Recently, developments in the R language, and in particular the Shiny package for R, 8 have allowed R programmers to interactively show the output for R programs to Web-browsers. 7 While Berkeley Madonna has found useful roles in presenting model predictions to nonpharmacometricians, it is proprietary software (albeit inexpensive) and is not readily adapted to simulations of variability. The Berkeley Madonna software provides an alternative approach where models can be specified as differential equations and the simulated results shown in real-time for different parameter values by use of sliders. However, the plots are static and to investigate different values for model parameters the models need to be re-simulated and plots updated manually. Recent developments such as the ggplot2 4, 5 package for the R data analysis and statistical language 6 have allowed sophisticated and flexible plotting of data and population model output. 1, 2 However, the process of making predictions from population models has been largely time-consuming, and remained the province of dedicated pharmacometricians using specialized software limiting its wider applicability.

Population models have found important roles in the development, regulation, and optimal use of pharmaceuticals.

A robust simulation model is an important tool for predicting new data-the consequences of changes in the dosing regimen or covariate influences.

A population pharmacokinetic and/or pharmacodynamic model can be thought of as an elegant and concise description of the underlying mechanisms and variability in a data set.

Shiny package r