Pharmacokinetic/pharmacodynamic modeling of biomarker response to sunitinib in healthy volunteers

Renal Carcinoma and Angiogenesis: Therapeutic Target and Biomarkers of Response in Current Therapies

Due to the aberrant hypervascularization and the high immune infiltration of renal tumours, current therapeutic regimens of renal cell carcinoma (RCC) target angiogenic or immunosuppressive pathways or both. Tumour angiogenesis plays an essential role in tumour growth and immunosuppression. Indeed, the aberrant vasculature promotes hypoxia and can also exert immunosuppressive functions. In addition, pro-angiogenic factors, including VEGF-A, have an immunosuppressive action on immune cells. Despite the progress of treatments in RCC, there are still non responders or acquired resistance. Currently, no biomarkers are used in clinical practice to guide the choice between the different available treatments. Considering the role of angiogenesis in RCC, angiogenesis-related markers are interesting candidates. They have been studied in the response to antiangiogenic drugs (AA) and show interest in predicting the response. They have been less studied in immunotherapy alone or combined with AA. In this review, we will discuss the role of angiogenesis in tumour growth and immune escape and the place of angiogenesis-targeted biomarkers to predict response to current therapies in RCC.

Optimization of blood pressure measurement practices for pharmacodynamic analyses of tyrosine-kinase inhibitors

Blood pressure measurements form a critical component of adverse event monitoring for tyrosine kinase inhibitors, but might also serve as a biomarker for dose titrations. This study explored the impact of various sources of within-individual variation on blood pressure readings to improve measurement practices and evaluated the utility for individual- and population-level dose selection. A pharmacokinetic-pharmacodynamic modeling framework was created to describe circadian blood pressure changes, inter- and intra-day variability, changes from dipper to non-dipper profiles, and the relationship between drug exposure and blood pressure changes over time. The framework was used to quantitatively evaluate the influence of physiological and pharmacological aspects on blood pressure measurements, as well as to compare measurement techniques, including office-based, home-based, and ambulatory 24-h blood pressure readings. Circadian changes, as well as random intra-day and inter-day variability, were found to be the largest sources of within-individual variation in blood pressure. Office-based and ambulatory 24-h measurements gave rise to potential bias (>5 mmHg), which was mitigated by model-based estimations. Our findings suggest that 5-8 consecutive, home-based, measurements taken at a consistent time around noon, or alternatively within a limited time frame (e.g., 8.00 a.m. to 12.00 p.m. or 12.00 p.m. to 5.00 p.m.), will give rise to the most consistent blood pressure estimates. Blood pressure measurements likely do not represent a sufficiently accurate method for individual-level dose selection, but may be valuable for population-level dose identification. A user-friendly tool has been made available to allow for interactive blood pressure simulations and estimations for the investigated scenarios.

Population Pharmacokinetics of Sunitinib and its Active Metabolite SU012662 in Pediatric Patients with Gastrointestinal Stromal Tumors or Other Solid Tumors

BACKGROUND AND OBJECTIVE

Population pharmacokinetic analysis explored the pharmacokinetics of sunitinib and its primary active metabolite, SU012662, in children and evaluated the sunitinib dose(s) that produce comparable plasma exposures to adults receiving the approved daily dose.

METHODS

Data were from 65 children with gastrointestinal stromal tumors (GIST) or solid tumors. Pharmacokinetic models of sunitinib and SU012662 were developed using a systematic multi-step approach employing nonlinear mixed-effects modeling. The effect of predefined covariates on pharmacokinetic parameters was assessed. Final models were validated using visual predictive check and statistical techniques.

RESULTS

The final dataset comprised 439 sunitinib and 417 SU012662 post-baseline plasma observations. Base models were characterized by two-compartment models with first-order absorption and lag time. Body surface area (BSA) was the only covariate that affected (P < 0.001) pharmacokinetic parameters for sunitinib and SU012662 and was incorporated into the final models. Bootstrap results indicated that the final models represented the final dataset adequately. Based on the final models, a sunitinib dose of ~ 20mg/m²/day in children with GIST aged 6-17 years would be expected to lead to similar total plasma exposures of sunitinib and SU012661 as a dose of 50 mg/day in an adult with GIST on schedule 4/2.

CONCLUSIONS

In children with GIST or solid tumors receiving sunitinib, population pharmacokinetic analysis identified BSA as the only covariate that affected pharmacokinetic parameters and predicted a dose of ~ 20 mg/m²/day as achieving equivalent exposure to 50 mg/day in adults with GIST on schedule 4/2.

TRIAL REGISTRATION

ClinicalTrials.gov identifiers (date registered): NCT01396148 (July 2011); NCT01462695 (October 2011); NCT00387920 (October 2006).

Extrapolation of pharmacokinetics and pharmacodynamics of sunitinib in children with gastrointestinal stromal tumors

Purpose

The starting dose of sunitinib in children with gastrointestinal stromal tumors (GIST) was extrapolated based on data in adults with GIST or solid tumors and children with solid tumors.

Methods

Integrated population pharmacokinetics (PK), PK/pharmacodynamics (PD), and exposure–response analyses using nonlinear mixed-effects modeling approaches were performed to extrapolate PK and PD of sunitinib in children with GIST at projected dose(s) with plasma drug exposures comparable to 50-mg/day in adults with GIST. The analysis datasets included PK/PD data in adults with GIST and adults and children with solid tumors. The effect of covariates on PK and safety/efficacy endpoints were explored.

