In esqLABS/esqlabsR: esqLABS utilities package

knitr::opts_chunk$set(
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library(tidyr)
library(dplyr)

esqlabsR

The {esqlabsR} package facilitates and standardizes the modeling and simulation of physiologically based kinetic (PBK) and quantitative systems pharmacology/toxicology (QSP/T) models implemented in the Open Systems Pharmacology Software (OSPS).

The {esqlabsR} package is designed for PBK modelers who use the OSPS suite. By using this package, you can streamline your modeling and simulation (M&S) workflow and ensure standardized and reproducible practices.

The package provides functions to:

• Design, import and run Simulations,
• Generate standardized plots and other reporting materials,
• Interact with the OSPS features using simple Excel files.

To get started with the esqlabsR package, please follow the Get Started tutorial.

Installation

Pre-requisites

• For Windows
• For Linux

Install the package

You can install the package by running:

install.packages("pak")
pak::pak("esqLABS/esqlabsR@*release")

The latest development version of the package can also be installed with:

pak::pak("esqLABS/esqlabsR")

Note: For projects created for version 3 of esqlabsR package, refer to esqlabsRLegacy.

Usage

showtext::showtext_opts(dpi = 300)

You can start with the "Get Started" vignette: vignette("esqlabsR").

{esqlabsR} workflows require a specific project structure. You can initialize a new project by running:

esqlabsR::initProject()

This will create the required folder structure and files for your project in the working directory from where you run the command.

Below is a simple example of how to work with the package:

# load esqlabsR
library(esqlabsR)

# Load excel-based configuration
# The function `exampleProjectConfigurationPath()` returns the path to the example project
# configuration included in the package. Replace the variable `configurationPath`
# with the path to you project configuration file.
configurationPath <- exampleProjectConfigurationPath()

myProjectConfiguration <-
  createProjectConfiguration(configurationPath)

# Define which scenarios to run
scenarioNames <- c("TestScenario")
# Set scenario names to NULL if you want to simulate all scenarios defined in the
# excel file
# scenarioNames <- NULL

# Create `ScenarioConfiguration` objects from excel files
scenarioConfigurations <- readScenarioConfigurationFromExcel(
  scenarioNames = scenarioNames,
  projectConfiguration = myProjectConfiguration
)

# Define custom parameters for the scenarios. These parameter will be applied
# additionally to the paremetrization specified in the Excel files.
customParam <- list(
  paths = c(
    "Aciclovir|Lipophilicity"
  ),
  values = c(
    -0.1
  ),
  units = c(
    "Log Units"
  )
)

# Create simulation scenarios defined in the excel files and apply the custom parameters
myScenarios <- createScenarios(
  scenarioConfigurations = scenarioConfigurations,
  customParams = customParam
)

# Adjust simulation run options, if necessary.
# E.g. disable check for negative values if required
simulationRunOptions <- ospsuite::SimulationRunOptions$new()
simulationRunOptions$checkForNegativeValues <- FALSE

# Run simulations
simulatedScenariosResults <- runScenarios(
  scenarios = myScenarios,
  simulationRunOptions = simulationRunOptions
)

# Save results and store the path to the results for later re-use
outputFolder <- saveScenarioResults(simulatedScenariosResults, myProjectConfiguration)

# Load observed data using the default importer configuration provided with the package. Alternatively, you can load a custom data importer configuration.
dataSheets <- c("Laskin 1982.Group A")
observedData <- esqlabsR::loadObservedData(
  projectConfiguration = myProjectConfiguration,
  sheets = dataSheets
)

########## Create figures defined in the Plots.xlsx file########
plots <- createPlotsFromExcel(
  plotGridNames = c(
    "Aciclovir",
    "Aciclovir2"
  ),
  simulatedScenarios = simulatedScenariosResults,
  observedData = observedData,
  projectConfiguration = myProjectConfiguration,
  outputFolder = outputFolder,
  stopIfNotFound = TRUE
)

plots$Aciclovir

Learn More

You can find more information on specific topics in dedicated vignettes:

• Start with vignette("esqlabsR-workflow-overview") to learn about the esqlabsR's streamlined workflow.
• vignette("esqlabsR-project-structure") details the structure and purpose of each component file and directory of an esqlabsR project.
• vignette("esqlabsR-design-scenarios") explains how you can design your own simulations only using excel files.
• vignette("esqlabsR-run-simulations") describes all you need to know to run your customized simulations.
• vignette("esqlabsR-plot-results") explains how to generate visualizations from simulations.

Related Work

{esqlabsR} relies on the following Open Systems Pharmacology R packages:

• rSharp
• ospsuite.utils
• tlf
• ospsuite

Contributing

• Follow the OSPS-R coding standards.
• Our contribution guide can be found here.

Code of Conduct

Please note that the esqlabsR project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

esqLABS/esqlabsR documentation built on April 17, 2025, 10:51 a.m.