Execute a PopSim Run

This RMarkdown file executes an existing PopSim Run. The script utilizes the gastroPlusAPI package to communicate with the GastroPlus X 10.2 service.

To customize your study with this script for a different simulation / project / variables, please make changes to the “Set Input Information” section.

Configure required packages

Load other necessary packages required to execute the script
Load gastroPlusAPI package

R

library(tidyverse)
library(gastroPlusAPI)
library(gastroPlusRModuLens)

Set working directory

Set working directory as the current source editor context

R

if (rstudioapi::isAvailable()){
  current_working_directory <- dirname(rstudioapi::getSourceEditorContext()$path)
  setwd(current_working_directory)
}

Start GPX Service

Establishes a connection to the GastroPlus service, which allows R to communicate with GastroPlus through its API

R

gpx_service <- start_service(verbose=FALSE)

CODE

✔ Configured the GastroPlus Service

R

gpx_service$is_alive()

CODE

[1] TRUE

Set Input Information

Make modification to the variables in this chunk to customize your analysis.

project_path = Location of the project with the Population Simulation run popsim_run_name = Name of the Population Simulation run to be executed compound_name = Name of the Compound in the Simulation

R

project_path = "../../ProjectFiles/Valproate-VBE.gpproject"
popsim_run_name = "popsim_2_trial_100_pop"
compound_name = "Valproate"

Execute the run

Checks if the specified run exists in the project and executes it

R

open_project(project_path)

#available runs
get_runs()

CODE

# A tibble: 4 × 1
  run_name                           
  <chr>                              
1 Exploratory Simulation             
2 popsim_2_trial_100_pop             
3 vbe_slow_vs_slightly_slow          
4 vbe_replicate_slow_vs_slightly_slow

R

#execute the run
execute_run(popsim_run_name)

Process Run Output

Get summary output for all iterations in the run

R

#Get summary output table for all simulations in the run
summary_output <- get_summary_output_tidy(popsim_run_name)
#Review available simulations in the PopSim run
get_simulations_in_run(popsim_run_name)

CODE

[[1]]
[1] "500mg-ER Slow"

R

#Get concentration plasma for all the iterations in the run

plasma_concentration_series_descriptor <- build_series_descriptors(compound_name, c(CompartmentType$SystemicCirculation, StateType$ConcentrationPlasma))

#Get concentration plasma data for all the iterations within the popsim run
series_data <- get_series_data_run(run_name= popsim_run_name, series_descriptor= plasma_concentration_series_descriptor)

glimpse(series_data)

CODE

Rows: 28,326
Columns: 11
$ run_name                        <chr> "popsim_2_trial_100_pop", "popsim_2_tr…
$ simulation_name                 <chr> "500mg-ER Slow", "500mg-ER Slow", "500…
$ series_name                     <chr> "Valproate - Systemic Circulation - Co…
$ dependent_unit                  <chr> "ng/mL", "ng/mL", "ng/mL", "ng/mL", "n…
$ independent_unit                <chr> "h", "h", "h", "h", "h", "h", "h", "h"…
$ iteration                       <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
$ dependent                       <dbl> 0.000000e+00, 1.594398e-16, 3.545188e-…
$ independent                     <dbl> 0.000000e+00, 1.211665e-05, 6.298034e-…
$ simulation_iteration_key_name   <chr> "500mg-ER Slow \a1 \a1", "500mg-ER Slo…
$ simulation_iteration_key_name_2 <chr> "500mg-ER Slow | Trial 1", "500mg-ER S…
$ trial                           <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…

R

#plot with group as a stratifier using modulens

Kill GPX Service

R

gpx_service$kill()

CODE

[1] TRUE