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Performs NCA calculations and population PK model diagnosis.

Source: R/ncappc.R
ncappc.Rd

ncappc is a flexible tool, to

  1. perform a traditional NCA

  2. perform simulation-based posterior predictive checks for a population PK model using NCA metrics.

Usage

ncappc(
  obsFile = "nca_original.npctab.dta",
  simFile = "nca_simulation.1.npctab.dta.zip",
  str1Nm = NULL,
  str1 = NULL,
  str2Nm = NULL,
  str2 = NULL,
  str3Nm = NULL,
  str3 = NULL,
  concUnit = NULL,
  timeUnit = NULL,
  doseUnit = NULL,
  obsLog = FALSE,
  simLog = obsLog,
  psnOut = TRUE,
  idNmObs = "ID",
  timeNmObs = "TIME",
  concNmObs = "DV",
  idNmSim = idNmObs,
  timeNmSim = timeNmObs,
  concNmSim = concNmObs,
  onlyNCA = FALSE,
  AUCTimeRange = NULL,
  backExtrp = FALSE,
  LambdaTimeRange = NULL,
  LambdaExclude = NULL,
  doseAmtNm = NULL,
  adminType = "extravascular",
  doseType = "ns",
  doseTime = NULL,
  Tau = NULL,
  TI = NULL,
  method = "linearup-logdown",
  blqNm = NULL,
  blqExcl = 1,
  evid = TRUE,
  evidIncl = 0,
  mdv = FALSE,
  filterNm = NULL,
  filterExcl = NULL,
  negConcExcl = FALSE,
  param = c("AUClast", "Cmax"),
  timeFormat = "number",
  dateColNm = NULL,
  dateFormat = NULL,
  spread = "npi",
  tabCol = c("AUClast", "Cmax", "Tmax", "AUCINF_obs", "Vz_obs", "Cl_obs", "HL_Lambda_z"),
  figFormat = "tiff",
  noPlot = FALSE,
  printOut = TRUE,
  studyName = NULL,
  new_data_method = TRUE,
  overwrite_SIMDATA = NULL,
  overwrite_sim_est_file = NULL,
  outFileNm = NULL,
  out_format = "html",
  gg_theme = theme_bw(),
  parallel = FALSE,
  extrapolate = FALSE,
  timing = FALSE,
  ...
)

Arguments

obsFile

Observed concentration-time data from an internal data frame or an external table with comma, tab or space as separators.

simFile

NONMEM simulation output with the simulated concentration-time data from an internal data frame or an external table. NULL produces just the NCA output, a filename or data frame produces the NCA output as well as the PopPK diagnosis. If new_data_method=TRUE then this can be a compressed file as well.

str1Nm

Column name for 1st level population stratifier. Default is NULL

str1

Stratification ID of the members within 1st level stratification (e.g c(1,2)). Default is NULL

str2Nm

Column name for 2nd level population stratifier. Default is NULL

str2

Stratification ID of the members within 2nd level stratification (e.g c(1,2)). Default is NULL

str3Nm

Column name for 3rd level population stratifier. Default is NULL

str3

Stratification ID of the members within 3rd level stratification (e.g c(1,2)). Default is NULL

concUnit

Unit of concentration (e.g. "ng/mL"). Default is NULL

timeUnit

Unit of time (e.g. "h"). Default is NULL

doseUnit

Unit of dose amount (e.g. "ng"). Default is NULL

obsLog

If TRUE concentration in observed data is in logarithmic scale. Default is FALSE

simLog

If TRUE concentration in simulated data is in logarithmic scale. Default is FALSE

psnOut

If TRUE observed data is an output from PsN or in NONMEM output format. Default is TRUE

idNmObs

Column name for ID in observed data. Default is "ID"

timeNmObs

Column name for time in observed data. Default is "TIME"

concNmObs

Column name for concentration in observed data. Default is "DV"

idNmSim

Column name for ID in simulated data. Default is "ID"

timeNmSim

Column name for time in simulated data. Default is "TIME"

concNmSim

Column name for concentration in simulated data. Default is "DV"

onlyNCA

If TRUE only NCA is performed and ppc part is ignored although simFile is not NULL. Default is FALSE

