Introduction

NonCompart R package (Bae 2018; Kim et al. 2018) can conduct a noncompartmental analysis as similar as possible to the most widely used commercial software for pharmacokinetic analysis, i.e. Phoenix^® WinNonlin^® (Certara USA 2018). This document provides validation of noncompartmental analysis performed by NonCompart R package version 0.4.4 as compared to the results from the commercial software, WinNonlin^® version 6.3 and 7.0.

Results

A function, Equal() will return TRUE if there is no difference between results from NonCompart and WinNonlin.

# install.packages("NonCompart", repos="http://r.acr.kr")
library(NonCompart)
RptCfg = read.csv("RptCfg.csv", as.is=TRUE)

Equal = function(Wres, Rres, Tol=0.001)
{
  Wres[,"ID"] = as.character(Wres[,"Subject"])
  ColName0 = colnames(Rres)
  rownames(RptCfg) = RptCfg[,"PPTESTCD"]
  colnames(Rres) = c(ColName0[1], RptCfg[ColName0[-1],"WNL"])
  Inter = intersect(colnames(Wres), colnames(Rres))
  
  IsSame = TRUE
  for (i in 1:nrow(Wres)) {
    for (j in Inter) {
      R = as.numeric(Rres[i,j])
      W = as.numeric(Wres[i,j])
      if (W != 0) {
        if(abs((R - W)/W) > Tol) {
          print(Wres[i,j])
          print(Rres[i,j])
          IsSame = FALSE
        }
      }
    }
  }
  return(IsSame)
}

Eight comparison tests were performed using Theoph and Indometh default datasets. (Table 1) Detailed side-by-side comparison is in Appendix A.

Table 1: Description of settings for the noncompartmental analysis performed in WinNonlin and links to the raw data

Theoph[,"Subject"] = as.numeric(as.character(Theoph[,"Subject"]))
Indometh[,"Subject"] = as.numeric(as.character(Indometh[,"Subject"]))

Wres1 = read.csv("Final_Parameters_Pivoted_Theoph_Linear.csv")
Rres1 = tblNCA(Theoph, "Subject", "Time", "conc", dose=320, concUnit="mg/L")
Equal(Wres1, Rres1)

## [1] TRUE

Wres2 = read.csv("Final_Parameters_Pivoted_Theoph_Log.csv")
Rres2 = tblNCA(Theoph, "Subject", "Time", "conc", dose=320, down="Log", 
               concUnit="mg/L")
Equal(Wres2, Rres2)

## [1] TRUE

Wres3 = read.csv("Final_Parameters_Pivoted_Indometh_Linear.csv")
Rres3 = tblNCA(Indometh, "Subject", "time", "conc", dose=25, adm="Bolus", 
               concUnit="mg/L", R2ADJ=0.8)
Equal(Wres3, Rres3)

## [1] TRUE

Wres4 = read.csv("Final_Parameters_Pivoted_Indometh_Log.csv")
Rres4 = tblNCA(Indometh, "Subject", "time", "conc", dose=25, adm="Bolus", 
               down="Log", concUnit="mg/L", R2ADJ=0.8)
Equal(Wres4, Rres4)

## [1] TRUE

Wres5 = read.csv("Final_Parameters_Pivoted_Indometh_Linear_Infusion.csv")
Rres5 = tblNCA(Indometh, "Subject", "time", "conc", dose=25, adm="Infusion", 
               dur=0.25, concUnit="mg/L", R2ADJ=0.8)
Equal(Wres5, Rres5)

## [1] TRUE

Wres6 = read.csv("Final_Parameters_Pivoted_Indometh_Log_Infusion.csv")
Rres6 = tblNCA(Indometh, "Subject", "time", "conc", dose=25, adm="Infusion", 
               dur=0.25, down="Log", concUnit="mg/L", R2ADJ=0.8)
Equal(Wres6, Rres6)

## [1] TRUE

Wres7 = read.csv("Final_Parameters_Pivoted_Indometh_Linear_Wrong_Extravascular.csv")
Rres7 = tblNCA(Indometh, "Subject", "time", "conc", dose=25, concUnit="mg/L", 
               R2ADJ=0.8)
Equal(Wres7, Rres7)

## [1] TRUE

Wres8 = read.csv("Final_Parameters_Pivoted_Indometh_Log_Wrong_Extravascular.csv")
Rres8 = tblNCA(Indometh, "Subject", "time", "conc", dose=25, down="Log", 
               concUnit="mg/L", R2ADJ=0.8)
Equal(Wres8, Rres8)

## [1] TRUE

Conclusion

There is no discrepancy between results from NonCompart and WinNonlin. We also performed multiple analyses with the real clinical trial datasets and have found no differences (data not shown: confidential). Noncompartmental analysis performed by the open-source R package, NonCompart can be qualified and validated enough to acquire the identical results of the commercial software, WinNonlin.

Please report issues regarding validation of the R package to https://github.com/asancpt/NonCompart-tests/issues.

Affiliation:
Sungpil Han
M.D/Ph.D, Resident
Department of Clinical Pharmacology and Therapeutics,
Asan Medical Center, University of Ulsan,
Seoul 05505, Republic of Korea
E-mail: shan@acp.kr
URL: www.github.com/shanmdphd

Side-by-side comparison of results

library(dplyr)
library(tidyr)

table_wres_rres <- function(wres, rres, Caption){
  wres %>% 
    gather(WNL, WinNonlin, -Subject) %>% 
    left_join(RptCfg %>% select(PPTESTCD, WNL), by = "WNL") %>% 
    left_join(rres %>% as.data.frame() %>% gather(PPTESTCD, NonCompart, -Subject),
              by = c("Subject", "PPTESTCD")) %>% 
    select(Subject, PPTESTCD, WNL, NonCompart, WinNonlin) %>% 
    mutate(NonCompart = as.numeric(NonCompart),
           WinNonlin = as.numeric(WinNonlin)) %>% 
    mutate(Difference = ifelse((NonCompart - WinNonlin) / WinNonlin < 0.001, 
                               yes = 0, no = 'Larger than tol.')) %>% 
    mutate(Difference = ifelse(is.na(Difference), 0, Difference)) %>% 
    filter(!is.na(WinNonlin) & !is.na(NonCompart)) %>% 
    knitr::kable(longtable = TRUE, booktabs = TRUE, # format = "latex", 
                 caption = Caption) %>% 
    add_header_above(c(" ", "Pharmacokinetic Parameters" = 2, "Values" = 2, " ")) %>% 
    kable_styling(latex_options = c("repeat_header"))
}

table_wres_rres(Wres1, Rres1, 
                Caption = 'Theoph (n=12), Linear, Extravascular')

table_wres_rres(Wres2, Rres2,
                Caption = 'Theoph (n=12), Log, Extravascular')

table_wres_rres(Wres3, Rres3,
                Caption = 'Indometh (n=6), Linear, IV Bolus')

table_wres_rres(Wres4, Rres4,
                Caption = 'Indometh (n=6), Log, IV Bolus')