Influence of CYP3A4 inhibition on the steady-state pharmacokinetics of imatinib

Physiologically based pharmacokinetic modeling of imatinib and N-desmethyl imatinib for drug-drug interaction predictions

The first-generation tyrosine kinase inhibitor imatinib has revolutionized the development of targeted cancer therapy and remains among the frontline treatments, for example, against chronic myeloid leukemia. As a substrate of cytochrome P450 (CYP) 2C8, CYP3A4, and various transporters, imatinib is highly susceptible to drug-drug interactions (DDIs) when co-administered with corresponding perpetrator drugs. Additionally, imatinib and its main metabolite N-desmethyl imatinib (NDMI) act as inhibitors of CYP2C8, CYP2D6, and CYP3A4 affecting their own metabolism as well as the exposure of co-medications. This work presents the development of a parent-metabolite whole-body physiologically based pharmacokinetic (PBPK) model for imatinib and NDMI used for the investigation and prediction of different DDI scenarios centered around imatinib as both a victim and perpetrator drug. Model development was performed in PK-Sim® using a total of 60 plasma concentration-time profiles of imatinib and NDMI in healthy subjects and cancer patients. Metabolism of both compounds was integrated via CYP2C8 and CYP3A4, with imatinib additionally transported via P-glycoprotein. The subsequently developed DDI network demonstrated good predictive performance. DDIs involving imatinib and NDMI were simulated with perpetrator drugs rifampicin, ketoconazole, and gemfibrozil as well as victim drugs simvastatin and metoprolol. Overall, 12/12 predicted DDI area under the curve determined between first and last plasma concentration measurements (AUClast) ratios and 12/12 predicted DDI maximum plasma concentration (Cmax) ratios were within twofold of the respective observed ratios. Potential applications of the final model include model-informed drug development or the support of model-informed precision dosing.

Pharmacokinetic Interaction Between Imatinib and Metformin in Rats

BACKGROUND AND OBJECTIVE

Imatinib is primarily transported into the liver by organic cation transporter 1 (OCT1), organic anion transporting polypeptide 1B3 (OATP1B3), and novel organic cation transporter 2 (OCTN2), which is the first step in the metabolic and elimination of imatinib. Patients taking imatinib may concurrently take metformin, a substrate for OCT1. Drug-drug interactions (DDI) may occur between imatinib and metformin, affecting the clinical efficacy of imatinib. This experiment aimed to investigate the pharmacokinetic effects of metformin on imatinib and its active metabolism of N-desmethyl imatinib in rats.

METHODS

Twenty healthy Sprague-Dawley rats were selected and randomly divided into control and experimental groups (10 rats per group). The control group was orally administered imatinib (30 mg/kg) for 14 days, and the experimental group was orally co-administered imatinib (30 mg/kg) and metformin (200 mg/kg) for 14 days. The plasma concentrations of imatinib and N-desmethyl imatinib in rats were determined by ultra-performance liquid chromatography-mass spectrometry. Pharmacokinetic parameters were calculated by DAS2.0 software.

RESULTS

After single-dose co-administration of imatinib and metformin on day 1, the AUC0-24 (area under the plasma concentration-time curve) and Cmax (maximum concentration) of imatinib and the MRT (mean residence time) and Cmax of N-desmethyl imatinib in the experimental group were significantly decreased compared with the control group (P < 0.05). After multiple-dose co-administration of imatinib and metformin for 14 days, the AUC0-24 and Cmax of both imatinib and N-desmethyl imatinib were significantly decreased in the experimental group (P < 0.05).

CONCLUSION

With both single and multiple co-administration doses, metformin significantly changed the pharmacokinetic parameters of imatinib and N-desmethyl imatinib. The results suggest that care should be taken when metformin and imatinib are co-administered.

Clinical pharmacokinetics and drug-drug interactions of tyrosine-kinase inhibitors in chronic myeloid leukemia: A clinical perspective

In the past decade, numerous tyrosine kinase inhibitors (TKIs) have been introduced in the treatment of chronic myeloid leukemia. Given the significant interpatient variability in TKIs pharmacokinetics, potential drug-drug interactions (DDIs) can greatly impact patient therapy. This review aims to discuss the pharmacokinetic characteristics of TKIs, specifically focusing on their absorption, distribution, metabolism, and excretion profiles. Additionally, it provides a comprehensive overview of the utilization of TKIs in special populations such as the elderly, children, and patients with liver or kidney dysfunction. We also highlight known or suspected DDIs between TKIs and other drugs, highlighting various clinically relevant interactions. Moreover, specific recommendations are provided to guide haemato-oncologists, oncologists, and clinical pharmacists in managing DDIs during TKI treatment in daily clinical practice.

Unique Cabozantinib Dosing Considerations in People Living with HIV and Cancer

A recent article characterized dosing recommendations for cabozantinib in people living with HIV (PLWH) and cancer, a group that is often excluded from clinical trials. This study suggests cabozantinib is effective in cancers disproportionately impacting PLWH and has translational implications for the design of studies evaluating drug-drug interactions. See related article by Haigentz et al., p. 5038.

CYP3A4*22 Genotype-Guided Dosing of Kinase Inhibitors in Cancer Patients

INTRODUCTION

A genetic variant explaining a part of the exposure of many kinase inhibitors (KIs) is the single nucleotide polymorphism (SNP) CYP3A4*22, resulting in less CYP3A4 enzyme activity. The primary aim of this study was to investigate if the systemic exposure is non-inferior after a dose reduction of KIs metabolized by CYP3A4 in CYP3A4*22 carriers compared to patients without this SNP (i.e., wildtype patients) receiving the standard dose.

METHODS

In this multicenter, prospective, non-inferiority study, patients were screened for the presence of CYP3A4*22. Patients with the CYP3A4*22 SNP received a 20-33% dose reduction. At steady state, a pharmacokinetic (PK) analysis was performed and compared to the PK results from wildtype patients treated with the registered dose using a two-stage individual patient data meta-analysis approach.

RESULTS

In total, 207 patients were included in the final analysis. The CYP3A4*22 SNP was found in 16% of the patients in the final analysis (n = 34). Most of the included patients received imatinib (37%) or pazopanib (22%) treatment. The overall geometric mean ratio (GMR) comparing the exposure of the CYP3A4*22 carriers to the exposure of the wildtype CYP3A4 patients was 0.89 (90% confidence interval: 0.77-1.03).

CONCLUSION

Non-inferiority could not be proven for dose reduction of KIs metabolized by CYP3A4 in CYP3A4*22 carriers compared to the registered dose in wildtype patients. Therefore, an up-front dose reduction based upon the CYP3A4*22 SNP for all KIs does not seem an eligible new way of personalized therapy.

TRIAL REGISTRATION

International Clinical Trials Registry Platform Search Portal; number NL7514; registered 11/02/2019.

