(demo)Created by Hsin-ya Lee and Yung-jin Lee (mobilePK@gmail.com)
ivivc for R -
A Tool for “in vitro-in vivo
Correlation" Exploration with
(demo)
Created by Hsin-ya Lee and Yung-jin Lee (mobilePK@gmail.com)
Introduction
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. In order to prove the
validity of a new formulation, which is bioequivalent with a target
formulation, a considerable amount of efforts is required to study
bioequivalence/bioavailability.
Thus, data analysis of IVIVC attracts great attention from the pharmaceutical
industry. The purpose of this study
is to develop an IVIVC tool (ivivc)
running in R.
Installation & Upgrade: ivivc for R is one of
R
packages. Thus, users have to
download and install
R first, and then run it.
Under R Console, users can click
"Packages"
from the menu then ->"Install package(s)..." --> select a CRAN mirror site near
you and you will see the list of currently available
R packages.
Just select "ivivc" from the list and click "OK" to start
installation. Then it's done! If you want to
upgrade from
previous version of ivivc for R when a new version is released, please go
to the menu and
click
"Packages", and then select "Update packages...". then
select a CRAN mirror site near you and click "OK". Done! Pretty easy to upgrade.
If you're running Linux PC or Mac OS X, you may not see the menu
but
the R Console. You can read this
R
Installation and Administration (pdf ) for detailed information. You
can also type help("INSTALL") or help("install.packages") in R Console for
information on how to install packages from this directory. Don't worry
about this. You only need
to do this once. After these installation, you now can run ivivc by simply typing
"library(ivivc) (enter)"
under R Console.
Remove ivivc for R: Simply go to the directory of R where you
installed and then go to the sub-directory of /library, delete ivivc.
Methods
Development and validation are 2 critical
steps in the evaluation of an IVIVC model. In the first, the development of
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 literatures 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∞).
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 an one-compartment model or a two-compartment model. Moreover, we use "reshape" package to rearrange some data format in
"ivivc" package. Then, "sciplot"
package assists us to plot
the mean values and standard
error (or other summary statistics) of observed or predicted concentrations.