Results

Two-compartment models with lag time were successfully used to describe the PK of sunitinib and its active metabolite SU012662. PK/PD models were successfully built to describe key continuous safety and efficacy endpoints. The effect of age on sunitinib apparent clearance (CL/F) and body surface area on SU012662 CL/F was statistically significant (P ≤ 0.001): children who were younger or of smaller body size had lower CL/F; however, age and body size did not appear to negatively affect safety or efficacy response to plasma drug exposure.

Conclusion

Based on PK, safety, and efficacy trial simulations, a sunitinib starting dose of ~ 25 mg/m²/day was predicted to provide comparable plasma drug exposures in children with GIST as in adults with GIST treated with 50 mg/day. However, in the absence of a tumor type effect of sunitinib on CL/F in children, the projected equivalent dose for this population would be ~ 20 mg/m²/day.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00280-020-04221-x.

Population pharmacokinetics-pharmacodynamics of sunitinib in pediatric patients with solid tumors

Purpose

The safety profile of sunitinib in children, including the impact of sunitinib exposure on safety endpoints, was assessed using population pharmacokinetic (PK) and pharmacokinetic–pharmacodynamic (PK–PD) models.

Methods

Data were from two clinical studies in 59 children with solid tumors (age range 2–21 years, 28 male/31 female, body weight range 16.2–100 kg, body surface are [BSA] range 0.7–2.1 m²). Analysis of covariates that affected PK and PD parameters was conducted using a nonlinear mixed-effects model. Safety and tolerability endpoints were absolute neutrophil count, hepatic transaminases, diastolic blood pressure, hemoglobin, lymphocyte count, platelet count, white blood cell count, hand-foot syndrome, fatigue, nausea, intracranial hemorrhage, and vomiting.

Results

The models well described the time courses of concentrations of sunitinib and its primary active metabolite SU012662, as well as safety and tolerability endpoints. In PK models for sunitinib and SU012662, BSA was the only covariate that statistically significantly affected apparent clearance (CL/F) and apparent central volume of distribution (Vc/F). Higher BSA was associated with greater CL/F and Vc/F. No statistically significant covariates were identified in the PK–PD models. For safety endpoints that had a sufficient number of adverse events, a higher probability of adverse events was associated with higher average plasma sunitinib concentrations.

Conclusion

In PK models, BSA was the only covariate that affected major PK parameters of sunitinib and SU012662. Based on analysis of safety and tolerability endpoints, the PK–PD relationships were mainly driven by sunitinib plasma exposures and were not affected by age, sex, respective baseline safety endpoint values, baseline Eastern Cooperative Oncology Group performance status, or body size.

Trial registration

ClinicalTrials.gov: NCT00387920 (registered October 13, 2006), NCT01462695 (registered October 31, 2011).

Electronic supplementary material

The online version of this article (10.1007/s00280-020-04106-z) contains supplementary material, which is available to authorized users.

A multicentre phase 1b/2 study of tivozanib in patients with advanced inoperable hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is a major cause of cancer-related death. It is a highly vascular tumour with multiple angiogenic factors, most importantly vascular endothelial growth factor (VEGF), involved in HCC progression. Tivozanib is an oral inhibitor of VEGFR-1/2/3 with promising activity against HCC in vivo.

Methods

We conducted a phase 1b/2 study of tivozanib in patients with advanced HCC. The safety, dosing, pharmacokinetics, pharmacodynamics, and preliminary antineoplastic efficacy of tivozanib were evaluated.

Results

Twenty-seven patients received at least one dose of tivozanib. Using a 3+3 design, the recommended phase 2 dose (RP2D) of tivozanib was determined to be 1 mg per os once daily, 21 days on–7 days off. The median progression-free and overall survival were 24 weeks and 9 months, respectively, for patients treated at RP2D. The overall response rate was 21%. Treatment was well tolerated. A significant decrease in soluble plasma VEGFR-2 was noted, assuring adequate target engagement.

Conclusions

Although this study did not proceed to stage 2, there was an early efficacy signal with a very favourable toxicity profile. A phase 1/2 trial of tivozanib in combination with durvalumab is currently underway.

Trial registration

ClinicalTrials.gov NCT01835223, registered on 15 April 2013.

Reviewing the role of healthy volunteer studies in drug development

BACKGROUND

With the exception of genotoxic oncology drugs, first-in-human, Phase 1 clinical studies of investigational drugs have traditionally been conducted in healthy volunteers (HVs). The primary goal of these studies is to investigate the pharmacokinetics and pharmacodynamics of a novel drug candidate, determine appropriate dosing, and document safety and tolerability.

MAIN BODY

When tailored to specific study objectives, HV studies are beneficial to manufacturers and patients alike and can be applied to both non-oncology and oncology drug development. Enrollment of HVs not only increases study accrual rates for dose-escalation studies but also alleviates the ethical concern of enrolling patients with disease in a short-term study at subtherapeutic doses when other studies (e.g. Phase 2 or Phase 3 studies) may be more appropriate for the patient. The use of HVs in non-oncology Phase 1 clinical trials is relatively safe but nonetheless poses ethical challenges because of the potential risks to which HVs are exposed. In general, most adverse events associated with non-oncology drugs are mild in severity, and serious adverse events are rare, but examples of severe toxicity have been reported. The use of HVs in the clinical development of oncology drugs is more limited but is nonetheless useful for evaluating clinical pharmacology and establishing an appropriate starting dose for studies in cancer patients. During the development of oncology drugs, clinical pharmacology studies in HVs have been used to assess pharmacokinetics, drug metabolism, food effects, potential drug-drug interactions, effects of hepatic and renal impairment, and other pharmacologic parameters vital for clinical decision-making in oncology. Studies in HVs are also being used to evaluate biosimilars versus established anticancer biologic agents.