Population pharmacokinetic modelling of imatinib in healthy subjects receiving a single dose of 400 mg

Purpose

Imatinib is indicated for treatment of CML, GIST, etc. The population pharmacokinetics (popPK) of imatinib in patients under long-term treatment are reported in literature. Data obtained from bioequivalence trials for healthy subjects were used to evaluate the influence of demographic and pharmacogenetic factors on imatinib pharmacokinetics (PK) in a collective without concurrent drugs, organ dysfunction, inflammation etc. In addition, the differences in PK between the healthy subjects and a patient cohort was examined to identify possible disease effects.

Methods

26 volunteers were administered orally with single dose of 400 mg imatinib. 16–19 plasma samples per volunteer were collected from 0.5 up to 72 h post-dose. The popPK was built and post hoc estimates were compared with previously published PK parameters evaluated by non-compartmental analysis in the same cohort. The predictivity of the model for data collected from 40 patients with gastrointestinal stromal tumors at steady state was evaluated.

Results

The popPK was best described by a two-compartment transit model with first-order elimination. No significant covariates were identified, probably due to the small cohort and the narrow range of demographic covariates; CYP3A5 phenotypes appeared to have some influence on the clearance of imatinib. Good agreement between non-compartment and popPK analyses was observed with the differences of the geometric means/ median of PK estimates below 10%. The model indicated lower clearance for patients compared to healthy volunteers (p value < 0.01).

Conclusion

The two-compartment transit model adequately describes the absorption and distribution of imatinib in healthy volunteers. For patients, a lower clearance of imatinib compared to healthy volunteer was estimated by the model. The model can be applied for dose individualization based on trough concentrations assuming no significant differences in absorption between patients and healthy volunteers.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00280-022-04454-y.

Physiologically-Based Pharmacokinetic Modeling Approaches for Patients with SARS-CoV-2 Infection: A Case Study with Imatinib

Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) infection, which causes coronavirus disease 2019 (COVID‐19), manifests as mild respiratory symptoms to severe respiratory failure and is associated with inflammation and other physiological changes. Of note, substantial increases in plasma concentrations of α₁‐acid‐glycoprotein and interleukin‐6 have been observed among patients admitted to the hospital with advanced SARS‐CoV‐2 infection. A physiologically based pharmacokinetic (PBPK) approach is a useful tool to evaluate and predict disease‐related changes on drug pharmacokinetics. A PBPK model of imatinib has previously been developed and verified in healthy people and patients with cancer. In this study, the PBPK model of imatinib was successfully extrapolated to patients with SARS‐CoV‐2 infection by accounting for disease‐related changes in plasma α₁‐acid‐glycoprotein concentrations and the potential drug interaction between imatinib and dexamethasone. The model demonstrated a good predictive performance in describing total and unbound imatinib concentrations in patients with SARS‐CoV‐2 infection. PBPK simulations highlight that an equivalent dose of imatinib may lead to substantially higher total drug concentrations in patients with SARS‐CoV‐2 infection compared to that in patients with cancer, while the unbound concentrations remain comparable between the 2 patient populations. This supports the notion that unbound trough concentration is a better exposure metric for dose adjustment of imatinib in patients with SARS‐CoV‐2 infection, compared to the corresponding total drug concentration. Potential strategies for refinement and generalization of the PBPK modeling approach in the patient population with SARS‐CoV‐2 are also provided in this article, which could be used to guide study design and inform dose adjustment in the future.

Synthesis of benzimidazole/triphenylamine-based compounds, evaluation of their bioactivities and an in silico study with receptor tyrosine kinases

The antiproliferative activity of AL-1 against various cancer cells indicated the applicability of the BI-TPA-based compound as a potential multi-cancer inhibitor.

External evaluation of population pharmacokinetic models of imatinib in adults diagnosed with chronic myeloid leukaemia

AIMS

Imatinib is considered the standard first-line treatment in newly diagnosed patients with chronic-phase myeloid leukaemia (CML). Several imatinib population pharmacokinetic (popPK) models have been developed. However, their predictive performance has not been well established when extrapolated to different populations. Therefore, this study aimed to perform an external evaluation of available imatinib popPK models developed mainly in adult patients, and to evaluate the improvement in individual model-based predictions through Bayesian forecasting computed by each model at different treatment occasions.

METHODS

A literature review was conducted through PubMed and Scopus to identify popPK models. Therapeutic drug monitoring data collected in adult CML patients treated with imatinib was used for external evaluation, including prediction- and simulated-based diagnostics together with Bayesian forecasting analysis.

RESULTS

Fourteen imatinib popPK studies were included for model-performance evaluation. A total of 99 imatinib samples were collected from 48 adult CML patients undergoing imatinib treatment with a minimum of one plasma concentration measured at steady-state between January 2016 and December 2020. The model proposed by Petain et al showed the best performance concerning prediction-based diagnostics in the studied population. Bayesian forecasting demonstrated a significant improvement in predictive performance at the second visit. Inter-occasion variability contributed to reducing bias and improving individual model-based predictions.

CONCLUSIONS

Imatinib popPK studies developed in Caucasian subjects including α1-acid glycoprotein showed the best model performance in terms of overall bias and precision. Moreover, two imatinib samples from different visits appear sufficient to reach an adequate model-based individual prediction performance trough Bayesian forecasting.

Elevated acute phase proteins affect pharmacokinetics in COVID-19 trials: Lessons from the CounterCOVID - imatinib study

This study aimed to determine whether published pharmacokinetic (PK) models can adequately predict the PK profile of imatinib in a new indication, such as coronavirus disease 2019 (COVID‐19). Total (bound + unbound) and unbound imatinib plasma concentrations obtained from 134 patients with COVID‐19 participating in the CounterCovid study and from an historical dataset of 20 patients with gastrointestinal stromal tumor (GIST) and 85 patients with chronic myeloid leukemia (CML) were compared. Total imatinib area under the concentration time curve (AUC), maximum concentration (C_max) and trough concentration (C_trough) were 2.32‐fold (95% confidence interval [CI] 1.34–3.29), 2.31‐fold (95% CI 1.33–3.29), and 2.32‐fold (95% CI 1.11–3.53) lower, respectively, for patients with CML/GIST compared with patients with COVID‐19, whereas unbound concentrations were comparable among groups. Inclusion of alpha1‐acid glycoprotein (AAG) concentrations measured in patients with COVID‐19 into a previously published model developed to predict free imatinib concentrations in patients with GIST using total imatinib and plasma AAG concentration measurements (AAG‐PK‐Model) gave an estimated mean (SD) prediction error (PE) of −20% (31%) for total and −7.0% (56%) for unbound concentrations. Further covariate modeling with this combined dataset showed that in addition to AAG; age, bodyweight, albumin, CRP, and intensive care unit admission were predictive of total imatinib oral clearance. In conclusion, high total and unaltered unbound concentrations of imatinib in COVID‐19 compared to CML/GIST were a result of variability in acute phase proteins. This is a textbook example of how failure to take into account differences in plasma protein binding and the unbound fraction when interpreting PK of highly protein bound drugs, such as imatinib, could lead to selection of a dose with suboptimal efficacy in patients with COVID‐19.

