British Journal of Clinical Pharmacology
DOI:10.1111/j.1365-2125.2007.03040.x
Population pharmacokinetics of gemcitabine and its metabolite in patients with cancer: effect of oxaliplatin and infusion rate
Correspondence Professor Andrew J. McLachlan, Faculty of Pharmacy, Building A15, The University of Sydney, NSW 2006, Australia. Tel.: + 61 2 9351 4452 Fax: + 61 2 9351 4391 E-mail:
[email protected] ----------------------------------------------------------------------
Keywords chemotherapy, dFdU, gemcitabine, metabolism, oxaliplatin, pharmacokinetics ----------------------------------------------------------------------
Received 27 March 2007
Accepted 1,2
3
3
4
Xuemin Jiang, Peter Galettis, Matthew Links, Paul L. Mitchell & Andrew J. McLachlan1,5
26 July 2007
Published OnlineEarly 24 October 2007
1
Faculty of Pharmacy, The University of Sydney, Sydney, 3Cancer Care Centre, St George Hospital, and St George Clinical School, UNSW, Kogarah, NSW and 4Department of Medical Oncology and Ludwig Institute for Cancer Research, Austin Hospital, Melbourne, VIC, Australia, 2Department of Medicine, University of Chicago, Chicago, IL, USA and 5Centre for Education and Research on Ageing, Concord Repatriation General Hospital, Concord, NSW, Australia
WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT • Gemcitabine is an anticancer drug which is metabolized to a number of metabolites, administered using different dosing regimens and increasingly used in combination with oxaliplatin. • The impact of dosing strategies and combination therapy on the pharmacokinetics of gemcitabine and its main metabolite is not clearly understood.
AIMS To characterize the population pharmacokinetics of gemcitabine and its metabolite (dFdU) in patients with cancer and identify factors that are influential in gemcitabine dose regimen design.
METHODS Gemcitabine and dFdU plasma concentration–time and clinical data from 94 patients with cancer and nonlinear mixed effect modelling were used to characterize gemcitabine and metabolite pharmacokinetic variability and identify influential covariates.
RESULTS
WHAT THIS STUDY ADDS • This study has characterized the pharmacokinetics of gemcitabine and its main metabolite in people with cancer, including the variability between patients and on different occasions. • Gemcitabine metabolite (but not gemcitabine) pharmacokinetics were significantly affected by co-administration with oxaliplatin and were dependent on the order of administration. • The clinical implications of this observation remain to be established.
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Gemcitabine and dFdU pharmacokinetics were described by a two-compartment model with first-order elimination. The population mean (and between-subject variability, CV%) for clearance and volume of distribution of the central compartment (VC) for gemcitabine were 2.7 l min-1 (31%) and 15 l (39%), respectively, and 0.04 l min-1 (35%) and 46 l (15%), respectively, for dFdU. Oxaliplatin co-administration significantly decreased dFdU VC by 35% when gemcitabine was administered first and by 46% when oxaliplatin was administered first compared with patients who received gemcitabine alone.
CONCLUSIONS Co-administration of gemcitabine with oxaliplatin significantly affected the pharmacokinetics of dFdU. The clinical significance of this observation in the context of gemcitabine safety and efficacy is worthy of further investigation.
