undid previous change

Author: certara-aonasanwo

.RData

@@ -1,6 +1,6 @@
 # Simcyp R package - forest plot example
 
-# This script will show you: 
+# This script will show you:
 # 1. How to run the Simcyp Simulator from R
 # 2. How to extract the necessary data for forest plots
 # 3. How to use those data to make a forest plot
@@ -28,8 +28,8 @@ setwd(path_user)
 # this to use the Simcyp package. We're based in the UK, so, USA folks, please
 # note the spelling here! :)
 Simcyp::Initialise(filePath = "C:/Program Files/Simcyp Simulator V24/Screens/SystemFiles",
-                   requestedVersion = 24, 
-                   species = SpeciesID$Human) 
+                   requestedVersion = 24,
+                   species = SpeciesID$Human)
 
 # If you've already run this script in the past -- maybe you're only interested
 # in tweaking the appearance of your forest plot, for example -- then you don't
@@ -39,58 +39,58 @@ Simcyp::Initialise(filePath = "C:/Program Files/Simcyp Simulator V24/Screens/Sys
 if(file.exists("SV-Atazanavir Forest Data.RData")){
    load("SV-Atazanavir Forest Data.RData")
 } else {
-   
+
    # We will run 5 DDI simulations and store their results; specifically, we
    # need the AUC and Cmax ratios for the forest plot.
-   
+
    # Get workspace names
    SimcypWksz <- list.files(pattern = "wksz")
-   
+
    # Creating lists to store data
    ForestData <- list()
    SimTime <- list() # This is optional; it just tracks how long each iteration takes.
-   
-   for (Wks in SimcypWksz){ 
-      
+
+   for (Wks in SimcypWksz){
+
       tic(msg = paste("Simulation", Wks))
-      
+
       # Setting what workspace to simulate
       SetWorkspace(Wks)
       # This will give you useful summary information on your simulation. Check
       # that you're simulating what you think you're simulating! :)
-      
+
       # Run the simulation and save to database. For saving our database files,
       # we'll use the same file name as the workspace but with the ".db" extension.
       DBfilename <- sub("wksz", "db", Wks)
       Simulate(database = DBfilename)
-      
+
       # Make a connection with the database file using RSQLite
       conn <- RSQLite::dbConnect(SQLite(), DBfilename)
-      
-      # Extract the population statistics of the predicted AUC and Cmax ratios 
+
+      # Extract the population statistics of the predicted AUC and Cmax ratios
       ForestData[[Wks]] <- GetForestData_DB(Alpha = 0.1,
                                             Upper = 95,
-                                            Lower = 5, 
-                                            conn, 
-                                            Last_Dose = TRUE, 
+                                            Lower = 5,
+                                            conn,
+                                            Last_Dose = TRUE,
                                             AUC_Type = "AUCt")
-      
+
       SimTime[[Wks]] <- toc(log = TRUE)
-      
+
       # Disconnect from the database
       RSQLite::dbDisconnect(conn)
-      
+
    }
-   
+
    # Putting all the forest data into a single data.frame
    ForestData <- bind_rows(ForestData)
-   
+
    # Check the times for each iteration
    map(SimTime, "toc")
-   
-   save(ForestData, SimTime, SimcypWksz, 
+
+   save(ForestData, SimTime, SimcypWksz,
         file = "SV-Atazanavir Forest Data.RData")
-   
+
 }
 
 # Setting up observed data ---------------------------------------------------
@@ -101,7 +101,7 @@ if(file.exists("SV-Atazanavir Forest Data.RData")){
 # those data are set up because we'll set up the observed data in the same way:
 glimpse(ForestData)
 
-# Columns we'll need to match in the observed data: 
+# Columns we'll need to match in the observed data:
 
 # File
 # We'll need to specify which simulation file should be matched to the observed
@@ -112,25 +112,25 @@ glimpse(ForestData)
 # In the forest data we extracted from those simulations, you'll see that we
 # have named the PK parameters either "AUCt_ratio" or "Cmax_ratio". We'll use
 # those exact same names for the PK parameters in the observed data so that the
-# forest_plot function knows which parameters match. 
+# forest_plot function knows which parameters match.
 
