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Review
. 2009 Jun;11(2):225-37.
doi: 10.1208/s12248-009-9099-y. Epub 2009 Apr 21.

Population-based mechanistic prediction of oral drug absorption

Masoud Jamei  1 , David Turner, Jiansong Yang, Sibylle Neuhoff, Sebastian Polak, Amin Rostami-Hodjegan, Geoffrey Tucker
Affiliations
Review

Population-based mechanistic prediction of oral drug absorption

Masoud Jamei et al. AAPS J. 2009 Jun.

Abstract

The bioavailability of drugs from oral formulations is influenced by many physiological factors including gastrointestinal fluid composition, pH and dynamics, transit and motility, and metabolism and transport, each of which may vary with age, gender, race, food, and disease. Therefore, oral bioavailability, particularly of poorly soluble and/or poorly permeable compounds and those that are extensively metabolized, often exhibits a high degree of inter- and intra-individual variability. While several models and algorithms have been developed to predict bioavailability in an average person, efforts to accommodate intrinsic variability in the component processes are less common. An approach that incorporates such variability for human populations within a mechanistic framework is described together with examples of its application to drug and formulation development.

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Figures

Fig. 1
Fig. 1
Kinetic processes within each intestinal segment of the ADAM model (see text for explanation of symbols)
Fig. 2
Fig. 2
The distribution of human small intestinal transit time (5)
Fig. 3
Fig. 3
Theoretical relationship between fraction absorbed (fa), intestinal permeability (P eff,man), and intestinal transit time (Tsi), assuming rapid dissolution (127)
Fig. 4
Fig. 4
Predicted values of fa and its variability for enalaprilat, lisinopril, metoprolol, and naproxene. Simulations were done for ten trials each with ten subjects selected randomly from a virtual population of 100 subjects (median and 5th and 95th percentiles for the whole population and each trial are shown)
Fig. 5
Fig. 5
Simulation of the effect of a decrease in the intestinal transit time secondary to disease on the bioavailability of a enalaprilat and b metoprolol
Fig. 6
Fig. 6
Predicted values of the gut extraction ratio (E G) of midazolam. Simulations were done for ten trials each with five subjects selected randomly from a virtual population of 100 subjects (median and 5th and 95th percentiles for the whole population and each trial are shown) (131)
Fig. 7
Fig. 7
Predicted fractions of a dose of midazolam (mean ± SD) a absorbed and b metabolized in different segments of the intestine (131)
Fig. 8
Fig. 8
Observed and predicted mean plasma concentrations of metoprolol after administration in a slow-release formulation (observed data are from Sirisuth and Eddington) (133)
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References

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