# PK MODELS test_that("Linear1InfusionSingleDose_kV", { modelFromLibrary = list("PKModel" = "Linear1BolusSingleDose_kV") # model modelParameters modelParameters = list( ModelParameter( name = "k", distribution = LogNormal( mu = 0.25, omega = sqrt(0.25) ) ), ModelParameter( name = "V", distribution = LogNormal( mu = 15, omega = sqrt(0.1) ) ) ) # Error Model errorModelRespPK = Combined1( output = "RespPK", sigmaInter = 0.5, sigmaSlope = 0.15 ) modelError = list( errorModelRespPK ) # administration administration = Administration( outcome = "RespPK", timeDose = c( 0 ), dose = c( 100 ) ) # sampling times samplingTimes = SamplingTimes( outcome = "RespPK", samplings = c( 0.33, 1.5, 5, 12 ) ) # arm arm1 = Arm( name = "BrasTest", size = 200, administrations = list( administration ) , samplingTimes = list( samplingTimes ) ) # design design1 = Design( name = "design1", arms = list( arm1 ) ) # Evaluation evaluationFIM = Evaluation( name = "Linear1BolusSingleDose_kV", modelFromLibrary = modelFromLibrary, modelParameters = modelParameters, modelError = modelError, outputs = list( "RespPK" ), designs = list( design1 ), fimType = "population", odeSolverParameters = list( atol = 1e-8, rtol = 1e-8 ) ) evaluationFIM = run( evaluationFIM ) FisherMatrix = getFisherMatrix(evaluationFIM ) detPopulationFim =det( FisherMatrix$fisherMatrix ) valueDetPopulationFim = 1456484950098966784 tol = 1e-6 expect_equal(detPopulationFim,valueDetPopulationFim, tolerance = tol) }) ############################################################################################################################ test_that("Linear1BolusSingleDose_ClV", { modelFromLibrary = list("PKModel" = "Linear1BolusSingleDose_ClV") # model modelParameters modelParameters = list( ModelParameter( name = "Cl", distribution = LogNormal( mu = 3.75, omega = sqrt(0.25) ) ), ModelParameter( name = "V", distribution = LogNormal( mu = 15, omega = sqrt(0.1) ) ) ) # Error Model errorModelRespPK = Combined1( output = "RespPK", sigmaInter = 0.5, sigmaSlope = 0.15 ) modelError = list( errorModelRespPK ) # administration administration = Administration( outcome = "RespPK", timeDose = c( 0 ), dose = c( 100 ) ) # sampling times samplingTimes = SamplingTimes( outcome = "RespPK", samplings = c( 0.33, 1.5, 5, 12 ) ) # arm arm1 = Arm( name = "BrasTest", size = 200, administrations = list( administration ) , samplingTimes = list( samplingTimes ) ) # design design1 = Design( name = "design1", arms = list( arm1 ) ) # -------------------------------------- # Evaluation # Evaluate the Fisher Information Matrix for the PopulationFIM evaluationFIM = Evaluation( name = "Linear1BolusSingleDose_ClV", modelFromLibrary = modelFromLibrary, modelParameters = modelParameters, modelError = modelError, outputs = list( "RespPK" ), designs = list( design1 ), fimType = "population", odeSolverParameters = list( atol = 1e-8, rtol = 1e-8 ) ) evaluationFIM = run( evaluationFIM ) FisherMatrix = getFisherMatrix(evaluationFIM ) detPopulationFim =det( FisherMatrix$fisherMatrix ) valueDetPopulationFim = 7292815928272215 tol = 1e-6 expect_equal(detPopulationFim,valueDetPopulationFim, tolerance = ) }) test_that("Linear1InfusionSingleDose_kV", { # -------------------------------------- # model definition modelFromLibrary = list("PKModel" = "Linear1InfusionSingleDose_kV") # model modelParameters modelParameters = list( ModelParameter( name = "V", distribution = LogNormal( mu = 3.5, omega = sqrt(0.09) ) ), ModelParameter( name = "k", distribution = LogNormal( mu = 0.6, omega = sqrt(0.09) ) ) ) # Error Model errorModelRespPK = Combined1( output = "RespPK", sigmaInter = 0.1, sigmaSlope = 0.1 ) modelError = list( errorModelRespPK ) # administration administration = Administration( outcome = "RespPK", Tinf = c(2), timeDose = c( 0 ), dose = c( 30 ) ) # sampling times samplingTimes = SamplingTimes( outcome = "RespPK", samplings = c( 0.5, 1, 4, 8 ) ) # arm arm1 = Arm( name = "BrasTest", size = 40, administrations = list( administration ) , samplingTimes = list( samplingTimes ) ) # design design1 = Design( name = "design1", arms = list( arm1 ) ) # -------------------------------------- # Evaluation # Evaluate the Fisher Information Matrix for the PopulationFIM evaluationFIM = Evaluation( name = "Linear1InfusionSingleDose_kV", modelFromLibrary = modelFromLibrary, modelParameters = modelParameters, modelError = modelError, outputs = list( "RespPK" ), designs = list( design1 ), fimType = "population", odeSolverParameters = list( atol = 1e-8, rtol = 1e-8 ) ) evaluationFIM = run( evaluationFIM ) FisherMatrix = getFisherMatrix(evaluationFIM ) detPopulationFim =det( FisherMatrix$fisherMatrix ) detPopulationFim valueDetPopulationFim = 1976729482139640576.0 tol = 1e-6 expect_equal(detPopulationFim,valueDetPopulationFim, tolerance = tol ) }) test_that("Model PK 1cpt : Linear1InfusionSingleDose_VCl", { # -------------------------------------- # model definition # model equations modelFromLibrary = list("PKModel" = "Linear1InfusionSingleDose_ClV") #Linear1InfusionSingleDose_VCl # model modelParameters modelParameters = list( ModelParameter( name = "V", distribution = LogNormal( mu = 3.5, omega = sqrt(0.09) ) ), ModelParameter( name = "Cl", distribution = LogNormal( mu = 2, omega = sqrt(0.09) ) ) ) # Error Model errorModelRespPK = Combined1( output = "RespPK", sigmaInter = 0.1, sigmaSlope = 0.1 ) modelError = list( errorModelRespPK ) # administration administration = Administration( outcome = "RespPK", Tinf = c(2), timeDose = c( 0 ), dose = c( 30 ) ) # sampling times samplingTimes = SamplingTimes( outcome = "RespPK", samplings = c( 0.5, 1, 4, 8 ) ) # arm arm1 = Arm( name = "BrasTest", size = 40, administrations = list( administration ) , samplingTimes = list( samplingTimes ) ) # design design1 = Design( name = "design1", arms = list( arm1 ) ) # -------------------------------------- # Evaluation # Evaluate the Fisher Information Matrix for the PopulationFIM evaluationFIM = Evaluation( name = "Linear1InfusionSingleDose_ClV", modelFromLibrary = modelFromLibrary, modelParameters = modelParameters, modelError = modelError, outputs = list( "RespPK" ), designs = list( design1 ), fimType = "population", odeSolverParameters = list( atol = 1e-8, rtol = 1e-8 ) ) evaluationFIM = run( evaluationFIM ) FisherMatrix = getFisherMatrix(evaluationFIM ) detPopulationFim =det( FisherMatrix$fisherMatrix ) detPopulationFim valueDetPopulationFim = 155857928552697888.0 tol = 1e-6 expect_equal( detPopulationFim, valueDetPopulationFim, tolerance = tol ) }) test_that("Model PK 1cpt : Linear1FirstOrderSingleDose_kakV", { ## -------------------------------------- # model definition # model equations modelFromLibrary = list( "PKModel" = "Linear1FirstOrderSingleDose_kakV" ) # model modelParameters modelParameters = list( ModelParameter( name = "ka", distribution = LogNormal( mu = 2, omega = sqrt(1) ) ), ModelParameter( name = "k", distribution = LogNormal( mu = 0.25, omega = sqrt(0.25) ) ), ModelParameter( name = "V", distribution = LogNormal( mu = 15, omega = sqrt(0.1) ) ) ) # Error Model errorModelRespPK = Combined1( output = "RespPK", sigmaInter = 0.5, sigmaSlope = 0.15 ) modelError = list( errorModelRespPK ) # administration administration = Administration( outcome = "RespPK", timeDose = c( 0 ), dose = c( 100 ) ) # sampling times samplingTimes = SamplingTimes( outcome = "RespPK", samplings = c( 0.33, 1.5, 5, 12 ) ) # arm arm1 = Arm( name = "BrasTest", size = 200, administrations = list( administration ) , samplingTimes = list( samplingTimes ) ) # design design1 = Design( name = "design1", arms = list( arm1 ) ) # -------------------------------------- # Evaluation # Evaluate the Fisher Information Matrix for the PopulationFIM evaluationFIM = Evaluation( name = "Linear1FirstOrderSingleDose_kakV", modelFromLibrary = modelFromLibrary, modelParameters = modelParameters, modelError = modelError, outputs = list( "RespPK" ), designs = list( design1 ), fimType = "population", odeSolverParameters = list( atol = 1e-8, rtol = 1e-8 ) ) evaluationFIM = run( evaluationFIM ) FisherMatrix = getFisherMatrix(evaluationFIM ) detPopulationFim =det( FisherMatrix$fisherMatrix ) detPopulationFim valueDetPopulationFim = 293039672275859603466.0 tol = 1e-6 expect_equal( detPopulationFim, valueDetPopulationFim, tolerance = tol ) }) test_that("Model PK 1cpt : Linear1FirstOrderSingleDose_kaClV", { modelFromLibrary = list("PKModel" = "Linear1FirstOrderSingleDose_kaClV") # model modelParameters modelParameters = list( ModelParameter( name = "V", distribution = LogNormal( mu = 8, omega = sqrt(0.020) ) ), ModelParameter( name = "Cl", distribution = LogNormal( mu = 0.13, omega = sqrt(0.06) ) ), ModelParameter( name = "ka", distribution = LogNormal( mu = 1.6, omega = sqrt(0.7) ) ) ) # Error Model errorModelRespPK = Combined1( output = "RespPK", sigmaInter = 0.6, sigmaSlope = 0.07 ) modelError = list( errorModelRespPK ) # administration administration = Administration( outcome = "RespPK", timeDose = c( 0 ), dose = c( 100 ) ) # sampling times samplingTimes = SamplingTimes( outcome = "RespPK", samplings = c( 0.5, 1, 2, 6, 9, 12, 24, 36, 48, 72, 96, 120) ) # arm arm1 = Arm( name = "BrasTest", size = 32, administrations = list( administration ) , samplingTimes = list( samplingTimes ) ) # design design1 = Design( name = "design1", arms = list( arm1 ) ) # Evaluate the Fisher Information Matrix for the PopulationFIM evaluationFIM = Evaluation( name = "Linear1FirstOrderSingleDose_kaClV", modelFromLibrary = modelFromLibrary, modelParameters = modelParameters, modelError = modelError, outputs = list( "RespPK" ), designs = list( design1 ), fimType = "population", odeSolverParameters = list( atol = 1e-8, rtol = 1e-8 ) ) evaluationFIM = run( evaluationFIM ) FisherMatrix = getFisherMatrix(evaluationFIM ) detPopulationFim =det( FisherMatrix$fisherMatrix ) valueDetPopulationFim = 75038812388902169470420.0 # Evaluate the Fisher Information Matrix for the individual FIM evaluationFIM = Evaluation( name = "Linear1FirstOrderSingleDose_kaClV", modelFromLibrary = modelFromLibrary, modelParameters = modelParameters, modelError = modelError, outputs = list( "RespPK" ), designs = list( design1 ), fimType = "individual", optimizerParameters = list( atol = 1e-8, rtol = 1e-8 ) ) evaluationFIM = run( evaluationFIM ) FisherMatrix = getFisherMatrix(evaluationFIM ) detIndividualFim =det( FisherMatrix$fisherMatrix ) valueDetIndividualFim = 1532105538 tol = 1e-6 expect_equal( detPopulationFim, valueDetPopulationFim, tolerance = tol ) expect_equal( detIndividualFim, valueDetIndividualFim, tolerance = tol ) }) # -------------------------------------- # model definition # model equations test_that("Model PK 1cpt : Linear1FirstOrderSingleDose_kaClV (BayesianFIM instead of PopulationFIM)", { modelFromLibrary = list("PKModel" = "Linear1FirstOrderSingleDose_kaClV") # model modelParameters modelParameters = list( ModelParameter( name = "V", distribution = LogNormal( mu = 8, omega = sqrt(0.020) ) ), ModelParameter( name = "Cl", distribution = LogNormal( mu = 0.13, omega = sqrt(0.06) ) ), ModelParameter( name = "ka", distribution = LogNormal( mu = 1.6, omega = sqrt(0.7) ) ) ) # Error Model errorModelRespPK = Combined1( output = "RespPK", sigmaInter = 0.6, sigmaSlope = 0.07 ) modelError = list( errorModelRespPK ) # administration administration = Administration( outcome = "RespPK", timeDose = c( 