Therapeutic drug monitoring of tamoxifen using LC-MS/MS

An Optimized LC-MS/MS Method for Quantification of Sunitinib and N -Desethyl Sunitinib in Human Plasma and Its Application for Therapeutic Drug Monitoring

BACKGROUND

Sunitinib (SUN) malate is an oral, multitargeted, tyrosine kinase inhibitor approved for the treatment of metastatic renal cell carcinoma, imatinib-resistant or imatinib-intolerant gastrointestinal stromal tumors, and pancreatic neuroendocrine tumors. SUN has a narrow therapeutic window and high variability in interpatient pharmacokinetic parameters. Clinical detection methods for SUN and N -desethyl SUN limit the application of SUN to therapeutic drug monitoring. All published methods for quantifying SUN in human plasma require strict light protection to avoid light-induced isomerism or the use of additional quantitative software. To avoid these difficult processes in clinical routines, the authors propose a novel method that merges the peaks of the E -isomer and Z -isomer of SUN or N -desethyl SUN into a single peak.

METHODS

The E -isomer and Z -isomer peaks of SUN or N -desethyl SUN were merged into a single peak by optimizing the mobile phases to decrease the resolution of the isomers. A suitable chromatographic column was selected to obtain a good peak shape. Thereafter, the conventional and single-peak methods (SPM) were simultaneously validated and compared according to the guidelines published by the Food and Drug Administration in 2018 and the Chinese Pharmacopoeia in 2020.

RESULTS

The verification results showed that the SPM was superior to the conventional method in the matrix effect and met the requirements for biological sample analysis. SPM was then applied to detect the total steady-state concentration of SUN and N -desethyl SUN in tumor patients who received SUN malate.

CONCLUSIONS

The established SPM makes the detection of SUN and N -desethyl SUN easier and faster without light protection or extra quantitative software, making it more appropriate for routine clinical use. The clinical application results showed that 12 patients took 37.5 mg per day, with a median total trough steady-state concentration of 75.0 ng/mL.

Limitations of Tamoxifen Application for In Vivo Genome Editing Using Cre/ERT2 System

Inducible Cre-dependent systems are frequently used to produce both conditional knockouts and transgenic mice with regulated expression of the gene of interest. Induction can be achieved by doxycycline-dependent transcription of the wild type gene or OH-tamoxifen-dependent nuclear translocation of the chimeric Cre/ER^T2 protein. However, both of these activation strategies have some limitations. We analyzed the efficiency of knockout in different tissues and found out that it correlates with the concentration of the hydroxytamoxifen and endoxifen-the active metabolites of tamoxifen-measured by LC-MS in these tissues. We also describe two cases of Cdk8^{floxed/floxed}/Rosa-Cre-ER^T2 mice tamoxifen-induced knockout limitations. In the first case, the standard scheme of tamoxifen administration does not lead to complete knockout formation in the brain or in the uterus. Tamoxifen metabolite measurements in multiple tissues were performed and it has been shown that low recombinase activity in the brain is due to the low levels of tamoxifen active metabolites. Increase of tamoxifen dosage (1.5 fold) and duration of activation (from 5 to 7 days) allowed us to significantly improve the knockout rate in the brain, but not in the uterus. In the second case, knockout induction during embryonic development was impossible due to the negative effect of tamoxifen on gestation. Although DNA editing in the embryos was achieved in some cases, the treatment led to different complications of the pregnancy in wild-type female mice. We propose to use doxycycline-induced Cre systems in such models.

Volumetric Absorptive Microsampling as a New Biosampling Tool for Monitoring of Tamoxifen, Endoxifen, 4-OH Tamoxifen and N-Desmethyltamoxifen in Breast Cancer Patients

INTRODUCTION

In this research, we used a volumetric absorptive microsampling (VAMS) technique to collect blood samples from the patients. A rapid and simple sample preparation method and LC-MS.MS assay was then developed and validated for the simultaneous analysis of tamoxifen and its three active metabolites.

METHODS

VAMS extraction was performed in methanol by sonication-assisted extraction method for 25 min after 2 hof VAMS drying. Separation was carried out using Acquity UPLC BEH C18 column (2.1 x 100 mm; 1.7 µm), with a flow rate of 0.2 mL/min, and the mobile phase gradient of formic acid 0.1% and formic acid 0.1% in acetonitrile for 5 min. The multiple reaction monitoring (MRM) values were set at m/z 358.31>58.27 for N-desmethyltamoxifen, m/z 372.33>72.28 for tamoxifen, m/z 388.22>72.28 for 4-hydroxytamoxifen, m/z 374.25>58.25 for endoxifen, and m/z 260.26>116.12 for propranolol.

