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Kim, Han, Cho, Yoon, and Bae: Development of R packages: ‘NonCompart’ and ‘ncar’ for noncompartmental analysis (NCA)
Original Article

Translational and Clinical Pharmacology 2018; 26(1): 10-15.

Published online: 16 March 2018

DOI: https://doi.org/10.12793/tcp.2018.26.1.10

Development of R packages: ‘NonCompart’ and ‘ncar’ for noncompartmental analysis (NCA)

Hyungsub Kim, Sungpil Han, Yong-Soon Cho, Seok-Kyu Yoon, Kyun-Seop Bae

Department of Clinical Pharmacology and Therapeutics, Asan Medical Center, University of Ulsan, Seoul 05505, Republic of Korea.

Correspondence: K. S. Bae; Tel: +82-2-3010-4611, Fax: +82-2-3010-4623, ksbae@amc.seoul.kr

Received 2 January 2018       Revised 2 March 2018       Accepted 2 March 2018

Copyright © 2018 Translational and Clinical Pharmacology

Translational and Clinical Pharmacology

(open-access, http://creativecommons.org/licenses/by-nc/3.0/):

It is identical to the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/).

Abstract

Noncompartmental analysis (NCA) is a primary analytical approach for pharmacokinetic studies, and its parameters act as decision criteria in bioequivalent studies. Currently, NCA is usually carried out by commercial softwares such as WinNonlin®. In this article, we introduce our newly-developed two R packages, NonCompart (NonCompartmental analysis for pharmacokinetic data) and ncar (NonCompartmental Analysis for pharmacokinetic Report), which can perform NCA and produce complete NCA reports in both pdf and rtf formats. These packages are compatible with CDISC (Clinical Data Interchange Standards Consortium) standard as well. We demonstrate how the results of WinNonlin® are reproduced and how NCA reports can be obtained. With these R packages, we aimed to help researchers carry out NCA and utilize the output for early stages of drug development process. These R packages are freely available for download from the CRAN repository.

Keywords: NonCompart, ncar, R, noncompartmental analysis (NCA)

Introduction

The aim of pharmacokinetic (PK) studies is to examine the kinetics of a drug with regard to absorption, distribution, metabolism and elimination in the body. PK data analysis consists of noncompartmental analysis (NCA) and nonlinear regression analysis.[12] NCA uses the trapezoidal rule for measurement of area under the concentration-time curve (AUC), and requires fewer assumptions than model-based analysis.[2] NCA allows for estimation of various PK parameters such as AUC, peak observed drug concentration (Cmax), time of peak concentration (Tmax), and elimination half-life. Particularly, AUC and Cmax are often accepted as the criteria for approval of bioequivalent drugs.
R, a widely-used computer language, is a suite of libraries of statistical and mathematical computations.[3] Despite its relatively small base system compared with other commercial softwares for NCA such as WinNonlin®[4] and Kinetica,[5] R has robust functions for scientific computation and numerous add-in packages for use in various fields.[6] Therefore, many efforts are being made to replace commercial softwares with R packages.
In this article, we introduce two newly-developed R packages, NonCompart and ncar, that are compatible with SDTM (Study Data Tabulation Model)-formatted dataset of CDISC (Clinical Data Interchange Standards Consortium), which is the standard of documentation submitted to regulatory authorities,[7] while providing a practical method for producing complete NCA reports.

Methods

R packages (NonCompart and ncar)

Two R packages (NonCompart and ncar) for NCA were developed in the open-source R programming language in order to allow free public use. R packages can be installed and loaded using the following scripts.
R code
install.packages(c("NonCompart","ncar"))
library(NonCompart)
library(ncar)
Detailed documentation and examples for each package can be found on the online user manual in the CRAN repository (http://cran.r-project.org/web/packages/NonCompart/index.html, http://cran.r-project.org/web/packages/ncar/index.html) or directly within the R console by entering ?function (e.g.?NonCompart,?ncar). These two packages are implemented in R and can accept a set of input arguments that allow for generation of NCA output. The names of most NCA metrics estimated by the function of these packages are consistent with those used in WinNonlin® (Table 1).

