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Clin Pharmacokinet. 2011 May;50(5):331-47. doi: 10.2165/11539680-000000000-00000.

Simulation of human intravenous and oral pharmacokinetics of 21 diverse compounds using physiologically based pharmacokinetic modelling.

Author information

1
Department of Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide RD, Sandwich, UK. hannah.jones@pfizer.com

Abstract

BACKGROUND:

The importance of predicting human pharmacokinetics during compound selection has been recognized in the pharmaceutical industry. To this end there are many different approaches that are applied.

METHODS:

In this study we compared the accuracy of physiologically based pharmacokinetic (PBPK) methodologies implemented in GastroPlus™ with the one-compartment approach routinely used at Pfizer for human pharmacokinetic plasma concentration-time profile prediction. Twenty-one Pfizer compounds were selected based on the availability of relevant preclinical and clinical data. Intravenous and oral human simulations were performed for each compound. To understand any mispredictions, simulations were also performed using the observed clearance (CL) value as input into the model.

RESULTS:

The simulation results using PBPK were shown to be superior to those obtained via traditional one-compartment analyses. In many cases, this difference was statistically significant. Specifically, the results showed that the PBPK approach was able to accurately predict passive distribution and absorption processes. Some issues and limitations remain with respect to the prediction of CL and active transport processes and these need to be improved to further increase the utility of PBPK modelling. A particular advantage of the PBPK approach is its ability to accurately predict the multiphasic shape of the pharmacokinetic profiles for many of the compounds tested.

CONCLUSION:

The results from this evaluation demonstrate the utility of PBPK methodology for the prediction of human pharmacokinetics. This methodology can be applied at different stages to enhance the understanding of the compounds in a particular chemical series, guide experiments, aid candidate selection and inform clinical trial design.

[Indexed for MEDLINE]

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