AIMS: Tamoxifen is considered a pro-drug of its active metabolite endoxifen. The major metabolic enzymes involved in endoxifen formation are CYP2D6 and CYP3A. There is considerable evidence that variability in activity of these enzymes influences endoxifen exposure and thereby may influence the clinical outcome of tamoxifen treatment. We aimed to quantify the impact of metabolic phenotype on the pharmacokinetics of tamoxifen and endoxifen. METHODS: We assessed the CYP2D6 and CYP3A metabolic phenotypes in 40 breast cancer patients on tamoxifen treatment with a single dose of dextromethorphan as a dual phenotypic probe for CYP2D6 and CYP3A. The pharmacokinetics of dextromethorphan, tamoxifen and their relevant metabolites were analyzed using non-linear mixed effects modelling. RESULTS: Population pharmacokinetic models were developed for dextromethorphan, tamoxifen and their metabolites. In the final model for tamoxifen, the dextromethorphan derived metabolic phenotypes for CYP2D6 as well as CYP3A significantly (P < 0.0001) explained 54% of the observed variability in endoxifen formation (inter-individual variability reduced from 55% to 25%). CONCLUSIONS: We have shown that not only CYP2D6, but also CYP3A enzyme activity influences the tamoxifen to endoxifen conversion in breast cancer patients. Our developed model may be used to assess separately the impact of CYP2D6 and CYP3A mediated drug-drug interactions with tamoxifen without the necessity of administering this anti-oestrogenic drug and to support Bayesian guided therapeutic drug monitoring of tamoxifen in routine clinical practice.
AIMS: Tamoxifen is considered a pro-drug of its active metabolite endoxifen. The major metabolic enzymes involved in endoxifen formation are CYP2D6 and CYP3A. There is considerable evidence that variability in activity of these enzymes influences endoxifen exposure and thereby may influence the clinical outcome of tamoxifen treatment. We aimed to quantify the impact of metabolic phenotype on the pharmacokinetics of tamoxifen and endoxifen. METHODS: We assessed the CYP2D6 and CYP3A metabolic phenotypes in 40 breast cancerpatients on tamoxifen treatment with a single dose of dextromethorphan as a dual phenotypic probe for CYP2D6 and CYP3A. The pharmacokinetics of dextromethorphan, tamoxifen and their relevant metabolites were analyzed using non-linear mixed effects modelling. RESULTS: Population pharmacokinetic models were developed for dextromethorphan, tamoxifen and their metabolites. In the final model for tamoxifen, the dextromethorphan derived metabolic phenotypes for CYP2D6 as well as CYP3A significantly (P < 0.0001) explained 54% of the observed variability in endoxifen formation (inter-individual variability reduced from 55% to 25%). CONCLUSIONS: We have shown that not only CYP2D6, but also CYP3A enzyme activity influences the tamoxifen to endoxifen conversion in breast cancerpatients. Our developed model may be used to assess separately the impact of CYP2D6 and CYP3A mediated drug-drug interactions with tamoxifen without the necessity of administering this anti-oestrogenic drug and to support Bayesian guided therapeutic drug monitoring of tamoxifen in routine clinical practice.
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