Practical Guidelines for Therapeutic Drug Monitoring of Anticancer Tyrosine Kinase Inhibitors: Focus on the Pharmacokinetic Targets

BSA and ABCB1 polymorphism affect the pharmacokinetics of sunitinib and its active metabolite in Asian mRCC patients receiving an attenuated sunitinib dosing regimen

PURPOSE

An attenuated dosing (AD) sunitinib regimen of 37.5 mg daily has been suggested to reduce the toxicity reported with the standard dosing regimen to metastatic renal cell carcinoma (mRCC) patients. The aim of this study was to characterize the population pharmacokinetic (PK) properties of sunitinib and SU12662, the active metabolite, in patients receiving the AD regimen and to ascertain significant covariates influencing PK parameters.

METHODS

Thirty-one mRCC patients receiving AD sunitinib regimen were included. Plasma samples were collected on day 29 of each treatment cycle after the start of the therapy. Nonlinear mixed-effects modeling was applied to estimate the population PK properties of sunitinib and SU12662 as well as the effect of covariates on PK parameters. Monte Carlo simulation was also performed to predict the total trough level (TTL) of sunitinib and SU12662.

RESULTS

Sunitinib population means for CL/F and V d /F central were 13.8 L/h and 1720 L, respectively. SU12662 population means for CL/F and V d /F were 42.1 L/h and 1410 L, respectively. Body surface area (BSA) and ABCB1 polymorphism significantly influenced the CL/F variability of sunitinib: CL/F parent = 13.8 × exp((BSA - 1.75) × 2.08 + (ABCB1 genotype - 0.67) × 0.61), ABCB1-0: wild genotype, 1: mutant genotype. The effect size of ABCB1 mutant genotype and BSA greater than 1.75 m(2) in relation to sunitinib clearance was 31.14 % (p = 0.006) and 22.11 % (p = 0.011), respectively, relative to the reference group.

CONCLUSIONS

Adjusting doses of sunitinib according to BSA and ABCB1 polymorphism in Asian mRCC patients may be recommended for sufficient attainment of a target TTL of sunitinib and its metabolite.

Urinary Dopamine as a Potential Index of the Transport Activity of Multidrug and Toxin Extrusion in the Kidney

Dopamine is a cationic natriuretic catecholamine synthesized in proximal tubular cells (PTCs) of the kidney before secretion into the lumen, a key site of its action. However, the molecular mechanisms underlying dopamine secretion into the lumen remain unclear. Multidrug and toxin extrusion (MATE) is a H⁺/organic cation antiporter that is highly expressed in the brush border membrane of PTCs and mediates the efflux of organic cations, including metformin and cisplatin, from the epithelial cells into the urine. Therefore, we hypothesized that MATE mediates dopamine secretion, a cationic catecholamine, into the tubule lumen, thereby regulating natriuresis. Here, we show that [³H]dopamine uptake in human (h) MATE1-, hMATE-2K- and mouse (m) MATE-expressing cells exhibited saturable kinetics. Fluid retention and decreased urinary excretion of dopamine and Na⁺ were observed in Mate1-knockout mice compared to that in wild-type mice. Imatinib, a MATE inhibitor, inhibited [³H]dopamine uptake by hMATE1-, hMATE2-K- and mMATE1-expressing cells in a concentration-dependent manner. At clinically-relevant concentrations, imatinib inhibited [³H]dopamine uptake by hMATE1- and hMATE2-K-expressing cells. The urinary excretion of dopamine and Na⁺ decreased and fluid retention occurred in imatinib-treated mice. In conclusion, MATE transporters secrete renally-synthesized dopamine, and therefore, urinary dopamine has the potential to be an index of the MATE transporter activity.

