⛔ [DEPRECATED] rspeaksnonmem

R package for working with and executing NONMEM control files, also integrating PsN.

This package is deprecated and will not be updated or further maintained. I suggest instead using the package {Pharmpy} and {Pharmr} developed by Uppsala University, Sweden. https://pharmpy.github.io/latest/index.html. These packages implement much of the functionality in {rspeaksnonmem} in a better and more consistent way, and are actively maintained.

Description

rspeaksnonmem is designed to allow the user to craft workflows based on a given NONMEM model.

After importing and parsing a control stream to an R object (using the RNMImport package), rspeaksnonmem allows the user to easily change initial estimates, change data attributes or change task properties (estimation or simulation settings) without having to change the model. This saves a lot of textual searching by the user. The resulting data, parameter, model and task information is then written back out to file using an existing (possibly the original) model as a template.

rspeaksnonmem also allows the user to run NONMEM models from R either directly running the nmfe.bat or by calling Perl speaks NONMEM functions like "execute". Other PsN functions can be run from R - VPC (Visual Predictive Check), bootstrap, SSE (Stochastic Simulation and Estimation).

ISOP Study Group demonstration

rspeaksnonmem was demonstrated at an ISOP Study Group webinar which is available on YouTube: https://www.youtube.com/watch?v=VFdGnWrRXw8.

Installation

Eventually, rspeaksnonmem will be released to CRAN, but while still in development rspeaksnonmem can most easily be installed from GitHub using the devtools package:

library(devtools)
install_github("MikeKSmith/rspeaksnonmem")

Dependencies

rspeaksnonmem relies on the package RNMImport function importNmMod which reads and parses the NONMEM control stream. rspeaksnonmem then works with the data, parameter values, and task information separately from the model.

Before installation of rspeaksnonmem, the package RNMImport needs to be installed. This package is not on CRAN but is available on R-Forge. You can install from there using:

install.packages("RNMImport", repos="http://R-Forge.R-project.org")

or download the .tar file from R-Forge and run in R:

install.packages("~/Downloads/RNMImport_4.0-27.tar.gz", repos=NULL, type = "source")