Therapeutic drug monitoring of imatinib: is there a rationale for also quantifying its active metabolite ?

INTRODUCTION: Therapeutic drug monitoring of imatinib is widely performed to individualize imatinib dosage. While N-desmethyl imatinib is an active metabolite of imatinib, its concentrations are not routinely determined. METHODS: Imatinib and N-desmethyl imatinib trough plasma concentrations at steady-state were obtained from 295 patients with either chronic myeloid leukemia or gastrointestinal stromal tumor to see whether N-desmethyl imatinib provided additional information. Pharmacokinetic data were analyzed using a nonlinear mixed effect approach. Correlations between several pharmacokinetic metrics of drug exposure were evaluated. RESULTS: The mean value of the N-desmethyl imatinib/imatinib ratio of trough concentrations was 0.31 with half of the values between 0.23-0.37. N-desmethyl imatinib and total (i.e., N-desmethyl imatinib plus imatinib) trough plasma concentrations or area-under-the curve values were closely correlated with imatinib values. The distribution of imatinib or total concentrations between patients requiring imatinib dosage adjustment, or not, were similar. CONCLUSION: These results do not clearly support routine N-desmethyl monitoring since it does not provide additional information to imatinib data.

Body Surface Area Dosing of High-Dose Methotrexate Should Be Reconsidered, Particularly in Overweight, Adult Patients.

BACKGROUND: High-dose methotrexate is used for treating several types of cancer. However, it is associated with a high risk of acute kidney injury (AKI), especially in patients with high MTX concentrations. Although therapeutic drug monitoring is performed to monitor MTX concentrations, it is unclear what concentration should be considered critical, thus requiring rescue protocols to prevent nephrotoxicity. METHODS: Patients treated with high-dose methotrexate for lymphoma or acute lymphoblastic leukemia and those benefited from therapeutic drug monitoring were included. The relationship between MTX concentrations and the presence or absence of AKI was assessed. MTX concentrations were analyzed using a population pharmacokinetic approach. Specific attention was given to morphological covariates because MTX doses are individualized according to body surface area (BSA). RESULTS: In total, 328 patients and 657 cycles of treatment were analyzed. Higher MTX concentrations were observed in the AKI+ group. For cycle 1, all patients showing an MTX concentration >6 µM at 36 hours or >2 µM at 48 hours after infusion developed nephrotoxicity. The final pharmacokinetic model had 2 compartments and included the effect of age on clearance (CL) and of body weight on peripheral distribution volume. None of the morphological covariates tested on CL led to significant improvement in the model. Higher MTX concentrations were observed in patients with extreme BSA values (≥2 m2) or body mass index (≥25 kg/m2). Patients with AKI who received at least 1 cycle had higher BSA and BMI. CONCLUSIONS: The results from this study provide additional information on the relationship between MTX concentration and nephrotoxicity. Patients with a plasma MTX concentration >6 µM at 36 hours were more likely to manifest AKI. In addition, the results suggest that overweight patients have a high AKI risk and that BSA-based adjustment of MTX dose is not appropriate.

Pharmacokinetic and Pharmacogenetic Study of Etoposide in High-Dose Protocol (TI-CE) for Advanced Germ Cell Tumors.

BACKGROUND: Etoposide dosing is based on body surface area. We evaluated if further dose individualization would be required for high dose (HD) etoposide within the TI-CE (taxol, ifosfamide, carboplatin, and etoposide) protocol. METHODS: Eighty-eight patients received 400 mg/m2/day of etoposide as a 1-hour IV infusion on 3 consecutive days over 3 cycles as part of a phase II trial evaluating efficacy of therapeutic drug monitoring (TDM) of carboplatin in the TI-CE HD protocol. Pharmacokinetic (PK) data were analyzed using population PK model on NONMEM to quantify inter- and intra-individual variabilities. Relationship between etoposide exposure and pharmacodynamic (PD) endpoints, and between selected genetic polymorphisms and tumor response or toxicity were evaluated. RESULTS: The inter-patient, inter- and intra-cycle variabilities of clearance were 16%, 9% and 0.1%, respectively. The PK-PD relationship was not significant despite a trend toward higher etoposide exposure in patients responding to treatment. A significant correlation was found between exposure and extended neutropenia at cycle 3. A significant association between UGT1A1*28 polymorphism and late neutropenia was observed but needs further evaluation. CONCLUSIONS: The present study suggests that neither a priori dose individualization nor dose adaptation using TDM is required validating body surface area dosing of etoposide in the TI-CE protocol.

