pksummary_mult: Make a summary PK table for a report or slide deck - THIS...

In shirewoman2/Consultancy: Standardized tools for using R within the Simcyp Consultancy Team

Make a summary PK table for a report or slide deck - THIS FUNCTION HAS BEEN DEPRECATED IN FAVOR OF THE FUNCTION pk_table.

Description

Make a summary PK table for a report or slide deck - THIS FUNCTION HAS BEEN DEPRECATED IN FAVOR OF THE FUNCTION pk_table.

Usage

pksummary_mult(
  sim_data_files = NA,
  compoundsToExtract = "substrate",
  tissues = "plasma",
  PKparameters = NA,
  PKorder = "default",
  sheet_PKparameters = NA,
  observed_PK = NA,
  existing_exp_details = NA,
  mean_type = NA,
  use_median_for_tmax = TRUE,
  includeCV = TRUE,
  includeSD = FALSE,
  includeConfInt = TRUE,
  includeMedian = FALSE,
  includeRange = FALSE,
  includePerc = FALSE,
  includeTrialMeans = FALSE,
  concatVariability = FALSE,
  variability_format = "to",
  convert_conc_units = NA,
  include_dose_num = NA,
  add_header_for_DDI = TRUE,
  rounding = NA,
  prettify_columns = TRUE,
  extract_forest_data = FALSE,
  checkDataSource = TRUE,
  highlight_gmr_colors = NA,
  highlight_so_cutoffs = NA,
  highlight_so_colors = "yellow to red",
  save_table = NA,
  single_table = FALSE,
  page_orientation = "portrait",
  fontsize = 11,
  ...,
  adjust_conc_units = NA
)