Therapeutic drug monitoring and tyrosine kinase inhibitors

The therapeutic activity of drugs can be optimized by establishing an individualized dosage, based on the measurement of the drug concentration in the serum, particularly if the drugs are characterized by an inter-individual variation in pharmacokinetics that results in an under- or overexposure to treatment. In recent years, several tyrosine kinase inhibitors (TKIs) have been developed to block intracellular signaling pathways in tumor cells. These oral drugs are candidates for therapeutic drug monitoring (TDM) due to their high inter-individual variability for therapeutic and toxic effects. Following a literature search on PubMed, studies on TKIs and their pharmacokinetic characteristics, plasma quantification and inter-individual variability was studied. TDM is commonly used in various medical fields, including cardiology and psychiatry, but is not often applied in oncology. Plasma concentration monitoring has been thoroughly studied for imatinib, in order to evaluate the usefulness of TDM. The measurement of plasma concentration can be performed by various analytical techniques, with liquid chromatography-mass spectrometry being the reference method. This method is currently used to monitor the efficacy and tolerability of imatinib treatments. Although TDM is already being used for imatinib, additional studies are required in order to improve this practice with the inclusion of other TKIs.

Recent developments in the chromatographic bioanalysis of approved kinase inhibitor drugs in oncology

In recent years (2010-present) there has been an increase in the number of publications reporting the development, validation and use of bioanalytical methods in the rapidly expanding drug class of small molecule protein kinase inhibitors. Most reports describe the technological set-up of the methods that have allowed for drug concentration measurements from various sample types. This includes plasma, dried blood-spot, and tissue-analysis. Also method development, exploration of various techniques, as well as measurement and identification of metabolites were addressed. For the bioanalysis, a variety of sample-pretreatment methods like protein-precipitation, liquid-liquid extraction, and solid-phase extraction have been employed, all varying in complexity, cleanliness and time-consumption. Chromatographic separation, nowadays, is more focused on separating components from ion-suppressive effects, since for MS/MS detection, various components do not have to be baseline separated. For detection multiple types of detectors were used, ranging from state-of-the-art high resolution, and tandem mass spectrometry with low picogram per milliliter detection limits to the classical UV-detector with several nanograms per milliliter limits. As new bioanalytical methods have arisen that do rely on chromatographic separation, for example for high-throughput analysis, these are addressed in this review as well.

Monte Carlo simulations of the clinical benefits from therapeutic drug monitoring of sunitinib in patients with gastrointestinal stromal tumours

PURPOSE

Therapeutic drug monitoring (TDM) is being considered as a tool to individualise sunitinib treatment of gastrointestinal stromal tumours (GIST). Here, we used computer simulations to assess the expected impact of sunitinib TDM on the clinical outcome of patients with GIST.

METHODS

Monte Carlo simulations were performed in R, based on previously published pharmacokinetic-pharmacodynamic models. Clinical trials with dose-limiting toxicity and patient dropout were simulated to establish the study size required to obtain sufficient statistical power for comparison of TDM-guided and fixed dosing.

RESULTS

The simulations revealed that TDM might increase time to tumour progression by about 1-2 months (15-31 %) in eligible patients. However, the number of subjects required for a sufficient statistical power to quantify clinical benefit of TDM guided is likely to be prohibitively high (>1000).

CONCLUSION

Although data from randomised clinical trials on the clinical impact of sunitinib TDM are lacking, our findings support implementation of sunitinib TDM in clinical practice. For rare cancers with well-defined exposure-response relationships, modelling and simulation might allow the optimisation of dosing strategies when clinical trials cannot be performed due to low number of 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.

Regulatory aspects of human radiolabeled mass balance studies in oncology: concise review

Human radiolabeled mass balance studies are performed to obtain information about the absorption, distribution, metabolism, and excretion of a drug in development. The main goals are to determine the route of elimination and major metabolic pathways. This review provides an overview of the current regulatory guidelines concerning human radiolabeled mass balance studies and discusses scientific trends seen in the last decade with a focus on mass balance studies of anticancer drugs. This paper also provides an overview of mass balance studies of anticancer agents that were executed in the last 10 years.

An Automated Homogeneous Immunoassay for Quantitating Imatinib Concentrations in Plasma

BACKGROUND

Imatinib pharmacokinetic variability and the relationship of trough concentrations with clinical outcomes have been extensively reported. Although physical methods to quantitate imatinib exist, they are not widely available for routine use. An automated homogenous immunoassay for imatinib has been developed, facilitating routine imatinib testing.

