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simulated by changing physiological parameters and inserting the relevant
solubility data into the appropriate ACAT compartments (stomach,
intestine, and colon). The food effect for each drug was estimated by
comparing AUC or C
max
between fasted, fed, and/or high-fat conditions.
Predicted and observed plasma concentration-time profi les and food
effects were compared for a range of doses to assess the accuracy of the
simulations. The obtained results demonstrated that GI simulation using
GastroPlus™ was able to correctly predict the observed plasma exposure
in fasted, fed, and high-fat conditions for all six compounds. Also, the
applied method was able to accurately distinguish between minor and
signifi cant food effects. Therefore, it was concluded that biorelevant
solubility tests, in conjunction with physiologically based absorption
modeling, can be used to predict food effects caused by solubility and
dissolution rate limitations, and/or degradation. However, it was stressed
that the accuracy of a generated drug-specifi c absorption model needs to
be carefully verifi ed before proceeding to predict the effect of food.
An important issue emphasized from different studies (Mueller et al.,
1994; Schug et al., 2002a,b; Zhang et al., 2011) is related to the
formulation-dependent food effects. Zhang et al. (2011) incorporated
gastric emptying time and different drug
in vivo
solubilities under fasted
and fed states into the generated CBZ absorption model and observed
that co-administration of CBZ IR suspension with food resulted in
decreased C
max
and prolonged t
max
, probably due to a prolonged gastric
emptying time, while co-administration of the IR tablet and XR capsule
with food resulted in increased C
max
and earlier t
max
in comparison with
the PK parameters obtained under fasted state. A possible explanation of
this phenomenon was that the presence of a high-fat meal induced the
increase in bile salts concentration in the GI tract, thus enhancing the
dissolution rate of low soluble CBZ from the IR tablet and XR capsule.
Jones et al. developed a novel strategy for predicting human
pharmacokinetics in fasted and fed states, by using PBPK absorption
modeling across different species (Jones et al., 2006a). The proposed
strategy implies that the absorption models are fi rst generated for the
selected preclinical species (e.g. mouse, rat, dog, monkey) on the basis of
data generated during drug research and preclinical development, and
afterwards verifi ed thoroughly by comparing the simulation outcomes with
the results of
in vivo
animal studies. If the prediction was proven to be
accurate, then the same
in vitro
absorption parameters and the same
assumptions can be used to predict human pharmacokinetics. However, if
the animal model was incomplete, further refi nement of the model is needed
in order to provide more accurate simulations in humans (Figure 6.11).
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