Concomitant use of tamoxifen and endoxifen in postmenopausal early breast cancer: prediction of plasma levels by physiologically-based pharmacokinetic modeling

Model-Based Quantification of Impact of Genetic Polymorphisms and Co-Medications on Pharmacokinetics of Tamoxifen and Six Metabolites in Breast Cancer

Variations in clinical response to tamoxifen (TAM) may be related to polymorphic cytochromes P450 (CYPs) involved in forming its active metabolite endoxifen (ENDO). We developed a population pharmacokinetic (PopPK) model for tamoxifen and six metabolites to determine clinically relevant factors of ENDO exposure. Concentration-time data for TAM and 6 metabolites come from a prospective, multicenter, 3-year follow-up study of adjuvant TAM (20 mg/day) in patients with breast cancer, with plasma samples drawn every 6 months, and genotypes for 63 genetic polymorphisms (PHACS study, NCT01127295). Concentration data for TAM and 6 metabolites from 928 patients (n = 27,433 concentrations) were analyzed simultaneously with a 7-compartment PopPK model. CYP2D6 phenotype (poor metabolizer (PM), intermediate metabolizer (IM), normal metabolizer (NM), and ultra-rapid metabolizer (UM)), CYP3A4*22, CYP2C19*2, and CYP2B6*6 genotypes, concomitant CYP2D6 inhibitors, age, and body weight had a significant impact on TAM metabolism. Formation of ENDO from N-desmethyltamoxifen was decreased by 84% (relative standard error (RSE) = 14%) in PM patients and by 47% (RSE = 9%) in IM patients and increased in UM patients by 27% (RSE = 12%) compared with NM patients. Dose-adjustment simulations support an increase from 20 mg/day to 40 and 80 mg/day in IM patients and PM patients, respectively, to reach ENDO levels similar to those in NM patients. However, when considering Antiestrogenic Activity Score (AAS), a dose increase to 60 mg/day in PM patients seems sufficient. This PopPK model can be used as a tool to predict ENDO levels or AAS according to the patient's CYP2D6 phenotype for TAM dose adaptation.

Exploiting Pharmacokinetic Models of Tamoxifen and Endoxifen to Identify Factors Causing Subtherapeutic Concentrations in Breast Cancer Patients

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

Utility of physiologically based pharmacokinetic (PBPK) modeling in oncology drug development and its accuracy: a systematic review

PURPOSE

Physiologically based pharmacokinetic (PBPK) modeling, a mathematical modeling approach which uses a pharmacokinetic model to mimick human physiology to predict drug concentration-time profiles, has been used for the discover and development of drugs in various fields, including oncology, since 2000. There have been a few general review articles on the utilization of PBPK in the development of oncology drugs, but these do not include an evaluation of model prediction accuracy. We therefore conducted a systematic review to define the accuracy of PBPK model prediction and its utility throughout all the developmental phases of oncology drugs.

METHODS

A systematic search was performed in the PubMed, PubMed Central and Cochrane Library databases from 1980 to February 2017 for articles (1) written in English, (2) focused on oncology or antineoplastic or anticancer drugs, tumor or cancer or anticancer drugs listed in the U.S. National Institutes of Health and (3) involving a PBPK model. The absolute-average-folding-errors (AAFEs) of the area under the curve (AUC) between predicted and observed values in each article were calculated to assess model prediction accuracy.

RESULTS

Of the 2341 articles initially identified by our search of the databases, 40 were included in the review analysis. These articles reported on six types of studies, i.e. in vivo (n = 4), first-in-human (n = 5), phase II/III clinical trials (n = 9), organ impairment (n = 3), pediatrics (n = 4) and drug-drug interactions (n = 15). AAFEs of the predicted AUC for all groups of studies were within 1.3-fold of each other despite variations in experimental methodologies.

CONCLUSION

PBPK modeling is a potential tool which can be effectively applied throughout all phases of oncology drug development. The number of experimental animals and human participants enrolled in the studies can be reduced using PBPK modeling and PBPK-population-PK modeling. The limited number of publications of unsuccessful model application to date may contribute to bias toward the usefulness of modeling.