Software

WinNonlin® (Pharsight, Mountain View, CA, USA)[4] in Microsoft-Windows 7 (64 bit) was used for the computation. R 3.4.2 in Microsoft-Windows 7 (64 bit) was used for the comparison of calculated values.

Dataset

To compare the outputs generated by R packages and WinNonlin®, we used Theoph dataset obtained from the R software. The Theoph dataset has 132 observations from 12 subjects. A portion of the Theoph dataset (subject ID = 8) is shown in Table 2.

Results

NonCompart package: performance of NCA

This package conducts NCA as similarly as possible to the most widely used commercial PK analysis software. The NonCompart package has two main functions, tblNCA and sNCA, for use in multiple subjects and one subject, respectively. Figure 1 shows an example of output by tblNCA. The input data for tblNCA( ) should be in a long format as exemplified by the Theoph dataset.
It is possible to input several keys such as subject demographics and information regarding dose, period, or sequence; the result of tblNCA( ) will print the key columns and the carried keys can be further used for additional statistical analysis (i.e. descriptive statistics, bioequivalence test, t-test, or ANOVA). The adm argument can be 'Extravascular', 'Bolus', or 'Infusion' and the down argument can be either 'Linear' or 'Log'. The greatest advantage of this package is that the outputs produced by this package are compatible with those of pharmacokinetic parameter (PP) TESTCD of CDISC SDTM.
R code
tblNCA(Theoph, key = "Subject", colTime ="Time", colConc = "conc", dose = 320, adm = "Extravascular", dur = 0, doseUnit = "mg", timeUnit = "h", concUnit = "mg/L", down = "Linear")
IntAUC( ) function calculates interval (partial) AUC (from t1 and t2) with the given series of time and concentration. The interval AUC (0.5–11 hour) of the subject 8 can be calculated using the Theoph dataset with the following R script.
R code
Time = Theoph[Theoph$Subject == 8, "Time"]
Concentration = Theoph[Theoph$Subject == 8, "conc"]
Res =sNCA(Time, Concentration, dose = 320, concUnit = "mg/L")
IntAUC(Time, Concentration, t1 = 0.5, t2 = 11, Res)
[1] 58.26022

ncar package: generation of NCA reports

This package generates complete NCA reports including plots with both linear and logarithmic scale. Its two main functions are pdfNCA and rtfNCA, which produce pdf file format and rtf file format, respectively. The generated reports are similar to those generated from commercial softwares, but like NonCompart, this package has the advantage of using PPTESTCD of CDISC SDTM. ncar produces NCA reports through NonCompart and converts them into Microsoft Word format when using rtfNCA( ), which is convenient for editing. Reports generated by pdfNCA( )function show individual plots with trend lines that joins the dots used for calculating terminal slopes. Figure 2 shows an example of an NCA report in pdf format and an individual concentration-time plot.
R code
pdfNCA(fileName = "pdfNCA-Theoph.pdf", Theoph, colSubj = "Subject", colTime = "Time", colConc = "conc", dose = 320, doseUnit = "mg", timeUnit = "h", concU nit = "mg/L", down = "Linear")

Validation of NCA results between R packages and WinNonlin®

To demonstrate the accordance of outputs by ncar package and WinNonlin®, we performed NCA using Theoph dataset obtained from the R software. For comparison of the NCA results, we selected the following conditions: extravascular, linear-up linear-down, and best fit. We found no discrepancy between the two results as shown in Table 3 (a randomized subject, Subject ID = 8).
In order to further validate these packages, we compared NCA results using Indometh, another available dataset of the R software as well as other datasets of a number of subjects from several phase 1 clinical trials with different dosing routes such as infusion, bolus, and oral route. As a result, we could not find any discrepancy between outputs generated by the R packages and WinNonlin®.