METHODS

Imatinib-selective monoclonal antibodies, without substantial cross-reactivity to the N-desmethyl metabolite or N-desmethyl conjugates, were produced. The antibodies were conjugated to 200 nm particles to develop immunoassay reagents on the Beckman Coulter AU480 analyzer. These reagents were analytically validated using Clinical Laboratory Standards Institute protocols. Method comparison to liquid chromatography tandem mass spectrometry (LC-MS/MS) was conducted using 77 plasma samples collected from subjects receiving imatinib.

RESULTS

The assay requires 4 µL of sample without pretreatment. The nonlinear calibration curve ranges from 0 to 3000 ng/mL. With automated sample dilution, concentrations of up to 9000 ng/mL can be quantitated. The AU480 produces the first result in 10 minutes and up to 400 tests per hour. Repeatability ranged from 2.0% to 6.0% coefficient of variation, and within-laboratory reproducibility ranged from 2.9% to 7.4% coefficient of variation. Standard curve stability was 2 weeks and on-board reagent stability was 6 weeks. For clinical samples with imatinib concentrations from 438 to 2691 ng/mL, method comparison with LC-MS/MS gave a slope of 0.995 with a y-intercept of 24.3 and a correlation coefficient of 0.978.

CONCLUSIONS

The immunoassay is suitable for quantitating imatinib in human plasma, demonstrating good correlation with a physical method. Testing for optimal imatinib exposure can now be performed on routine clinical analyzers.

Everolimus pharmacokinetics and its exposure-toxicity relationship in patients with thyroid cancer

Background

Everolimus is a mTOR inhibitor used for the treatment of different solid malignancies. Many patients treated with the registered fixed 10 mg dose once daily are in need of dose interruptions, reductions or treatment discontinuation due to severe adverse events. This study determined the correlation between systemic everolimus exposure and toxicity. Additionally, the effect of different covariates on everolimus pharmacokinetics (PK) was explored.

Methods

Forty-two patients with advanced thyroid carcinoma were treated with 10 mg everolimus once daily. Serial pharmacokinetic sampling was performed on days 1 and 15. Subsequently, a population PK model was developed using NONMEM to estimate individual PK values used for analysis of an exposure–toxicity relationship. Furthermore, this model was used to investigate the influence of patient characteristics and genetic polymorphisms in genes coding for enzymes relevant in everolimus PK.

Results

Patients who required a dose reduction (n = 18) due to toxicity at any time during treatment had significant higher everolimus exposures [mean AUC_0–24 (SD) 600 (274) vs. 395 (129) µg h/L, P = 0.008] than patients without a dose reduction (n = 22). A significant association between everolimus exposure and stomatitis was found in the four-level ordered logistic regression analysis (P = 0.047). The presence of at least one TTT haplotype in the ABCB1 gene was associated with a 21 % decrease in everolimus exposure.

Conclusion

The current study showed that dose reductions and everolimus-induced stomatitis were strongly associated with systemic everolimus drug exposure in patients with cancer. Our findings confirm observations from another study in patients with cancer and show us that everolimus is a good candidate for individualized dosing in patients with cancer.

ClinicalTrial.gov number

NCT01118065.

Electronic supplementary material

The online version of this article (doi:10.1007/s00280-016-3050-6) contains supplementary material, which is available to authorized users.

Relationship Between Sunitinib Pharmacokinetics and Administration Time: Preclinical and Clinical Evidence

Background and Objective

Circadian rhythms may influence the pharmacokinetics of drugs. This study aimed to elucidate whether the pharmacokinetics of the orally administered drug sunitinib are subject to circadian variation.

Methods

We performed studies in male FVB-mice aged 8–12 weeks, treated with single-dose sunitinib at six dosing times. Plasma and tissue samples were obtained for pharmacokinetic analysis and to monitor messenger RNA (mRNA) expression of metabolizing enzymes and drug transporters. A prospective randomized crossover study was performed in which patients took sunitinib once daily at 8 a.m., 1 p.m., and 6 p.m at three subsequent courses. Patients were blindly randomized into two groups, which determined the sequence of the sunitinib dosing time. The primary endpoint in both studies was the difference in plasma area under the concentration–time curve (AUC) of sunitinib and its active metabolite SU12662 between dosing times.