Cetuximab pharmacokinetic/pharmacodynamics relationships in advanced head and neck carcinoma patients.

AIMS: Cetuximab associated with cisplatin and 5-fluorouracil is used to treat patients with inoperable or metastatic head and neck squamous cell carcinomas (HNSCC) up until disease progression or unacceptable toxicities. To date, no biomarkers of efficacy are available to select patients who will benefit from treatment. METHODS: An ancillary pharmacokinetics (PK) exploration was performed in the context of a prospective study investigating circulating-tumour cells vs progression-free survival (PFS). Cetuximab plasma concentrations were analysed according to a population PK model. Individual exposure parameters were confronted with soluble epidermal growth factor receptor (sEGFR) concentrations, tumour response and PFS. RESULTS: PK data (28 patients, 203 observations) were best described by a two-compartment model with linear elimination. Performance status (PS) significantly correlated to both cetuximab clearance and central volume of distribution with both parameters increasing by 33.3% (95% CI 1-65.6) for each 1-point increase of PS compared to PS = 0. Univariate analysis showed that patients with higher trough cetuximab concentrations at Day 7 (Cmin,D7 ) had better tumour response (P = 0.03) and longer PFS (P = 0.035). However, multivariate analysis revealed that only PS and tumour size at baseline remained significantly associated with PFS. Levels of sEGFR increased during cetuximab treatment but were not associated with PFS in the multivariate analysis. CONCLUSIONS: Our study prospectively indicates that PS is likely a confounding factor in the relationship between cetuximab PK and PFS, patients with a poor PS having lower cetuximab plasma exposure and lower PFS.

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.

Population pharmacokinetics of rituximab with or without plasmapheresis in kidney patients with antibody-mediated disease.

AIMS: Both rituximab and plasmapheresis can be associated in the treatment of immune-mediated kidney diseases. The real impact of plasmapheresis on rituximab pharmacokinetics is unknown. The aim of this study was to compare rituximab pharmacokinetics between patients requiring plasmapheresis and others without plasmapheresis. METHODS: The study included 20 patients receiving one or several infusions of rituximab. In 10 patients, plasmapheresis sessions were also performed (between two and six sessions per patient). Rituximab concentrations were measured in blood samples in all patients and in discarded plasma obtained by plasmapheresis using an enzyme-linked immunosorbent assay method. Data were analysed according to a population pharmacokinetic approach. RESULTS: The mean percentage of rituximab removed during the first plasmapheresis session ranged between 47 and 54% when plasmapheresis was performed between 24 and 72 h after rituximab infusion. Rituximab pharmacokinetics was adequately described by a two-compartment model with first-order elimination. Plasmapheresis had a significant impact on rituximab pharmacokinetics, with an increase of rituximab clearance by a factor of 261 (95% confidence interval 146-376), i.e. from 6.64 to 1733 ml h(-1) . Plasmapheresis performed 24 h after rituximab infusion decreased the rituximab area under the curve by 26%. CONCLUSIONS: Plasmapheresis removed an important amount of rituximab when performed less than 3 days after infusion. The removal of rituximab led to a significant decrease of the area under the curve. This pharmacokinetic observation should be taken into account for rituximab dosing, e.g. an additional third rituximab infusion may be recommended when three plasmapheresis sessions are performed after the first rituximab infusion.

