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时间:2020-06-21
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1、JournalofSoutheastUniversity(EnglishEdition)Vo1.30,No.1,PP.122—127Mar.2014ISSN1003—7985Bayesiananalysisformixed-effectsmodeldefinedbystochasticdifferentialequationsYanFangrong,,ZhangPing,LuTao,LinJinguan(DepartmentofMathematics,SoutheastUniversity,Nanjing210096,Chi
2、na)(DepartmentofMathematics,ChinaPharmaceuticalUniversity,Nanjing210009,China)(LaboratoryofMolecularDesignandDrugDiscovery,ChinaPharmaceuticalUniversity,Nanjing210009,China)(StateKeyLaboratoryofNaturalMedicines,ChinaPharmaceuticalUniversity,Nanjing210009,China)Abst
3、ract:Thenonlinearmixed—effectsmodelwithstochasticdeveloped.differentialequations(SDEs)isusedtomodelthepopulationNonlinearmixed.effectsmodeling(N0NMEM1haspharmacokinetic(PPK)datathatareextendedfromordinarybeenprovedtobeakindofwidelyusedandeffectivetooldifferentialeq
4、uations(0DEs)byaddingastochastictermtofordescribingthepharmacokinetic(PK)andpharmaco—thestateequation.Comparedwiththe0DEs.theSDEscandynamic(PD)propertiesofdrugs1-21.Theflexibilityofmodelcorrelatedresidualswhichareubiquitousiuactualmodelingcorrelationstructures,with
5、thetotalvariationpharmacokineticproblems.TheBayesianestimationisseparatedintointer.andintra.individualvariationcontrib.providedfornonlinearmixed—effectsmodelsbasedonutestotherapidlygrowingquantityofnonlinearmixed—stochasticdifferentialequations.CombiningtheGibbsand
6、theeffectsmodels.ThismodelingapproachusuallyleadstoMetropolis—Hastingsalgorithms,thepopulationandindividualmoreaccurateestimationofpopulationparameters,espeparametervaluesaregiventhroughtheparameterposteriorciallyinpharmacokinetic/pharmacodynamic(PI<//PD)predictive
7、distributions.Theanalysisandsimulationresultsmodelsincludingrandomeffects.However.thetradition.showthattheperformanceoftheBayesianestimationforalnonlinearmixed—effectsmodelsaremostfrequentlymixed—effectsSDEsmodelandanalysisofpopulationbasedonordinarydifferentialequ
8、ations(ODEs),assum.pharmacokineticdataisreliable.Theresultssuggestthattheingthattheinter—individualvariationisindependentwimproposedmethodisfeasi
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