© 2007 The Authors Journal compilation © 2007 Blackwell Publishing Ltd
Population pharmacokinetics of gemcitabine
Introduction Gemcitabine is an anticancer drug used for a range of cancers, including nonsmall cell lung cancer (NSCLC) [1], pancreatic cancer [2] and breast cancer [3]. Like other anticancer drugs, gemcitabine demonstrates high betweensubject variability in drug response [4], with a narrow safety margin and a wide range of adverse reactions such as flu-like syndrome, oedema, haematological disturbances, proteinuria and haematuria, which supports the need for individualized dose regimens to optimize clinical outcomes [5]. After administration gemcitabine is converted intracellularly to active diphosphate (dFdCDP) and triphosphate (dFdCTP) metabolites, with deoxycytidine kinase being the rate-limiting enzyme [6, 7]. Gemcitabine is also metabolized to its inactive metabolite 2′,2′-difluorodeoxyuridine (dFdU) in liver, kidney, blood and other tissues [5, 8]. About 99% of dFdU is subsequently excreted by kidney [9]. Gemcitabine and dFdU have been shown to have linear pharmacokinetics over the dose range of 87–2500 mg m-2, but the conversion of gemcitabine to dFdCDP and dFdCTP is saturated at high concentration of gemcitabine [10, 11]. Gemcitabine is often used in combination with other types of anticancer drug in the management of various malignancies [12–14]. An additive and synergistic cytotoxic action has been observed for gemcitabine in combination with cisplatin [15]. The clinical utility of this combination is limited by the risk of serious side-effects [13]. Recently, a combination with oxaliplatin has been investigated [4, 16, 17]. Oxaliplatin is an antineoplastic drug, which has a different spectrum of toxicities compared with gemcitabine [18]. However, few studies regarding this combination have investigated the potential for a pharmacokinetic interaction between these agents [5, 17]. The population pharmacokinetic approach offers a number of advantages in assessing the possible implications of chemotherapeutic drug combinations, allowing for the simultaneous analysis of all factors that contribute to drug concentrations and drug responses in patients [19, 20].The aims of this study were to (i) characterize the population pharmacokinetics of gemcitabine and its metabolite dFdU in patients with diverse tumour types, (ii) identify the effect of oxaliplatin (and administration order) on the pharmacokinetics of gemcitabine, and (iii) investigate the possible impact of gemcitabine infusion rate on the disposition of gemcitabine and dFdU in patients with cancer.
Methods
or metastatic disease; no chemotherapy (hormonal therapy excluded) for at least 4 weeks before enrolment in study (6 weeks for mitomycin or nitrosoureas); World Health Organization performance status 0–2; estimated life expectancy of at least 12 weeks; patient compliance and geographical proximity that allowed adequate follow-up; baseline neurosensory toxicity National Cancer Institute Common Toxicity Criteria ⱕ grade I (grade I is defined as loss of deep tendon reflexes, or paraesthesia (including tinging) not interfering with function (patients with objective sensory loss were not eligible)); adequate organ function including adequate bone marrow reserve (absolute neutrophil count ⱖ1.5 ¥ 109 l-1, platelets ⱖ100 ¥ 109 l-1, haemoglobin ⱖ9 g dl-1); hepatic function [bilirubin ⱕ1.5 times upper limit of normal (¥ULN), alkaline phosphatase (ALP), aspartate transaminase (AST) and alanine transaminase (ALT) ⱕ3.0 ¥ ULN (ALP, AST and ALT ⱕ5 ¥ ULN is acceptable if liver has tumour involvement)]; renal function (serum creatinine ⱕ0.16 mmol l-1 and based on estimated creatinine clearance, CLCR, calculated using the Cockcroft and Gault nomogram); signed informed consent; minimum age 18 years; patients on study with reproductive potential, or with female partners with reproductive potential, must use an effective contraceptive method during the trial and for 3 months after the study. Patients who had received prior radiation therapy were allowed provided ⱕ30% of bone marrow-producing areas had been irradiated and patients must have recovered from the acute toxic effects of the treatment prior to study enrolment completed at least 2 weeks prior to commencing study treatment. Patients were excluded for any of the following reasons: patients receiving another investigational drug; active infection, which in the opinion of the investigator would compromise the patient’s ability to tolerate therapy; uncontrolled brain metastases; patients with meningeal metastases; pregnancy or breast-feeding; serious concomitant medical or psychiatric disorders which would compromise the safety of the patient or their ability to complete the study, at the discretion of the investigator; significant cardiovascular disease: unstable angina, myocardial infarction with 3 months or significant cardiac failure.
Drug administration Gemcitabine (Eli Lilly Australia Pty Ltd, West Ryde, Australia) was diluted in 0.9% saline and given as a 30-min or 100-min infusion, whereas oxaliplatin (Sanofi-Synthelabo Australia Pty Ltd, Macquarie Park, Austalia) was diluted in 500 ml of 5% glucose and given as a 2-h infusion.The dose regimens for gemcitabine and oxaliplatin are described in Table 1.
