Abstract
With the advent of polytherapy for cancer treatment it has become prudent to minimize, as much as possible, the potential for drug–drug interactions (DDI). Toward this end, the metabolic and transporter pathways involved in the disposition of a drug candidate (phenotyping) and potential for inhibition and induction of drug-metabolizing enzymes and transporters are evaluated in vitro. 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 chapter will attempt to summarize different examples from the literature where animal models have been used to predict cytochrome P450 3A (CYP3A)- and P-glycoprotein-based DDI. When employing data from animal models one needs to be aware of species differences in enzyme- and transporter-activity leading to differences in pharmacokinetics, clearance pathways as well as species differences in selectivity and affinity of probe substrates and inhibitors. Because of these differences, in vivo animal studies alone, cannot be predictive of human DDI. 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 DDI potential.
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Marathe, P.H., Rodrigues, A.D. (2010). Examination of CYP3A and P-Glycoprotein-Mediated Drug–Drug Interactions Using Animal Models. In: Zhou, J. (eds) Multi-Drug Resistance in Cancer. Methods in Molecular Biology, vol 596. Humana Press. https://doi.org/10.1007/978-1-60761-416-6_17
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