Results

Sunitinib and SU12662 plasma AUC in mice followed an ~12-h rhythm as a function of administration time (p ≤ 0.04). The combined AUC from time zero to 10 h (AUC₁₀) was 14–27 % higher when sunitinib was administered at 4 a.m. and 4 p.m. than at 8 a.m. and 8 p.m. Twenty-four-hour rhythms were seen in the mRNA levels of drug transporters and metabolizing enzymes. In 12 patients, sunitinib trough concentrations (C_trough) were higher when the drug was taken at 1 p.m. or 6 p.m. than when taken at 8 a.m. (C_{trough-1 p.m}. 66.0 ng/mL; C_{trough-6 p.m.} 58.9 ng/mL; C_{trough-8 a.m.} 50.7 ng/mL; p = 0.006). The AUC was not significantly different between dosing times.

Conclusions

Our results indicate that sunitinib pharmacokinetics follow an ~12-h rhythm in mice. In humans, morning dosing resulted in lower C_trough values, probably resulting from differences in elimination. This can have implications for therapeutic drug monitoring.

Electronic supplementary material

The online version of this article (doi:10.1007/s40262-015-0239-5) contains supplementary material, which is available to authorized users.

The Use of Dried Blood Spots for Pharmacokinetic Monitoring of Vemurafenib Treatment in Melanoma Patients

Pharmacokinetic monitoring is increasingly becoming an important part of clinical care of tyrosine kinase inhibitor treatment. Vemurafenib is an oral tyrosine kinase inhibitor that inhibits mutated serine/threonine protein kinase B-Raf (BRAF) and is approved for the treatment of adult patients with BRAF V600 mutation-positive unresectable or metastatic melanoma. The aim of this study was to establish the relationship between dried blood spot (DBS) and plasma concentrations of vemurafenib to enable the use of DBS sampling, which is a minimally invasive form of sample collection. In total, 43 paired plasma and DBS samples (in duplicate) were obtained from 8 melanoma patients on vemurafenib therapy and were analyzed using high-performance liquid chromatography-tandem mass spectrometry. Plasma concentrations were predicted from the DBS concentrations using 2 methods: (1) individual hematocrit correction and blood cell-to-plasma partitioning and (2) the calculated slope explaining the relationship between DBS and plasma concentrations (without individual hematocrit correction). Vemurafenib DBS concentrations and plasma concentrations showed a strong correlation (r = 0.964), and the relationship could be described by ([vemurafenib]plasma = [vemurafenib]DBS /0.64). The predicted plasma concentrations were within ±20% of the analyzed plasma concentrations in 97% and 100% of the samples for the methods with and without hematocrit correction, respectively. In conclusion, DBS concentrations and plasma concentrations of vemurafenib are highly correlated. Plasma concentrations can be predicted from DBS concentration using the blood cell-to-plasma partition and the average hematocrit value of this cohort (0.40 L/L). DBS sampling for pharmacokinetic monitoring of vemurafenib treatment can be used in clinical practice.

Effect of food and acid-reducing agents on the absorption of oral targeted therapies in solid tumors

Oral targeted therapies represent an increasingly important group of drugs within modern oncology. With the shift from intravenously to orally administered drugs, drug absorption is a newly introduced factor in drug disposition. The process of absorption can have a large effect on inter- and intrasubject variability in drug exposure and thereby potentially treatment benefit or the severity of toxicities. The intake of oral targeted therapies with food and concomitant use of acid-reducing agents (ARAs) can significantly affect drug absorption. The size and direction of the effect of food and ARAs on drug absorption varies among drugs as a result of different chemical characteristics. Therefore, an awareness and understanding of these effects for each drug is essential to optimize patient outcomes.

Integrated semi-physiological pharmacokinetic model for both sunitinib and its active metabolite SU12662

AIMS

Previously published pharmacokinetic (PK) models for sunitinib and its active metabolite SU12662 were based on a limited dataset or lacked important elements such as correlations between sunitinib and its metabolite. The current study aimed to develop an improved PK model that circumvented these limitations and to prove the utility of the PK model in treatment optimization in clinical practice.