Discussion

We developed two R packages—NonCompart and ncar for NCA. Through these packages, we aimed to implement the following functionalities for performing NCA: 1) CDISC SDTM terms; 2) automatic slope selection with the same criterion of WinNonlin®; 3) supporting both ‘linear-up linear-down’ and ‘linear-up log-down’ method; and 4) interval (partial) AUCs with ‘linear’ or ‘log’ interpolation method. These packages are convenient and efficient because they enable preparation of data and NCA as well as generation of reports including plots together in R software. As shown in Figure 2B, the NCA plot allows for automatic slope selection, however, it is not possible to manually choose the points used for calculating terminal slope. In addition, any error or change can easily be fixed, and users may choose calculation methods between linear and logarithmic, which support ‘linear-up linear-down’ and ‘linear-up log-down’ method, respectively. Our results showed that our R packages meet the aforementioned objectives.
Since the PPTESTCD of SDTM is used in the R packages, it is helpful to construct PP domain. In the present practice, one has to change variables from WinNonlin® one by one, which is an especially difficult task for those without specific knowledge on SDTM. A number of packages can perform NCA, but no package—even commercial softwares—can give outputs in the format of SDTM or receive SDTM-formatted input data. It is important to ensure that the reports are legible to sponsors and regulatory bodies by generating a consistent and systematic result, as well as the exact results of NCA.
As shown in Table 3, comparison of NCA results obtained by WinNonlin® and ncar package (including another package) showed no significant discrepancies. These two R packages are fast and easy-to-use tool-set that can successfully perform NCA with concentration–time data. Specifically, the ncar package can produce a comprehensive set of graphical and tabular outputs that summarize the NCA results, which is a complete report in pdf or rtf format. Our two newly-developed packages are free and open-source, so they can be used to develop other useful packages as well. We hope that NonCompart and ncar packages will enable researchers to easily perform NCA, and contribute to facilitation of drug discovery process.

Acknowledgements

This research was supported by the EDISON (EDucation-research Integration through Simulation On the Net) Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (Grant number: 016M3C1A6936614). We thank Dr. Joon Seo Lim from the Scientific Publications Team at Asan Medical Center for his editorial assistance in preparing this manuscript.

Notes

Conflicts of interests: -Authors: The authors declare that they have no conflict of interests

-Reviewers: Nothing to declare

-Editors: Nothing to declare

References

1. Acharya C, Hooker AC, Turkyilmaz GY, Jonsson S, Karlsson MO. A diagnostic tool for population models using non-compartmental analysis: The ncappc package for R. Comput Methods Programs Biomed. 2016; 127:83–93. DOI: 10.1016/j.cmpb.2016.01.013. PMID: 27000291.
crossref
2. Gabrielsson J, Weiner D. Non-compartmental analysis. Methods Mol Biol. 2012; 929:377. PMID: 23007438.
crossref
3. The R Project for Statistical Computing. R. Accessed 6 November 2017. http://www.r-project.org/.
5. Thermo Fisher Scientific, Kinetica. Accessed 28 February 2018. https://www.thermofisher.com/order/catalog/product/INF-24000/.
6. Kim MG, Yim DS, Bae KS. R-based reproduction of the estimation process hidden behind NONMEN Part 1: first-order approximation method. Transl Clin Pharmacol. 2015; 23:1–7.
7. Clinical Data Interchange Standards Consortium (CDISC). Study Data Tabulation Model Implementation Guide: Human Clinical Trials Version 3.2. Accessed 28 February 2018. https://www.cdisc.org/system/files/all/standard_category/application/pdf/sdtmig_v3.2.pdf.
Figure 1

Example of NonCompart package functions. Example by tblNCA.

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Figure 2

Examples of ncar package functions. (A) Example of a NCA report in pdf format by pdfNCA, (B) Individual concentration-time plots (left: linear scale, right: log-linear scale).