Biological Role of Pazopanib and Sunitinib Aldehyde Derivatives in Drug-Induced Liver Injury.

Tyrosine kinase inhibitors pazopanib and sunitinib are both used to treat advanced renal cell carcinoma but expose patients to an increased risk of hepatotoxicity. We have previously identified two aldehyde derivatives for pazopanib and sunitinib (P-CHO and S-CHO, respectively) in liver microsomes. In this study, we aimed to decipher their role in hepatotoxicity by treating HepG2 and HepaRG hepatic cell lines with these derivatives and evaluating cell viability, mitochondrial dysfunction, and oxidative stress accumulation. Additionally, plasma concentrations of P-CHO were assessed in a cohort of patients treated with pazopanib. Results showed that S-CHO slightly decreased the viability of HepG2, but to a lesser extent than sunitinib, and affected the maximal respiratory capacity of the mitochondrial chain. P-CHO decreased viability and ATP production in HepG2. Traces of P-CHO were detected in the plasma of patients treated with pazopanib. Overall, these results showed that P-CHO and S-CHO affect hepatocyte integrity and could be involved in the pazopanib and sunitinib hepatotoxicity.

Serum concentrations of ribavirin and pegylated interferon and viral responses in patients infected with HIV and HCV.

The hepatitis C virus (HCV) infects a substantial proportion of patients infected with human immunodeficiency virus (HIV). Patients infected with both HCV and HIV respond poorly to anti-HCV treatment with pegylated interferon alpha and ribavirin. But few data are available on the influence of ribavirin and interferon concentrations on treatment outcome for these patients. This study investigated the relationship between the serum pegylated interferon and ribavirin concentrations 3 and 6 months after treatment initiation, and treatment outcome in 35 HCV-HIV coinfected patients. The pegylated interferon and ribavirin concentrations at months 3 and 6 were similar. The pegylated interferon concentrations at 3 months in responders and nonresponders were similar. However, responders tended to have higher ribavirin concentrations (2,322 ng/ml) than nonresponders (1,833 ng/ml; P = 0.08). Responders infected with HCV genotype 1 or 4 had higher ribavirin concentrations (2,672 ng/ml) than did similarly infected nonresponders (1,758 ng/ml; P = 0.04). ROC curve analysis showed that a ribavirin concentration of 2,300 ng/ml was the best threshold for predicting a nonresponse (ROC area = 0.80 +/- 0.12). Thus ribavirin concentrations influence treatment outcome in HIV patients infected with HCV genotype 1 or 4. Monitoring ribavirin concentrations could help adapt ribavirin concentrations and improve the sustained virological response.

Simultaneous monitoring of pazopanib and its metabolites by UPLC-MS/MS.

Pazopanib is a multi-targeted tyrosine kinase inhibitor (TKI) approved as first-line treatment for patients with advanced renal cell carcinoma (RCC) and as second-line treatment for patients with advanced soft tissue sarcoma (STS) previously treated with chemotherapy. The most common adverse events, observed during the RCC and STS trials, were gastrointestinal disorders, hypertension, fatigue, elevated ALAT and ASAT, but the molecular mechanisms explaining pazopanib toxicity remain unclear. Therapeutic activity is considered to be mainly dependent on pazopanib exposure as the primary metabolites are inactive or display low plasma concentrations, but metabolites may be involved in toxicity as relationships between metabolite profiles and toxicity have not been evaluated. We report here, for the first time, the validation of a method for the simultaneous quantification of pazopanib and semi-quantification of its metabolites (relative determination). As there are no standards available, pazopanib metabolites were generated with human liver microsomes (HLM) to provide controls in the development of an UPLC-MS/MS method for monitoring both pazopanib and metabolites. The optimised method was validated for specificity, linearity, sensitivity, precision, accuracy, matrix effect and stability. The coefficient of variation (CV%) for intra-day and inter-day precision varied from 2.1% to 7.9% and 5.6% to 13.1% respectively. The biases varied from -12% to 2.3% (intra-day) and 3.8% to 13.1% (inter-day) for accuracy evaluation. Intra-day and inter-day precision CV were respectively 20.1% and 19.6% and accuracy biases were between 20.7% (intra-day) and 3.8% (inter-day) at the limit of quantification. The recoveries from matrix samples spiked with pazopanib were respectively 102.6 ±â€¯12.9% and 102.5 ±â€¯1.2% at low and high levels of calibration range. No matrix effect was evidenced as demonstrated by the normalised matrix factor values: 1.3 ±â€¯0.1 and 1.2 ±â€¯0.2 respectively measured at low and high part of calibration range. A good stability of pazopanib was observed during short term, long term and in process storage conditions and after three freeze/thaw cycles. The method was applied to clinical samples from three patients treated with pazopanib to establish the metabolite profiles (semi-quantitative data) during treatment. The assessment of metabolite profiles could be useful to improve our understanding of the occurrence of adverse events and to improve pazopanib pharmacokinetic-pharmacodynamic relationships.

