In Vivo Animal Models for Investigating Potential CYP3A- and Pgp-Mediated Drug-Drug Interactions

Author(s): Punit H. Marathe, A. David Rodrigues.

Journal Name: Current Drug Metabolism

Volume 7 , Issue 7 , 2006

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Abstract:

With the advent of polytherapy it has become prudent to minimize, as much as possible, the potential for drugdrug interactions. Towards this end, the metabolic and transporter pathways involved in the disposition of a drug candidate (phenotyping) are evaluated in vitro employing available human tissue and specific reagents. Likewise, in vitro screening for inhibition and induction of drug-metabolizing enzymes and transporters is conducted also. Such in vitro human data can be made available prior to human dosing and enable in vitro to in vivo -based predictions of clinical outcomes. Despite some success, however, in vitro systems are not dynamic and sometimes fail to predict drug-drug interactions for a variety of reasons. In comparison, relatively less effort has been made to evaluate predictions based on data derived from in vivo animal models. This review will attempt to summarize different examples from the literature where animal models have been used to predict cytochrome P450 3A (CYP3A)- and P-glycoprotein (Pgp)-based drug-drug interactions. When employing data from animal models one needs to be aware of species differences in pharmacokinetics, clearance pathways and selectivity and affinity of probe substrates and inhibitors. Because of these differences, in vivo animal studies alone, cannot be predictive of human drug-drug interactions. Despite these caveats, the information obtained from validated in vivo animal models may prove useful when used in conjunction with in vitro-in vivo extrapolation methods. Such an integrated data set can be used to select drug candidates with a reduced drug interaction potential.

Keywords: pharmacokinetics, drug-drug interactions, in vivo animal studies, phenotyping

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Article Details

VOLUME: 7
ISSUE: 7
Year: 2006
Page: [687 - 704]
Pages: 18
DOI: 10.2174/138920006778520598
Price: $58

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