nlmeODE (version 0.2-7)

PKsim: Simulation of PK data with multiple IV infusions and SC bolus doses

Description

Simulation data of multiple intravenous infusions and SC bolus doses. Estimation of model parameters as well as extent and time of the infusions.

Examples

OneCompAbs <- list(DiffEq=list(
                     dA1dt = ~ -ka*A1,
                     dA2dt = ~ ka*A1 - CL/V1*A2),
                   ObsEq=list(
                     SC= ~0,
                     C = ~ A2/V1),        
                   States=c("A1","A2"), 
                   Parms=c("ka","CL","V1","F1"),
                   Init=list(0,0))

ID    <- rep(seq(1:18),each=11)
Time  <- rep(seq(0,100,by=10),18)
Dose  <- c(rep(c(100,0,0,100,0,0,0,0,0,0,0),6),rep(c(100,0,0,0,0,0,0,100,0,0,0),6),rep(c(100,0,0,0,0,0,0,0,0,0,0),6))
Rate  <- c(rep(rep(0,11),6),rep(c(5,rep(0,10)),6),rep(rep(0,11),6))
Cmt   <- c(rep(1,6*11),rep(c(2,0,0,0,0,0,0,1,0,0,0),6),rep(2,6*11))
Conc  <- rep(0,18*11)

Data <- as.data.frame(list(ID=ID,Time=Time,Dose=Dose,Rate=Rate,Cmt=Cmt,Conc=Conc))

SimData <- groupedData( Conc ~ Time | ID,
               data = Data,
               labels = list( x = "Time", y = "Concentration"))

OneCompAbsModel <- nlmeODE(OneCompAbs,SimData)

kaSim <- rep(log(rep(0.05,18))+0.3*rnorm(18),each=11)
CLSim <- rep(log(rep(0.5,18))+0.2*rnorm(18),each=11)
V1Sim <- rep(log(rep(10,18))+0.1*rnorm(18),each=11)
F1Sim <- rep(log(0.8),18*11)

SimData$Sim <- OneCompAbsModel(kaSim,CLSim,V1Sim,F1Sim,SimData$Time,SimData$ID)

SimData$Conc <- SimData$Sim + 0.3*rnorm(dim(SimData)[1])

Data <- groupedData( Conc ~ Time | ID,
               data = SimData,
               labels = list( x = "Time", y = "Concentration"))

plot(Data,aspect=1/1)

#Estimation of model parameters
OneCompAbsModel <- nlmeODE(OneCompAbs,Data)

#Remove '#' below to run the estimation

#fit1 <- nlme(Conc ~ OneCompAbsModel(ka,CL,V1,F1,Time,ID),
#        data = Data, fixed=ka+CL+V1+F1~1, random = pdDiag(ka+CL+V1~1), 
#        start=c(ka=log(0.05),CL=log(0.5),V1=log(10.0),F1=log(0.8)),
#        control=list(msVerbose=TRUE,tolerance=1e-3,pnlsTol=1e-1,msTol=1e-3),
#        verbose=TRUE)

#plot(augPred(fit1,level=0:1,length.out=300),aspect=1/1)

#Estimation of rate of infusion
Data$Rate[Data$Rate==5] <- -1

OneCompAbs <- list(DiffEq=list(
                     dA1dt = ~ -ka*A1,
                     dA2dt = ~ ka*A1 - CL/V1*A2),
                   ObsEq=list(
                     SC= ~0,
                     C = ~ A2/V1),        
                   States=c("A1","A2"), 
                   Parms=c("ka","CL","V1","F1","Rate"),
                   Init=list(0,0))

OneCompAbsModel <- nlmeODE(OneCompAbs,Data)

#Remove '#' below to run the estimation

#fit2 <- nlme(Conc ~ OneCompAbsModel(ka,CL,V1,F1,Rate,Time,ID),
#        data = Data, fixed=ka+CL+V1+F1+Rate~1, random = pdDiag(ka+CL+V1~1), 
#        start=c(ka=log(0.05),CL=log(0.5),V1=log(10.0),F1=log(0.8),Rate=log(5)),
#        control=list(msVerbose=TRUE,tolerance=1e-3,pnlsTol=1e-1,msTol=1e-3),
#        verbose=TRUE)

#plot(augPred(fit2,level=0:1,length.out=300),aspect=1/1)

#Estimation of length of infusion
Data$Rate[Data$Rate==-1] <- -2

OneCompAbs <- list(DiffEq=list(
                     dA1dt = ~ -ka*A1,
                     dA2dt = ~ ka*A1 - CL/V1*A2),
                   ObsEq=list(
                     SC= ~0,
                     C = ~ A2/V1),        
                   States=c("A1","A2"), 
                   Parms=c("ka","CL","V1","F1","Tcrit"),
                   Init=list(0,0))

OneCompAbsModel <- nlmeODE(OneCompAbs,Data)

#Remove '#' below to run the estimation

#fit3 <- nlme(Conc ~ OneCompAbsModel(ka,CL,V1,F1,Tcrit,Time,ID),
#        data = Data, fixed=ka+CL+V1+F1+Tcrit~1, random = pdDiag(ka+CL+V1~1), 
#        start=c(ka=log(0.05),CL=log(0.5),V1=log(10.0),F1=log(0.8),Tcrit=log(20)),
#        control=list(msVerbose=TRUE,tolerance=1e-3,pnlsTol=1e-1,msTol=1e-3),
#        verbose=TRUE)

#plot(augPred(fit3,level=0:1,length.out=300),aspect=1/1)