Therapeutic drug monitoring and dose adaptation of cisplatin in a newborn with hepatoblastoma: a case report.

PURPOSE: Chemotherapy dosing in neonates represents a major clinical challenge because of a lack of clinical pharmacology information in this patient population. In this study, we investigate the use of cisplatin dose adaptation based on therapeutic drug monitoring in a 2-week-old neonate with localized hepatoblastoma. METHODS: Cisplatin concentrations were determined in plasma and ultrafiltrate samples collected on each of six cycles of a monotherapy regimen, beginning with a dose of 1.6 mg/kg at 16 days of age. Pharmacokinetic data were analyzed to generate clearance (CL) and area under the curve (AUC0-∞) for each administration. Toxicity and clinical response were monitored. RESULTS: The first cisplatin dose (1.6 mg/kg) resulted in an AUC0-∞ of 535 µg/mL · min, was well tolerated and associated with a good response. This AUC was, therefore, considered as an appropriate target for this patient. Increases in cisplatin CL were observed across consecutive treatment cycles, and, therefore, dose was gradually increased to finally reach 2.5 mg/kg on the sixth cycle. Treatment was well tolerated over the six courses and resulted in a good response, with the patient remaining in remission at 15 months. Cisplatin CL was significantly correlated to age (p = 0.013) and weight (p = 0.013). CONCLUSIONS: Our study provides useful data on the pharmacokinetics of cisplatin monotherapy in neonates treated within the first few weeks of life. These data provide a reference point to support clinicians in determining appropriate dosing regimens for neonates and support the implementation of therapeutic drug monitoring in such challenging patients.

Pharmacokinetic interaction between pazopanib and cisplatin regimen.

PURPOSE: A phase I study combining daily oral pazopanib and cisplatin (given iv every 3 weeks) was performed in order to determine the maximum tolerated dose of both drugs in combination. Pharmacokinetic interactions were evaluated. METHODS: Plasma pazopanib and ultrafilterable cisplatin concentrations were obtained in 32 patients treated according to four levels of dose corresponding to 200, 400 or 600 mg daily dose of pazopanib and 60 or 75 mg/m(2) of cisplatin. Two sequences of treatment were performed in order to explore any interaction of cisplatin on pazopanib pharmacokinetics and inversely. Data were analyzed using the NONMEM program. RESULTS: Maximum tolerated dose was 400 mg of pazopanib and 75 mg/m(2) of cisplatin. Mean (CV % for inter-individual variability) cisplatin clearance was 10.3 L/h (33.2 %) and appeared not to be influenced by pazopanib. However, pazopanib pharmacokinetics was significantly modified by the cisplatin regimen. Mean (CV %) of oral pazopanib clearance was 0.66 L/h (55 %) at Day 0 (before cisplatin administration), 24.8 % lower at Day 1 and 32.9 % lower at Day 2. The interaction is less likely to be due to cisplatin than to a competitive inhibition of pazopanib metabolism and efflux by aprepitant, an antiemetic drug systematically administered with cisplatin. The plasma pazopanib exposures observed at Day 0 with a 400 mg dose were similar to those observed at the recommended dose of pazopanib in monochemotherapy (800 mg) during the first-in-man phase 1 study. CONCLUSION: The observed pazopanib plasma overexposure probably contributed to the poor tolerance encountered during this phase 1 study.