Healthy volunteers in first-in-human oncology drug development for small molecules

This review provides tools to consider the inclusion of healthy volunteers (HVs) in first-in-human (FIH) oncology clinical trials with small molecules, including targeted and immunomodulatory agents, a strategy that was not envisioned with classic chemotherapy. To enable an FIH oncology trial in HVs compared to cancer patients (CPs), a robust nonclinical package must be generated, which includes toxicokinetic and pharmacokinetic studies, as well as more extensive safety pharmacology, toxicology and genotoxicity studies. This strategy could provide an early clinical characterization of the pharmacokinetic parameters and clinical safety profile in the absence of comorbidities and concomitant medication. It also avoids the ethical issue of administrating subtherapeutic doses to CPs, and could potentially help to accelerate the timelines of clinical drug development for patient care. That being said, stakeholders involved in these studies need to proceed with caution, fully understand the regulatory guidance and thoroughly evaluate the benefits and risks. This paper serves to address the regulatory guidance and other considerations needed when using healthy volunteers in early oncology trials.

A Review of CYP3A Drug-Drug Interaction Studies: Practical Guidelines for Patients Using Targeted Oral Anticancer Drugs

Many oral anticancer drugs are metabolized by CYP3A. Clinical drug-drug interaction (DDI) studies often only examine the effect of strong CYP3A inhibitors and inducers. The effect of moderate or weak inhibitors or inducers can be examined using physiologically based pharmacokinetic simulations, but data from these simulations are not always available early after approval of a drug. In this review we provide recommendations for clinical practice on how to deal with DDIs of oral anticancer drugs if only data from strong CYP3A inhibitors or inducers is available. These recommendations were based on reviewed data of oral anticancer drugs primarily metabolized by CYP3A and approved for the treatment of solid tumors from January 1st, 2013 to December 31st, 2015. In addition, three drugs that were registered before the new EMA guideline was issued (i.e., everolimus, imatinib, and sunitinib), were reviewed. DDIs are often complex, but if no data is available from moderate CYP3A inhibitors/inducers, a change in exposure of 50% compared with strong inhibitors/inducers can be assumed. No a priori dose adaptations are indicated for weak inhibitors/inducers, because their interacting effect is small. In case pharmacologically active metabolites are involved, the metabolic pathway, the ratio of the parent to the metabolites, and the potency of the metabolites should be taken into account.

Physiologically-based pharmacokinetic model predictions of inter-ethnic differences in imatinib pharmacokinetics and dosing regimens

AIMS

This study implements a physiologically-based pharmacokinetic (PBPK) modelling approach to investigate inter-ethnic differences in imatinib pharmacokinetics and dosing regimens.

METHODS

A PBPK model of imatinib was built in the Simcyp Simulator (version 17) integrating in vitro drug metabolism and clinical pharmacokinetic data. The model accounts for ethnic differences in body size and abundance of drug-metabolising enzymes and proteins involved in imatinib disposition. Utility of this model for prediction of imatinib pharmacokinetics was evaluated across different dosing regimens and ethnic groups. The impact of ethnicity on imatinib dosing was then assessed based on the established range of trough concentrations (C_ss,min ).

RESULTS

The PBPK model of imatinib demonstrated excellent predictive performance in describing pharmacokinetics and the attained C_ss,min in patients from different ethnic groups, shown by prediction differences that were within 1.25-fold of the clinically-reported values in published studies. PBPK simulation suggested a similar dose of imatinib (400-600 mg/d) to achieve the desirable range of C_ss,min (1000-3200 ng/mL) in populations of European, Japanese and Chinese ancestry. The simulation indicated that patients of African ancestry may benefit from a higher initial dose (600-800 mg/d) to achieve imatinib target concentrations, due to a higher apparent clearance (CL/F) of imatinib compared to other ethnic groups; however, the clinical data to support this are currently limited.

CONCLUSION

PBPK simulations highlighted a potential ethnic difference in the recommended initial dose of imatinib between populations of European and African ancestry, but not populations of Chinese and Japanese ancestry.

Distribution of alleles, genotypes and haplotypes of the CYP2B6 (rs3745274; rs2279343) and CYP3A4 (rs2740574) genes in the Malian population: Implication for pharmacogenetics

Cytochrome P450 enzymes play a central role in the phase I biotransformation process of a wide range of compounds, including xenobiotics, drugs, hormones and vitamins. It is noteworthy that these enzymes are highly polymorphic and, depending on the genetic makeup, an individual may have impaired enzymatic activity. Therefore, the identification of genetic variants in these genes could facilitate the implementation of pharmacogenetic studies and genetic predisposition to multifactorial diseases. We have established the frequencies of CYP2B6 (rs3745274; rs2279343) and CYP3A4 (rs2740574) alleles and genotypes in 209 healthy Malian subjects using TaqMan drug metabolism genotyping assays for allelic discrimination. Allele frequencies were 37% for CYP2B6 rs3745274; 38% for CYP2B6 rs2279343; and 75% for CYP3A4 rs2740574 respectively. Overall, the frequencies observed in Mali are statistically comparable to those reported across Africa except North Africa. The major haplotypes in CYP2B6 rs3745274 and CYP2B6 rs2279343 were represented by GA (60.24%) followed by TG (35.36%). We noted a strong linkage disequilibrium between CYP2B6 rs3745274 and CYP2B6 rs2279343 with D' = 0.91 and r2 = 0.9. The frequencies of the genotypic combinations were 43.5% (GT/AG), 37.3% (GG/AA) and 11.5% (TT/GG) in the combination of CYP2B6-rs3745274 and CYP2B6-rs2279343; 26.8% (GT/CC), 25.4%, (GT/CT), 17.2% and GG/CT in the combination CYP2B6-rs3745274-CYP3A4-rs2740574; 26.8% (AG/CC), 23.9% (AA/CC), 19.1% (AG/CT), and 11% (AA/CT) in the combination CYP2B6-rs2279343-CYP3A4-rs2740574, respectively. The most common triple genotype was GT/AG/CC with 24.9%, followed by GG/AA/CC with 23.9%, GT/AG/CT with 16.7%, and GG/AA/CT with 10%. Our results provide new insights into the distribution of these pharmacogenetically relevant genes in the Malian population. Moreover, these data will be useful for studies of individual genetic variability to drugs and genetic predisposition to diseases.