AUCTimeRange

User-defined window of time used to estimate AUC. Default is NULL

backExtrp

If TRUE back-extrapolation is performed while estimating AUC. Default is FALSE

LambdaTimeRange

User-defined window of time to estimate elimination rate-constant. This argument lets the user to choose a specific window of time to be used to estimate the elimination rate constant (Lambda) in the elimination phase. The accepted format for the input to this argument is a numeric array of two elements; c(14,24) will estimate the Lambda using the data within the time units 14 to 24. Default is NULL

LambdaExclude

User-defined excluded observation time points for estimation of Lambda. This can be numeric value or logical condition (e.g. c(1, 2, "<20", ">=100", "!=100")). Default is NULL

doseAmtNm

Column name to specify dose amount. Default is NULL

adminType

Route of administration. Allowed options are iv-bolus, iv-infusion or extravascular. Default is "extravascular"

doseType

Steady-state (ss) or non-steady-state (ns) dose. Default is "ns"

doseTime

Dose time prior to the first observation for steady-state data. Default is NULL

Tau

Dosing interval for steady-state data. Default is NULL

TI

Infusion duration. If TI is a single numeric value, TI is the same for all individuals. If TI is the name of a column with numeric data present in the data set, TI is set to the unique value of the column for a given individual. Default is NULL

method

Method to estimate AUC. linear method applies the linear trapezoidal rule to estimate the area under the curve. log method applies the logarithmic trapezoidal rule to estimate the area under the curve. linearup-logdown method applies the linear trapezoidal rule to estimate the area under the curve for the ascending part of the curve and the logarithmic trapezoidal rule to estimate the area under the curve for the descending part of the curve. Default is "linearup-logdown"

blqNm

Name of BLQ column if used to exclude data. Default is NULL

blqExcl

Excluded BLQ value; either a numeric value or a logical condition (e.g. 1 or ">=1" or c(1,">3")). Used only if the blqNm is not NULL. Default is "1"

evid

If TRUE EVID is used to filter data. Default is TRUE

evidIncl

Included values in EVID. Default is "0"

mdv

If TRUE MDV is used to include data when MDV=0. Default is FALSE

filterNm

Column name to filter data. Default is NULL

filterExcl

Row exclusion criteria based on the column defined by filterNm. This can be numeric value or logical condition (e.g. c(1, 2, "<20", ">=100", "!=100")). Default is NULL

negConcExcl

If TRUE negative concentrations are excluded. Default is FALSE

param

NCA parameters (AUClast, AUClower_upper, AUCINF_obs, AUCINF_pred, AUMClast, Cmax, Tmax, HL_Lambda_z). Default is (c"AUClast", "Cmax")

timeFormat

time format (number, H:M, H:M:S). Default is "number"

dateColNm

column name for date if used (e.g. "Date", "DATE"). Default is NULL

dateFormat

date format (D-M-Y, D/M/Y or any other combination of D,M,Y). Default is NULL

spread

Measure of the spread of simulated data ("ppi" (95% parametric prediction interval) or "npi" (95% nonparametric prediction interval)). Default is "npi"

tabCol

Output columns to be printed in the report in addition to ID, dose and population strata information (list of NCA metrics in a string array). Default is c("AUClast", "Cmax", "Tmax", "AUCINF_obs", "Vz_obs", "Cl_obs", "HL_Lambda_z")

figFormat

format of the produced figures (bmp, jpeg, tiff, png). Default is "tiff"

noPlot

If TRUE only NCA calculations are performed without any plot generation. Default is FALSE