RESULTS AND DISCUSSION

The lower limit of quantification value (LLOQ) was 2.50 ng/mL for tamoxifen, 2.50 ng/mL for endoxifen, 1.50 ng/mL for 4-hydroxitamoxifen, and 2.00 ng/mL for N-desmethyltamoxifen. Accuracy (%bias) and precision (%CV) were within 20% for LLOQ and 15% for other concentrations. There were no interference responses >20% of the LLOQ and 5% of the internal standard. The level of ion suppression in all analytes was less than 7%. The preparation system developed in this study successfully extracted more than 90% of analytes from the matrix with precision below 15%. Carryover was shown to be below 6% in all analytes. Stability of analytes in VAMS was demonstrated for up to 30 days, under room temperature storage in a sealed plastic bag with desiccant. This method was successfully applied to analyze tamoxifen and the metabolites level in 30 ER+ breast cancer patients.

Comparison of Population Pharmacokinetics Based on Steady-State Assumption Versus Electronically Monitored Adherence to Lopinavir, Atazanavir, Efavirenz, and Etravirine: A Retrospective Study

BACKGROUND

Population pharmacokinetic (PopPK) analyses often rely on steady state and full adherence to prescribed dosage regimen assumptions from data gathered during therapeutic drug monitoring (TDM). Nonadherence is common in chronic diseases such as HIV. This study evaluates the impact of adherence measurement by electronic monitoring on PopPK parameter estimation and individual concentration profile predictions, and also the influence of adherence issues on the clinical interpretation of a concentration measurement.

METHODS

Published PopPK models for lopinavir, atazanavir, efavirenz, and etravirine were applied to estimate PK parameters and individual concentrations in 140 HIV patients taking part in a medication adherence program using 2 dosing data sets. The first set included the last dose reported by the patient with steady-state and full adherence assumptions; the second set used detailed electronic dosing history. PopPK parameter estimates and individual predictions were compared between the 2 dosing entries.

RESULTS

Clearance estimates and likewise predicted concentrations did not markedly differ between the 2 dosing histories. However, certain patterns of nonadherence such as sparse missed doses or consecutive missed doses lead to suboptimal drug exposure. The interpretation based on self-reported information would have concluded on a wrongly appropriate individual exposure.

CONCLUSIONS

PopPK analysis assuming steady state with full adherence produced similar results to those based on detailed electronic dosing history reconciled with patients' allegations. Self-reported last dose intake appeared reliable for concentration predictions and therapeutic drug monitoring interpretation for most patients followed at the medication adherence program. Yet, clinicians should be aware that concentration predictions based on self-reported last dose intake might be overestimated in case of undetected patterns of nonadherence, increasing the risk of forthcoming therapeutic failure.

Estimation of tamoxifen metabolite concentrations in the blood of breast cancer patients through CYP2D6 genotype activity score

Tamoxifen, a prodrug used for adjuvant breast cancer therapy, requires conversion to the active metabolite endoxifen through CYP 2D6. We aimed to construct an algorithm to predict endoxifen concentrations based on a patient’s CYP 2D6 genotype, demographic factors, and co-medication use. Eighty-eight women enrolled in the UCSF TamGen II study and 81 women enrolled in a prospective study at Dana-Farber Cancer Institute were included in this analysis. All the women had been on tamoxifen for at least 3 months before blood collection. Demographic information included the patient’s age, race/ethnicity, body mass index (where available), and self-reported and measured medications and herbals that affect 2D6 activity. DNA was extracted and genotyped for 2D6 (Amplichip, Roche Diagnostics). An activity score was calculated based on genotypes and adjusted for use of medications known to inhibit 2D6. Serum was tested for tamoxifen and metabolite concentrations and for the presence of drugs by liquid chromatography/mass spectrometry. Univariate and multivariate regression analysis were computed for age, body mass index, ethnicity, and adjusted activity score to predict tamoxifen metabolite concentrations in the training data-set of UCSF patients, and the resulting algorithm was validated in the Dana-Farber patients. For the training set, the correlation coefficient (r2) for log endoxifen and N-desmethyltamoxifen:endoxifen ratio to activity score, age, and race, were 0.520 and 0.659, respectively; 0.324 and 0.567 for the validation; and 0.396 and 0.615 for both the datasets combined. An algorithm that incorporates genotype and demographic variables can be used to predict endoxifen concentrations for women on tamoxifen therapy. If endoxifen levels are confirmed to be predictive of tamoxifen benefit, then this algorithm may be helpful to determine which women warrant endoxifen testing.