Prediction of human pharmacokinetics--gut-wall metabolism.
Intestinal mucosal cells operate with different metabolic and transport activity, and not all of them are involved in drug absorption and metabolism. The fraction of these cells involved is dependent on the absorption characteristics of compounds and is difficult to predict (it is probably small). The cells also appear comparably impermeable. This shows a limited applicability of microsome intrinsic clearance (CL(int))-data for prediction of gut-wall metabolism, and the difficulty to predict the gut-wall CL (CL(GW)) and extraction ratio (E(GW)). The objectives of this review were to evaluate determinants and methods for prediction of first-pass and systemic E(GW) and CL(GW) in man, and if required and possible, develop new simple prediction methodology. Animal gut-wall metabolism data do not appear reliable for scaling to man. In general, the systemic CL(GW) is low compared with the hepatic CL. For a moderately extracted CYP3A4-substrate with high permeability, midazolam, the gut-wall/hepatic CL-ratio is only 1/35. This suggests (as a general rule) that systemic CL(GW) can be neglected when predicting the total CL. First-pass E(GW) could be of importance, especially for substrates of CYP3A4 and conjugating enzymes. For several reasons, including those presented above and that blood flow based models are not applicable in the absorptive direction, it seems poorly predicted with available methodology. Prediction errors are large (several-fold on average; maximum approximately 15-fold). A new simple first-pass E(GW)-prediction method that compensates for regional and local differences in absorption and metabolic activity has been developed. It has been based on human cell in-vitro CL(int) and fractional absorption from the small intestine for reference (including verapamil) and test substances, and in-vivo first-pass E(GW)-data for reference substances. First-pass E(GW)-values for CYP3A4-substrates with various degrees of gastrointestinal uptake and CL(int) and a CYP2D6-substrate were well-predicted (negligible errors). More high quality in-vitro CL(int)- and in-vivo E(GW)-data are required for further validation of the method.
Fagerholm
Urban
U
Clinical Pharmacology, AstraZeneca R&D Södertälje, S-151 85 Södertälje, Sweden. urban.fagerholm@astrazeneca.com
D000818:Animals; D005544:Forecasting; D006801:Humans; D007408:Intestinal Absorption; D007413:Intestinal Mucosa / Q000166:cytology / Q000378:metabolism*; D008954:Models, Biological; D004364:Pharmaceutical Preparations / Q000378:metabolism*; D010599:Pharmacokinetics; D013045:Species Specificity
D004364:Pharmaceutical Preparations