Drug-drug interactions with tyrosine-kinase inhibitors:A clinical perspective

In the past decade, many tyrosine-kinase inhibitors have been introduced in oncology and haemato-oncology. Because this new class of drugs is extensively used, serious drug-drug interactions are an increasing risk. In this Review, we give a comprehensive overview of known or suspected drug-drug interactions between tyrosine-kinase inhibitors and other drugs. We discuss all haemato-oncological and oncological tyrosine-kinase inhibitors that had been approved by Aug 1, 2013, by the US Food and Drug Administration or the European Medicines Agency. Various clinically relevant drug interactions with tyrosine-kinase inhibitors have been identified. Most interactions concern altered bioavailability due to altered stomach pH, metabolism by cytochrome P450 isoenzymes, and prolongation of the QTc interval. To guarantee the safe use of tyrosine-kinase inhibitors, a drugs review for each patient is needed. This Review provides specific recommendations to guide haemato-oncologists, oncologists, and clinical pharmacists, through the process of managing drug-drug interactions during treatment with tyrosine-kinase inhibitors in daily clinical practice

A phase I dose-escalation and pharmacokinetic study of a micellar nanoparticle with entrapped docetaxel (CPC634) in patients with advanced solid tumours

Background: CPC634 is docetaxel entrapped in core-cross linked polymeric micelles. In preclinical studies, CPC634 demonstrated enhanced pharmacokinetics and improved therapeutic index. This phase I dose escalation study is the first-in-human study with CPC634. Methods: adult patients with advanced solid tumours received CPC634 intravenously either 3-weekly (Q3W) (part 1, dose range 15–100 mg/m2 ), 2-weekly (Q2W) (part 2, 45 mg/m2 ) or Q3W with dexamethasone premedication (part 3, 60 mg/m2 ). Results: thirty-three patients were enrolled. Skin toxicity was dose limiting (DLT) at ≥60 mg/m2 in part 1 and at 45 mg/m2 in part 2 and was the most common CPC634 related grade ≥ 3 adverse event (24%). With dexamethasone premedication no DLTs were observed at 60 mg/m2 Q3W. CPC634 exhibited a dose-proportional\ud pharmacokinetic profile. At 60 mg/m2 , the plasma area under the curve was 4067.5 ± 2974.0 ng/h/mL and the peak plasma level 217.3 ± 91.9 ng/mL with a half-life of 39.7 ± 9.4 h for released docetaxel. Conclusion: CPC634 could be administered safely upon pretreatment with dexamethasone. Cumulative skin toxicity was the main DLT. The recommended phase 2 dose was determined at 60 mg/m2 Q3W with dexamethasone premedication

Integrated Data Analysis of Six Clinical Studies Points Toward Model-Informed Precision Dosing of Tamoxifen

Introduction: At tamoxifen standard dosing, ∼20% of breast cancer patients do not reach proposed target endoxifen concentrations >5.97 ng/mL. Thus, better understanding the large interindividual variability in tamoxifen pharmacokinetics (PK) is crucial. By applying non-linear mixed-effects (NLME) modeling to a pooled ‘real-world’ clinical PK database, we aimed to (i) dissect several levels of variability and identify factors predictive for endoxifen exposure and (ii) assess different tamoxifen dosing strategies for their potential to increase the number of patients reaching target endoxifen concentrations. Methods: Tamoxifen and endoxifen concentrations with genetic and demographic data of 468 breast cancer patients from six reported studies were used to develop a NLME parent-metabolite PK model. Different levels of variability on model parameters or measurements were investigated and the impact of covariates thereupon explored. The model was subsequently applied in a simulation-based comparison of three dosing strategies with increasing degree of dose individualization for a large virtual breast cancer population. Interindividual variability of endoxifen concentrations and the fraction of patients at risk for not reaching target concentrations were assessed for each dosing strategy. Results and Conclusions: The integrated NLME model enabled to differentiate and quantify four levels of variability (interstudy, interindividual, interoccasion, and intraindividual). Strong influential factors, i.e., CYP2D6 activity score, drug–drug interactions with CYP3A and CYP2D6 inducers/inhibitors and age, were reliably identified, reducing interoccasion variability to <20% CV. Yet, unexplained interindividual variability in endoxifen formation remained large (47.2% CV). Hence, therapeutic drug monitoring seems promising for achieving endoxifen target concentrations. Three tamoxifen dosing strategies [standard dosing (20 mg QD), CYP2D6-guided dosing (20, 40, and 60 mg QD) and individual model-informed precision dosing (MIPD)] using three therapeutic drug monitoring samples (5–120 mg QD) were compared, leveraging the model. The proportion of patients at risk for not reaching target concentrations was 22.2% in standard dosing, 16.0% in CYP2D6-guided dosing and 7.19% in MIPD. While in CYP2D6-guided- and standard dosing interindividual variability in endoxifen concentrations was high (64.0% CV and 68.1% CV, respectively), it was considerably reduced in MIPD (24.0% CV). Hence, MIPD demonstrated to be the most promising strategy for achieving target endoxifen concentrations