METHODS

One thousand two hundred and five plasma samples from 70 cancer patients were collected from three PK studies with sunitinib and SU12662. A semi-physiological PK model for sunitinib and SU12662 was developed incorporating pre-systemic metabolism using non-linear mixed effects modelling (nonmem). Allometric scaling based on body weight was applied. The final model was used for simulation of the PK of different treatment regimens.

RESULTS

Sunitinib and SU12662 PK were best described by a one and two compartment model, respectively. Introduction of pre-systemic formation of SU12662 strongly improved model fit, compared with solely systemic metabolism. The clearance of sunitinib and SU12662 was estimated at 35.7 (relative standard error (RSE) 5.7%) l h(-1) and 17.1 (RSE 7.4%) l h(-1), respectively for 70 kg patients. Correlation coefficients were estimated between inter-individual variability of both clearances, both volumes of distribution and between clearance and volume of distribution of SU12662 as 0.53, 0.48 and 0.45, respectively. Simulation of the PK model predicted correctly the ratio of patients who did not reach proposed PK targets for efficacy.

CONCLUSIONS

A semi-physiological PK model for sunitinib and SU12662 in cancer patients was presented including pre-systemic metabolism. The model was superior to previous PK models in many aspects.

Determination of unbound fraction of pazopanib in vitro and in cancer patients reveals albumin as the main binding site

INTRODUCTION

Pazopanib exhibits wide inter-patient pharmacokinetic variability which may contribute to differences in treatment outcome. Unbound drug concentrations are believed to be more relevant to pharmacological responses than total concentrations. Thus it is desirable to evaluate pazopanib binding on plasma proteins and different factors potentially affecting this process.

METHODS

An equilibrium dialysis method coupled with UPLC-MS/MS assay has been optimized and validated for the determination of pazopanib unbound fraction (fu%) in human plasma. Pazopanib binding in the plasma of healthy volunteers and in isolated protein solutions was investigated. The unbound fraction was determined for 24 cancer patients treated daily with pazopanib.

RESULTS

We found that pazopanib was extensively bound in human plasma (>99.9 %) with a mean fu% value of 0.0106 ± 0.0013 % at 40 μg/mL. Protein binding was concentration independent over a clinically relevant range of concentrations. In isolated protein solutions, pazopanib at 40 μg/mL was mainly bound to albumin (40 g/L) and to a lesser extent to α1-acid glycoprotein (1 g/L) and low density lipoproteins (1.2 g/L), with a mean fu% of 0.0073 ± 0.0022 %, 0.992 ± 0.44 % and 7.4 ± 1.7 % respectively. Inter-patient variability (CV%) of fu% in cancer patients was limited (27.2 %). A correlation was observed between individual unbound fraction values and albuminemia.

CONCLUSIONS

Pazopanib exhibits extensive binding to plasma proteins in human plasma. Variable albumin concentrations, frequently observed in cancer patients, may affect pazopanib unbound fraction with implications for inter-patient variability in drug efficacy and toxicity.

Routine therapeutic drug monitoring of tyrosine kinase inhibitors by HPLC-UV or LC-MS/MS methods

Analytical methods using high performance liquid chromatography coupled to ultraviolet detection (HPLC-UV) or liquid chromatography-tandem mass spectrometry (LC-MS/MS) have been reported for the quantification of oral tyrosine kinase inhibitors (TKIs) such as imatinib, nilotinib, and dasatinib in biological fluids. An LC-MS/MS method can simultaneously assay multiple TKIs and their metabolites with high sensitivity and selectivity for low plasma concentrations less than 1 ng/mL. For quantification of imatinib, nilotinib, and dasatinib, a limit of quantification (LOQ) of less than 10 ng/mL, 10 ng/mL, and 0.1 ng/mL, respectively, in the clinical setting is necessary. Because simpler and more cost-efficient methodology is desired for clinical analysis, plasma concentrations of imatinib and nilotinib (target trough concentrations of 1000 ng/mL and 800 ng/mL, respectively) could be assayed by an HPLC-UV method after comparison with results obtained from the standard LC-MS/MS method. However, in the quantification of dasatinib, the LC-MS/MS method that has high sensitivity and selectivity and is free from interference by endogenous impurities is superior to the HPLC-UV method. Highly precise analytical methods are needed for individualized treatment via dose adjustment of oral anticancer drugs, in particular those with low target plasma concentrations less than 10 ng/mL.

