Exploiting Pharmacokinetic Models of Tamoxifen and Endoxifen to Identify Factors Causing Subtherapeutic Concentrations in Breast Cancer Patients
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Background and Objectives
A better understanding of the highly variable pharmacokinetics (PK) of tamoxifen and its active metabolite endoxifen in breast cancer patients is crucial to support individualised treatment. This study used a modelling and simulation approach to quantitatively assess the influence of cytochrome P450 (CYP) 2D6 activity and other relevant factors on tamoxifen and endoxifen PK to identify subgroups at risk for subtherapeutic endoxifen concentrations.
Simulations were performed using two previously published PK models jointly describing tamoxifen and endoxifen with CYP2D6 and CYP3A4/5 enzyme activities implemented as covariates. Steady-state predictions were compared between models and with the literature values. Factors potentially causing between-model discrepancies were explored. A previously published threshold (6 ng/mL) was used to identify patients with subtherapeutic endoxifen concentrations and to perform a dose adaptation study.
Steady-state predictions of tamoxifen and endoxifen were considerably different between the models. The factors, differences in sampling time, adherence and bioavailability, were not able to fully capture between-model variability. Endoxifen steady-state fluctuations within a dosing interval were minimal (<6%). Poor (97%) and intermediate (54%) CYP2D6 metabolisers failed to achieve therapeutic endoxifen concentrations, suggesting adapted doses of tamoxifen 80 and 40 mg, respectively, achieving therapeutic endoxifen concentrations in 89.7% of patients (standard dosing 45.2%). However, interindividual variability remained.
To achieve therapeutic endoxifen concentrations early in treatment, it is advisable to initiate treatment by CYP2D6 genotype/phenotype-guided dosing, followed by therapeutic drug monitoring at steady-state. We strongly advocate to adequately measure, report and prospectively investigate influential factors (i.e. adherence, bioavailability, time to PK steady-state) in clinical trials.
The authors thank the High-Performance Computing Service of ZEDAT at Freie Universitaet Berlin (http://www.zedat.fuberlin.de/Compute) for computing time.
Compliance with Ethical Standards
No sources of funding were used in the preparation of this study.
Conflicts of interest
Lena Klopp-Schulze, Markus Joerger, Sebastian G. Wicha, Rob ter Heine, Chantal Csajka and Zinnia P. Parra-Guillen declare no conflicts of interest. Charlotte Kloft reports grants from an industry consortium (AbbVie Deutschland GmbH & Co. KG, Boehringer Ingelheim Pharma GmbH & Co. KG, Grünenthal GmbH, F. Hoffmann-La Roche Ltd, Merck KGaA and Sanofi) and the Innovative Medicines Initiative-Joint Undertaking (‘DDMoRe’), both outside the submitted work.
This article does not contain any studies with human participants or animals performed by any of the authors.
Parts of the results of this study were presented as posters at the 24th and 25th Population Approach Group Europe (PAGE) annual meeting (2015 and 2016). Preliminary results of the dose adaptation study have been presented at the Central European Society of Anticancer-Drug Research (CESAR) meeting (2015) and thereupon published as an extended abstract .
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