Patients Patients were included in the study only if they met all of the following criteria [17], which included histological or cytological diagnosis of a solid malignancy; no curative treatment options available; evidence of locally advanced
Pharmacokinetic study Gemcitabine and dFdU concentration–time data were derived from patients participating in three clinical studies (Table 1). Study 1 was an open-label, dose escalation, Phase Br J Clin Pharmacol
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Table 1 Dose regimens investigated in this study
Age (median, range) sex (M/F)
Study
Indication
Infusion time (min)
Gemcitabine/oxaliplatin doses (mg m-2)
1
60 (43–72) years 15M/6F
Diverse tumour type
Gemcitabine for 30 min, then oxaliplatin for 120 min
750/40; 1000/50 1250/60; 1250/70 1500/80
2
62 (33–85) years 33M/10F
NSCLC
Gemcitabine for 30 min, then oxaliplatin for 120 min Oxaliplatin for 120 min, then gemcitabine for 30 min
1250/70 70/1250
3
70 (54–82) years 21M/10F
Diverse tumour type
Gemcitabine only for 30 min or 100 min
1000
NSCLC, Nonsmall cell lung cancer.
I study in patients (n = 21) with locally advanced or metastatic solid tumours who had received a maximum of two prior chemotherapy regimens. In Study 1 gemcitabine and oxaliplatin were given on days 1 and 8 of a 21-day cycle with a maximum of eight cycles [17]. Study 2 was a randomized Phase II sequencing study in advanced NSCLC patients (n = 43), who were randomized to determine the order of gemcitabine/oxaliplatin combination administration. Patients received gemcitabine followed by oxaliplatin or oxaliplatin followed by gemcitabine on days 1 and 8 of a 21-day cycle with a minimum of four and a maximum of six cycles. Study 3 was a randomized crossover study in which patients (n = 31) received gemcitabine administered as a 30-min infusion vs. 100-min infusion. The characteristics of people in each study were very similar (Table 1), with each study having a similar proportion of men and women and equivalent patient age ranges (33–82 years). In each study, blood samples for each patient in the first cycle were collected at 0, 10, 25, 40 min and 1, 1.5, 2, 2.5, 4, 7, 24 h and up to 192 h post gemcitabine dose. Blood samples were immediately centrifuged at 1500 g for 15 min and plasma was harvested and stored at -20°C until analysis. All three clinical trials were approved by the South-east Sydney and Illawarra Area Health Service Human Research Ethics Committee (Southern Section) Australia. All participants gave written informed consent before entering the study.
Analytic methods Gemcitabine and dFdU concentrations were measured by a validated high-performance liquid chromatography assay using UV detection at 272 nm [17]. The standard curve ranged from 0.2 to 50 mg ml-1 for both gemcitabine and dFdU. Intra-assay variation ranged between 2 and 12%, and interassay variation ranged between 3 and 12% for both gemcitabine and dFdU. Accuracy of the assay was between 95 and 104% for gemcitabine and dFdU.The limit of quantification for the assay was 0.2 mg ml-1 for both gemcitabine and dFdU. 328 /
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Population pharmacokinetic model development Patient characteristics, dosing and plasma concentrations of gemcitabine and dFdU analysed in this study were combined from the three clinical trials. A nonlinear mixed effect modelling approach was employed to analyse simultaneously the gemcitabine and dFdU pharmacokinetic data using the first-order (FO) estimation method implemented in NONMEM version 5 level 1.1 (ADVAN6 TRANS1 TOL5) [21]. Standard model development and evaluation methods were employed for the population pharmacokinetic modelling [19]. Briefly, structural and statistical models were first developed without including possible covariates. Plots of posterior Bayes estimates of the etas vs. potential covariates were used to screen for the potential covariate relationships. The covariates with the potential relationship on the pharmacokinetic parameter estimates were