Clinical Approach to Cardiovascular Toxicity of Oral Antineoplastic Agents: JACC State-of-the-Art Review

Precision medicine has ushered in a new era of targeted treatments for numerous malignancies, leading to improvements in overall survival. Unlike traditional chemotherapy, many molecular targeted antineoplastic agents are available in oral formulation, leading to enhanced patient convenience and a perception of reduced risk of adverse effects. Although oral antineoplastic agents are generally well-tolerated, cardiovascular toxicities are being reported with increasing frequency in part due to U.S. Food and Drug Administration and manufacturer recommended cardiac monitoring. Monitoring strategies have focused on left ventricular dysfunction, hypertension, and QT prolongation/arrhythmias. Given the rapid pace of development and availability of new oral antineoplastic agents, the purpose of this review is to provide clinicians with an up-to-date practical approach to monitoring and management of cardiovascular toxicities with the aim of improving overall outcomes for patients with cancer.

Recent advances in computational metabolite structure predictions and altered metabolic pathways assessment to inform drug development processes

Many drug candidates fail during preclinical and clinical trials due to variable or unexpected metabolism which may lead to variability in drug efficacy or adverse drug reactions. The drug metabolism field aims to address this important issue from many angles which range from the study of drug-drug interactions, pharmacogenomics, computational metabolic modeling, and others. This manuscript aims to provide brief but comprehensive manuscript summaries highlighting the conclusions and scientific importance of seven exceptional manuscripts published in recent years within the field of drug metabolism. Two main topics within the field are reviewed: novel computational metabolic modeling approaches which provide complex outputs beyond site of metabolism predictions, and experimental approaches designed to discern the impacts of interindividual variability and species differences on drug metabolism. The computational approaches discussed provide novel outputs in metabolite structure and formation likelihood and/or extend beyond the saturated field of drug phase I metabolism, while the experimental metabolic pathways assessments aim to highlight the impacts of genetic polymorphisms and clinical animal model metabolic differences on human metabolism and subsequent health outcomes.

Identification of Enzymes Oxidizing the Tyrosine Kinase Inhibitor Cabozantinib: Cabozantinib Is Predominantly Oxidized by CYP3A4 and Its Oxidation Is Stimulated by cyt b5 Activity

Herein, the in vitro metabolism of tyrosine kinase inhibitor cabozantinib, the drug used for the treatment of metastatic medullary thyroid cancer and advanced renal cell carcinoma, was studied using hepatic microsomal samples of different human donors, human recombinant cytochromes P450 (CYPs), flavin-containing mono-oxygenases (FMOs) and aldehyde oxidase. After incubation with human microsomes, three metabolites, namely cabozantinib N-oxide, desmethyl cabozantinib and monohydroxy cabozantinib, were detected. Significant correlations were found between CYP3A4 activity and generation of all metabolites. The privileged role of CYP3A4 was further confirmed by examining the effect of CYP inhibitors and by human recombinant enzymes. Only four of all tested human recombinant cytochrome P450 were able to oxidize cabozantinib, and CYP3A4 exhibited the most efficient activity. Importantly, cytochrome b₅ (cyt b₅) stimulates the CYP3A4-catalyzed formation of cabozantinib metabolites. In addition, cyt b₅ also stimulates the activity of CYP3A5, whereas two other enzymes, CYP1A1 and 1B1, were not affected by cyt b₅. Since CYP3A4 exhibits high expression in the human liver and was found to be the most efficient enzyme in cabozantinib oxidation, we examined the kinetics of this oxidation. The present study provides substantial insights into the metabolism of cabozantinib and brings novel findings related to cabozantinib pharmacokinetics towards possible utilization in personalized medicine.

Potential for pharmacokinetic interactions between Schisandra sphenanthera and bosutinib, but not imatinib: in vitro metabolism study combined with a physiologically-based pharmacokinetic modelling approach

AIMS

This study aimed to investigate the potential interaction between Schisandra sphenanthera, imatinib and bosutinib combining in vitro and in silico methods.

METHODS

In vitro metabolism of imatinib and bosutinib using recombinant enzymes and human liver microsomes were investigated in the presence and absence of Schisandra lignans. Physiologically-based pharmacokinetic (PBPK) models for the lignans accounting for reversible and mechanism-based inhibitions and induction of CYP3A enzymes were built in the Simcyp Simulator (version 17) and evaluated for their capability to predict interactions with midazolam and tacrolimus. Their potential effect on systemic exposures of imatinib and bosutinib were predicted using PBPK in silico simulations.

RESULTS

Schisantherin A and schisandrol B, but not schisandrin A, potently inhibited CYP3A4-mediated metabolism of imatinib and bosutinib. All three compounds showed a strong reversible inhibition on CYP2C8 enzyme with k_i of less than 0.5 μmol L^-1 . The verified PBPK models were able to describe the increase in systemic exposure of midazolam and tacrolimus due to co-administration of S. sphenanthera, consistent with the reported changes in the corresponding clinical interaction study (AUC ratio of 2.0 vs 2.1 and 2.4 vs 2.1, respectively). The PBPK simulation predicted that at recommended dosing regimens of S. sphenanthera, co-administration would result in an increase in bosutinib exposure (AUC ratio 3.0) but not in imatinib exposure.

CONCLUSION

PBPK models for Schisandra lignans were successfully developed. Interaction between imatinib and Schisandra lignans was unlikely to be of clinical importance. Conversely, S. sphenanthera at a clinically-relevant dose results in a predicted three-fold increase in bosutinib systemic exposure.

Implementation of a Physiologically Based Pharmacokinetic Modeling Approach to Guide Optimal Dosing Regimens for Imatinib and Potential Drug Interactions in Paediatrics

Long-term use of imatinib is effective and well-tolerated in children with chronic myeloid leukaemia (CML) yet defining an optimal dosing regimen for imatinib in younger patients is a challenge. The potential interactions between imatinib and coadministered drugs in this "special" population also remains largely unexplored. This study implements a physiologically based pharmacokinetic (PBPK) modeling approach to investigate optimal dosing regimens and potential drug interactions with imatinib in the paediatric population. A PBPK model for imatinib was developed in the Simcyp Simulator (version 17) utilizing in silico, in vitro drug metabolism, and in vivo pharmacokinetic data and verified using an independent set of published clinical pharmacokinetic data. The model was then extrapolated to children and adolescents (aged 2-18 years) by incorporating developmental changes in organ size and maturation of drug-metabolising enzymes and plasma protein responsible for imatinib disposition. The PBPK model described imatinib pharmacokinetics in adult and paediatric populations and predicted drug interaction with carbamazepine, a cytochrome P450 (CYP)3A4 and 2C8 inducer, with a good accuracy (evaluated by visual inspections of the simulation results and predicted pharmacokinetic parameters that were within 1.25-fold of the clinically observed values). The PBPK simulation suggests that the optimal dosing regimen range for imatinib is 230-340 mg/m2/d in paediatrics, which is supported by the recommended initial dose for treatment of childhood CML. The simulations also highlighted that children and adults being treated with imatinib have similar vulnerability to CYP modulations. A PBPK model for imatinib was successfully developed with an excellent performance in predicting imatinib pharmacokinetics across age groups. This PBPK model is beneficial to guide optimal dosing regimens for imatinib and predict drug interactions with CYP modulators in the paediatric population.

