integration of ODE (cum AUC) and prediction table

[MahmoudAliAfifi]

Dear colleagues,

I used nlmixr2 to fit simulated data, but I faced some problems:
1- values of zeros in the compartment values [A, A2,A3, A4]
2- in A4 I am trying to calculate the AUC.
3- I do not know how to get the table of predictions.

I attached the code. below

do_nlmixrODE_nlme <- function(i) {
  datr<- fread(paste0(".//bootdata//",
                      paste0("bootdata",i,model,"N=", Nsubjects,",n=",ifelse(!sparse,length(time_points),4),
                             ",Frel=", frel_form["Frel"]),".csv"))
  compartmental.infusion.model <- function() {
    ini({
      theta_v1 <- 1.187843 #the log value
      theta_v2	<- 0.6365768  #the log value
      theta_v3<- 	0.6729445  #the log value 
      Q1	<- -5.839602  #the log value
      Q2	<- -3.137296  #the log value
      theta_Vmax<- 	5.181784  #the log value
      theta_Km	<- 6.842683  #the log value
      theta_Ke<- 	-6.119298 #the log value
      # theta_formulation <- 0.04879016 
      eta_v1 ~	0.0217  #the log value
      eta_km	~ 0.121  #the log value
      eta_Ke	~ 0.0292 #the log value
      prop.sd <-  0.00000001  #the log value
      
      
    })
    # and a model block with the error sppecification and model specification
    model({
      Kel<- exp(theta_Ke + eta_Ke) #changed to the exp(log format)
      km<- exp(theta_Km + eta_km)  #changed to the exp(log format)
      V1<-  exp(theta_v1 + eta_v1) #changed to the exp(log format)
      CL<- Kel * V1 #changed to the exp(log format)
      V2<- exp(theta_v2) #changed to the exp(log format)
      V3<- exp(theta_v3)#changed to the exp(log format)
      Q1 <-  exp(Q1)
      Q2 <- exp(Q2)
      C1<- A1/V1
      C2<- A2/V2
      C3<- A3/V3
      CUMAUC= A4
      d/dt(A1)= - Kel*A1 - theta_Vmax * C1/(km + C1) - Q1*(C1 - C2) - Q2*(C1 - C3)
      d/dt(A2)= Q1 * (C1 - C2)
      d/dt(A3)=Q2 * (C1 - C3)
      d/dt(A4)<- C1
      C1 ~ add(prop.sd) # I added a small proportional error.
    })    
    
    
  }
  fit <-
    nlmixr2(
      compartmental.infusion.model,
      data = datr,
      est = "saem")
  save(fit, file = paste("fit_NLME_ODE_UUI_", i, ".Rdata", sep = "")) #the fit will be saved as R object in the directory
}
#install.packages("doParallel")
library(doParallel)
cl <- makeCluster(numCores)
registerDoParallel(cl)
tic()

nlmixr_out <-
  foreach(i = 1:NBOOT, .packages = c('nlmixr2', "data.table")) %dopar% do_nlmixrODE_nlme(i)