CONCLUSION

A thorough assessment of toxicity and pharmacology throughout the drug development process is critical to ensure the safety of HVs. With the appropriate safeguards, HVs will continue to play an important role in future drug development.

Tumor-Independent Host Secretomes Induced By Angiogenesis and Immune-Checkpoint Inhibitors

The levels of various circulating blood proteins can change in response to cancer therapy. Monitoring therapy-induced secretomes (TIS) may have use as biomarkers for establishing optimal biological effect (such as dosing) or identifying sources of toxicity and drug resistance. Although TIS can derive from tumor cells directly, nontumor "host" treatment responses can also impact systemic secretory programs. For targeted inhibitors of the tumor microenvironment, including antiangiogenic and immune-checkpoint therapies, host TIS could explain unexpected collateral "side effects" of treatment. Here, we describe a comparative transcriptomic and proteomic analysis of host TIS in tissues and plasma from cancer-free mice treated with antibody and receptor tyrosine kinase inhibitors (RTKI) of the VEGF, cMet/ALK, and PD-1 pathways. We found that all cancer therapies elicit TIS independent of tumor growth, with systemic secretory gene change intensity higher in RTKIs compared with antibodies. Our results show that host TIS signatures differ between drug target, drug class, and dose. Notably, protein and gene host TIS signatures were not always predictive for each other, suggesting limitations to transcriptomic-only approaches to clinical biomarker development for circulating proteins. Together, these are the first studies to assess and compare "off-target" host secretory effects of VEGF and PD-1 pathway inhibition that occur independent of tumor stage or tumor response to therapy. Testing treatment impact on normal tissues to establish host-mediated TIS signatures (or "therasomes") may be important for identifying disease agnostic biomarkers to predict benefits (or limitations) of drug combinatory approaches. Mol Cancer Ther; 17(7); 1602-12. ©2018 AACR.

Quantifying the relationship between inhibition of VEGF receptor 2, drug-induced blood pressure elevation and hypertension

BACKGROUND AND PURPOSE

Several anti-angiogenic cancer drugs that inhibit VEGF receptor (VEGFR) signalling for efficacy are associated with a 15-60% incidence of hypertension. Tyrosine kinase inhibitors (TKIs) that have off-target activity at VEGFR-2 may also cause blood pressure elevation as an undesirable side effect. Therefore, the ability to translate VEGFR-2 off-target potency into blood pressure elevation would be useful in development of novel TKIs. Here, we have sought to quantify the relationship between VEGFR-2 inhibition and blood pressure elevation for a range of kinase inhibitors.

EXPERIMENTAL APPROACH

Porcine aortic endothelial cells overexpressing VEGFR-2 (PAE) were used to determine IC₅₀ for VEGFR-2 phosphorylation. These IC₅₀ values were compared with published reports of exposure attained during clinical use and the corresponding incidence of all-grade hypertension. Unbound average plasma concentration (C_av,u ) was selected to be the most appropriate pharmacokinetic parameter. The pharmacokinetic-pharmacodynamic (PKPD) relationship for blood pressure elevation was investigated for selected kinase inhibitors, using data derived either from clinical papers or from rat telemetry experiments.

KEY RESULTS

All-grade hypertension was predominantly observed when the C_av,u was >0.1-fold of the VEGFR-2 (PAE) IC₅₀ . Furthermore, based on the PKPD analysis, an exposure-dependent blood pressure elevation >1 mmHg was observed only when the C_av,u was >0.1-fold of the VEGFR-2 (PAE) IC₅₀ .

CONCLUSIONS AND IMPLICATIONS

Taken together, these data show that the risk of blood pressure elevation is proportional to the amount of VEGFR-2 inhibition, and a margin of >10-fold between VEGFR-2 IC₅₀ and C_av,u appears to confer a minimal risk of hypertension.

Pharmacokinetics and Pharmacodynamics of Meloxicam in East Asian Populations: The Role of Ethnicity on Drug Response

We aimed to reanalyze the differences in the pharmacokinetics (PKs) of meloxicam in East Asian populations based on a population approach using previously published data and to investigate the factors found in population PK analysis that affect the pharmacodynamics (PDs) of meloxicam. Population PK analysis was performed in 119 healthy male subjects (30 Japanese, 30 Chinese, 29 Korean, and 30 white) under strictly controlled trial conditions with regulated meals and a single lot of the drug. We found that CYP2C9 genotype and lean body mass were statistically significant predictors of clearance and volume of distribution, respectively. A statistical significant difference in the PK parameters between ethnic groups could not be identified. Simulations using PK/PD models showed that CYP2C9 genotype is the factor that affects the PDs of meloxicam. The genetic polymorphisms highlighted in this study would be beneficial for conducting clinical trials in East Asians with similar genetic backgrounds.