Imatinib, sunitinib and pazopanib: From flat-fixed dosing towards a pharmacokinetically guided personalized dose

Tyrosine kinase inhibitors (TKIs) are anti‐cancer drugs that target tyrosine kinases, enzymes that are involved in multiple cellular processes. Currently, multiple oral TKIs have been introduced in the treatment of solid tumours, all administered in a fixed dose, although large interpatient pharmacokinetic (PK) variability is described. For imatinib, sunitinib and pazopanib exposure‐treatment outcome (efficacy and toxicity) relationships have been established and therapeutic windows have been defined, therefore dose optimization based on the measured blood concentration, called therapeutic drug monitoring (TDM), can be valuable in increasing efficacy and reducing the toxicity of these drugs.

In this review, an overview of the current knowledge on TDM guided individualized dosing of imatinib, sunitinib and pazopanib for the treatment of solid tumours is presented. We summarize preclinical and clinical data that have defined thresholds for efficacy and toxicity. Furthermore, PK models and factors that influence the PK of these drugs which partly explain the interpatient PK variability are summarized. Finally, pharmacological interventions that have been performed to optimize plasma concentrations are described. Based on current literature, we advise which methods should be used to optimize exposure to imatinib, sunitinib and pazopanib.

Genetic Polymorphisms and Adverse Events on Unbound Imatinib and Its Active Metabolite Concentration in Patients With Gastrointestinal Stromal Tumors

Imatinib is a first-line drug for the treatment of gastrointestinal stromal tumors (GIST). This study aims to investigate the influence of different kinds of protein concentrations and genetic polymorphisms of metabolizing enzymes and drug transporters on unbound imatinib and its active metabolite N-desmethyl-imatinib concentration, as well as the relationship between adverse drug reactions (ADRs) and drug concentration. A total of 62 Chinese patients with GIST were genotyped for five single nucleotide polymorphisms (SNPs). Total and unbound 3h and trough concentration of imatinib and N-desmethyl-imatinib in GIST patients were determined by an LC-MS/MS method combined with an equilibrium dialysis. Single-Use Red Plate with inserts was used to separate the unbound drug. When the protein concentration became higher, the unbound imatinib and N-desmethyl-imatinib plasma concentration got higher (p < 0.05). Patients with GA genotype in rs755828176 had significantly higher unbound N-desmethyl-imatinib dose-adjusted trough plasma concentrations (p = 0.012). Patients with CC genotype in rs3814055 had significantly higher unbound imatinib dose-adjusted trough plasma concentrations (p = 0.040). The mean total imatinib C_3h of patients with ADRs (3.10 ± 0.96 µg/ml) was significantly higher than that of patients without ADRs (p = 0.023). The mean total N-desmethyl-imatinib C_3h of patients (0.64 ± 0.21 µg/ml) with ADRs was significantly higher than that of patients without ADRs (p = 0.004). The mean unbound N-desmethyl-imatinib C_3h of patients with ADRs (6.49 ± 2.53 ng/ml) was significantly higher than that of patients without ADRs (p = 0.042). The total and unbound C_3h of imatinib and N-desmethyl-imatinib in patients with ADRs was significantly higher than that in patients without ADRs (p < 0.05). Protein concentrations have great influence on the unbound imatinib and N-desmethyl-imatinib concentrations. The genetic polymorphisms of CYP3A4 rs755828176 and NR1I2 rs3814055 were significantly associated with unbound imatinib and N-desmethyl-imatinib dose-adjusted trough plasma levels. The total and unbound imatinib or N-desmethyl-imatinib concentration in patients with GIST was also significantly correlated with ADRs.

Drug-drug interaction study of imatinib and voriconazole in vitro and in vivo

Background: In clinical practice, common problem polypharmacy could result in the increased risks of drug-drug interactions (DDIs). Co-administered imatinib (IMA) and voriconazole (VOR) as one treatment protocol in cancer patients with fungal infections are common.Purpose: The aim of the present study was to assess the potential DDIs associated with the concurrent use of IMA and VOR in rat liver microsomes (RLMs) and in rats.Methods and results: The concentration levels of IMA, VOR, and their metabolites N-desmethyl IMA (CGP74588) and N-oxide voriconazole (N-oxide VOR) were determined by ultra performance liquid chromatography-tandem mass spectrometry. In vitro study of RLMs, VOR inhibited the IMA metabolism with the half-maximal inhibitory concentration (IC₅₀) of 105.20 μM, while IC₅₀ for IMA against VOR was 61.30 μM. After co-administered IMA and VOR in rats, the C _max of IMA was increased significantly, while the AUC_0→t, AUC_0→∞, and C _max of CGP74588 were decreased significantly. In addition, similar results were also found that the main pharmacokinetic parameters (AUC_0→t, AUC_0→∞, MRT_0→∞, T _max, and C _max) of VOR were increased significantly, while the AUC_0→t, AUC_0→∞, and C _max of N-oxide VOR were decreased significantly. Incorporation of all the results indicated that both drugs had a inhibitory effect on each other's metabolism in vitro and in vivo.Conclusion: Thus, it is of great value to monitor the concomitant use of IMA and VOR in the clinic to reduce the risks of unexpected clinical outcomes.

The impact of azole antifungal drugs on imatinib metabolism in human liver microsomes

1. Imatinib is widely used for the treatment of hematologic malignancies. It is common that imatinib is clinically co-prescribed with azole antifungal agents since these patients are more prone to invasive antifungal infection. The present study was to investigate the effects of azole antifungal drugs, including ketoconazole, fluconazole, voriconazole, itraconazole and posaconazole on imatinib metabolism. 2. The main metabolites, 1-OH midazolam and N-desmethyl imatinib, were determined in the absence and in the presence of various levels of ketoconazole, fluconazole, voriconazole, itraconazole and posaconazole. The relevant assay was also performed to screen mechanism-based inhibitors (MBI). 3.   The inhibition ability of 1-OH midazolam formation from midazolam based on IC₅₀ values was ketoconazole (0.09 µM)>itraconazole (0.31 µM)> posaconazole (0.68 µM)>voriconazole (2.10 µM) > fluconazole (8.90 µM). Similarly, the rank order of inhibitory effects on formation of N-desmethyl imatinib from imatinib was ketoconazole (4.58 µM)>itraconazole (17.45 µM)> posaconazole (31.02 µM)> voriconazole (367.9 µM) >fluconazole (1.11 mM). Posaconazole and itraconazole displayed evidence of MBI. Additionally, imatinib was also shown as a MBI of CYP3A with IC₅₀ value of 5.40 µM against the midazolam. 4. The significant difference in IC₅₀ values of midazolam and imatinib inhibited by azole antifungal agents was observed. The role of CYP2C8 in imatinib metabolism and imatinib autoinhibits CYP3A activity may explain this difference. Our findings suggest that the azole antifungal agents might have limited impacts on imatinib exposure by CYP3A activity.