Cystatin C as a new covariate to predict renal elimination of drugs: application to carboplatin.

BACKGROUND AND OBJECTIVE: The individual dosing of drugs that are mainly eliminated unchanged in the urine is made possible by assessing renal function. Most of the methods used are based on serum creatinine (SCr) levels. Cystatin C (CysC) has been proposed as an alternative endogenous marker of the glomerular filtration rate (GFR). Carboplatin is one of the drugs for which elimination is most dependent on the GFR. A prospective clinical trial including 45 patients was conducted to assess the value of serum CysC as a predictor of carboplatin clearance (CL). METHODS: The patients were receiving carboplatin as part of established protocols. Carboplatin was administered as a daily 60-minute infusion at doses ranging from 290 to 1700mg. A population pharmacokinetic analysis was performed using the nonlinear mixed effect modelling NONMEM program according to a two-compartment pharmacokinetic model. RESULTS: Data from 30 patients were used to test the relationships between carboplatin CL and morphological, biological and demographic covariates previously proposed for prediction of the GFR. The interindividual variability of carboplatin CL decreased from 31% (no covariate) to 14% by taking into account five covariates (SCr, CysC, bodyweight [BW], age and sex). Prospective evaluation of these relationships using the data from the other 15 patients confirmed that the best equation to predict carboplatin CL was based on these five covariates, with a mean absolute percentage error of 13% as an assessment of precision. NONMEM analysis of the whole dataset (n = 45 patients) was performed. The best covariate equation corresponding to the overall analysis was: CL (mL/min) = 110 x (SCr/75)-0.512 x (CysC/1.0)-0.327 x (BW/65)0.474 x (age/56)-0.387 x 0.854sex, with SCr in micromol/L, CysC in mg/L, BW in kilograms, age in years and sex = 0 if male and 1 if female. To put the value of CysC as an endogenous marker of the GFR into perspective, covariate equations without SCr were also evaluated; a better prediction was obtained by considering CysC together with age and BW (interindividual variability of 16.6% vs 23.3% for CysC alone). CONCLUSION: CysC is a marker of drug elimination that is at least as good as SCr for predicting carboplatin CL. The model based on five covariates was superior to those based on only four covariates (with BW, age and sex combined with either SCr or CysC), indicating that CysC and SCr are not completely redundant to each other. Further pharmacokinetic evaluation is needed to determine whether SCr or CysC is the better marker of renal elimination of other drugs.

Ribavirin pharmacokinetics in renal and liver transplant patients: evidence that it depends on renal function.

BACKGROUND: Ribavirin is approved for the treatment of chronic hepatitis C virus (HCV) infection. However, no recommendation exists for dosing patients with impaired renal function. METHODS: The authors performed a pharmacokinetic study in 21 HCV-positive renal or liver transplant patients. The mean creatinine clearance (ClCr) calculated by the Cockcroft-Gault equation was 57 mL/min (0.95 mL/s; range, 17 to 89 mL/min [0.28 to 1.48 mL/s]). Twelve blood samples were obtained during a 96-hour period after the first single administration of 1,000 mg of ribavirin. After the first pharmacokinetics (PK) and the pharmacodynamics (PD) profile was completed, the patients received ribavirin at 1,000 mg/d with or without interferon-alpha. A blood sample was taken monthly just before the oral administration of ribavirin. Plasma ribavirin concentrations were determined by high-performance liquid chromatography. RESULTS: A total of 428 plasma concentrations were analyzed by a population pharmacokinetic method using the NONlinear Mixed Effect Model program. The mean observed ribavirin apparent clearance (CL/F) was 9.1 L/h (with an interindividual variability of 39%). The influences of the age, sex, body weight (BW), serum creatinine (Scr), ClCr, hemoglobin, and graft status on CL/F were examined. CL/F was highly correlated with ClCr (r = 0.63, P < 0.01). The final regression formula was CL/F (L/h) = 32.3 x BW x (1 - 0.0094 x age) x (1 - 0.42 x sex)/Scr, where sex = 0 for men and 1 for women; Scr is in micromoles per liter. Sex had a larger influence on CL/F than that corresponding to the Cockcroft-Gault equation (ie, 15%). CONCLUSION: The authors present the parameters that determine ribavirin clearance in HCV+ transplant patients with normal or impaired renal function. Moreover, we suggest ribavirin daily doses according to various levels of renal function.