Taste, smell and mouthfeel disturbances in patients with gastrointestinal stromal tumors treated with tyrosine-kinase inhibitors

CONTEXT: Taste, smell, and mouthfeel disturbances are underrated and underreported, but important side effects of anti-cancer medication. These symptoms are associated with a lower quality of life (QoL). The prevalence and the impact of taste, smell, and mouthfeel disturbances on daily life in patients with a gastrointestinal stromal tumor (GIST) are largely unknown. OBJECTIVES: This exploratory study assessed the prevalence and type of taste, smell, and mouthfeel disturbances and their impact on daily life and QoL in patients with a GIST treated with a tyrosine-kinase inhibitor (TKI). METHODS: Patients currently treated with TKIs for GIST completed a standardized questionnaire. The questionnaire addressed changes in taste, smell, and mouthfeel and, if changes occurred, impact on daily life and QoL. Statistics are descriptive. RESULTS: A total of 65 GIST patients on TKI treatment completed the questionnaire. Of these patients, 79%, 12%, and 9% currently used imatinib, sunitinib, and regorafenib respectively. Taste, smell, and mouthfeel disturbances were reported by 25 (38%), 15 (23%), and 36 (55%) patients respectively. Salty and sweet tastes were mostly affected, respectively in 14 and 13 patients. A dry mouth was experienced by 29 (45%) patients. Taste disturbances were more often reported to have impact on daily life and QoL (80% and 60%) than smell (47% and 31%) and mouthfeel disturbances (47% and 30%). CONCLUSION: Taste, smell, and mouthfeel disturbances are frequent side effects of TKIs in GIST patients. Daily life and QoL are affected in a considerable number of those patients. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NL7827 (2019-06-25)

Clinical implications of food-drug interactions with small-molecule kinase inhibitors

During the past two decades, small-molecule kinase inhibitors have proven to be valuable in the treatment of solid and haematological tumours. However, because of their oral administration, the intrapatient and interpatient exposure to small-molecule kinase inhibitors (SMKIs) is highly variable and is affected by many factors, such as concomitant use of food and herbs. Food-drug interactions are capable of altering the systemic bioavailability and pharmacokinetics of these drugs. The most important mechanisms underlying food-drug interactions are gastrointestinal drug absorption and hepatic metabolism through cytochrome P450 isoenzymes. As food-drug interactions can lead to therapy failure or severe toxicity, knowledge of these interactions is essential. This Review provides a comprehensive overview of published studies involving food-drug interactions and herb-drug interactions for all registered SMKIs up to Oct 1, 2019. We critically discuss US Food and Drug Administration (FDA) and European Medicines Agency (EMA) guidelines concerning food-drug interactions and offer clear recommendations for their management in clinical practice

Clinical Utility of Circulating Tumor DNA in Patients With Advanced KRAS^G12C-Mutated NSCLC Treated With Sotorasib