0 ), dose = c( 100 ) ) # sampling times samplingTimes = SamplingTimes( outcome = "RespPK", samplings = c( 0.5, 1, 2, 6, 9, 12, 24, 36, 48, 72, 96, 120) ) # arm arm1 = Arm( name = "BrasTest", size = 32, administrations = list( administration ) , samplingTimes = list( samplingTimes ) ) # design design1 = Design( name = "design1", arms = list( arm1 ) ) # -------------------------------------- # Evaluation # Evaluate the Fisher Information Matrix for the PopulationFIM evaluationFIM = Evaluation( name = "Linear1FirstOrderSingleDose_kaClV", modelFromLibrary = modelFromLibrary, modelParameters = modelParameters, modelError = modelError, outputs = list( "RespPK" ), designs = list( design1 ), fimType = "Bayesian", odeSolverParameters = list( atol = 1e-8, rtol = 1e-8 ) ) evaluationFIM = run( evaluationFIM ) FisherMatrix = getFisherMatrix(evaluationFIM ) detBayesianFim =det( FisherMatrix$fisherMatrix ) valueDetBayesianFim = 7349326.937090975232422 tol = 1e-6 expect_equal(valueDetBayesianFim,detBayesianFim, tolerance = tol ) }) test_that("Model PK 1cpt : Linear1InfusionSingleDose_ClV", { # -------------------------------------- # model definition # model equations modelFromLibrary = list("PKModel" = "Linear1InfusionSingleDose_ClV") # model modelParameters modelParameters = list( ModelParameter( name = "V", distribution = LogNormal( mu = 3.5, omega = sqrt(0.09) ) ), ModelParameter( name = "Cl", distribution = LogNormal( mu = 2, omega = sqrt(0.09) ) ) ) # Error Model errorModelRespPK = Combined1( output = "RespPK", sigmaInter = 0.1, sigmaSlope = 0.1 ) modelError = list( errorModelRespPK ) # administration administration = Administration( outcome = "RespPK", Tinf=c(2), tau=c(12), dose = c( 30 ) ) # sampling times samplingTimes = SamplingTimes( outcome = "RespPK", samplings = c( 0, 1,2,5,7,8, 10,12,14, 15, 16, 20, 21, 30 ) ) # arm arm1 = Arm( name = "BrasTest", size = 40, administrations = list( administration ) , samplingTimes = list( samplingTimes ) ) # design design1 = Design( name = "design1", arms = list( arm1 ) ) # -------------------------------------- # Evaluation # Evaluate the Fisher Information Matrix for the PopulationFIM evaluationFIM = Evaluation( name = "Linear1InfusionSingleDose_ClV", modelFromLibrary = modelFromLibrary, modelParameters = modelParameters, modelError = modelError, outputs = list( "RespPK" ), designs = list( design1 ), fimType = "population", odeSolverParameters = list( atol = 1e-8, rtol = 1e-8 ) ) evaluationFIM = run( evaluationFIM ) FisherMatrix = getFisherMatrix(evaluationFIM ) detPopulationFim =det( FisherMatrix$fisherMatrix ) valueDetPopulationFim = 15171420395090292736 tol = 1e-6 expect_equal(valueDetPopulationFim,detPopulationFim, tolerance = tol ) }) test_that("Model PK 1cpt : Linear1FirstOrderSingleDose_kaClV", { modelFromLibrary = list("PKModel" = "Linear1FirstOrderSingleDose_kaClV") # model modelParameters modelParameters = list( ModelParameter( name = "V", distribution = LogNormal( mu = 8, omega = sqrt(0.020) ) ), ModelParameter( name = "Cl", distribution = LogNormal( mu = 0.13, omega = sqrt(0.06) ) ), ModelParameter( name = "ka", distribution = LogNormal( mu = 1.6, omega = sqrt(0.7) ) ) ) # Error Model errorModelRespPK = Combined1( output = "RespPK", sigmaInter = 0.6, sigmaSlope = 0.07 ) modelError = list( errorModelRespPK ) # administration administration = Administration( outcome = "RespPK", timeDose = c( 0, 80, 160 ), dose = c( 100,100,100 ) ) # sampling times samplingTimes = SamplingTimes( outcome = "RespPK", samplings = c( 0.5, 1, 2, 6, 12, 48, 72, 120, 165, 220 ) ) # arm arm1 = Arm( name = "BrasTest", size = 32, administrations = list( administration ) , samplingTimes = list( samplingTimes ) ) # design design1 = Design( name = "design1", arms = list( arm1 ) ) # -------------------------------------- # Evaluation # Evaluate the Fisher Information Matrix for the PopulationFIM evaluationFIM = Evaluation( name = "Linear1FirstOrderSingleDose_kaClV", modelFromLibrary = modelFromLibrary, modelParameters = modelParameters, modelError = modelError, outputs = list( "RespPK" ), designs = list( design1 ), fimType = "population", odeSolverParameters = list( atol = 1e-8, rtol = 1e-8 ) ) evaluationFIM = run( evaluationFIM ) FisherMatrix = getFisherMatrix(evaluationFIM ) detPopulationFim = det( FisherMatrix$fisherMatrix ) valueDetPopulationFim = 23048351728920705368024 # Evaluate the Fisher Information Matrix for the individual FIM evaluationFIM = Evaluation( name = "Linear1FirstOrderSingleDose_kaClV", modelFromLibrary = modelFromLibrary, modelParameters = modelParameters, modelError = modelError, outputs = list( "RespPK" ), designs = list( design1 ), fimType = "individual", odeSolverParameters = list( atol = 1e-8, rtol = 1e-8 ) ) evaluationFIM = run( evaluationFIM ) FisherMatrix = getFisherMatrix(evaluationFIM ) detIndividualFim =det( FisherMatrix$fisherMatrix ) valueDetIndividualFim = 618022401.4696867465973 tol = 1e-6 expect_equal( detPopulationFim, valueDetPopulationFim, tolerance = tol ) expect_equal( detIndividualFim, valueDetIndividualFim, tolerance = tol ) }) ################################################################################################################################### test_that("Model PK 2cpts : Linear2BolusSingleDose_ClQV1V2", { # -------------------------------------- # model definition # model equations modelFromLibrary = list("PKModel" = "Linear2BolusSingleDose_ClQV1V2") # model modelParameters modelParameters = list( ModelParameter( name = "Cl", distribution = LogNormal( mu = 0.4, omega = sqrt(0.2) ) ), ModelParameter( name = "V1", distribution = LogNormal( mu = 10, omega = sqrt(0.1) ) ), ModelParameter( name = "Q", distribution = LogNormal( mu = 2, omega = sqrt(0.05) ) ), ModelParameter( name = "V2", distribution = LogNormal( mu = 50, omega = sqrt(0.4) ) ) ) # Error Model errorModelRespPK = Combined1( output = "RespPK", sigmaInter = 0.6, sigmaSlope = 0.07 ) modelError = list( errorModelRespPK ) # administration administration = Administration( outcome = "RespPK", timeDose = c( 0 ), dose = c( 100 ) ) # sampling times samplingTimes = SamplingTimes( outcome = "RespPK", samplings = c( 0.5, 1, 2, 6, 9, 12, 24, 36, 48, 72, 96, 120) ) # arm arm1 = Arm( name = "BrasTest", size = 32, administrations = list( administration ) , samplingTimes = list( samplingTimes ) ) # design design1 = Design( name = "design1", arms = list( arm1 ) ) # -------------------------------------- # Evaluation # Evaluate the Fisher Information Matrix for the PopulationFIM evaluationFIM = Evaluation( name = "Linear2BolusSingleDose_ClQV1V2", modelFromLibrary = modelFromLibrary, modelParameters = modelParameters, modelError = modelError, outputs = list( "RespPK" ), designs = list( design1 ), fimType = "population", odeSolverParameters = list( atol = 1e-8, rtol = 1e-8 ) ) evaluationFIM = run( evaluationFIM ) FisherMatrix = getFisherMatrix(evaluationFIM ) detPopulationFim =det( FisherMatrix$fisherMatrix ) valueDetPopulationFim = 45852890814.07175445557 tol = 1e-6 expect_equal(detPopulationFim,valueDetPopulationFim, tolerance = tol ) }) ################################################################################################################################### test_that("Model PK 2cpts : Linear2BolusSingleDose_kk12k21V", { # -------------------------------------- # model definition # model equations modelFromLibrary = list("PKModel" = "Linear2BolusSingleDose_kk12k21V") # model modelParameters modelParameters = list( ModelParameter( name = "k", distribution = LogNormal( mu = 0.25, omega = sqrt(0.25) ) ), ModelParameter( name = "V", distribution = LogNormal( mu = 15.00, omega = sqrt(0.10) ) ), ModelParameter( name = "k12", distribution = LogNormal( mu = 1.00, omega = sqrt(0.40) ) ), ModelParameter( name = "k21", distribution = LogNormal( mu = 0.80, omega = sqrt(0.30) ) ) ) # Error Model errorModelRespPK = Combined1( output = "RespPK", sigmaInter = 0.5, sigmaSlope = 0.15 ) modelError = list( errorModelRespPK ) # administration administration = Administration( outcome = "RespPK", timeDose = c( 0 ), dose = c( 100 ) ) # sampling times samplingTimes = SamplingTimes( outcome = "RespPK", samplings = c(0.33, 1.5, 3, 5, 8, 12 ) ) # arm arm1 = Arm( name = "BrasTest", size = 200, administrations = list( administration ) , samplingTimes = list( samplingTimes ) ) # design design1 = Design( name = "design1", arms = list( arm1 ) ) # -------------------------------------- # Evaluation # Evaluate the Fisher Information Matrix for the PopulationFIM evaluationFIM = Evaluation( name = "Linear2BolusSingleDose_kk12k21V", modelFromLibrary = modelFromLibrary, modelParameters = modelParameters, modelError = modelError, outputs = list( "RespPK"), designs = list( design1 ), fimType = "population", odeSolverParameters = list( atol = 1e-8, rtol = 1e-8 ) ) evaluationFIM = run( evaluationFIM ) FisherMatrix = getFisherMatrix(evaluationFIM ) detPopulationFim =det( FisherMatrix$fisherMatrix ) detPopulationFim valueDetPopulationFim = 1733176644421398016.0 tol = 1e-6 expect_equal(detPopulationFim,valueDetPopulationFim, tolerance = tol ) }) ################################################################################################################################### test_that("Model PK 1cpt : MichaelisMenten1FirstOrderSingleDose_kaVmKmV", { # -------------------------------------- # model definition # model equations modelFromLibrary = list("PKModel" = "MichaelisMenten1FirstOrderSingleDose_kaVmKmV") # model modelParameters modelParameters = list( ModelParameter( name = "ka", distribution = LogNormal( mu = 1.0, omega = sqrt(0.20) ) ), ModelParameter( name = "V", distribution = LogNormal( mu = 15.00, omega = sqrt(0.25) ) ), ModelParameter( name = "Vm", distribution = LogNormal( mu = 0.08, omega = sqrt(0.10) ) ), ModelParameter( name = "Km", distribution = LogNormal( mu = 0.40, omega = sqrt(0.30) ) ) ) # Error Model errorModelRespPK = Combined1( output = "RespPK", sigmaInter = 0.5, sigmaSlope = 0.15 ) modelError = list( errorModelRespPK ) # administration administration = Administration( outcome = "RespPK", timeDose = c( 0 ), dose = c( 100 ) ) # sampling times samplingTimes = SamplingTimes( outcome = "RespPK", samplings = c( 0, 0.33, 1.5, 3, 5, 8, 11, 12 ) ) # arm arm1 = Arm( name = "BrasTest", size = 200, administrations = list( administration ) , samplingTimes = list( samplingTimes ) , initialCondition = list( "C1" = 0 ) ) # design design1 = Design( name = "design1", arms = list( arm1 ) ) # -------------------------------------- # Evaluation # Evaluate the Fisher Information Matrix for the PopulationFIM evaluationFIM = Evaluation( name = "MichaelisMenten1FirstOrderSingleDose_kaVmKmV", modelFromLibrary = modelFromLibrary, modelParameters = modelParameters, modelError = modelError, outputs = list( "RespPK" = "C1" ), designs = list( design1 ), fimType = "population", odeSolverParameters = list( atol = 1e-8, rtol = 1e-8 ) ) evaluationFIM = run( evaluationFIM ) FisherMatrix = getFisherMatrix(evaluationFIM ) detPopulationFim =det( FisherMatrix$fisherMatrix ) detPopulationFim valueDetPopulationFim = 592523761240 tol = 1e-6 expect_equal(detPopulationFim,valueDetPopulationFim, tolerance = tol ) }) test_that("Model PK 1cpt : MichaelisMenten1BolusSingleDose_VmKm", { # model equations modelFromLibrary = list("PKModel" = "MichaelisMenten1BolusSingleDose_VmKm") # model modelParameters