Dexamethasone as a probe for docetaxel clearance.

PURPOSE: A pilot study was conducted in 23 patients in order to assess the correlation between docetaxel clearance (CL) and pharmacokinetics of dexamethasone. Dexamethasone is mainly 6-beta hydroxylated by CYP3A4, and is regularly used as standard docetaxel premedication. Genotyping of known functional single nucleotide polymorphism (SNP) of CYP3A5 (G22893A) and mdr-1 (G2677T, G2677A, and C3435T) have been performed in order to tentatively correlate genotype with docetaxel and dexamethasone pharmacokinetics. PATIENTS AND METHODS: To be eligible for this study, patients were required to have a solid malignancy for which docetaxel was indicated. A population pharmacokinetic approach was used to determine individual pharmacokinetic parameters of both docetaxel and dexamethasone by Bayesian analysis, and to screen relationships between docetaxel CL and patients' demographic, phenotype and genotype covariates. RESULTS: Three different pharmacokinetic parameters of dexamethasone were significantly correlated with docetaxel CL: dexamethasone plasma clearance (DPC) that ranged between 7.7 and 27.2 l/h, urinary amount of 6beta-hydroxydexamethasone, and the ratio between urinary amount of 6beta-hydroxydexamethasone and unchanged dexamethasone. The best covariate model was docetaxel CL (l/h) = 356 x fu(alpha1-AG) x (1-0.17 x HPMT)(1+0.126 x DPC) where fu(alpha1-AG) is the unbound plasma fraction of docetaxel calculated from alpha1-acid glycoprotein plasma level, and HPMT is hepatic metastasis coded as 1 if present or 0 if absent. No significant difference in docetaxel CL was observed between the several genotypes. CONCLUSIONS: Dexamethasone may be used as a probe to predict docetaxel clearances, hence reducing interindividual variability.

Population pharmacokinetics of oxaliplatin.

The objective of this study was to explore correlations between a variety of covariates and oxaliplatin ultrafilterable and blood pharmacokinetic parameters. Data from 40 patients receiving oxaliplatin combined with 5-fluorouracil and levofolinic acid as standard treatment for advanced colorectal cancer were analysed. Plasma ultrafilterable, blood, and urine platinum concentrations were determined by flameless atomic absorption spectrophotometry. Data were analysed according to a population pharmacokinetic method using the NONMEM program. The best fit for oxaliplatin plasma ultrafilterable clearance (CL) was given by the following equation, which considers four covariates: body surface area (BSA, in metres squared), age (in years), sex (0 if male, 1 if female), and serum creatinine (Scr, in micromoles per liter): CL (l/h)=5.49xBSA+4.55xBSAx(140-AGE)x(1-0.15xSEX)/Scr. By taking into account these covariates, the interindividual variability in CL decreased from 43% to 33%. Renal clearance represented 34% of the overall elimination. This value was obtained by recovering urine over only 5 h from the beginning of the infusion and modelling the data using NONMEM. We would recommend the use of this methodology for pharmacokinetic studies in oncology in which renal clearances of the drug are presently rarely explored. The oxaliplatin blood concentrations versus time observed during the three-cycle period were well-described by a three-compartment model with first-order elimination from the central compartment. No significant intrapatient pharmacokinetic variability was observed between cycles. The relationship we obtained using the population approach between oxaliplatin CL and covariates may allow rational reduction of oxaliplatin dose in cases of elevated serum creatinine levels.