Population Pharmacokinetic/Pharmacodynamic Modeling of Sunitinib by Dosing Schedule in Patients with Advanced Renal Cell Carcinoma or Gastrointestinal Stromal Tumor

Background

Sunitinib is a multi-targeted tyrosine kinase inhibitor used in the treatment of advanced renal cell carcinoma (RCC) and imatinib-resistant/intolerant gastrointestinal stromal tumors (GIST).

Methods

A meta-analysis of 10 prospective clinical studies in advanced RCC and GIST was performed to support the development of pharmacokinetic (PK) and PK/pharmacodynamic (PD) models that account for the effects of important covariates. These models were used to make predictions with respect to the PK, safety, and efficacy of sunitinib when administered on the traditional 4-weeks-on/2-weeks-off schedule (Schedule 4/2) versus an alternative schedule of 2 weeks on/1 week off (Schedule 2/1).

Results

The covariates found to have a significant effect on one or more of the PK or PD parameter studies included, age, sex, body weight, race, baseline Eastern Cooperative Oncology Group performance status, tumor type, and dosing schedule. The models predicted that, in both RCC and GIST patients, Schedule 2/1 would have comparable efficacy to Schedule 4/2, despite some differences in PK profiles. The models also predicted that, in both indications, sunitinib-related thrombocytopenia would be less severe when sunitinib was administered on Schedule 2/1 dosing compared with Schedule 4/2.

Conclusion

These findings support the use of sunitinib on Schedule 2/1 as a potential alternative to Schedule 4/2 because it allows for the management of toxicity without loss of efficacy.

Electronic supplementary material

The online version of this article (doi:10.1007/s40262-016-0404-5) contains supplementary material, which is available to authorized users.

Population Modeling Integrating Pharmacokinetics, Pharmacodynamics, Pharmacogenetics, and Clinical Outcome in Patients With Sunitinib-Treated Cancer

The tyrosine kinase inhibitor sunitinib is used as first‐line therapy in patients with metastasized renal cell carcinoma (mRCC), given in fixed‐dose regimens despite its high variability in pharmacokinetics (PKs). Interindividual variability of drug exposure may be responsible for differences in response. Therefore, dosing strategies based on pharmacokinetic/pharmacodynamic (PK/PD) models may be useful to optimize treatment. Plasma concentrations of sunitinib, its active metabolite SU12662, and the soluble vascular endothelial growth factor receptors sVEGFR‐2 and sVEGFR‐3, were measured in 26 patients with mRCC within the EuroTARGET project and 21 patients with metastasized colorectal cancer (mCRC) from the C‐II‐005 study. Based on these observations, PK/PD models with potential influence of genetic predictors were developed and linked to time‐to‐event (TTE) models. Baseline sVEGFR‐2 levels were associated with clinical outcome in patients with mRCC, whereas active drug PKs seemed to be more predictive in patients with mCRC. The models provide the basis of PK/PD‐guided strategies for the individualization of anti‐angiogenic therapies.

A Pharmacometric Framework for Axitinib Exposure, Efficacy, and Safety in Metastatic Renal Cell Carcinoma Patients

The relationships between exposure, biomarkers (vascular endothelial growth factor (VEGF), soluble VEGF receptors (sVEGFR)-1, -2, -3, and soluble stem cell factor receptor (sKIT)), tumor sum of longest diameters (SLD), diastolic blood pressure (dBP), and overall survival (OS) were investigated in a modeling framework. The dataset included 64 metastatic renal cell carcinoma patients (mRCC) treated with oral axitinib. Biomarker timecourses were described by indirect response (IDR) models where axitinib inhibits sVEGFR-1, -2, and -3 production, and VEGF degradation. No effect was identified on sKIT. A tumor model using sVEGFR-3 dynamics as driver predicted SLD data well. An IDR model, with axitinib exposure stimulating the response, characterized dBP increase. In a time-to-event model the SLD timecourse predicted OS better than exposure, biomarker- or dBP-related metrics. This type of framework can be used to relate pharmacokinetics, efficacy, and safety to long-term clinical outcome in mRCC patients treated with VEGFR inhibitors. (ClinicalTrial.gov identifier NCT00569946.).

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.

Bridging Sunitinib Exposure to Time-to-Tumor Progression in Hepatocellular Carcinoma Patients With Mathematical Modeling of an Angiogenic Biomarker

Hepatocellular carcinoma (HCC) is third in cancer-related causes of death worldwide and its treatment is a significant unmet medical need. Sunitinib is a selective tyrosine kinase inhibitor of the angiogenic biomarker: soluble vascular endothelial growth factor receptor-2 (sVEGFR2 ). Sunitinib failed its primary overall survival endpoint in patients with advanced HCC in a phase III trial compared to sorafenib. In the present study, pharmacokinetic-pharmacodynamic modeling was used to link drug-exposure to tumor-growth-inhibition (TGI) and time-to-tumor progression (TTP) through sVEGFR2 dynamics. The results suggest that 1) active drug concentration (i.e., sunitinib and its metabolite) inhibits the release of sVEGFR2 and that such inhibition is associated with TGI, and 2) daily sVEGFR2 exposure is likely a reliable predictor for the TTP in HCC patients. Moreover, the model quantitatively links the dynamics of an angiogenesis biomarker to TTP and accurately predicts observed literature-reported results of placebo treatment.