Application of PBPK Modeling and Virtual Clinical Study Approaches to Predict the Outcomes of CYP2D6 Genotype-Guided Dosing of Tamoxifen

The Tamoxifen Response by CYP2D6 Genotype‐based Treatment‐1 (TARGET‐1) study (n = 180) was conducted from 2012–2017 in Japan to determine the efficacy of tamoxifen dosing guided by cytochrome P450 2D6 (CYP2D6) genotypes. To predict its outcomes prior to completion, we constructed the comprehensive physiologically based pharmacokinetic (PBPK) models of tamoxifen and its metabolites and performed virtual TARGET‐1 studies. Our analyses indicated that the expected probability to achieve the end point (demonstrating the superior efficacy of the escalated tamoxifen dose over the standard dose in patients carrying CYP2D6 variants) was 0.469 on average. As the population size of this virtual clinical study (VCS) increased, the expected probability was substantially increased (0.674 for n = 260). Our analyses also informed that the probability to achieve the end point in the TARGET‐1 study was negatively impacted by a large variability in endoxifen levels. Our current efforts demonstrate the promising utility of the PBPK modeling and VCS approaches in prospectively designing effective clinical trials.

Addressing Adherence Using Genotype-Specific PBPK Modeling-Impact of Drug Holidays on Tamoxifen and Endoxifen Plasma Levels

Introduction: Tamoxifen is one of the most common treatment opportunities for hormonal positive breast cancer. Despite its good tolerability, patients demonstrate decreasing adherence over years impacting on therapeutic success. PBPK modeling was applied to demonstrate the impact of drug holidays on plasma levels of tamoxifen and its active metabolite endoxifen for different CYP2D6 genotypes.

Materials and Methods: A virtual study with 24,000 patients was conducted in order to investigate the development of tamoxifen steady-state kinetics in patient groups of different CYP2D6 genotypes. The impact of drug holidays on steady-state kinetics was investigated assuming changing drug holiday scenarios.

Results: Drug holidays in CYP2D6 extensive and intermediate metabolizers (EMs, IMs) exceeding 1 month lead to a decrease of endoxifen steady-state trough levels below the 5th percentile of the control group. Assuming drug holidays of 1, 2, or 3 months and administering a fixed-dose combination of 20 mg tamoxifen and 3 mg endoxifen EMs demonstrated re-established endoxifen steady-state trough levels after 5, 8, and 9 days. IMs receiving the same fixed-dose combination demonstrated re-established endoxifen steady-state trough levels after 7, 10, and 11 days.

Discussion: The PBPK model impressively demonstrates the impact of drug holidays in different CYP2D6 genotypes on PK. Population simulation results indicate that drug holidays of more than 2 weeks cause a tremendous decrease of plasma levels despite the long half-life of tamoxifen. To improve therapeutic success, PBPK modeling allows identifying genotype-specific differences in PK following drug holidays and adequate treatment with loading doses.

In Vivo Performance and Properties of Tamoxifen Metabolites for CreERT2 Control

Mutant Estrogen Receptor (ERT2) ligand-binding domain fusions with Cre recombinase are a key tool for spatio-temporally controlled genetic recombination with the Cre/lox system. CreERT2 is efficiently activated in a concentration-dependent manner by the Tamoxifen metabolite trans-4-OH-Tamoxifen (trans-4-OHT). Reproducible and efficient Cre/lox experimentation is hindered by the gradual loss of CreERT2 induction potency upon prolonged storage of dissolved trans-4-OHT, which potentially results from gradual trans-to-cis isomerization or degradation. Here, we combined zebrafish CreERT2 recombination experiments and cell culture assays to document the gradual activity loss of trans-4-OHT and describe the alternative Tamoxifen metabolite Endoxifen as more stable alternative compound. Endoxifen retains potent activation upon prolonged storage (3 months), yet consistently induces half the ERT2 domain fusion activity compared to fresh trans-4-OHT. Using ¹H-NMR analysis, we reveal that trans-4-OHT isomerization is undetectable upon prolonged storage in either DMSO or Ethanol, ruling out isomer transformation as cause for the gradual loss of trans-4-OHT activity. We further establish that both trans-4-OHT and Endoxifen are insensitive to light exposure under regular laboratory handling conditions. We attribute the gradual loss of trans-4-OHT potency to precipitation over time, and show that heating of aged trans-4-OHT aliquots reinstates their CreERT2 induction potential. Our data establish Endoxifen as potent and reproducible complementary compound to 4-OHT to control ERT2 domain fusion proteins in vivo, and provide a framework for efficient chemically controlled recombination experiments.