Pharmacokinetics of pazopanib administered in combination with bevacizumab.

A combination of monoclonal antibody that binds and inhibits effects induced by vascular endothelial growth factor and tyrosine kinase inhibitor of vascular endothelial growth factor receptor represents a promising concept to block pathological angiogenesis completely. A phase I study combining daily oral pazopanib and bevacizumab (given iv every 2 weeks) was performed in order to determine the maximum tolerated dose of the two drugs in combination. Pazopanib pharmacokinetics were evaluated to compare pharmacokinetic parameters given alone and those observed on the day of the bevacizumab administration. Plasma pazopanib concentrations were obtained in 25 patients treated at two dose levels (400 or 600 mg) at Day 1 (given alone) and Day 15 (the day of the 7.5 mg/kg bevacizumab infusion), and analyzed using the NONMEM program. The apparent oral clearance (CL/F, mean value of 0.60 L/h) presented an inter-individual variability of 40 %, and an inter-occasion of 27 %. A modest but statistically significant decrease in CL/F was observed from Day 1 to Day 15 (-16.4, 95 % confidence interval of -8.5 to -27.2 %). However, trough pazopanib concentrations observed at Day 16 (24 h after the bevacizumab iv infusion) were not significantly higher than those observed just before the beginning of the bevacizumab iv infusion, suggesting that the pharmacokinetic change between Day 1 and Day 15 was not due to an interaction of bevacizumab. Overall, the mean observed concentrations at the maximum tolerated pazopanib dose (600 mg) at both Day 1 and Day 15 were higher than those observed at 800 mg once daily level (corresponding to the recommended dose when given alone) during the first-in-man phase 1 study of pazopanib in monochemotherapy. This first population pharmacokinetic analysis of pazopanib shows that inter-individual and inter-study pharmacokinetic variability emphasize the need for further evaluation of therapeutic drug monitoring for pazopanib as suggested for other tyrosine kinase inhibitors.

Should therapeutic drug monitoring of the unbound fraction of imatinib and its main active metabolite N-desmethyl-imatinib be developed?

PURPOSE: The European Society for Medical Oncology recommends therapeutic drug monitoring (TDM) for imatinib, based on total plasma concentrations in cases of sub-optimal response, failure, or adverse events. Imatinib is highly bound to alpha-1 acid glycoprotein (AGP) in the plasma. We determined the unbound plasma fraction of both imatinib and its main active metabolite (N-desmethyl-imatinib) in plasma from 44 patients. The objective was to quantify the inter-individual variability of the protein binding of imatinib in order to discuss the potential benefits and limits of TDM of free plasma concentrations. PATIENTS AND METHODS: The quantification of unbound fraction of imatinib and N-desmethyl-imatinib was performed using plasma ultrafiltration coupled with LC-MS/MS measurement. 60 pre-dose plasma samples were obtained at steady state within TDM in 44 chronic myeloid leukemia patients. RESULTS: The mean unbound fractions of imatinib and N-desmethyl-imatinib were 2.94 and 5.10 %, respectively, with inter-individual variability (CV in %) of 57 % for imatinib and 71 % for the metabolite. For 11 patients, repeated blood sampling gave a mean intra-individual variability of 28 % for imatinib and 34 % for N-desmethyl-imatinib. No correlation was observed between these measured individual imatinib unbound fraction values and those obtained using an equation based on AGP levels previously proposed by Widmer et al. The mean N-desmethyl-imatinib/imatinib ratio was determined for both total (0.69) and unbound (1.10) concentrations, with inter-individual variabilities of 71 and 86 %, respectively. CONCLUSION: The large inter-individual variability for the unbound fraction of both imatinib and N-desmethyl-imatinib warrants further evaluation of the pharmacokinetic-pharmacodynamic relationship as a potential relevant marker of imatinib therapeutic outcomes.