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.

Population pharmacokinetic-pharmacodynamic modelling in oncology: a tool for predicting clinical response

In oncology trials, overall survival (OS) is considered the most reliable and preferred endpoint to evaluate the benefit of drug treatment. Other relevant variables are also collected from patients for a given drug and its indication, and it is important to characterize the dynamic effects and links between these variables in order to improve the speed and efficiency of clinical oncology drug development. However, the drug-induced effects and causal relationships are often difficult to interpret because of temporal differences. To address this, population pharmacokinetic–pharmacodynamic (PKPD) modelling and parametric time-to-event (TTE) models are becoming more frequently applied. Population PKPD and TTE models allow for exploration towards describing the data, understanding the disease and drug action over time, investigating relevance of biomarkers, quantifying patient variability and in designing successful trials. In addition, development of models characterizing both desired and adverse effects in a modelling framework support exploration of risk-benefit of different dosing schedules. In this review, we have summarized population PKPD modelling analyses describing tumour, tumour marker and biomarker responses, as well as adverse effects, from anticancer drug treatment data. Various model-based metrics used to drive PD response and predict OS for oncology drugs and their indications are also discussed.

Population pharmacokinetic-pharmacodynamic modelling of 24-h diastolic ambulatory blood pressure changes mediated by axitinib in patients with metastatic renal cell carcinoma

BACKGROUND

Increased blood pressure (BP) is commonly observed in patients treated with vascular endothelial growth factor pathway inhibitors, including axitinib. Ambulatory BP monitoring (ABPM) and pharmacokinetic data were collected in a randomised, double-blind phase II study of axitinib with or without dose titration in previously untreated patients with metastatic renal cell carcinoma.

OBJECTIVE

Aims of these analyses were to (1) develop a population pharmacokinetic-pharmacodynamic model for describing the relationship between axitinib exposure and changes in diastolic BP (dBP) and (2) simulate changes in dBP with different axitinib dosing regimens.

METHODS

We employed a three-stage modelling approach, which included development of (1) a baseline 24-h ABPM model, (2) a pharmacokinetic model from serial and sparse pharmacokinetic data, and (3) an indirect-response, maximum-effect (Emax) model to evaluate the exposure-driven effect of axitinib on dBP. Simulations (N = 1,000) were performed using the final pharmacokinetic-pharmacodynamic model to evaluate dBP changes on days 4 and 15 of treatment with different axitinib doses.

RESULTS

Baseline ABPM data from 62 patients were best described by 24-h mean dBP and two cosine terms. The final indirect-response Emax model showed good agreement between observed 24-h ABPM data and population and individual predictions. The maximum increase in dBP was 20.8 %, and the axitinib concentration at which 50 % of the maximal increase in dBP was reached was 12.4 ng/mL.

CONCLUSION

Our model adequately describes the relationship between axitinib exposure and dBP increases. Results from these analyses may potentially be applied to infer dBP changes in patients administered axitinib at nonstandard doses.

Predictive biomarker candidates to delineate efficacy of antiangiogenic treatment in renal cell carcinoma

Antiangiogenic therapy is currently considered as the cornerstone of treatment in metastatic kidney cancer. A monoclonal antibody against the vascular endothelial growth factor (VEGF) and several tyrosine kinase inhibitors targeting the VEGF receptors demonstrated, 7 years ago, to deeply impact the outcome of this tumor and became a model of integration of molecular knowledge into clinical practice. Unfortunately, no further improvement in survival has been made and 20-25 % of cases remain primary refractory to these drugs, with an overall dismal prognosis. Since biomarker predictors of activity are lacking, their development could highly help in the process of making clinical decisions when choosing the best option for every patient or prompting the inclusion in clinical trials. This unmet medical need could become even more relevant if new immunotherapy confirms its initial promising results in this pathology. In this article, we provide an insight of current state of the art regarding the prediction of antiangiogenic efficacy in kidney cancer and propose new strategies for the implementation of such markers in clinical practice.

Circulating cytokines and monocyte subpopulations as biomarkers of outcome and biological activity in sunitinib-treated patients with advanced neuroendocrine tumours

BACKGROUND

Sunitinib is approved worldwide for treatment of advanced pancreatic neuroendocrine tumours (pNET), but no validated markers exist to predict response. This analysis explored biomarkers associated with sunitinib activity and clinical benefit in patients with pNET and carcinoid tumours in a phase II study.

METHODS

Plasma was assessed for vascular endothelial growth factor (VEGF)-A, soluble VEGF receptor (sVEGFR)-2, sVEGFR-3, interleukin (IL)-8 (n=105), and stromal cell-derived factor (SDF)-1α (n=28). Pre-treatment levels were compared between tumour types and correlated with response, progression-free (PFS), and overall survival (OS). Changes in circulating myelomonocytic and endothelial cells were also analysed.

RESULTS

Stromal cell-derived factor-1α and sVEGFR-2 levels were higher in pNET than in carcinoid (P=0.003 and 0.041, respectively). High (above-median) baseline SDF-1α was associated with worse PFS, OS, and response in pNET, and high sVEGFR-2 with longer OS (P⩽0.05). For carcinoid, high IL-8, sVEGFR-3, and SDF-1α were associated with shorter PFS and OS, and high IL-8 and SDF-1α with worse response (P⩽0.05). Among circulating cell types, monocytes showed the largest on-treatment decrease, particularly CD14+ monocytes co-expressing VEGFR-1 or CXCR4.