Introduction: For patients with KRASG12C-mutated NSCLC who are treated with sotorasib, there is a lack of biomarkers to guide treatment decisions. We therefore investigated the clinical utility of pretreatment and on-treatment circulating tumor DNA (ctDNA) and treatment-emergent alterations on disease progression. Methods: Patients with KRASG12C-mutated NSCLC treated with sotorasib were prospectively enrolled in our biomarker study (NCT05221372). Plasma samples were collected before sotorasib treatment, at first-response evaluation and at disease progression. The TruSight Oncology 500 panel was used for ctDNA and variant allele frequency analysis. Tumor response and progression-free survival were assessed per Response Evaluation Criteria in Solid Tumors version 1.1. Results: Pretreatment KRASG12C ctDNA was detected in 50 of 66 patients (76%). Patients with detectable KRASG12C had inferior progression-free survival (hazard ratio [HR] 2.13 [95% confidence interval [CI]: 1.06–4.30], p = 0.031) and overall survival (HR 2.61 [95% CI: 1.16–5.91], p = 0.017). At first-response evaluation (n = 40), 29 patients (73%) had a molecular response. Molecular nonresponders had inferior overall survival (HR 3.58 [95% CI: 1.65–7.74], p = 0.00059). The disease control rate was significantly higher in those with a molecular response (97% versus 64%, p = 0.015). KRAS amplifications were identified as recurrent treatment-emergent alterations. Conclusions: Our data suggest detectable pretreatment KRASG12C ctDNA as a marker for poor prognosis and on-treatment ctDNA clearance as a marker for treatment response. We identified KRAS amplifications as a potential recurring resistance mechanism to sotorasib. Identifying patients with superior prognosis could aid in optimizing time of treatment initiation, and identifying patients at risk of early progression could allow for earlier treatment decisions.</p

Effects of methimazole on the elimination of irinotecan

Purpose: To study the possible pharmacokinetic and pharmacodynamic interactions between irinotecan and methimazole. Methods: A patient treated for colorectal cancer with single agent irinotecan received methimazole co-medication for Graves' disease. Irinotecan pharmacokinetics and side effects were followed during a total of four courses (two courses with and two courses without methimazole). Results: Plasma concentrations of the active irinotecan metabolite SN-38 and its inactive metabolite SN-38-Glucuronide were both higher (a mean increase of 14 and 67%, respectively) with methimazole co-medication, compared to irinotecan monotherapy. As a result, the mean SN-38 glucuronidation rate increased with 47% during concurrent treatment. Other possible confounding factors did not change over time. Specific adverse events due to methimazole co-treatment were not seen. Conclusions: Additional in vitro experiments suggest that these results can be explained by induction of UGT1A1 by methimazole, leading to higher SN-38G concentrations. The prescribed combination of these drugs may lead to highly toxic intestinal SN-38 levels. We therefore advise physicians to be very careful in combining methimazole with regular irinotecan doses, especially in patients who are prone to irinotecan toxicity

Meta-analysis on the association of VEGFR1 genetic variants with sunitinib outcome in metastatic renal cell carcinoma patients

VEGFR1 rs9582036 and rs9554320 were previously reported the association with sunitinib progression-free survival (PFS) and overall survival (OS) in patients with metastatic renal cell carcinoma (mRCC). Hereafter, the association of both single nucleotide polymorphisms (SNPs) with PFS/OS was confirmed in two independent mRCC cohorts. The aim of the current study was to validate the associations of both SNPs with sunitinib outcome in three independent well-characterized cohorts (SUTOX, CCF and SOGUG) including 286 sunitinib-treated mRCC patients, as well as to perform a meta-analysis of current and published data combined. We found that rs9582036 and rs9554320 showed a significant association with sunitinib PFS in the CCF cohort (HR: 0.254, 95%CI: 0.092-0.703; P=0.008 and HR: 0.430, 95%CI: 0.200- 0.927