included in the model by a forward inclusion and backward elimination strategy [19]. Categorical covariates including sex, tumour type and combination with oxaliplatin were modelled using indicator variables, whereas continuous covariates (e.g. age, body weight, body surface area, gemcitabine infusion rate and estimated CLCR) were centred to their respective mean values and their influence on model parameters were evaluated using multiplicative models [21]. Only a few patients had missing data related to patient characteristics, and these were replaced with the relevant population mean value. The NONMEM-generated objective function value (OFV), which is equal to the likelihood ratio test, and the visual predictive check were used in the pharmacokinetic model selection process.The visual predictive check was conducted using 100 simulated concentration–time datasets generated from the identical study design using the NONMEM-generated pharmacokinetic estimates. Strict selection criteria were used for covariate model development, as this analysis used the FO estimation method [22]. For covariate model selection, a reduction of the OFV ⱖ10.83 units (P = 0.001, d.f. = 1) was used for forward inclusion and backward elimination. The
Population pharmacokinetics of gemcitabine
Table 2
Table 3
Patient characteristics
Gemcitabine and dFdU population pharmacokinetic parameter estimates No. of patients
Median
Range
94
65
33–85
Weight (kg)
93
73
BSA (m2)
92
Estimated CLCR (ml min-1)
91
Parameter* Age (year)
1.8 83
Estimates
BSV (CV%)
BOV (CV%)
37–120
Qgem (l min-1)
0.7
44
–
1.2–2.5
CLgem (l min-1)
2.7
31
12
37–150
VC,gem (l)
15
39
93
VP,gem (l)
15
64
–
Sex Male
68
–
–
QdFdU/F (l min-1)
0.2
29
–
Female
26
–
–
CLdFdU/F (l min-1)
0.04
35
11
Tumour type NSCLC Pancreatic Diverse type
47 14 33
– – –
– – –
Gemcitabine/oxaliplatin
38
–
–
Oxaliplatin/gemcitabine
25
–
–
Gemcitabine alone
31
–
–
Infusion rate (mg min-1)
94
55
15–95
BSA, Body surface area; NSCLC, nonsmall cell lung cancer.
physiological relevance, decrease in between-subject variability and improvement in the diagnostic plots (generated using Wings for NONMEM [23]) were also considered during covariate selection processes. In this study a >20% difference in pharmacokinetic parameters (with and without covariate) was considered to be of clinical significance [24].
Results Population pharmacokinetic database A total of 652 plasma concentrations of gemcitabine and 1130 plasma concentrations of its metabolite (dFdU) were included from three clinical trials involving 94 patients with 122 concentration–time profiles. Typically, these profiles consisted of between three and six samples collected at different time points for gemcitabine, and 12 blood sampling time points for dFdU in each patient were used for this data analysis. Table 2 summarizes the patient characteristics and potential covariates.
Population pharmacokinetics The pharmacokinetics of both gemcitabine and dFdU in plasma were best described by a two-compartment pharmacokinetic model with FO elimination rate. The pharmacokinetic model for dFdU was incorporated with a FO formation rate. Proportional statistical models were employed to describe the between-subject variability, between-occasion variability and residual error for gemcitabine and dFdU. The population mean pharmacokinetic parameters for gemcitabine and dFdU with their corresponding between-subject variability (BSV), betweenoccasion variability (BOV) and residual error estimated
VC,dFdU/F(l)
46
15
10
VP,dFdU/F(l)
192
38
–
sGEM
40
–
sdFdU
19
–
Residual variability
*The parameters described are intercompartmental clearance (Q), systemic clearance (CL) and the volume of distribution of the central (Vc) and peripheral (Vp) compartments for gemcitabine (subscript, gem) and its metabolite (subscript, dFdU). Note: apparent pharmacokinetic parameters are derived for dFdU as the fraction (F) of gemcitabine converted to this metabolite. F is not explicitly estimated. BSV, between-subject variability; BOV, between-occasion variability.
