Computer- aided biopharmaceutical characterization: gastrointestinal absorption simulation - Computer-Aided Applications in Pharmaceutical Technology - page 204

6.5 Virtual trial

In the later stages of formulation development, it is especially valuable to
anticipate inter-subject variability that may infl uence oral drug
bioavailability. In this way, the formulator might gain a better insight on
what can be achieved by means of the formulation.
In order to in silico simulate the infl uence of population variability and/
or the combined effect of formulation variables that are not precise values,
but for which distributions of values can be estimated, the Virtual Trial
feature in GastroPlus™ can be used. This feature allows the user to perform
stochastic simulations on a number of virtual subjects, wherein the values
of the selected variables are randomly sampled from predetermined
distributions (defi ned as means with coeffi cients of variation (CV%) in
absolute or log space). CV% values are usually estimated on the basis of
previous knowledge or analysis of literature data. The results of the
simulations are expressed as means and coeffi cients of variation for fraction
of drug absorbed, bioavailability, t max , C max , and AUC values, as well as
absolute minimum and maximum values for each of these parameters
reached during the trials. Also, the average C p -time curve, 90% confi dence
intervals, probability contours (10, 25, 50, 75, 90, 95, and 100%), and
experimental data with possible BE limits (if available), are displayed.
An illustration of the use of virtual trials for in silico modeling of oral
drug absorption can be seen in the paper of Tubic et al. (2006). Although
the prime objective of this study was to demonstrate how an in silico
approach can be used to predict nonlinear dose-dependent absorption
properties of talinolol, this section will focus solely on the results of
virtual trial simulations. The reason why the authors performed
simulations in a virtual trial mode was to include the effects of
physiological variables, such as transit times in various GI compartments,
GI pH, lengths and radii, PK parameters, plasma protein binding, and
renal CL on talinolol absorption. Stochastic variables were randomly
selected within the range defi ned by the means with predetermined
coeffi cients of variation in log normal space, and used for the simulation.
Virtual trials were performed with 12 subjects (equal to the number of
subjects used in the clinical study), and the results were presented as
mean C p vs. time profi le with 90% confi dence intervals around the mean,
along with C p vs. time curves for 25, 75, and 100% probability of
simulated patient data. The simulation results revealed that all of the
observed clinical data lay within the minimal and maximal individual
patient simulations, suggesting that the CV% values used for the log
normal distributions of the stochastic variables produced variability that

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