Managing Pharmacotherapy in People Living With HIV and Concomitant Malignancy

Objective: To describe data with selected malignancies in people living with HIV (PLWH) and HIV in individuals affected by both conditions and to summarize drug-drug interactions (DDIs) with clinical recommendations for point-of-care review of combination therapies. Data Sources: Literature searches were performed (2005 to December 2018) in MEDLINE and EMBASE to identify studies of malignancies in PLWH in the modern era. Study Selection and Data Extraction: Article bibliographies and drug interaction databases were reviewed. Search terms included HIV, antiretroviral therapy, antineoplastic agents, malignancies, and drug interactions. Data Synthesis: In the pre-antiretroviral therapy (ART) era, malignancies in PLWH were AIDS-defining illnesses, and life expectancy was shorter. Nowadays, PLWH are living longer and developing malignancies, including lung, anal, and prostate cancers. Concurrently, the oncology landscape has evolved, with novel oral targeted agents and immunotherapies becoming routine elements of care. The increased need for and complexity with antineoplastics in PLWH has led to recommendations for multidisciplinary care of this unique population. Evaluation of DDIs requires review of metabolic pathways, absorption mechanisms, and various drug transporters associated with antineoplastics and ART. Relevance to Patient Care and Clinical Practice: This review summarizes available data of non-AIDS-defining malignancies, principles of HIV care in the patient with malignancy, and guidance for assessing DDIs between antineoplastics and ART. Summary DDI tables provide point-of-care recommendations. Conclusions: The availability of ART has transformed AIDS into a chronic medical condition, and PLWH are experiencing age-related malignancies. Pharmacists play an important role in the management of this patient population.

Generation of a Weakly Acidic Amorphous Solid Dispersion of the Weak Base Ritonavir with Equivalent In Vitro and In Vivo Performance to Norvir Tablet

Ritonavir is an anti-viral compound that has also been employed extensively as a CYP3A4 and P-glycoprotein (Pgp) inhibitor to boost the pharmacokinetic performance of compounds that undergo first pass metabolism. For use in combination products, there is a desire to minimize the mass contribution of the ritonavir system to reduce patient pill burden in these combination products. In this study, KinetiSol® processing was utilized to produce an amorphous solid dispersion of ritonavir at two times the drug load of the commercially available form of ritonavir, and the composition was subsequently developed into a tablet dosage form. The amorphous intermediate was demonstrated to be amorphous by X-ray powder diffraction and ¹³C solid-state nuclear magnetic resonance and an intimately mixed single-phase system by modulated differential scanning calorimetry and ¹H T₁/¹H T_1ρ solid-state nuclear magnetic resonance relaxation. In vitro transmembrane flux analysis showed similar permeation rates for the KinetiSol-made tablet and the reference tablet dosage form, Norvir®. In vivo pharmacokinetic comparison between the two dosage forms resulted in equivalent exposure with approximately 20% Cmax reduction for the KinetiSol tablet. These performance gains were realized with a concurrent reduction in dosage form mass of 45%.

Pharmacogenetics and the treatment of chronic myeloid leukemia: how relevant clinically? An update

Despite the excellent efficacy and improved clinical responses obtained with imatinib mesylate (IM), development of resistance in a significant proportion of chronic myeloid leukemia (CML) patients on IM therapy have emerged as a challenging problem in clinical practice. Resistance to imatinib can be due to heterogeneous array of factors involving BCR/ABL-dependent and BCR/ABL-independent pathways. Although BCR/ABL mutation is the major contributory factor for IM resistance, reduced bio-availability of IM in leukemic cells is also an important pharmacokinetic factor that contributes to development of resistance to IM in CML patients. The contribution of polymorphisms of the pharmacogenes in relation to IM disposition and treatment outcomes have been studied by various research groups in numerous population cohorts. However, the conclusions arising from these studies have been highly inconsistent. This review encompasses an updated insight into the impact of pharmacogenetic variability on treatment response of IM in CML patients.

Therapeutic drug monitoring of imatinib, nilotinib, and dasatinib for patients with chronic myeloid leukemia

Imatinib, nilotinib, and dasatinib are tyrosine kinase inhibitors (TKIs) that have become first-line treatments for Philadelphia chromosome-positive chronic myeloid leukemia (CML). According to European LeukemiaNet recommendations, the clinical response of CML patients receiving TKI therapy should be evaluated after 3, 6, and 12 months. For patients not achieving a satisfactory response within 3 months, the mean plasma concentration for the three months of TKI administration must be considered. In TKI therapy for CML patients, therapeutic drug monitoring is a new strategy for dosage optimization to obtain a faster and more effective clinical response. The imatinib plasma trough concentration (C₀) should be set above 1000 ng/mL to obtain a response and below 3000 ng/mL to avoid serious adverse events such as neutropenia. For patients with a UGT1A1*6/*6, *6/*28, or *28/*28 genotype initially administered 300-400 mg/d, a target nilotinib C₀ of 500 ng/mL is recommended to prevent elevation of bilirubin levels, whereas for patients with the UGT1A1*1 allele initially administered 600 mg/d, a target nilotinib C₀ of 800 ng/mL is recommended. For dasatinib, it is recommended that a higher Cmax or C₂ (above 50 ng/mL) to obtain a clinical response and a lower C₀ (less than 2.5 ng/mL) to avoid pleural effusion be maintained by once daily administration of dasatinib. Although at present clinicians consider the next pharmacotherapy from clinical responses (efficacy/toxicity) obtained by a fixed dosage of TKI, the TKI dosage should be adjusted based on target plasma concentrations to maximize the efficacy and to minimize the incidence of adverse events.