Arguments

sim_data_files	a character vector of simulator output files, each in quotes and encapsulated with c(...), NA to extract PK data for all the Excel files in the current folder, or "recursive" to extract PK data for all the Excel files in the current folder and all subfolders. If you do want specific simulations, please take pity on your poor R coders and do not request PK parameters for the same simulation file names in different subfolders in the same function call; it's too confusing and we might give you incorrect results.
compoundsToExtract	For which compound(s) do you want to extract PK data? Options are any combination of the following: "substrate" (default), "primary metabolite 1", "primary metabolite 2", "secondary metabolite", "inhibitor 1" – this can be an inducer, inhibitor, activator, or suppresesor, but it's labeled as "Inhibitor 1" in the simulator, "inhibitor 2" for the 2nd inhibitor listed in the simulation, "inhibitor 1 metabolite" for the primary metabolite of inhibitor 1 "all" for all possible compounds present in the simulations To specify multiple compounds, enclose the compound IDs with parentheses, e.g., compoundsToExtract = c("substrate", "inhibitor 1")
tissues	For which tissue(s) would you like the PK parameters to be pulled? Options are any combination of "plasma" (default), "unbound plasma", "blood", "unbound blood", "peripheral plasma", or "peripheral blood". NOTE: PK for peripheral sampling is not as well tested as for other tissues and is only set up for V21+. Please check your results carefully.. For multiple tissues, enclose them with parentheses, e.g., tissues = c("blood", "plasma")
PKparameters	(optional) the PK parameters to include as a character vector. By default, if you have a single-dose simulation, the parameters will include AUC and Cmax for dose 1, and, if you have a multiple-dose simulation, AUC and Cmax for the last dose. Also by default, if you have a perpetrator present, the parameters will include the AUC and Cmax values with and without the perpetrator as well as those ratios. Alternatively, you can specify a vector of any combination of specific, individual parameters, e.g., c("Cmax_dose1", "AUCtau_last"). Be sure to encapsulate the parameters you want with c(...)! To see the full set of possible parameters to extract, enter view(PKParameterDefinitions) into the console. If you would like PK pulled from a specific custom interval, please supply a named character vector where the names are the PK parameters and the values are the tabs. Example: sheet_PKparameters = c("AUCinf_dose1" = NA, "AUCt" = "Int AUC userT(1)(Sub)(CPlasma)", "AUCtau_last" = NA) Please note that we would like the PK parameters that are for either dose 1 or the last dose to have NA listed for the tab. It is also ok to supply this named character vector to the argument sheet_PKparameters instead, but please do not supply it to both. If you supply observed data using either the argument report_input_file or the argument observed_PK and do not specify anything for PKparameters, the PK parameters will be those included for the observed data. Parameters that don't make sense for your scenario – such as asking for AUCinf_dose1_withInhib when your simulation did not include an inhibitor or perpetrator – will not be included. tmax will be listed as median, min, and max rather than mean, lower and higher confidence interval or percentiles. Similarly, if you request trial means, the values for tmax will be the range of medians for the trials rather than the range of means. An example of acceptable input here: PKparameters = c("AUCtau_last", "AUCtau_last_withInhib", "Cmax_last", "Cmax_last_withInhib", "AUCtau_ratio_last", "Cmax_ratio_last").
PKorder	Would you like the order of the PK parameters to be the order specified in the Consultancy Report Template (default), or would you like the order to match the order you specified with the argument PKparameters? Options are "default" or "user specified".
sheet_PKparameters	(optional) If you want the PK parameters to be pulled from a specific tab in the simulator output file, list that tab here. Otherwise, this should be left as NA. If you want some parameters from a custom-interval tab and others from the regular tabs, please supply a named character vector where the names are the PK parameters and the values are the tabs. Example: sheet_PKparameters = c("AUCinf_dose1" = NA, "AUCt" = "Int AUC userT(1)(Sub)(CPlasma)", "AUCtau_last" = NA) Please note that we would like the PK parameters that are for either dose 1 or the last dose to have NA listed for the tab. It is also ok to supply this named character vector to the argument PKparameters instead, but please do not supply it to both.
observed_PK	(optional) If you have a data.frame, a named numeric vector, or an Excel or csv file with observed PK parameters, supply the full file name in quotes or supply the unquoted name of the the data.frame or vector here, and the simulated-to-observed mean ratios will be calculated. If you supply an Excel file, R will be looking to read a tab named exactly "observed PK". The supplied data.frame or file must be set up in one of two possible ways: Columns for each of the PK parameters you would like to compare, and those column names must be among the PK parameter options listed in PKParameterDefinitions. If you would like the output table to include the observed data CV for any of the parameters, add "_CV" to the end of the parameter name, e.g., "AUCinf_dose1_CV". A column titled "PKparameter" and a column titled "Value". (It's fine if there are other columns as well.) All the items in the column "PKparameter" must be among the PK parameter options listed in PKParameterDefinitions. Additionally, if you have more than one set of PK parameters, you must include a column titled "File" that lists which simulator output file should be compared to that observed data. If there's only one set of PK parameters, you can omit the column "File" and the PK data will be compared to ALL the simulated files included in sim_data_files. Please see the "Example" section of this help file for examples of how to set this up. One last warning: It is extremely difficult to accommodate things code-wise when the same simulation file names appear in multiple subfolders. Please take pity on your poor R coders and do not request PK parameters for the same simulation file names in different subfolders in the same function call; it's too confusing and we might give you incorrect results.