CONCLUSIONS

Interleukin-8, sVEGFR-3, and SDF-1α were identified as predictors of sunitinib clinical outcome. Putative pro-tumorigenic CXCR4+ and VEGFR-1+ monocytes represent novel candidate markers and biologically relevant targets explaining the activity of sunitinib.

Systems pharmacology approaches for optimization of antiangiogenic therapies: challenges and opportunities

Targeted therapies have become an important therapeutic paradigm for multiple malignancies. The rapid development of resistance to these therapies impedes the successful management of advanced cancer. Due to the redundancy in angiogenic signaling, alternative proangiogenic factors are activated upon treatment with anti-VEGF agents. Higher doses of the agents lead to greater stimulation of compensatory proangiogenic pathways that limit the therapeutic efficacy of VEGF-targeted drugs and produce escape mechanisms for tumor. Evidence suggests that dose intensity and schedules affect the dynamics of the development of this resistance. Thus, an optimal dosing regimen is crucial to maximizing the therapeutic benefit of antiangiogenic agents and limiting treatment resistance. A systems pharmacology approach using multiscale computational modeling can facilitate a mechanistic understanding of these dynamics of angiogenic biomarkers and their impacts on tumor reduction and resistance. Herein, we discuss a systems pharmacology approach integrating the biology of VEGF-targeted therapy resistance, including circulating biomarkers, and pharmacodynamics to enable the optimization of antiangiogenic therapy for therapeutic gains.

Current management of patients with gastrointestinal stromal tumor receiving the multitargeted tyrosine kinase inhibitor sunitinib

BACKGROUND

Gastrointestinal stromal tumor (GIST), a form of soft tissue sarcoma, is often detected incidentally or at an advanced stage. The tyrosine kinase inhibitor sunitinib malate (Sutent * ) is established as second-line treatment for the management of GIST after disease progression on, or intolerance to, first-line imatinib treatment. Several published reviews give guidance on management of side effects in patients with advanced renal cell carcinoma treated with sunitinib, but fewer publications cover side-effect management in patients with GIST.

SCOPE

Using published articles and abstracts, prescribing information, and personal experience in managing patients with GIST at a specialized center of excellence for cancer care, I review side-effect management recommendations for patients with GIST treated with sunitinib and provide an overview of GIST.

FINDINGS

Sunitinib has a well described side-effect profile: most side effects occurring in patients with GIST can be easily managed by standard medical intervention and/or dose modification.

CONCLUSION

Care of patients with GIST can be enhanced through communication, support, knowledge, and education, with the goal of providing effective therapy and optimal symptom control.

Quantitative insight in utilizing circulating angiogenic factors as biomarkers for antiangiogenic therapy: systems pharmacology approach

Circulating angiogenic factors (CAF) like vascular endothelial growth factor (VEGF), placental growth factor (PlGF), and sVEGFR2 have potential as biomarkers for antiangiogenic therapy. The interpretation of changes in CAF is complicated by the dynamic nature of the tumor and host cells emanating CAF in response to VEGF pathway inhibition. We developed a systems pharmacology model of anti-VEGF agents to investigate CAF modulation by tumor and host cells, and the relationship between overall CAF changes in response to sunitinib and antitumor efficacy. This model distinguishes between the tumor cells' contributions from tumor-independent response to therapy and total plasma CAF correlating with antitumor activity. Altered VEGF is more likely to serve as a useful biomarker reflecting tumor responses in cancer patients whose pretreatment VEGF is higher than baseline VEGF in healthy subjects. Our findings provide a mechanistic insight into tumor modulation of angiogenic molecules, and may explain the inconsistent results found in previous biomarker studies.

Clinical pharmacokinetics of tyrosine kinase inhibitors: implications for therapeutic drug monitoring

The treatment of many malignancies has been improved in recent years by the introduction of molecular targeted therapies. These drugs interact preferentially with specific targets that are mutated and/or overexpressed in malignant cells. A group of such targets are the tyrosine kinases, against which a number of inhibitors (tyrosine kinase inhibitors, TKIs) have been developed. Imatinib, a TKI with targets that include the breakpoint cluster region-Abelson (bcr-abl) fusion protein kinase and mast/stem cell growth factor receptor kinase (c-Kit), was the first clinically successful drug of this type and revolutionized the treatment and prognosis of chronic myeloid leukemia and gastrointestinal stromal tumors. This success paved the way for the development of other TKIs for the treatment of a range of hematological malignancies and solid tumors. To date, 14 TKIs have been approved for clinical use and many more are under investigation. All these agents are given orally and are substrates of a range of drug transporters and metabolizing enzymes. In addition, some TKIs are capable of inhibiting their own transporters and metabolizing enzymes, making their disposition and metabolism at steady-state unpredictable. A given dose can therefore give rise to markedly different plasma concentrations in different patients, favoring the selection of resistant clones in the case of subtherapeutic exposure, and increasing the risk of toxicity if dosage is excessive. The aim of this review was to summarize current knowledge of the clinical pharmacokinetics and known adverse effects of the TKIs that are available for clinical use and to provide practical guidance on the implications of these data in patient management, in particular with respect to therapeutic drug monitoring.