Seizures and cancer: drug interactions of anticonvulsants with chemotherapeutic agents, tyrosine kinase inhibitors and glucocorticoids

Patients with cancer commonly experience seizures. Combined therapy with anticonvulsant drugs (AEDs) and chemotherapeutic drugs or tyrosine kinase inhibitors carries inherent risks on drug-drug interactions (DDIs). In this review, pharmacokinetic studies of AEDs with chemotherapeutic drugs, tyrosine kinase inhibitors, and glucocorticoids are discussed, including data on maximum tolerated dose, drug clearance, elimination half-life, and organ exposure. Enzyme-inducing AEDs (EIAEDs) cause about a 2-fold to 3-fold faster clearance of concurrent chemotherapeutic drugs metabolized along the same pathway, including cyclophosphamide, irinotecan, paclitaxel, and teniposide, and up to 4-fold faster clearance with the tyrosine kinase inhibitors crizotinib, dasatinib, imatinib, and lapatinib. The use of tyrosine kinase inhibitors, particularly imatinib and crizotinib, may lead to enzyme inhibition of concurrent therapy. Many of the newer generation AEDs do not induce or inhibit drug metabolism, but they can alter enzyme activity by other drugs including AEDs, chemotherapeutics and tyrosine kinase inhibitors. Glucocorticoids can both induce and undergo metabolic change. Quantitative data on changes in drug metabolism help to apply the appropriate dose regimens. Because the large individual variability in metabolic activity increases the risks for undertreatment and/or toxicity, we advocate routine plasma drug monitoring. There are insufficient data available on the effects of tyrosine kinase inhibitors on AED metabolism.

Metabolism-related pharmacokinetic drug-drug interactions with tyrosine kinase inhibitors: current understanding, challenges and recommendations

Drug-drug interactions (DDIs) occur when a patient's response to the drug is modified by administration or co-exposure to another drug. The main cytochrome P450 (CYP) enzyme, CYP3A4, is implicated in the metabolism of almost all of the tyrosine kinase inhibitors (TKIs). Therefore, there is a substantial potential for interaction between TKIs and other drugs that modulate the activity of this metabolic pathway. Cancer patients are susceptible to DDIs as they receive many medications, either for supportive care or for treatment of toxicity. Differences in DDI outcomes are generally negligible because of the wide therapeutic window of common drugs. However for anticancer agents, serious clinical consequences may occur from small changes in drug metabolism and pharmacokinetics. Therefore, the objective of this review is to highlight the current understanding of DDIs among TKIs, with a focus on metabolism, as well as to identify challenges in the prediction of DDIs and provide recommendations.

Therapeutic drug monitoring of targeted anticancer therapy

New oral targeted anticancer therapies are revolutionizing cancer treatment by transforming previously deadly malignancies into chronically manageable conditions. Nevertheless, drug resistance, persistence of cancer stem cells, and adverse drug effects still limit their ability to stabilize or cure malignant diseases in the long term. Response to targeted anticancer therapy is influenced by tumor genetics and by variability in drug concentrations. However, despite a significant inter-patient pharmacokinetic variability, targeted anticancer drugs are essentially licensed at fixed doses. Their therapeutic use could however be optimized by individualization of their dosage, based on blood concentration measurements via the therapeutic drug monitoring (TDM). TDM can increase the probability of therapeutic responses to targeted anticancer therapies, and would help minimize the risk of major adverse reactions.

Personalizing chemotherapy dosing using pharmacological methods

PURPOSE

Given the toxic nature and narrow therapeutic index of traditional chemotherapeutics, better methods of dose and therapy selection are critical. Pharmacological methods, including pharmacogenomics and pharmacokinetics, offer a practical method to enrich drug exposure, reduce toxicity, and improve quality of life for patients.