modelParameters = list( ModelParameter( name = "Vm", distribution = LogNormal( mu = 0.08, omega = sqrt(0.10) ) ), ModelParameter( name = "Km", distribution = LogNormal( mu = 0.40, omega = sqrt(0.30) ) ) ) # Error Model errorModelRespPK = Combined1( output = "RespPK", sigmaInter = 0.5, sigmaSlope = 0.15 ) modelError = list( errorModelRespPK ) # administration administration = Administration( outcome = "C1", timeDose = c( 0 ), dose = c( 100 ) ) # sampling times samplingTimes = SamplingTimes( outcome = "C1", samplings = c( 0, 0.5, 1, 2, 6, 9, 12, 24, 36, 48, 72, 96, 120 ) ) # arm arm1 = Arm( name = "BrasTest", size = 200, administrations = list( administration ) , samplingTimes = list( samplingTimes ) , initialCondition = list( "C1" = 0 ) ) # design design1 = Design( name = "design1", arms = list( arm1 ) ) # -------------------------------------- # Evaluation # Evaluate the Fisher Information Matrix for the PopulationFIM evaluationFIM = Evaluation( name = "MichaelisMenten1BolusSingleDose_VmKm", modelFromLibrary = modelFromLibrary, modelParameters = modelParameters, modelError = modelError, outputs = list( "RespPK" = "C1" ), designs = list( design1 ), fimType = "population", odeSolverParameters = list( atol = 1e-8, rtol = 1e-8 ) ) evaluationFIM = run( evaluationFIM ) FisherMatrix = getFisherMatrix(evaluationFIM ) detPopulationFim =det( FisherMatrix$fisherMatrix ) valueDetPopulationFim = 0.015545625761308865323 tol = 1e-6 expect_equal( detPopulationFim, valueDetPopulationFim, tolerance = tol ) }) ################################################################################################################################### test_that("Model PK 1cpt : Linear1FirstOrderSingleDose_kaClV", { modelFromLibrary = list("PKModel" = "Linear1FirstOrderSingleDose_kaClV") modelParameters = list( ModelParameter( name = "V", distribution = LogNormal( mu = 63.000, omega = 0 ) ), ModelParameter( name = "Cl", distribution = LogNormal( mu = 0.513, omega = 0 ) ), ModelParameter( name = "ka", distribution = LogNormal( mu = 1.050, omega = sqrt(0.1) ) ) ) errorModelRespPK = Combined1( output = "RespPK", sigmaInter = 0, sigmaSlope = 0.0676 ) modelError = list( errorModelRespPK ) administration = Administration( outcome = "RespPK", timeDose = c( 0 ), dose = c( 5500 ) ) # sampling times samplingTimes = SamplingTimes( outcome = "RespPK", samplings = c( 0.01, 1, 3, 5, 7, 10, 13, 17, 24 ) ) # arm arm1 = Arm( name = "BrasTest", size = 25, administrations = list( administration ) , samplingTimes = list( samplingTimes ) ) # design design1 = Design( name = "design1", arms = list( arm1 ) ) # -------------------------------------- # Evaluation # Evaluate the Fisher Information Matrix for the PopulationFIM evaluationFIM = Evaluation( name = "Linear1FirstOrderSingleDose_kaClV", modelFromLibrary = modelFromLibrary, modelParameters = modelParameters, modelError = modelError, outputs = list( "RespPK" ), designs = list( design1 ), fimType = "population", odeSolverParameters = list( atol = 1e-8, rtol = 1e-8 ) ) evaluationFIM = run( evaluationFIM ) FisherMatrix = getFisherMatrix(evaluationFIM ) detPopulationFim =det( FisherMatrix$fisherMatrix ) detPopulationFim valueDetPopulationFim = 88354126194397.8 tol = 1e-6 expect_equal(detPopulationFim,valueDetPopulationFim, tolerance = tol ) }) ################################################################################################################################### test_that("Model PK 1cpt : Linear1FirstOrderSingleDose_kaClV", { # -------------------------------------- # model definition # model equations modelFromLibrary = list("PKModel" = "Linear1FirstOrderSingleDose_kaClV") # model modelParameters modelParameters = list( ModelParameter( name = "V", distribution = LogNormal( mu = 3.5, omega = sqrt( 0.09 ) ) ), ModelParameter( name = "Cl", distribution = LogNormal( mu = 2.0, omega = sqrt( 0.09 ) ) ), ModelParameter( name = "ka", distribution = LogNormal( mu = 1.0, omega = sqrt(0.09) ) ) ) # Error Model errorModelRespPK = Combined1( output = "RespPK", sigmaInter = 0.1, sigmaSlope = 0.1 ) modelError = list( errorModelRespPK ) # administration administration = Administration( outcome = "RespPK", timeDose = c( 0,12,24,36,48 ), dose = c( 30,30,30,30,30 ) ) # sampling times samplingTimes = SamplingTimes( outcome = "RespPK", samplings = c( 0.5, 1, 4, 8, 12.5, 13, 16, 20, 24.5, 25, 28, 32, 36.5, 37, 40, 44, 48.5, 49, 52, 56 ) ) # arm arm1 = Arm( name = "BrasTest", size = 40, administrations = list( administration ) , samplingTimes = list( samplingTimes ) ) # design design1 = Design( name = "design1", arms = list( arm1 ) ) # -------------------------------------- # Evaluation # Evaluate the Fisher Information Matrix for the PopulationFIM evaluationFIM = Evaluation( name = "Linear1FirstOrderSingleDose_kaClV", modelFromLibrary = modelFromLibrary, modelParameters = modelParameters, modelError = modelError, outputs = list( "RespPK" ), designs = list( design1 ), fimType = "population", odeSolverParameters = list( atol = 1e-8, rtol = 1e-8 ) ) evaluationFIM = run( evaluationFIM ) # get the determinant of the Fisher matrix FisherMatrix = getFisherMatrix(evaluationFIM ) detPopulationFim =det( FisherMatrix$fisherMatrix ) detPopulationFim valueDetPopulationFim = 2835909452801529708800884.0 tol = 1e-6 expect_equal(detPopulationFim,valueDetPopulationFim, tolerance = tol ) }) ################################################################################################################################### test_that("Model PK 1cpt : Linear1FirstOrderSteadyState_kaClVtau", { # -------------------------------------- # model definition # model equations modelFromLibrary = list("PKModel" = "Linear1FirstOrderSteadyState_kaClVtau") # model modelParameters modelParameters = list( ModelParameter( name = "ka", distribution = LogNormal( mu = 1.050, omega = sqrt(0.1) ) ), ModelParameter( name = "Cl", distribution = LogNormal( mu = 0.513, omega = 0 ) ), ModelParameter( name = "V", distribution = LogNormal( mu = 63.000, omega = 0 ) ) ) # Error Model errorModelRespPK = Combined1( output = "RespPK", sigmaInter = 0, sigmaSlope = 0.0676 ) modelError = list( errorModelRespPK ) # administration administration = Administration( outcome = "RespPK", tau = c(24), dose = c( 5500 ) ) # sampling times samplingTimes = SamplingTimes( outcome = "RespPK", samplings = c( 0.01, 1, 3, 5, 7, 10, 13, 17, 24 ) ) # arm arm1 = Arm( name = "BrasTest", size = 25, administrations = list( administration ) , samplingTimes = list( samplingTimes ) ) # design design1 = Design( name = "design1", arms = list( arm1 ) ) # -------------------------------------- # Evaluation # Evaluate the Fisher Information Matrix for the PopulationFIM evaluationFIM = Evaluation( name = "Linear1FirstOrderSteadyState_kaClVtau", modelFromLibrary = modelFromLibrary, modelParameters = modelParameters, modelError = modelError, outputs = list( "RespPK" ), designs = list( design1 ), fimType = "population", odeSolverParameters = list( atol = 1e-8, rtol = 1e-8 ) ) evaluationFIM = run( evaluationFIM ) # get the determinant of the Fisher matrix FisherMatrix = getFisherMatrix(evaluationFIM ) detPopulationFim =det( FisherMatrix$fisherMatrix ) detPopulationFim valueDetPopulationFim = 119307107145 tol = 1e-6 expect_equal(detPopulationFim,valueDetPopulationFim, tolerance = tol ) }) ############################################################################################################################ # END CODE ############################################################################################################################