Determination of unbound fraction of imatinib and N-desmethyl imatinib, validation of an UPLC-MS/MS assay and ultrafiltration method.

Imatinib is a small-molecule tyrosine kinase inhibitor with large inter-individual but low intra-individual pharmacokinetic variability with consistent concentration-efficacy and concentration-toxicity relationships. For these reasons imatinib therapeutic drug monitoring is based on total plasma concentrations. However, since a significant impact of unbound imatinib concentrations on clinical response and/or toxicity evaluation has been suggested, the quantification of free fraction of imatinib and its active metabolite are of interest for therapeutic monitoring. Hence a reliable method for both separation and assay of the free fraction is needed. Using plasma samples spiked with imatinib (from 1000 to 7500 ng/mL) and its metabolite (from 1000 to 2500 ng/mL), an ultrafiltration procedure and an UPLC assay which give reproductive values for unbound fractions of imatinib (mean 3.0±1.0%) and metabolite N-desmethyl imatinib (3.6±1.8%) have been developed. The validation of the analytical UPLC-MS/MS method associated to ultrafiltration for quantification of imatinib and N-desmethyl imatinib was reported. The LOQ was set at 10 ng/mL for imatinib and 20 ng/mL for N-desmethyl imatinib, intraday CV (%) ranged from 2.7 to 4.8% for imatinib and from 5.4 to 12.4% for N-desmethyl imatinib and interday CV (%) ranged from 5.6 to 6.5% for imatinib and from 5.4 to 16.1% for N-desmethyl imatinib. Methodological modifications were attempted to overcome non specific binding (NSB) on the ultrafiltration device. Two types of devices previously used for unbound determination of drugs were tested. Our results clearly showed that the methodology and the features of devices used for ultrafiltration could totally compromise the determination of unbound concentrations of a drug.

Factors for hematopoietic toxicity of carboplatin: refining the targeting of carboplatin systemic exposure.

PURPOSE: Area under the curve (AUC) dosing is routinely carried out for carboplatin, but the chosen target AUC values remain largely empirical. This multicenter pharmacokinetic-pharmacodynamic (PK-PD) study was performed to determine the covariates involved in the interindividual variability of carboplatin hematotoxicity that should be considered when choosing individual target AUCs. PATIENTS AND METHODS: Three hundred eighty-three patients received carboplatin as part of established regimens. A semi-physiologic population PK-PD model was applied to describe separately the time course of absolute neutrophil and platelet counts using NONMEM software. The plasma ultrafiltrable carboplatin concentration (C(Carbo)) was assumed to inhibit the proliferation of blood cell precursors through a linear model: drug effect = slope × C(Carbo). The slope corresponds to the patients' sensitivity to carboplatin hematotoxicity. The relationships between the patients' sensitivity to the neutropenic or thrombopenic effects of carboplatin and various covariates, including associated chemotherapies, demographic, biologic, and pharmacogenetic data, were studied. RESULTS: The sensitivity of carboplatin-induced thrombocytopenia decreased in the case of concomitant paclitaxel chemotherapy (slope decreased by 24%), whereas it increased with coadministration of etoposide and gemcitabine (slope increased by 45% and 133%, respectively). For neutropenia, the sensitivity increased when carboplatin was combined with other cytotoxics (slope increased by 76%). CONCLUSION: This study provides useful information to clinicians to better estimate the hematopoietic toxicity of carboplatin and thus choose more rationally carboplatin target AUCs as a function of pretreatment or concomitantly administered chemotherapies. For example, an AUC of 5 mg/mL · min is associated with a risk of grade 3 or 4 thrombocytopenia of 2% in combination with paclitaxel versus 38% with gemcitabine in a non-pretreated patient.