Sorafenib dose escalation is not uniformly associated with blood pressure elevations in normotensive patients with advanced malignancies

Hypertension with vascular endothelial growth factor (VEGF) receptor inhibitors is associated with superior treatment outcomes for advanced cancer patients. To determine whether increased doses of sorafenib cause incremental increases in blood pressure (BP) we measured 12-hour ambulatory BP in 41 normotensive advanced solid tumor patients in a randomized dose escalation study. After 7 days’ sorafenib (400mg BID) mean diastolic BP (DBP) increased in both study groups. After dose escalation, group A (400mg TID) had marginally significant further increase in 12-hour mean DBP (p=0.053) but group B (600mg BID) did not achieve statistically significant increases (p=0.25). Within groups, individuals varied in BP response to sorafenib dose escalation, but these differences did not correlate with changes in steady state plasma sorafenib concentrations. These findings in normotensive patients suggest BP is a complex pharmacodynamic biomarker of VEGF inhibition. Patients have intrinsic differences in sensitivity to the BP elevating effects of sorafenib.

Optimizing drug development of anti-cancer drugs in children using modelling and simulation

Modelling and simulation (M&S)-based approaches have been proposed to support paediatric drug development in order to design and analyze clinical studies efficiently. Development of anti-cancer drugs in the paediatric population is particularly challenging due to ethical and practical constraints. We aimed to review the application of M&S in the development of anti-cancer drugs in the paediatric population, and to identify where M&S-based approaches could provide additional support in paediatric drug development of anti-cancer drugs. A structured literature search on PubMed was performed. The majority of identified M&S-based studies aimed to use population PK modelling approaches to identify determinants of inter-individual variability, in order to optimize dosing regimens and to develop therapeutic drug monitoring strategies. Prospective applications of M&S approaches for PK-bridging studies have scarcely been reported for paediatric oncology. Based on recent developments of M&S in drug development there are several opportunities where M&S could support more informative bridging between children and adults, and increase efficiency of the design and analysis of paediatric clinical trials, which should ultimately lead to further optimization of drug treatment strategies in this population.

PKPD Modeling of VEGF, sVEGFR-2, sVEGFR-3, and sKIT as Predictors of Tumor Dynamics and Overall Survival Following Sunitinib Treatment in GIST

The predictive value of longitudinal biomarker data (vascular endothelial growth factor (VEGF), soluble VEGF receptor (sVEGFR)-2, sVEGFR-3, and soluble stem cell factor receptor (sKIT)) for tumor response and survival was assessed based on data from 303 patients with imatinib-resistant gastrointestinal stromal tumors (GIST) receiving sunitinib and/or placebo treatment. The longitudinal tumor size data were well characterized by a tumor growth inhibition model, which included, as significant descriptors of tumor size change, the model-predicted relative changes from baseline over time for sKIT (most significant) and sVEGFR-3, in addition to sunitinib exposure. Survival time was best described by a parametric time-to-event model with baseline tumor size and relative change in sVEGFR-3 over time as predictive factors. Based on the proposed modeling framework to link longitudinal biomarker data with overall survival using pharmacokinetic-pharmacodynamic models, sVEGFR-3 demonstrated the greatest predictive potential for overall survival following sunitinib treatment in GIST.CPT: Pharmacometrics & Systems Pharmacology (2013) 2, e84; doi:10.1038/psp.2013.61; advance online publication 20 November 2013.

Treatment-induced host-mediated mechanisms reducing the efficacy of antitumor therapies

In addition to its direct effects on tumor cells, chemotherapy can rapidly activate various host processes that contribute to therapy resistance and tumor regrowth. The host response to chemotherapy consists of changes in numerous cell types and cytokines. Examples include the acute mobilization and tumor homing of pro-angiogenic bone marrow-derived cells, activation of cells in the tumor microenvironment to produce systemic or paracrine factors, and tissue-specific responses that provide a protective niche for tumor cells. All of these factors reduce chemotherapy efficacy, and blocking the host response at various levels may therefore significantly improve treatment outcome. However, before the combination of conventional chemotherapy with agents blocking specific aspects of the host response can be implemented into clinical practice, a better understanding of the molecular mechanisms behind the host response is required.

Model-based treatment optimization of a novel VEGFR inhibitor

AIM

To evaluate dosing and intervention strategies for the phase II programme of a VEGF receptor inhibitor using PK-PD modelling and simulation, with the aim of maximizing (i) the number of patients on treatment and (ii) the average dose level during treatment.

METHODS

A previously developed PK-PD model for lenvatinib (E7080) was updated and parameters were re-estimated (141 patients, once daily and twice daily regimens). Treatment of lenvatinib was simulated for 16 weeks, initiated at 25 mg once daily. Outcome measures included the number of patients on treatment and overall drug exposure. A hypertension intervention design proposed for phase II studies was evaluated, including antihypertensive treatment and dose de-escalation. Additionally, a within-patient dose escalation was investigated, titrating up to 50 mg once daily unless unacceptable toxicity occurred.

RESULTS

Using the proposed antihypertension intervention design, 82% of patients could remain on treatment, and the mean dose administered was 21.5 mg day⁻¹. The adverse event (AE) guided dose titration increased the average dose by 4.6 mg day⁻¹, while only marginally increasing the percentage of patients dropping out due to toxicity (from 18% to 20.8%).

