Chapter 1 Introduction

1.1 Prerequisites

Several packages and pieces of software together create the nlmixr environment.

In general, these packages and software are:

• R (including variants such as Microsoft R Open and related GUIs, such as RGui and Rstudio)
• Python and SymPy
• RxODE (development release on GitHub)
• nlmixr (development release on GitHub)

Secondary R packages required by nlmixr are:

• n1qn1
• PreciseSums
• SnakeCharmR

Packages to support the use of nlmixr are:

• shinyMixR
• xpose.nlmixr

More specific information on the installation of packages and software can be found in Chapter 2.

1.2 Workflow

The ability to perform population modeling in R provides an opportunity to work via a single unified workflow for data management, data exploration, data analysis and report writing.

nlmixr can be used directly from the R command line or via the user-friendly R Shiny tool shinyMixR. The shinyMixR package provides a means to build a project-centric workflow around nlmixr from the R command line and from a streamlined Shiny application. This project tool was developed to enhance the usability and attractiveness of nlmixr, facilitating dynamic and interactive use in real-time for rapid model development. More on the use of shinyMixR in Chapter 3.3.