from the final population pharmacokinetic model are presented in Table 3. BSV was estimated on all of the pharmacokinetic parameters, whereas BOV was estimated on selected parameters (as reported in Table 3).The fraction of conversion (F) from gemcitabine to dFdU could not be independently estimated and hence apparent values of QdFdU/F, CLdFdU/F, VC,dFdU/F and VP,dFdU/F are reported. The population mean clearance of gemcitabine (CLgem) and volume of distribution of central compartment of gemcitabine (VC,gem) were 2.7 l min-1 and 15 l, respectively, whereas the population mean clearance of dFdU (CLdFdU/F) and volume of distribution of central compartment of dFdU (VC,dFdU/F) were 0.04 l min-1 and 46 l, respectively. Moderate variability was found in Qgem (BSV, 44%), CLgem (BSV 31%; BOV 12%), VP,gem (BSV 15%), QdFdU/F (BSV 29%), CLdFdU/F (BSV 35%; BOV 11%), VC,dFdU/F (BSV 15%; BOV 10%) and VP,dFdU (BSV 38%), whereas high variability was found in VC,gem (BSV 39%; BOV 93%). The model-building process identified a number of important covariate relationships with pharmacokinetic parameters. Table 4 summarizes the significant covariate effects identified using the likelihood ratio test. Estimated creatinine clearance (CLCR) was found to be significantly correlated with CLdFdU/F, whereas body surface area (BSA) was found to significantly effect the QdFdU/F and VC,dFdU/F. Co-administration with oxaliplatin, as either gemcitabine followed by oxaliplatin or oxaliplatin followed by gemcitabine, was found to decrease significantly the VC,dFdU/F and resulted in a decrease in the between-subject variability from 20% to 16%. Patients with NSCLC were found to have a significantly higher VC,dFdU when compared with other patients in this study cohort. The covariate relationships with pharmacokinetic parameter are described as follows: Br J Clin Pharmacol
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Table 4 Covariate model development
Model
Covariate
OFV
DOFV
1
Basic model
5864.6
–
WRES
4
2 1
2
CLCR on CLdFdU/F
5846.9
-17.7
3
BSA on VC,dFdU/F
5815.3
-31.6
0
4
Oxaliplatin on VC,dFdU/F
5708.3
-107.0
5
NSCLC on VC,dFdU/F
5683.5
-24.8
–1 –2
–0
Predicted gemcitabine concentration (mg/l)
Figure 2 40
Diagnostic plot of population weighted residuals vs. predicted concentration of gemcitabine (o, observed concentration; broken line, zero line; solid line, regression line)
20
0
10
20
30
40
Predicted gemcitabine concentration (mg/l)
Figure 1 Diagnostic plot of population observed concentration vs. predicted concentration of gemcitabine (o, observed concentration; broken line, line of identity; solid line, regression line)
CL dFdU F (1min−1) = 0.04 × (1+ 0.48 × CL CR 70 ) VC,dFdU F (1) = 46 × (BSA 1.73)0.93 × 0.65GEMOX × 0.54 OXGEM × 1.24NSCLC where CLdFdU/F is the population mean estimate of dFdU clearance; VC,dFdU/F is the population mean estimates of volume of distribution of dFdU in the central compartment; F is fraction converted from gemcitabine to dFdU; GEMOX = 1 for gemcitabine treatment first then oxaliplatin and GEMOX = 0 for otherwise; OXGEM = 1 for oxaliplatin treatment first then gemcitabine and OXGEM = 0 for otherwise; NSCLC = 1 for nonsmall cell lung cancer, NSCLC = 0 for otherwise. CLCR is the estimated creatinine clearance (ml min-1) and BSA is the body surface area. No other covariates (Table 2) investigated in this study were identified as having a significant impact on the disposition of gemcitabine or dFdU. The goodness-of-fit plots for gemcitabine and dFdU are presented in Figures 1–4. These diagnostic plots show that the population pharmacokinetic model performs good prediction for gemcitabine and dFdU concentration–time courses. Figures 5 and 6 show the pre330 /
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Observed dFdU concentration (mg/l)
Observed gemcitabine concentration (mg/l)
60
80
60
40
20
0
20
40
60
Predicted dFdU concentration (mg/l)
Figure 3 Diagnostic plot of population observed vs. predicted concentration of dFdU (o, observed concentration; broken line, line of identity; solid line, regression line)
dictive check for the final model for gemcitabine and dFdU and demonstrate excellent model performance.