METHODS

PubMed and key abstracts from the American Society of Clinical Oncology (ASCO) and American Association for Cancer Research (AACR) were searched until July 2015 for clinical data relating to pharmacogenomic- and/or pharmacokinetic-guided dosing of anticancer drugs.

RESULTS

Based on the results returned from a thorough search of the literature and the plausibility of utilizing pharmacogenomic and/or pharmacokinetic methods to personalize chemotherapy dosing, we identified several chemotherapeutic agents with the potential for therapy individualization. We highlight the available data, clinical validity, and utility of using pharmacogenomics to personalize therapy for tamoxifen, 5-fluorouracil, mercaptopurine, and irinotecan, in addition to using pharmacokinetics to personalize dosing for 5-fluorouracil, busulfan, methotrexate, taxanes, and topotecan.

CONCLUSION

A concerted effort should be made by researchers to further elucidate the role of pharmacological methods in personalizing chemotherapy dosing to optimize the risk-benefit profile. Clinicians should be aware of the clinical validity, utility, and availability of pharmacogenomic- and pharmacokinetic-guided therapies in clinical practice, to ultimately allow optimal dosing for each and every cancer patient.

Management of dose variability and side effects for individualized cancer pharmacotherapy with tyrosine kinase inhibitors

Molecular-targeted therapies with tyrosine kinase inhibitors (TKIs) have provided a major breakthrough in cancer treatment. These agents are given orally and demonstrated to be substrates for drug transporters. In clinical settings, TKIs are mainly used at a fixed dose, but wide interpatient variability has been observed in their pharmacokinetics and/or pharmacodynamics. Genetic polymorphisms of ABC transporters, drug-drug interaction and adherence are among the factors causing such variation. To overcome these problems, therapeutic drug monitoring has been applied in clinical practice for patient care. Skin disorders are frequently observed as adverse drug reactions when using TKIs, and are commonly managed by symptomatic therapy based on clinical experience. Recent studies have provided some insights into the molecular mechanisms underlying skin disorders induced by TKIs. This review article summarizes the accumulated clinical and basic pharmacological evidence of TKIs, focusing on erlotinib, sorafenib and sunitinib.

Variability in bioavailability of small molecular tyrosine kinase inhibitors

Small molecular tyrosine kinase inhibitors (smTKIs) are in the centre of the very quickly expanding area of personalized chemotherapy and oral applicability thereof. The number of drugs in this class is rapidly growing, with twenty current approvals by both the European Medicines Agency (EMA) and the Food and Drug Administration (FDA). The drugs are, however, generally characterized by a poor oral, and thus variable, bioavailability. This results in significant variation in plasma levels and exposure. The cause is a complex interplay of factors, including poor aqueous solubility, issued permeability, membrane transport and enzymatic metabolism. Additionally, food and drug-drug interactions can play a significant role. The issues related with an impaired bioavailability generally receive little attention. To the best of our knowledge, this article is the first to provide an overview of the factors that determine the bioavailability of the smTKIs.

Association of drug exposure with toxicity and clinical response in metastatic renal cell carcinoma patients receiving an attenuated dosing regimen of sunitinib

An attenuated dosing (AD) regimen of 37.5 mg daily in repeated 4 week on, 2 week off cycles has been proposed to ameliorate frequent dose modifications caused by the toxicity observed with the approved dosing regimen of sunitinib for metastatic renal cell carcinoma (mRCC). This study aimed to determine the effect of drug exposure on toxicity and clinical response in patients receiving this regimen. All mRCC patients receiving AD sunitinib were invited to participate. In week 4 of each cycle, toxicity and plasma levels were assessed. Clinical responses were assessed after two cycles. A total of 36 patients were recruited. Patients who manifested ≥grade 2 mucositis (126.46 vs 84.81 ng/mL, p = 0.04) and altered taste (159.91 vs 105.22 ng/mL, p = 0.05) had higher total exposure than those who had grade 1 or no toxicity. Twenty-six patients completed two treatment cycles; four (15%) had partial responses, 15 (58%) had a stable disease and 7 (27%) had progressive disease. No difference in the exposure levels was found among the patients with different clinical outcomes. The AD regimen of sunitinib in Asian mRCC patients provided sufficient drug exposure with a lower incidence of toxicity, with higher drug exposure being observed in patients who experienced toxicity.

