BDCM). Toxicological Sciences 2018, 167: 347-359. PMID: 30252107, PMCID: PMC10448349, DOI: 10.1093/toxsci/kfy236.Peer-Reviewed Original ResearchConceptsPharmacokinetic outcomesPK outcomesYounger age groupsDose-response studyBDCM concentrationsLarge inter-individual differencesPediatric populationLiver massBody weightAge groupsMicrosomal contentOral exposure routePharmacokinetic modelDose metricsDrink of waterEnzyme ontogenyOutcome variationEarly childhoodAdult findingsInter-individual differencesOutcomesNeonatesExposure routes
2009
Approaches for Assessing Risks to Sensitive Populations: Lessons Learned from Evaluating Risks in the Pediatric Population
Hines R, Sargent D, Autrup H, Birnbaum L, Brent R, Doerrer N, Hubal E, Juberg D, Laurent C, Luebke R, Olejniczak K, Portier C, Slikker W. Approaches for Assessing Risks to Sensitive Populations: Lessons Learned from Evaluating Risks in the Pediatric Population. Toxicological Sciences 2009, 113: 4-26. PMID: 19770482, PMCID: PMC3469276, DOI: 10.1093/toxsci/kfp217.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAge FactorsBiomarkersChildChild, PreschoolDose-Response Relationship, DrugEnvironmental ExposureEnvironmental MonitoringGenetic Predisposition to DiseaseGovernment RegulationHealth PolicyHumansInfantInfant, NewbornModels, BiologicalPharmacokineticsPublic HealthRisk AssessmentRisk FactorsToxicity Tests
2006
Population-Based Analysis of Methadone Distribution and Metabolism Using an Age-Dependent Physiologically Based Pharmacokinetic Model
Yang F, Tong X, McCarver D, Hines R, Beard D. Population-Based Analysis of Methadone Distribution and Metabolism Using an Age-Dependent Physiologically Based Pharmacokinetic Model. Journal Of Pharmacokinetics And Pharmacodynamics 2006, 33: 485-518. PMID: 16758333, DOI: 10.1007/s10928-006-9018-0.Peer-Reviewed Original ResearchMeSH KeywordsAdultAge FactorsAnalgesics, OpioidArea Under CurveBiological AvailabilityChild, PreschoolComputer SimulationHumansHydrogen-Ion ConcentrationInfantInfant, NewbornMaleMethadoneMiddle AgedModels, BiologicalMonte Carlo MethodProtein BindingRegression AnalysisStereoisomerismTissue DistributionConceptsInter-individual variabilityPediatric populationPharmacokinetic modelMethadone kineticsPopulation-based analysisPopulation-based pharmacokineticsMetabolism of methadoneMethadone distributionMethadone metabolismMethadone pharmacokineticsOpioid abstinencePediatric patientsClinical effectsPD relationshipBlood concentrationsPlasma concentrationsLimited pharmacokineticsPharmacodynamic dataOrosomucoid concentrationPK parametersPK dataMethadonePharmacokineticsClearance kineticsPBPK model