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Table 1

Description of PK parameters of WinNonlin® and the R packages

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Parameter WinNonlin® Description
b0 b0 Intercept
CMAX Cmax Max Concentration (Conc)
CMAXD Cmax_D Max Conc Norm by Dose
TMAX Tmax_D Time of Cmax
TLAG Tlag Time Until First Nonzero Conc
CLST Clast Last Nonzero Conc
CLSTP Clast_pred Last Nonzero Conc Pred
TLST Tlast Time of Last Nonzero Conc
LAMZHL HL_Lambda_z Half-Life Lambda z
LAMZ Lambda_z Lambda z
LAMZLL Lambda_z lower Lambda z Lower Limit
LAMZUL Lambda_z upper Lambda z Upper Limit
LAMZNPT No_points_Lambda_z Number of Points for Lambda z
CORRXY Corr_XY Correlation Between Time X and Log Conc Y
R2 Rsq R Squared
R2ADJ Rsq_adjusted R Squared Adjusted
AUCLST AUClast AUC to Last Nonzero Conc
AUCALL AUCall AUC All
AUCIFO AUCINF_obs AUC Infinity Obs
AUCIFOD AUCINF_D_obs AUC Infinity Obs Norm by Dose
AUCIFP AUCINF_Pred AUC Infinity Pred
AUCIFPD AUCINF_D_pred AUC Infinity Pred Norm by Dose
AUCPEO AUC_Extrap_obs AUC %Extrapolation Obs
AUCPEP AUC_Extrap_pred AUC %Extrapolation Pred
AUMCLST AUMClast AUMC to Last Nonzero Conc
AUMCIFO AUMCINF_obs AUMC Infinity Obs
AUMCIFP AUMCINF_pred AUMC Infinity Pred
AUMCPEO AUMC_Extrap_obs AUMC %Extrapolation Obs
AUMCPEP AUMC_Extrap_pred AUMC % Extrapolation Pred
VZFO Vz_F_obs Vz Obs by F
VZFP Vz_F_p Vz Pred by F
CLFO Cl_F_obs Total CL Obs by F
CLFP Cl_F_pred Total CL Pred by F
MRTEVLST MRTlast MRT Extravasc to Last Nonzero Conc
MRTEVIFO MRTINF_obs MRT Extravasc Infinity Obs
MRTEVIFP MRTINF_pred MRT Extravasc Infinity Pred
Table 2

Part of Theoph dataset with information on key (subject), time, and concentration

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Subject Weight (kg) Dose (mg) Time (h) Concentration (mg/ml)
8 70.5 4.53 0 0.00
8 70.5 4.53 0.25 3.05
8 70.5 4.53 0.52 3.05
8 70.5 4.53 0.98 7.31
8 70.5 4.53 2.02 7.56
8 70.5 4.53 3.53 6.59
8 70.5 4.53 5.05 5.88
8 70.5 4.53 7.15 4.73
8 70.5 4.53 9.05 4.57
8 70.5 4.53 12.10 3.00
8 70.5 4.53 24.12 1.25
Table 3

Comparison of NCA results generated from WinNonlin® and ncar package

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Parameter WinNonlin® ncar
CMAX 7.56 mg/L 7.5600 mg/L
CMAXD 0.023625 mg/L/mg 0.0236 mg/L/mg
TMAX 2.02 h 2.0200 h
TLAG 0 h 0.0000 h
CLST 1.25 mg/L 1.2500 mg/L
TLST 24.12 h 24.1200 h
LAMZHL 8.510037883 h 8.5100 h
LAMZ 0.08145054 /h 0.0815 /h
LAMZLL 3.53 h 3.5300 h
LAMZUL 24.12 h 24.1200 h
LAMZNPT 6 6
CORRXY −0.995496053 −0.9955
R2 0.991012391 0.991
R2ADJ 0.988765489 0.9888
AUCLST 88.55995 h*mg/L 88.5600 h*mg/L
AUCALL 88.55995 h*mg/L 88.5600 h*mg/L
AUCIFO 103.906687 h*mg/L 103.9067 h*mg/L
AUCIFOD 0.324708 h*mg/L/mg 0.3247 h*mg/L/mg
AUCIFP 103.643051 h*mg/L 103.6431 h*mg/L
AUCIFP 0.323884 h*mg/L/mg 0.3239 h*mg/L/mg
AUCPEO 14.77% 14.77%
AUCPEP 14.55% 14.55%
AUMCLST 739.534598 h2*mg/L 739.5346 h2*mg/L
AUMCIFO 1298.115755 h2*mg/L 1298.1158 h2*mg/L
AUMCIFP 1288.520116 h2*mg/L 1288.5201 h2*mg/L
AUMCPEO 43.03% 43.03%
AUMCPEP 42.61% 42.61%
VZFO 37.81050811 L 37.8105 L
VZFP 37.90668616 L 37.9067 L
CLFO 3.079686301 L/h 3.0797 L/h
CLFP 3.087520055 L/h 3.0875 L/h
MRTEVLST 8.35066639 h 8.3507 h
MRTEVIFO 12.49309159 h 12.4931 h
MRTEVIFP 12.43228656 h 12.4323 h
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