Role of the lean body mass and of pharmacogenetic variants on the pharmacokinetics and pharmacodynamics of sunitinib in cancer patients

INTRODUCTION

Sunitinib is a multikinase inhibitor active in various cancers types including renal cancers and endocrine tumors. The study analyzed the influence of the lean body mass (LBM) and of pharmacogenetic variants on the exposure to sunitinib and its active metabolite, SU12662, and on sunitinib toxicity and clinical activity.

MATERIALS AND METHODS

Exposure to sunitinib and SU12662 was assessed on days 10 and 21 during the first treatment cycle. Acute toxicity was graded using the NCI 4.0 CTCAE ver. 4.0. The LBM and 14 common single nucleotide polymorphisms in the CYP3A4/3A5, NR1I2, NR1I3, ABCB1, and ABCG2 genes were analyzed according to the drug exposure at day 10. Determinants (including sunitinib exposure and pharmacogenetic variants) for toxicities were assessed, as well as the relationship between drug exposure and survival in renal cancer patients.

RESULTS

Ninety-two patients (60 % with renal cancer) were assessable for pharmacokinetics, toxicity and survival, and 66 for genetic analysis. The LBM (p < 0.0001) and a polymorphism in the ABCG2 transporter (421C>A) (p = 0.014) were two independent parameters accounting for the variability of composite (sunitinib + SU12662) exposure. Advanced age (OR = 1.47 [1.01-2.15], p = 0.048) and high sunitinib exposure (OR = 1.16 [1.05-1.28], p = 0.005) were independently associated with any grade ≥ 3 acute toxicity, and high SU12662 exposure was associated with grade ≥ 2 thrombocytopenia (OR = 1.27 [1.03-1.57], p = 0.028). A high composite area under the curve (AUC) >1,973 ng/mL∙h at day 21 was associated with a doubled survival (35.2 vs 16.7 months; log-rank p = 0.0051) in renal cancer patients.

CONCLUSIONS

This study indicates that LBM and drug monitoring may be helpful in the management of sunitinib-treated patients.

Therapeutic drug monitoring in cancer--are we missing a trick?

Therapeutic drug monitoring (TDM) can be defined as the measurement of drug in biological samples to individualise treatment by adapting drug dose to improve efficacy and/or reduce toxicity. The cytotoxic drugs are characterised by steep dose-response relationships and narrow therapeutic windows. Inter-individual pharmacokinetic (PK) variability is often substantial. There are, however, a multitude of reasons why TDM has never been fully implemented in daily oncology practice. These include difficulties in establishing appropriate concentration target, common use of combination chemotherapies and the paucity of published data from pharmacological trials. The situation is different with targeted therapies. The large interindividual PK variability is influenced by the pharmacogenetic background of the patient (e.g. cytochrome P450 and ABC transporters polymorphisms), patient characteristics such as adherence to treatment and environmental factors (drug-drug interactions). Retrospective studies have shown that targeted drug exposure correlates with treatment response in various cancers. Evidence for imatinib currently exists, others are emerging for compounds including nilotinib, dasatinib, erlotinib, sunitinib, sorafenib and mammalian target of rapamycin (mTOR) inhibitors. Applications for TDM during oral targeted therapies may best be reserved for particular situations including lack of therapeutic response, severe or unexpected toxicities, anticipated drug-drug interactions and concerns over adherence treatment. There are still few data with monoclonal antibodies (mAbs) in favour of TDM approaches, even if data showed encouraging results with rituximab and cetuximab. TDM of mAbs is not yet supported by scientific evidence. Considerable effort should be made for targeted therapies to better define concentration-effect relationships and to perform comparative randomised trials of classic dosing versus pharmacokinetically-guided adaptive dosing.