CONCLUSIONS

The proposed hypertension intervention design is expected to be effective in maintaining patients on treatment with lenvatinib. The AE-guided dose titration with blood pressure as a biomarker yielded a higher overall dose level, without relevant increases in toxicity. Since increased exposure to lenvatinib seems correlated with increased treatment efficacy, the adaptive treatment design may thus be a valid approach to improve treatment outcome.

Circulating biomarkers in advanced renal cell carcinoma: clinical applications

Advances in understanding the biology of renal cell carcinoma (RCC) have resulted in treatment strategies based on molecularly targeted agents that have substantially improved the outcomes of patients with metastatic RCC. Agents targeting the vascular endothelial growth factor pathway and the mammalian target of rapamycin have shown efficacy in randomized clinical trials and received international approval for treating RCC. Multiple candidate biomarkers of the biologic activity of such targeted therapies as well as markers of treatment response and patients' prognosis are being evaluated to improve drug development and to identify patients who may obtain the greatest benefit from the various treatment options. This review summarizes recent developments in identifying circulating biomarkers of targeted therapies for metastatic RCC, including soluble proteins and circulating cells.

Determination of soluble vascular endothelial growth factor receptor 3 (sVEGFR-3) in plasma as pharmacodynamic biomarker

Soluble VEGFR-3 (sVEGFR-3) is a potential biomarker for the anti-angiogenic activity of tyrosine kinase inhibitors. The aim of this investigation was the validation of an enzyme-linked immunosorbent assay (ELISA) to measure sVEGFR-3 in human plasma and the investigation of its applicability in clinical trials as first step of the biomarker validation process. General validation criteria were assessed based on current guidelines and recommendations for immunoassays. The ELISA was applied in two clinical trials including healthy volunteers and metastatic colorectal cancer (mCRC) patients receiving 50 or 37.5mg sunitinib per day, respectively. SVEGFR-3 was measured at predefined time points. Undiluted, inactivated fetal calf serum was identified as surrogate matrix to substitute for human plasma. Dilutional linearity and parallelism could be successfully confirmed. The analyte was measured in the study matrix with intra- and inter-run precision and accuracy ≤20%. Stability was proven over a period of at least 15 months as well as upon three freeze-thaw cycles. SVEGFR-3 concentrations decreased in response to sunitinib to 57% (IQR 50-88%) and 58% (IQR 47-80%) of the respective baseline concentrations in healthy volunteers and mCRC patients, respectively, with subsequent increase after stop of treatment. The ELISA for the quantification of sVEGFR-3 in human plasma was successfully validated. The applicability of the assay was demonstrated in two clinical trials.

Pharmacodynamic modelling of biomarker data in oncology

The development of pharmacodynamic (PD) biomarkers in oncology has implications for design of clinical protocols from preclinical data and for predicting clinical outcomes from early clinical data. Two classes of biomarkers have received particular attention. Phosphoproteins in biopsy samples are markers of inhibition of signalling pathways, target sites for many novel agents. Biomarkers of apoptosis in plasma can measure tumour cell killing by drugs in phase I clinical trials. The predictive power of PD biomarkers is enhanced by data modelling. With pharmacokinetic models, PD models form PK/PD models that predict the time course both of drug concentration and drug effects. If biomarkers of drug toxicity are also measured, the models can predict drug selectivity as well as efficacy. PK/PD models, in conjunction with disease models, make possible virtual clinical trials, in which multiple trial designs are assessed in silico, so the optimal trial design can be selected for experimental evaluation.

Association of VEGF and VEGFR2 single nucleotide polymorphisms with hypertension and clinical outcome in metastatic clear cell renal cell carcinoma patients treated with sunitinib

PURPOSE

Biomarkers that predict response or toxicity to antiangiogenic therapy are sought to favorably inform the risk/benefit ratio. This study evaluated the association of vascular endothelial growth factor (VEGF) and VEGF receptor 2 (VEGFR2) genetic polymorphisms with the development of hypertension (HTN) and clinical outcome in metastatic clear cell renal cell carcinoma (MCCRCC) patients treated with sunitinib.

PATIENT AND METHODS

Sixty-three MCCRCC patients receiving sunitinib (50 mg 4/2) with available blood pressure (BP) data and germline DNA were retrospectively identified. A panel of candidate VEGF and VEGFR2 single nucleotide polymorphisms (SNPs) were evaluated for associations with the development of hypertension and clinical outcome.

RESULTS

VEGF SNP -634 genotype was associated with the prevalence and duration of sunitinib-induced hypertension (as defined by systolic pressure ≥150 mmHg and/or diastolic pressure ≥90 mmHg) in both univariable analysis (P = .03 and .01, respectively) and multivariable analysis, which adjusted for baseline BP and use of antihypertension medication (P = .05 and .02, respectively). Patients with the GG genotype were estimated to have a greater likelihood of being hypertensive during treatment compared with patients with the CC genotype (odds ratio of 13.62, 95% confidence interval [CI] 3.71-50.04). No single VEGF or VEGFR SNPs were found to correlate with clinical outcome. However, the combination of VEGF SNP 936 and VEGFR2 SNP 889 were associated with overall survival after adjustment for prognostic risk group (P = .03).

CONCLUSIONS

In MCCRCC patients treated with sunitinib, VEGF SNP -634 is associated with hypertension and a combination of VEGF SNP 936 and VEGFR2 SNP 889 genotypes is associated with overall survival.