ivivc for R

demo video

In vitro-in vivo correlation (IVIVC) is defined as the correlation between in-vitro drug dissolution profile and in vivo drug absorption profile. The main purpose of conducting an IVIVC study is to utilize in vitro dissolution profiles as a surrogate for in vivo bioequivalence and to support biowaivers. Recently, IVIVC has been also applied to formulation development in the industry. In order to prove the validity of a new formulation, which is bioequivalent with a target formulation, a considerable amount of effort is required to study bioequivalence/bioavailability. Thus, data analysis of IVIVC attracts great attention from the pharmaceutical industry. This package is to develop an IVIVC tool (ivivc) running in R.

Installation & Upgrade

Download and install R first. ivivc for R is one of R packages. However, it cannot be installed from R repository website since v0.2.2. Thus, please download and install it from here. Please read the contents following the file list panel for more details first. No need to download the file README.md since it has been displayed on the screen. The file - NEWS includes the change history. After installation, you now can run ivivc by simply typing "library(ivivc)" under R Console. Users will require an R script file called preinst.r from Sourceforge to install ivivc.

about preinst.r - from Sourceforge

PLEASE READ CAREFULLY TO SAVE YOUR TIME AND AVOID POSSIBLE ERRORS.
This file ("preinst.r")) is not a part of R packages, but an R script to automate the installation for all the required packages/libraries for package ivivc for R. Please download preinst.r and place/copy it to the R working directory. Use 'getwd()' to find out where the directory is. Under R console, type source("preinst.r") and click the package to install. You require the system administrator's privilege (Windows & Linux) to run this script. Answer "Yes" if asked for anything during installation. GTK+ runtime is now bundled with the RGtk2 package installation for the Windows platform, as well as more GTK+ (a.k.a. GTK2) themes were added.

Methods

Development and validation are 2 critical steps in the evaluation of an IVIVC model. In the first, the development of the level A IVIVC model is usually estimated by a two-stage process.(1) Deconvolution: the observed fraction of the drug absorbed is estimated based on the Wagner-Nelson method. IV, IR, or oral solution was attempted as the reference. Then, the pharmacokinetic parameters will be estimated using a nonlinear regression tool or obtained from literature reported previously. The IVIVC model is developed using the observed fraction of the drug absorbed and that of the drug dissolved. Based on the IVIVC model, the predicted fraction of the drug absorbed is calculated from the observed fraction of the drug dissolved. (2) Convolution: the predicted fraction of the drug absorbed is then convolved to the predicted plasma concentrations by using the convolution method. In the second stage, evaluating the predictability of a level A correlation focuses on estimating the percent prediction error (%PE) between the observed and predicted plasma concentration profiles, such as the difference in pharmacokinetic parameters (Cmax, and the area under the curve from time zero to infinity, AUC∞). Here is a .pdf sample file for the plots. A sample text output file from ivivc for R is here. The reference that we used to develop ivivc for R can be downloaded from here.
This package was performed together with several R packages. "PKfit" package is used to fit the reference data such as IV, IR, or oral solution by fitting a one-compartment model.

Dataset format: only *.csv format is supported for ivivc for R. Users are encouraged to run a demo first and find out the dataset format.