Quantitative Systems Pharmacology: A Framework for Context

Quantitative Systems Pharmacology (QSP) is receiving increased attention. As the momentum builds and the expectations grow it is important to (re)assess and formalize the basic concepts and approaches. In this short review, I argue that QSP, in addition to enabling the rational integration of data and development of complex models, maybe more importantly, provides the foundations for developing an integrated framework for the assessment of drugs and their impact on disease within a broader context expanding the envelope to account in great detail for physiology, environment and prior history. I articulate some of the critical enablers, major obstacles and exciting opportunities manifesting themselves along the way. Charting such overarching themes will enable practitioners to identify major and defining factors as the field progressively moves towards personalized and precision health care delivery.

Physiologically based pharmacokinetic and pharmacodynamic modeling in cancer drug development: status, potential and gaps

INTRODUCTION

Modeling and simulation have become important means of answering questions relevant to the development of a drug, making it possible to assess risks early and to reduce costs. Physiologically based pharmacokinetic and pharmacodynamic (PBPK/PD) models contribute to a comprehensive understanding of the drug, covering specific questions from early discovery through lifecycle management stages. As for other disease areas, in oncology, PBPK and PD models are important topics that remain to be addressed.

AREAS COVERED

This review describes current PBPK and PD approaches, their applicability in drug development in general and specifically in the area of oncology. It discusses the current status and then focuses on key challenges and the potential for future use. It provides cases in which modeling currently cannot answer the questions and assesses the requirements to close gaps for PBPK/PD in oncology.

EXPERT OPINION

PBPK/PD models have led to improvements in identifying risks and reducing costs during the drug development process. Nevertheless, there is a lot of potential, where more rigorous integration of biological knowledge and specific experimental design would result in a more comprehensive biological picture. Ideally, such approaches would reveal the extent to which preclinical work can be extrapolated to clinical settings, thus enabling reliable prediction and, ultimately, reducing failed trials in clinical oncology.

Pharmacogenomic diversity of tamoxifen metabolites and estrogen receptor genes in Hispanics and non-Hispanic whites with breast cancer

Ethnic differences in patient genetics and breast cancer (BC) biology contribute to ethnic disparities in cancer presentation and patient outcome. We prospectively evaluated SNPs within phase I and phase II tamoxifen (TAM) metabolizing enzymes, and the estrogen receptor gene (ESR1), aiming to identify potential pharmacogenomic ethnicity patterns in an ER-positive BC cohort constituted of Hispanic and Non-Hispanic White (NHW) women in South Texas. Plasma concentrations of TAM/metabolites were measured using HPLC. CYP2C9, CYP2D6 and SULT1A1 genotypes were determined by DNA sequencing/Pyrosequencing technology. ESR1 PvuII and XbaI SNPs were genotyped using Applied Biosystems Taqman Allelic Discrimination Assay. Hispanics had higher levels of TAM, 4-hydroxytamoxifen, and endoxifen than NHWs. There was a higher prevalence of CYP2D6 EM within Hispanics than NHWs, which corresponded to higher endoxifen levels, but no differences were verified with regard to CYP2C9 and SULT1A1. We found a higher incidence of the wild type forms of the ESR1 in Hispanics than NHWs. The performance status, the disease stage at diagnosis, and the use of aromatase inhibitors might have overcome the overall favorable pharmacogenomics profile of Hispanics when compared to NHWs in relation to TAM therapy responsiveness. Our data strongly point to ethnical peculiarities related to pharmacogenomics and demographic features of TAM treated Hispanics and NHWs. In the era of pharmacogenomics and its ultimate goal of individualized, efficacious and safe therapy, cancer studies focused on the Hispanic population are warranted because this is the fastest growing major demographic group, and an understudied segment in the U.S.