printOut

If TRUE tabular and graphical outputs are saved on the disk. Default is TRUE

studyName

Name of the study to be added as a description in the report. Default is NULL

new_data_method

If TRUE a faster method of reading data is tested. Default is TRUE

overwrite_SIMDATA

If TRUE new information is created in the SIMDATA directory. If FALSE the information in the SIMDATA directory is used. If NULL a dialog will come up to ask the user what to do. Default is NULL

overwrite_sim_est_file

If TRUE The NCA metrics are created again based on the simulation data. If FALSE the information in the ncaSimEst file is used. If NULL a dialog will come up to ask the user what to do. Default is NULL

outFileNm

Additional tag to the name of the output html and pdf output file hyphenated to the standard ncappc report file name standard ncappc report file name. Default is NULL

out_format

What type of output format should the NCA report have? Pass "all" to render all formats defined within the rmarkdown file. Pass "first" to render the first format defined within the rmarkdown file. Pass "html" to render in HTML. Pass "pdf" to render in PDF.

gg_theme

Which ggplot theme should be used for the plots?

parallel

Should the nca computations for the simulated data be run in parallel? See start_parallel for a description and additional arguments that can be added to this function and passed to start_parallel.

extrapolate

Should the NCA calculations extrapolate from the last observation to infinity?

timing

Should timings of calculations be reported to the screen?

...

Additional arguments passed to other functions, including start_parallel.

Value

NCA results and diagnostic test results

Details

Non-compartmental analysis (NCA) calculates pharmacokinetic (PK) metrics related to the systemic exposure to a drug following administration, e.g. area under the concentration-time curve and peak concentration. ncappc performs a traditional NCA using the observed plasma concentration-time data. In the presence of simulated plasma concentration-time data, ncappc also performs simulation-based posterior predictive checks (ppc) using NCA metrics for the corresponding population PK (PopPK) model used to generate the simulated data. The diagnostic analysis is performed at the population as well as the individual level. The distribution of the simulated population means of each NCA metric is compared with the corresponding observed population mean. The individual level comparison is performed based on the deviation of the mean of any NCA metric based on simulations for an individual from the corresponding NCA metric obtained from the observed data. Additionally, ncappc reports the normalized prediction distribution error (NPDE) of the simulated NCA metrics for each individual and their distribution within a population. ncappc produces two default outputs depending on the type of analysis performed, i.e., traditional NCA and PopPK diagnosis. The PopPK diagnosis feature of ncappc produces 7 sets of graphical outputs to assess the ability of a population model to simulate the concentration-time profile of a drug and thereby identify model misspecification. In addition, tabular outputs are generated showing the values of the NCA metrics estimated from the observed and the simulated data, along with the deviation, NPDE, regression parameters used to estimate the elimination rate constant and the related population statistics. The default values of the arguments used in ncappc are shown in the Usage section of this document and/or in bold in the Arguments section.

Examples

out <- ncappc(obsFile=system.file("extdata","pkdata.csv",package="ncappc"), 
  onlyNCA = TRUE,
  extrapolate = TRUE,
  printOut = FALSE,
  evid = FALSE,
  psnOut=FALSE)
  

data_1 <- data.frame(
  ID=1,
  TIME = c(0,0.25,0.5,1,1.5,2,3,4,6,8,12,16,24),
  DV=c(0, 0.07, 0.14, 0.21, 0.24, 0.27, 0.26, 0.25, 0.22, 0.19, 0.13, 0.081, 0.033)
)
out_1 <- ncappc(obsFile=data_1,
                onlyNCA = TRUE,
                extrapolate = TRUE,
                printOut = FALSE,
                evid = FALSE,
                timing=TRUE)
#> Time taken to estimate NCA parameters on observed data: 0.025 seconds.


data_2 <- dplyr::filter(data_1,TIME>17|TIME<3)
out_2 <- ncappc(obsFile=data_2,
                onlyNCA = TRUE,
                extrapolate = TRUE,
                printOut = FALSE,
                evid = FALSE,
                force_extrapolate=TRUE)