Discussion This study simultaneously investigated the population pharmacokinetics of gemcitabine and its metabolite dFdU, and examined the effect of covariates on the pharmacokinetics of these compounds. The parameter estimates for gemcitabine and dFdU in patients with cancer estimated using population pharmacokinetic modelling are in close agreement with previous values reported in the literature [5]. This study has identified several influential factors,
Population pharmacokinetics of gemcitabine
100
dFdU (mg/l)
4
WRES
2 1 0
10
1
–1 –2 0.1 0 –0
500
1000
1500
2000
Time (min)
50
Predicted dFdU concentration (mg/l)
Figure 6 Figure 4 Diagnostic plot of weighted residuals vs. predicted concentration of dFdU (o, observed concentration; broken line, zero line; solid line, line of identity)
Predictive check of dFdU concentration–time profile with 5th, 50th and 95th percentiles shown (o, observed concentrations). (Note: the first and second peaks derive from the 30-min and 100-min gemcitabine infusions, respectively.) These data were generated simultaneously. 5th percentile ), 50th percentile ( ), 95th percentile ( ), Observed (䊊) (
Gemcitabine (mg/l)
100
10
1
0.1 0
50
100
150
200
Time (min)
Figure 5 Predictive check of gemcitabine concentration–time profile with 5th, 50th and 95th percentiles shown (o, observed concentrations). (Note: the first and second peaks derive from the 30-min and 100-min gemcitabine infusions, respectively.) These data were generated simultaneously. 5th ), 50th percentile ( ), 95th percentile ( ), percentile ( Observed (䊊)
including estimated creatinine clearance on CLdFdU/F, BSA on VC,dFdU/F, co-administration of oxaliplatin on VC,dFdU/F and NSCLC on VC,dFdU/F. Furthermore, the study has identified that co-administration of gemcitabine with oxaliplatin significantly decreased the VC,dFdU/F. The mechanism of this interaction with dFdU is not clear, but suggests that oxaliplatin alters the tissue uptake of dFdU. Faivre et al. [4] have reported that no interaction between gemcitabine and oxaliplatin was identified, but a relatively small numbers of patients were recruited and no control group was used in the study design. There are a number of mechanisms by which a change in the distribution volume of dFdU could be clinically significant. The metabolite dFdU has a lower
intrinsic activity (IC50 45–200 mM) compared with gemcitabine (IC50 3–5 nM) [25]. However, the lower activity is countered by the observed increase in distribution and increased AUC (15 000 vs. 400 mg ml-1 min-1, data not shown), thereby potentially increasing the cytotoxic effects of dFdU in tissue.The change in volume of distribution reflects a change in uptake into tissues that are relevant for toxicity (e.g. lung and liver) or for response (tumour tissue). Evaluation of the clinical significance of these findings requires further study. Interestingly, this study found that BSA was an influential covariate on the dFdU distribution. Some commentaries [e.g. 26] have highlighted the limitation of BSA as a metric for body size, especially when proposed for use in dose individualization. In this study the impact of weight and height was also considered independently, but BSA remained the most influential measure of body size. The relationship between markers of renal function and dFdU clearance identified in this study was not surprising, given that about 99% of dFdU is excreted by the kidney [9]. The findings of this study are in agreement with dose recommendations that indicate precaution for patients with renal impairment. Although this study found that patients with NSCLC had an increase in VC,dFdU/F, there are no relevant reports in the literature to support this and it is worthy of further study. Gemcitabine infusion rate did not alter the pharmacokinetics of gemcitabine or dFdU. One limitation of this study is that the model developed describes the distribution of gemcitabine and dFdU within plasma; however, the major activity of gemcitabine is attributed to intracellular concentrations of the active metabolite dFdCTP [9]. Ongoing work is aimed at extending these observations to a model of intracellular dFdCTP accumulation. Br J Clin Pharmacol
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In conclusion, a two-compartment pharmacokinetic model describes the concentration–time profile after intravenous infusion of gemcitabine and dFdU. Renal function was the most influential covariate for dFdU clearance, whereas dFdU volume of distribution was influenced by BSA, administration of oxaliplatin and tumour type. The clinical significance of these observations requires further evaluation. Competing interests P.G. has received research funds from Eli-Lilly Australia Pty Ltd. M.L. has been funded for travel to several conferences, received research funding and worked as a consultant to EliLilly, the manufacturer of Gemcitabine. He has been funded for conference travel by Sanofi-Aventis, the manufacturer of oxaliplatin. He has also acted as a consultant on a Thoracic advisory board. P.L.M. has received honoraria for speaking from Eli-Lilly, the manufacturer of gemcitabine, and from Sanofi-Aventis, the manufacturer of oxaliplatin. He has also received honoraria for sitting on advisory boards for these companies.
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