Certara.R
provides a collection of packages and Shiny
applications designed for Pharmacometric workflows in R. Shiny
applications provide the ability to generate R code given
point-and-click operations, enabling a reproducible and extensible
workflow from Shiny GUI to RStudio. Learn
more
install.packages("Certara.R")
library(Certara.R)
install_certara_packages()
check_certara_package_versions()
The RsNLME
suite of packages use Certara’s NLME-Engine
for execution. Create, edit, and execute a Phoenix NLME model, directly
from R!
Certara.RsNLME
uses tidyverse syntax to build
Non-Linear-Mixed-Effects (NLME) models in R. Create and execute NLME
models using built-in R functions, or execute models with PML code used in
Phoenix PK/PD
Platform.
Certara.RsNLME.ModelBuilder
is an R package and Shiny application used to build an RsNLME model.
Use the GUI to select from various model building options and observe the PML update in real time. Additionally, users may generate the corresponding RsNLME code to reproduce the model object from R.
Certara.RsNLME.ModelExecutor
is an R package and Shiny application used to execute an RsNLME
model.
Use the GUI to add additional output tables, specify engine parameters, select various run types, and more!
Certara.RDarwin
is an R package designed to facilitate the usage of pyDarwin
with the Certara NLME pharmacometric modeling engine from the R command
line. The Python package, pyDarwin, is a powerful tool for using machine
learning algorithms for model selection.
Certara.DarwinReporter
is an R package that provides a Shiny application, in addition to
various plotting and data summary functions, for analyzing results of a
pyDarwin
automated machine learning based model search.
Certara.ModelResults
is an R package and Shiny GUI used to generate, customize, and report
model diagnostic plots and tables from NLME or NONMEM runs.
Users are not limited by the GUI however, Certara.ModelResults will
generate the underlying flextable
and
xpose
/ggplot2
code (.R
and/or
.Rmd
) for you inside the Shiny application, which you can
then use to recreate your plot and table objects in R, ensuring
reproducibility and trace-ability of model diagnostics for reporting
output.
Certara.Xpose.NLME
is an R package used to creates xpose
databases
(xpose_data
) for PML/NLME results. Additionally, Certara.Xpose.NLME
offers various covariate model diagnostic functions, not available in
the xpose
package.
coveffectsplot
is an R package that provide the function forest_plot and an
accompanying Shiny application that facilitates the production of forest
plots to visualize covariate effects as commonly used in pharmacometrics
population PK/PD report
Learn more about the package here.
Certara.VPCResults
is an R package and Shiny application used to parameterize and plot a
Visual Predictive Check (VPC).
Use the GUI to select from various binning or binless methods and specify options such as censoring, stratification, and prediction-corrected.
Users are not limited by the GUI however, Certara.VPCResults
will generate the underlying tidyvpc
and
ggplot2
code (.R
and/or .Rmd
) for
you inside the Shiny application, which you can then use to recreate
your plot and table objects in R, ensuring reproducibility of VPC’s for
reporting output.
The tidyvpc
package is used to perform a Visual Predictive Check (VPC), while
accounting for stratification, censoring, and prediction correction.
Using piping from ‘magrittr’, the intuitive syntax gives users a flexible and powerful method to generate VPCs using both traditional binning and a new binless approach Jamsen et al. (2018) doi:10.1002/psp4.12319 with Additive Quantile Regression (AQR) and Locally Estimated Scatterplot Smoothing (LOESS) prediction correction.
ggquickeda
is an R Shiny app/package providing a graphical user interface (GUI) to
ggplot2
and table1
.
It enables you to quickly explore your data and to detect trends on the fly. Create scatter plots, dotplots, boxplots, barplots, histograms, densities and summary statistics of one or multiple variable(s) by column(s) splits and an optional overall column.
In addition, ggquickeda
also provides the km, kmband and
kmticks geoms/stats to facilitate the plotting of Kaplan-Meier Survival
curves.
For a quick overview using an older version of the app head to this YouTube Tutorial.
ggcertara
is an R package to provide used to provide a standardized look for plots
employed by pharmacometricians. It provides a ggplot2
theme, color palette, and a collection of plotting functions for basic
goodness-of-fit diagnostic plots.
See the following vignette for an overview of the package.
table1c
is an R package for generating tables of descriptive statistics in HTML.
It is a light wrapper around the table1 package with some customizations
for the convenience of Certara IDD.
See the following vignette for an overview of the package.
pmxpartabc is an
R package for generating parameter estimates tables.
pmxpartabc
provides ease of table generation via
specification of NONMEM run_dir
or information contained in
a user-provided yaml
file. Additional support for bootstrap
estimates is provided.
Visit the pmxpartabc website for examples of usage details.
The scmreg
package
provides functions to perform Stepwise Covariate Modeling (SCM) in R.
With the scm_reg()
function, you can setup and execute a
stepwise covariate model selection using different regression techniques
and easily generate table output using the tabscm()
function.