Drug-Drug Interaction Potentials of Tyrosine Kinase Inhibitors via Inhibition of UDP-Glucuronosyltransferases

Tyrosine kinase inhibitors (TKIs) are anticancer drugs that may be co-administered with other drugs. The aims of this study are to investigate the inhibitory effects of TKIs on UDP-glucuronosyltransferase (UGT) activities, and to quantitatively evaluate their potential to cause drug-drug interactions (DDIs). Inhibition kinetic profiles of a panel of UGT enzymes (UGT1A1, 1A3, 1A4, 1A6, 1A7, 1A8, 1A9, 1A10, 2B4, 2B7, 2B15, and 2B17) by four TKIs (axitinib, imatinib, lapatinib and vandetanib) were characterized by using hepatic microsomes and recombinant proteins. Lapatinib exhibited potent competitive inhibition against UGT1A1 activity with a Ki of 0.5 μM. Imatinib was found to exhibit broad inhibition on several UGTs, particularly potent competitive inhibition against UGT2B17 with a Ki of 0.4 μM. The TKIs also exerted intermediate inhibition against several UGTs (i.e., UGT1A7 by lapatinib; UGT1A1 by imatinib; UGT1A4, 1A7 and 1A9 by axitinib; and UGT1A9 by vandetanib). Results from modeling for the quantitative prediction of DDI risk indicated that the coadministration of lapatinib or imatinib at clinical doses could result in a significant increase in AUC of drugs primarily cleared by UGT1A1 or 2B17. Lapatinib and imatinib may cause clinically significant DDIs when co-administered UGT1A1 or 2B17 substrates.

Human hepatocyte assessment of imatinib drug-drug interactions - complexities in clinical translation

AIM

Inducers and inhibitors of CYP3A, such as ritonavir and efavirenz, may be used as part of the highly active antiretroviral therapy (HAART) to treat HIV patients. HIV patients with chronic myeloid leukemia or gastrointestinal stromal tumour may need imatinib, a CYP3A4 substrate with known exposure response-relationships. Administration of imatinib to patients on ritonavir or efavirenz may result in altered imatinib exposure leading to increased toxicity or failure of therapy, respectively. We used primary human hepatocyte cultures to evaluate the magnitude of interaction between imatinib and ritonavir/efavirenz.

METHODS

Hepatocytes were pre-treated with vehicle, ritonavir, ketoconazole, efavirenz or rifampicin, and the metabolism of imatinib was characterized over time. Concentrations of imatinib and metabolite were quantitated in combined lysate and medium, using LC-MS.

RESULTS

The predicted changes in imatinib CLoral (95% CI) with ketoconazole, ritonavir, rifampicin and efavirenz were 4.0-fold (0, 9.2) lower, 2.8-fold (0.04, 5.5) lower, 2.9-fold (2.2, 3.5) higher and 2.0-fold (0.42, 3.5) higher, respectively. These predictions were in good agreement with clinical single dose drug-drug interaction studies, but not with reports of imatinib interactions at steady-state. Alterations in metabolism were similar after acute or chronic imatinib exposure.

CONCLUSIONS

In vitro human hepatocytes predicted increased clearance of imatinib with inducers and decreased clearance with inhibitors of CYP enzymes. The impact of HAART on imatinib may depend on whether it is being initiated or has already been dosed chronically in patients. Therapeutic drug monitoring may have a role in optimizing imatinib therapy in this patient population.

Population Pharmacokinetic Analysis of the Oral Absorption Process and Explaining Intra-Subject Variability in Plasma Exposures of Imatinib in Healthy Volunteers

BACKGROUND AND OBJECTIVE

Imatinib mesylate is presently the first-line treatment for chronic myeloid leukemia (CML). The aim of this study was to investigate the absorption and distribution kinetics of imatinib in healthy Iranian volunteers using nonlinear mixed effects modeling (NLMEM) to assess the overall, intra- and inter-subject variabilities in pharmacokinetic parameters after oral administration.

METHODS

This analysis was based on data from 24 healthy subjects who participated in a bioequivalence study after administering a single dose of 200 mg of each formulation. Imatinib concentrations were quantified using a validated liquid chromatography method. To simultaneously describe the imatinib pharmacokinetic profiles obtained with both formulations, a population pharmacokinetic model was applied to data using SAEM algorithm implemented in MONOLIX, whilst simulations were used by numerical solving of ordinary differential equations to calculate secondary parameters in individuals for bioequivalence studies.

RESULTS

According to goodness-of-fit criteria, a two-compartment open model with sequential zero- then first-order absorption and first-order elimination was used as the structural pharmacokinetic model. Inter-individual variability (IIV) was considered for all parameters. Typical population estimates (% IIV) were fraction of the drug absorbed with a zero-order kinetic (Fr) of 0.153 (47.9 %) in period (Tk0) of 0.714 h (47.4 %), first-order absorption rate constant (k a) of 0.94 h(-1)(31.2 %), oral clearance of 19 L/h (27.9 %), central volume of distribution (V c/F) of 139 L (21.5 %), apparent peripheral volume of distribution (V p/F) of 130 L (29.7 %) and the apparent inter-compartment clearance (Q/F) of 29.6 L/h (41.8 %). Body mass index (BMI) was the only covariate found to significantly affect V p /F. The coefficient of variation for intra-individual plasma exposure (AUC0-∞) was 27.8 %.

CONCLUSIONS

Analyses using NLMEM for imatinib exhibited absorption complexities such as two input rates and medium to high intra-individual variability in drug exposure.

Impact of CYP2C8*3 polymorphism on in vitro metabolism of imatinib to N-desmethyl imatinib

1. Imatinib is metabolized to N-desmethyl imatinib by CYPs 3A4 and 2C8. The effect of CYP2C8*3 genotype on N-desmethyl imatinib formation was unknown. 2. We examined imatinib N-demethylation in human liver microsomes (HLMs) genotyped for CYP2C8*3, in CYP2C8*3/*3 pooled HLMs and in recombinant CYP2C8 and CYP3A4 enzymes. Effects of CYP-selective inhibitors on N-demethylation were also determined. 3. A single-enzyme Michaelis-Menten model with autoinhibition best fitted CYP2C8*1/*1 HLM (n = 5) and recombinant CYP2C8 kinetic data (median ± SD Ki = 139 ± 61 µM and 149 µM, respectively). Recombinant CYP3A4 showed two-site enzyme kinetics with no autoinhibition. Three of four CYP2C8*1/*3 HLMs showed single-enzyme kinetics with no autoinhibition. Binding affinity was higher in CYP2C8*1/*3 than CYP2C8*1/*1 HLM (median ± SD Km = 6 ± 2 versus 11 ± 2 µM, P=0.04). CYP2C8*3/*3 (pooled HLM) also showed high binding affinity (Km = 4 µM) and single-enzyme weak autoinhibition (Ki = 449 µM) kinetics. CYP2C8 inhibitors reduced HLM N-demethylation by 47-75%, compared to 0-30% for CYP3A4 inhibitors. 4. In conclusion, CYP2C8*3 is a gain-of-function polymorphism for imatinib N-demethylation, which appears to be mainly mediated by CYP2C8 and not CYP3A4 in vitro in HLM.