existing_exp_details	If you have already run extractExpDetails_mult to get all the details from the "Input Sheet" (e.g., when you ran extractExpDetails you said exp_details = "Input Sheet" or exp_details = "all"), you can save some processing time by supplying that object here, unquoted. If left as NA, this function will run extractExpDetails behind the scenes to figure out some information about your experimental set up.
mean_type	What kind of means and CVs do you want listed in the output table? Options are "arithmetic" or "geometric" (default).
use_median_for_tmax	TRUE (default) or FALSE for whether to use median for tmax values, regardless of what the other summary statistics are. This is typically the case, but, if you've got client data where they actually gave you tmax using the same summary statistic as the other PK parameters (like geometric mean, for example), then set this to FALSE and whatever mean type you specified with the argument mean_type will also be used for tmax.
includeCV	TRUE (default) or FALSE for whether to include rows for CV in the table
includeSD	TRUE or FALSE (default) for whether to include rows for the standard deviation in the table
includeConfInt	TRUE (default) or FALSE for whether to include whatever confidence intervals were included in the simulator output file. Note that the confidence intervals are geometric since that's what the simulator outputs (see an AUC tab and the summary statistics; these values are the ones for, e.g., "90% confidence interval around the geometric mean(lower limit)").
includeMedian	TRUE or FALSE (default) for whether to include rows for the median in the table
includeRange	TRUE or FALSE (default) for whether to include the minimum and maximum values
includePerc	TRUE or FALSE (default) for whether to include 5th to 95th percentiles
includeTrialMeans	TRUE or FALSE (default) for whether to include the range of trial means for a given parameter. Note: This is calculated from individual values rather than being pulled directly from the output.
concatVariability	TRUE or FALSE (default) for whether to concatenate the variability. If "TRUE", the output will be formatted into a single row and listed as the lower confidence interval or percentile to the upper CI or percentile, e.g., "2400 to 2700". Please note that the current SimcypConsultancy template lists one row for each of the upper and lower values, so this should be set to FALSE for official reports.
variability_format	formatting used to indicate the variability When the variability is concatenated. Options are "to" (default) to get output like "X to Y", "hyphen" to get output like "X - Y", "brackets" to get output like "[X, Y]", or "parentheses" for the eponymous symbol if you're an American and a bracket if you're British, e.g., "(X, Y)". (Sorry for the ambiguity; this was written by an American who didn't originally realize that there was another name for parentheses.)
convert_conc_units	Would you like to convert the units to something other than what was used in the simulation? Default is NA to leave the units as is, but if you set the concentration units to something else, this will attempt to convert the units to match that. This only adjusts only the simulated values, since we're assuming that that's the most likely problem and that observed units are relatively easy to fix, and it also only affects AUC and Cmax values. Acceptable input is any concentration unit listed in the Excel form for PE data entry, e.g. convert_conc_units = "ng/mL" or convert_conc_units = "uM". Molar concentrations will be automatically converted using the molecular weight of whatever you set for compoundToExtract.
include_dose_num	NA (default), TRUE, or FALSE on whether to include the dose number when listing the PK parameter. By default, the parameter will be labeled, e.g., "Dose 1 Cmax ratio" or "Last dose AUCtau ratio", if you have PK data for both the first dose and the last dose. Also by default, if you have data only for the first dose or only for the last dose, the dose number will be omitted and it will be labeled, e.g., "AUCtau ratio" or "Cmax ratio". Set this to TRUE or FALSE as desired to override the default behavior and get exactly what you want.
add_header_for_DDI	TRUE (default) or FALSE for whether to add an extra header row to the top of your table denoting when the PK are for baseline, with a perpetrator, or are the geometric mean ratios.
rounding	option for what rounding to perform, if any. Options are: NA or "Consultancy" All output will be rounded according to Simcyp Consultancy Team standards: to three significant figures when the value is < 100 or to the ones place if the value is >= 100. Please see the function round_consultancy, which does the rounding here. "none" No rounding will be performed. "significant X" where "X" is a number Output will be rounded to X significant figures. "signif X" also works fine. "round X" where "X" is a number Output will be rounded to X digits "Word only" Output saved to Word or a csv file will be rounded using the function round_consultancy, but nothing will be rounded in the output R object. This can be useful when you want to have nicely rounded and formatted output in a Word file but you also want to use the results from pksummary_mult to make forest plots, which requires numbers that are not rounded.