 # GeoMean
 # What we plan to graph are the geometric means and geometric confidence
 # intervals (this is the most typical set of statistics for forest plots), so
 # we'll need the matching data in the observed data.frame. We don't have
 # observed confidence interval data, though, so we'll skip those. If we had
-# them, they would be shown as error bars on the plot. 
+# them, they would be shown as error bars on the plot.
 
 # What if you don't have all the observed data? That's fine. Skip whatever you
-# don't have and that simulation just won't have any observed data points. 
+# don't have and that simulation just won't have any observed data points.
 
 ObsRatios <- data.frame(File = c("Neely_raltegravirDDI",
                                  "Zhu_2010_raltegravirDDI",
                                  "Krishna_raltegravirDDI",
                                  "Iwamoto_2008_raltegravirDDI",
-                                 "Mummaneni_Clarith_ATZ_DDI"), 
-                        PKparameter = c(rep("AUCt_ratio", 5), 
-                                        rep("Cmax_ratio", 5)), 
+                                 "Mummaneni_Clarith_ATZ_DDI"),
+                        PKparameter = c(rep("AUCt_ratio", 5),
+                                        rep("Cmax_ratio", 5)),
                         GeoMean = c(1.72, 1.54, 1.67, 1.72, 1.94, # AUC ratios
                                     1.37, 1.39, 1.16, 1.53, 1.50)) # Cmax ratios
 
@@ -141,7 +141,7 @@ ObsRatios <- data.frame(File = c("Neely_raltegravirDDI",
 ?PlotForestDDI
 
 # Let's make draft forest plot with mostly default parameters.
-PlotForestDDI(SimForestData = ForestData, 
+PlotForestDDI(SimForestData = ForestData,
               ObsForestData = ObsRatios)
 
 # As you can see, the y axis is labeled according to the simulation, which does
@@ -157,47 +157,47 @@ YAxisLabels<- c("Neely_raltegravirDDI" = "Raltegravir\nNeely et al. (2010)",
                 "Mummaneni_Clarith_ATZ_DDI" = "Clarithromycin\nMummaneni et al. (2002)")
 
 # And the revised forest plot with the nicer labels:
-PlotForestDDI(SimForestData = ForestData, 
+PlotForestDDI(SimForestData = ForestData,
               ObsForestData = ObsRatios,
               y_axis_column = YAxisLabels)
 
 # There are a number of ways that you can customize your forest plot, and we
 # hope you'll play around with the function a bit with assistance from the help
 # file. Here are a few more options for an example.
 
-PlotForestDDI(SimForestData = ForestData, 
+PlotForestDDI(SimForestData = ForestData,
               ObsForestData = ObsRatios,
-              y_axis_column = YAxisLabels, 
+              y_axis_column = YAxisLabels,
               Mean_type = "Geometric",
               Variability_type = "CI",
-              
+
               # You can change the set of colors to one of the sets already
               # included (see the help file) or specify your own colors. We'll
               # use one of the built-in sets.
               color_set = "yellow to red",
-              
+
               # By default, the PlotForestDDI function orders the simulations
               # from strongest inhibition at the top to strongest induction at
               # the bottom, but you can specify that you want the order to be as
-              # it is in the source data.frame instead. 
-              y_order = "as is", 
-              
+              # it is in the source data.frame instead.
+              y_order = "as is",
+
               x_axis_title = "Geometric Mean Ratio (90% CI)",
               x_axis_limits = c(1, 2),
               graph_title = "Predicted Geometric Mean AUC and Cmax Ratios for DDI studies",
               graph_title_size = 14 ,
-              legend_position = "right", 
-              
+              legend_position = "right",
+
               # We recommend playing around with the output graph dimensions to
               # make sure things are clear and not smooshed together.
-              fig_height = 7, 
+              fig_height = 7,
               fig_width = 8,
               save_graph = "Forest plot SV-Atazanavir.png")
 
 
 # Finishing up -----------------------------------------------------------------
 
-Uninitialise()   # Uninitialise the Simcyp engine 
+Uninitialise()   # Uninitialise the Simcyp engine
 
 
 

Forest plot/Simcyp R package - forest plot example.R

@@ -1,4 +1,5 @@
 Version: 1.0
+ProjectId: b023b08c-22e4-4945-8319-3bcf5c190afb
 
 RestoreWorkspace: Default
 SaveWorkspace: Default