These applications require the mlxR package for the simulation and visualization of longitudinal data.



Introduction to pharmacokinetics modelling

Here, Shiny applications are embedded in html pages to illustrate some basic concepts in pharmacometrics.


absorption distribution elimination
Modelling the absorption process Modelling the distribution process Modelling the elimination process


Building a pharmacokinetics model

These Shiny applications allow one to interactively modify the PK model and the dosage regimen, and visualize the plasmatic concentration given by this model. Here, a R code is automatically updated on the fly according to the settings of the application.


ADME process absorption processes iv and oral administations
Modelling the ADME process with a PK model Comparing different absorption processes Combining oral and intraveinous administrations


Visualizing a statistical model


residual error model inter individual variability model time to event model
Residual error model Inter individual variability model Time to event model
Visualize several residual error models (constant, proportional, combined, exponential, …) Compute and display prediction intervals of a PK model assuming that the PK parameters are random variables Define your own hazard function, display the survival and hazard functions, simulate data and display the Kaplan Meier plot



Model fitting

The objective of these applications is to fit a model to longitudinal data.


Fitting a PK model Fitting a tumor growth model