prettify_columns	TRUE (default) or FALSE for whether to make easily human-readable column names. TRUE makes pretty column names such as "AUCinf (h*ng/mL)" whereas FALSE leaves the column with the R-friendly name from extractPK, e.g., "AUCinf_dose1".
extract_forest_data	TRUE or FALSE (default) to get forest-plot data at the same time. This only applies when the compound to extract is the substrate or a substrate metabolite. If set to TRUE, this will return a list that includes data formatted for use with the function forest_plot. Since the forest_plot function only works with simulations with perpetrators (at least, for now), this will only work for simulations that included a perpetrator.
checkDataSource	TRUE (default) or FALSE for whether to include in the output a data.frame that lists exactly where the data were pulled from the simulator output file. Useful for QCing.
highlight_gmr_colors	optionally specify a set of colors to use for highlighting geometric mean ratios for DDIs. Options are "yellow to red", "green to red" or a vector of 4 colors of your choosing. If left as NA, no highlighting for GMR level will be done.
highlight_so_cutoffs	optionally specify cutoffs for highlighting any simulated-to-observed ratios. Anything that is above those values or below the inverse of those values will be highlighted. To figure out what cells to highlight, this looks for a column titled "Statistic" or "Stat", then looks for what row contains "S/O" or "simulated (something something) observed" (as in, we'll use some wildcards to try to match your specific text). Next, it looks for any values in that same row that are above those cutoffs. This overrides anything else you specified for highlighting. The default is NA, for not highlighting based on S/O value. Acceptable input for, say, highlighting values that are > 125% or < 80% of the observed and also, with a second color, values that are > 150% or < 66% would be: highlight_so_cutoffs = c(1.25, 1.5). If you would like the middle range of values to be highlighted, include 1 in your cutoffs. For example, say you would like everything that's < 80% or > 125% to be highlighted red but you'd like the "good" values from 80% to 125% to be green, you can get that by specifying highlight_so_cutoffs = c(1, 1.25) and highlight_so_colors = c("green", "red"). This only applies when you save the table as a Word file.
highlight_so_colors	optionally specify a set of colors to use in the Word file output for highlighting S/O values outside the limits you specified with highlight_so_cutoffs. Options: "yellow to red" (default) A range of light yellow to light orange to light red. If you have included 1 in your cutoffs and you leave highlight_so_colors with the default setting, values in the middle, "good" range of S/O values will be highlighted a light green. "traffic" light green, yellow, and red designed to display values outside 1.25, 1.5, and 2 fold of unity, respectively. If you include 1 in highlight_so_cutoffs, you'll get a darker green for "good" S/O values. This color scheme was borrowed from Lisa, so if you've seen her slides, these will look familiar. a character vector of specific colors Any R-acceptable colors, will work here, e.g., highlight_so_colors = c("yellow", "orange", "red") If you do specify your own bespoke colors, you'll need to make sure that you supply one color for every value in highlight_so_cutoffs.
save_table	optionally save the output table and, if requested, the QC info, by supplying a file name in quotes here, e.g., "My nicely formatted table.docx" or "My table.csv", depending on whether you'd prefer to have the table saved as a Word or csv file. Do not include any slashes, dollar signs, or periods in the file name. (You can also save the table to a Word file later with the function formatTable_Simcyp.) If you supply only the file extension, e.g., save_table = "docx", the name of the file will be "PK summary table" with that extension. If you supply something other than just "docx" or just "csv" for the file name but you leave off the file extension, we'll assume you want it to be ".csv". All PK info will be included in a single Word or csv file, and, if checkDataSource = TRUE, that will be saved in a single csv file.
single_table	TRUE (default) or FALSE for whether to save all the PK data in a single table or break the data up by tissue, compound ID, and file into multiple tables. This only applies to the Word output.
page_orientation	set the page orientation for the Word file output to "portrait" (default) or "landscape"
fontsize	the numeric font size for Word output. Default is 11 point. This only applies when you save the table as a Word file.
...

Value

Returns a data.frame with summary PK parameters from multiple simulator output files

Examples

# Create PK summary tables for all the Simulator output files
# in your working directory with the default PK parameters
pksummary_mult(sim_data_files = NA)

# Include a data.frame of observed data for S/O comparisons
pksummary_mult(
    sim_data_files = NA,
    observed_PK = data.frame(File = c("mdz-5mg-qd-keto-400mg-qd.xlsx",
                                      "mdz-5mg-qd-rif-600mg-qd.xlsx"),
                             AUCtau_last = c(55, 55),
                             Cmax_last = c(20, 20),
                             AUCtau_last_withInhib = c(800, 20),
                             Cmax_last_withInhib = c(100, 5)))

shirewoman2/Consultancy documentation built on Feb. 18, 2025, 10 p.m.