Combination of imatinib and clotrimazole enhances cell growth inhibition in T47D breast cancer cells

Imatinib mesylate (IM), a tyrosine kinase inhibitor, is used as targeted cancer therapy. However, mono-targeting by IM does not always achieve full tumor eradication and thus it is recommended to combine IM with other anticancer agents. Clotrimazole (CLT) is an antifungal azole derivative with promising anticancer effects due to inhibiting the activity of glycolytic enzymes. The present study aimed to evaluate the effect of combining CLT with IM on breast cancer cell line in an attempt to establish effective new combination. T47D human breast cancer cell line was treated with different concentrations of IM and/or CLT for 48 h. IM-CLT interaction was determined by isobologram equation and combination index. Cell viability was confirmed by measuring LDH activity. As indicators of glycolysis inhibition, the expression of hexokinase-2 (HK-2) and 6-phosphofructo-1-kinase (PFK-1) plus the activity of intracellular lactate dehydrogenase (LDH) and pyruvate kinase (PK) were determined. In addition, glucose consumption and adenosine triphosphate (ATP) production were measured. Moreover, nitric oxide (NO), vascular endothelial growth factor (VEGF) and hypoxia inducible factor-α (HIF-α) were also determined as they are modulators for glycolysis. This study demonstrated that IM or CLT synergistically inhibited cell growth in T47D as shown by combination and dose reduction indices. The combination of 15 μM IM and 20 μM CLT significantly decreased glucose consumption, activity of both PK and intracellular LDH, while increased leaked LDH, VEGF and NO in the medium compared to each drug alone. Furthermore the combination decreased gene expression of HK-2, PFK-1 and ATP content compared to the control. In conclusion, the synergistic effect of CLT on IM cytotoxicity in T47D cell line maybe mediated through inhibition of glycolysis and increasing both NO and VEGF. Further studies are required to confirm the efficiency and safety of this combination.

Pharmacokinetics interaction between imatinib and genistein in rats

The objective of this work was to investigate the effect of orally administered genistein on the pharmacokinetics of imatinib and N-desmethyl imatinib in rats. Twenty-five healthy male SD (Sprague-Dawley) rats were randomly divided into five groups: A group (control group), B group (multiple dose of 100 mg/kg genistein for consecutive 15 days), C group (multiple dose of 50 mg/kg genistein for consecutive 15 days), D group (a single dose of 100 mg/kg genistein), and E group (a single dose of 50 mg/kg genistein). A single dose of imatinib is administered orally 30 min after administration of genistein (100 mg/kg or 50 mg/kg). The pharmacokinetic parameters of imatinib and N-desmethyl imatinib were calculated by DAS 3.0 software. The multiple dose of 100 mg/kg or 50 mg/kg genistein significantly (P < 0.05) decreased the AUC0-t and C max of imatinib. AUC0-t and the C max of N-desmethyl imatinib were also increased, but without any significant difference. However, the single dose of 100 mg/kg or 50 mg/kg genistein has no effect on the pharmacokinetics of imatinib and N-desmethyl imatinib. Those results indicated that multiple dose of genistein (100 mg/kg or 50 mg/kg) induces the metabolism of imatinib, while single dose of genistein has no effect.

Inhibitory effect of silybin on pharmacokinetics of imatinib in vivo and in vitro

The objective of this work was to investigate the effect of orally administered silybin on the pharmacokinetics of imatinib in rats and the metabolism of imatinib in human liver microsome and rat liver microsomes. Eighteen healthy male SD rats were randomly divided into 3 groups: group A (control group), group B (received multiple doses of 50 mg·kg−1 silybin for 15 consecutive days), and group C (received a single dose of 50 mg·kg−1 silybin). A single dose of imatinib was administered orally 30 min after administration of silybin (50 mg·kg−1). Imatinib plasma levels were measured by UPLC-MS/MS, and pharmacokinetic parameters were calculated by DAS 3.0 software (Bontz Inc., Beijing, China). In addition, human and rat liver microsome were performed to determine the effects of silybin metabolism of imatinib in vitro. The multiple doses or single dose of 50 mg·kg−1 silybin significantly decreased the area under the curve (0-t) of imatinib (p < 0.01). And the half-life (t1/2) of imatinib is significantly increased (p < 0.05 and p < 0.01, respectively). Also, silybin showed inhibitory effect on human and rat microsomes, the IC50 of silybin were 26.42 μmol·L−1 and 49.12 μmol·L−1 in human and rat liver microsomes, respectively. These results indicate that more attention should be paid to when imatinib is administrated combined with silybin.

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.

Clinical efficacy and safety of imatinib in the management of Ph(+) chronic myeloid or acute lymphoblastic leukemia in Chinese patients

Imatinib mesylate is considered the standard first-line systemic treatment for patients with chronic myeloid leukemia (CML) and functions by targeting BCR-ABL tyrosine kinases. Imatinib has substantially changed the clinical management and improved the prognosis of CML and Philadelphia chromosome-positive acute lymphocytic leukemia (Ph⁺ ALL). Here, we review the pharmacology, mode of action, and pharmacokinetics of imatinib; Chinese efficacy studies in CML and Ph⁺ ALL; safety and tolerability; patient-focused perspectives, such as quality of life, patient satisfaction, acceptability, and adherence; and uptake of imatinib.

Treatment with dasatinib for chronic myeloid leukemia following imatinib-induced hepatotoxicity

Treatment with the tyrosine kinase inhibitor (TKI) imatinib for chronic myeloid leukemia in chronic phase (CML-CP) of disease may cause severe hepatotoxicity in rare cases. However, it remains unclear (1) how imatinib-induced hepatotoxicity should be treated; and (2) if and how TKI treatment can be resumed after recovery. We report a 32-year-old woman with CML-CP and histology confirmed imatinib-induced liver toxicity after 6 months of treatment. In this case, the early administration of corticosteroid therapy resulted in rapid and complete hepatic recovery, and treatment for CML-CP with the second generation TKI dasatinib was continued safely after recovery. Thus, dasatinib represents an option for maintaining therapeutic response in patients in whom continuation of imatinib is not possible due to its hepatic toxicity.

Drug interactions with solid tumour-targeted therapies

Drug interactions are an on-going concern in the treatment of cancer, especially when targeted therapies, such as tyrosine kinase inhibitors (TKI) or mammalian target of rapamycin (mTOR) inhibitors, are being used. The emergence of elderly patients and/or patients with both cancer and other chronic co-morbidities leads to polypharmacy. Therefore, the risk of drug-drug interactions (DDI) becomes a clinically relevant issue, all the more so as TKIs and mTOR inhibitors are essentially metabolised by cytochrome P450 enzymes. These DDIs can result in variability in anticancer drug exposure, thus favouring the selection of resistant cellular clones or the occurrence of toxicity. This review provides a comprehensive overview of DDIs that involve targeted therapies approved by the FDA for the treatment of solid tumours for more than 3 years (sorafenib, sunitinib, erlotinib, gefitinib, imatinib, lapatinib, everolimus, temsirolimus) and medicinal herb or drugs. This review also provides some guidelines to help oncologists and pharmacists in their clinical practice.