Monolix
- Open Monolix
- Go to the menu Project/Load demo
- Load theophylline_project.mlxtran in folder 1.creating_and_using_models\libraries_of_models

- Monolix loads the project and the interface looks like the following figure

- The project is loaded and you can launch the workflow (in the presented case, the population parameter estimation, the Fisher Information Matrix calculation using linearization and the individual parameter estimation using the conditional modes) by clicking on the “Play” button.
- Several real time graphics showing the evolution of the tasks are displayed and at the end, some figures are displayed as in the following figure (in the presented case, the VPC is displayed).

Simulx
Simulx is a little bit different from the other applications because it does not have yet a user interface. To validate it, one should use R (version greater than 3.0.2) to run simulations.
- Open R or Rstudio
- The R-packages needed to run Simulx are defined here. Make sure you have all the required packages.
- Execute the following commands
# Define the mlxR library library("mlxR") # Define the model myModel <- inlineModel("[LONGITUDINAL] input = {V, Cl} EQUATION: Cc = pkmodel(V, Cl)") # Define the administration adm <- list(time=3, amount=40) # Define the output Cc <- list(name='Cc',time=seq(from=0, to=20, by=0.1)) # Run the simulation res <- simulx(model=myModel, parameter=c(V=10, Cl=4), output=Cc,treatment=adm) # Plot the concentration w.r.t. time print(ggplot(data=res$Cc, aes(x=time, y=Cc)) + geom_line(size=1)) - The computation is launched and the following graphic appears

