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J Pharm Pharmacol. 2007 Jul;59(7):905-16.

Prediction of human pharmacokinetics--gastrointestinal absorption.

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1
Clinical Pharmacology, AstraZeneca R&D Södertälje, S-151 85 Södertälje, Sweden. urban.fagerholm@astrazeneca.com

Abstract

Permeability (P(e)) and solubility/dissolution are two major determinants of gastrointestinal (GI) drug absorption. Good prediction of these is crucial for predicting doses, exposures and potential interactions, and for selecting appropriate candidate drugs. The main objective was to evaluate screening methods for prediction of GI P(e), solubility/dissolution and fraction absorbed (f(a)) in humans. The most accurate P(e) models for prediction of f(a) of passively transported and highly soluble compounds appear to be the 2/4/A1 rat small intestinal cell model (in-vitro and in-silico), a newly developed artificial-membrane method, and a semi-empirical approach based on in-vitro membrane affinity to immobilized lipid bilayers, effective molecular weight and physiological GI variables. The predictability of in-vitro Caco-2, in-situ perfusion and other artificial membrane methods seems comparably low. The P(e) and f(a) in humans for compounds that undergo mainly active transport were predicted poorly by all models investigated. However, the rat in-situ perfusion model appears useful for prediction of active uptake potential (complete active uptake is generally well predicted), and Caco-2 cells are useful for studying bidirectional active transport, respectively. Human intestinal in-vitro P(e), which correlates well with f(a) for passively transported compounds, could possibly also have potential to improve/enable predictions of f(a) for actively transported substances. Molecular descriptor data could give an indication of the passive absorption potential. The 'maximum absorbable dose' and 'dose number' approaches, and solubility/dissolution data obtained in aqueous media, appear to underestimate in-vivo dissolution to a considerable extent. Predictions of in-vivo dissolution should preferably be done from in-vitro dissolution data obtained using either real or validated simulated GI fluids.

PMID:
17637184
DOI:
10.1211/jpp.59.7.0001
[Indexed for MEDLINE]
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