Article date: May 2008
By: Kuresh A. Youdim, Aref Zayed, Maurice Dickins, Alex Phipps, Michelle Griffiths, Amanda Darekar, Ruth Hyland, Odette Fahmi, Susan Hurst, David R. Plowchalk, Jack Cook, Feng Guo, R. Scott Obach, in Volume 65, Issue 5, pages 680-692
WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT
AIMS
The aim of this study was to explore and optimize the in vitro and in silico approaches used for predicting clinical DDIs. A data set containing clinical information on the interaction of 20 Pfizer compounds with ketoconazole was used to assess the success of the techniques.
METHODS
The study calculated the fraction and the rate of metabolism of 20 Pfizer compounds via each cytochrome P450. Two approaches were used to determine fraction metabolized (fm); 1) by measuring substrate loss in human liver microsomes (HLM) in the presence and absence of specific chemical inhibitors and 2) by measuring substrate loss in individual cDNA expressed P450s (also referred to as recombinant P450s (rhCYP)) The fractions metabolized via each CYP were used to predict the drug–drug interaction due to CYP3A4 inhibition by ketoconazole using the modelling and simulation software SIMCYP®.
RESULTS
When in vitro data were generated using Gentest supersomes, 85% of predictions were within two‐fold of the observed clinical interaction. Using PanVera baculosomes, 70% of predictions were predicted within two‐fold. In contrast using chemical inhibitors the accuracy was lower, predicting only 37% of compounds within two‐fold of the clinical value. Poorly predicted compounds were found to either be metabolically stable and/or have high microsomal protein binding. The use of equilibrium dialysis to generate accurate protein binding measurements was especially important for highly bound drugs.
CONCLUSIONS
The current study demonstrated that the use of rhCYPs with SIMCYP® provides a robust in vitro system for predicting the likelihood and magnitude of changes in clinical exposure of compounds as a consequence of CYP3A4 inhibition by a concomitantly administered drug.
DOI: 10.1111/j.1365-2125.2007.03070.x
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