Population pharmacokinetics of ondansetron: a covariate analysis

Plasma and cerebrospinal fluid pharmacokinetics of ondansetron in humans

AIMS

Changes in serotonergic sensory modulation associated with overexpression of 5-HT3 receptors in the central nervous system (CNS) have been implicated in the pathophysiology of neuropathic pain after peripheral nerve damage. 5-HT3 receptor antagonists such as ondansetron can potentially alleviate neuropathic pain, but have limited effectiveness, due potentially to limited CNS access. However, there is currently limited information on CNS disposition of systemically-administered 5-HT3 receptor antagonists. This study evaluated the cerebrospinal fluid (CSF) disposition of ondansetron, as a surrogate of CNS penetration.

METHODS

Fifteen patients were given a single 16 mg intravenous 15 minute infusion of ondansetron, followed by serial blood and a single CSF sampling. Population pharmacokinetic (PK) modelling was implemented to describe the average and individual plasma and CSF profiles of ondansetron. A two-compartmental model was used to capture ondansetron plasma PK with a single CSF compartment to describe distribution to the CNS.

RESULTS

The individual model-estimated CSF to plasma partition coefficients of ondansetron were between 0.09 and 0.20. These values were mirrored in the calculated CSF penetration ratios, ranging from 0.08 to 0.26.

CONCLUSIONS

After intravenous administration, CSF concentrations of ondansetron were approximately 7-fold lower than those observed in the plasma. A model could be developed to describe individual CSF concentration-time profiles of ondansetron based on a single CSF data point. The low CSF penetration of ondansetron may explain its limited analgesic effectiveness, and affords an opportunity to explore enhancing its CNS penetration for targeting conditions such as neuropathic pain.

Gender and anthropometrics of patients undergoing cisplatin-containing chemotherapy as determinants of acute emesis over repeat courses

Objective. To characterize the anthropometric and pharmacotherapeutic variables related to acute emesis over repeat courses of cisplatin-containing regimens (≥50 mg/m survival analysis.2) by means of survival analysis.

Methods. A prospective, cross-sectional non-controlled study was started to analyse acute vomiting in patients treated in a general hospital. The patients received an intravenous combination of drugs based on metoclopramide (two 3 mg/kg doses), diphenhydramine (20 mg) and dexamethasone (20 mg) as first choice antiemetic treatment. An intravenous regimen based on ondansetron (8 mg) and dexamethasone (20 mg) was given as an alternative regimen. Therapeutic failure was defined as the recording of one or more vomiting episodes on a self-evaluation sheet. Other variables included were chemotherapeutic regimen, antiemetic regimen, gender, age, weight and height. The statistical analysis was developed using the Cox proportional hazards model.

Results. Eighty-eight patients were finally included in the study, 16 women (18%) and 72 men (82%). The metoclopramide-based regimen was administered to 74 patients (84%) and the ondansetron-based regimen to 14 patients (15%). The univariate analysis showed that any variable included in the study was significant. The multivariate survival analysis retained three variables: height (hazard ratio 1.22), gender (hazard ratio 2.12) and weight (hazard ratio 1.44) of the patients. It is hypothesized that gender and anthropometrics of patients could represent differences in pharmacokinetic and/or pharmacodynamic behaviour of cisplatin and/or antiemetics. The potential role of these parameters in these drugs is discussed.

Conclusions. Emesis over repeat courses in cisplatin-containing regimens seems a function of the gender and anthropometrics of patients, irrespective of the antiemetic regimen and the emetogenicity of the cytostatics. Dosing individualization of cisplatin and/or antiemetics based on pharmacokinetic and/or pharmacodynamic parameters can be a valid tool to increase the effectiveness and safety of these drugs.

Population pharmacokinetics and prophylactic anti-emetic efficacy of ramosetron in surgical patients

AIMS

This study characterized the pharmacokinetics of ramosetron and compared prophylactic anti-emetic efficacy with that of ondansetron in a large population.

METHODS

Fifty-eight patients consented to the pharmacokinetic analysis and were assigned randomly to receive 0.3, 0.45 or 0.6 mg ramosetron after induction of anaesthesia. Blood samples were acquired at preset intervals. Non-compartmental and population pharmacokinetic analyses were performed. In total, 1102 patients consented to the evaluation of prophylactic anti-emetic efficacy and were allocated randomly to receive 0.3 mg ramosetron or 4 mg ondansetron at the end of surgery. An additional 16 mg ondansetron were mixed in the intravenous patient-controlled analgesia pump of the ondansetron group. Post-operative nausea and vomiting (PONV) were evaluated 6, 24 and 48 h post-operatively using the Rhodes index of nausea, vomiting and retching (RINVR). Administration of rescue anti-emetics and adverse events were evaluated.

RESULTS

The pharmacokinetic parameter estimates were V1 (l) = 5.12, V2 (l) = 108, CL (l⋅min(-1) ) = 0.08 + (59⋅age(-1) ) × 0.09, Q (l⋅min(-1) ) = 1.42. The incidences of PONV in the ramosetron and ondansetron groups were 77 (13.9%) and 113 (20.6%) and 44 (7.9%) and 66 (12.0%) at 24 and 48 h post-operatively, respectively (P = 0.004, 0.030). RINVR was significantly lower in the ramosetron than the ondansetron group 24 and 48 h post-operatively (P = 0.003, 0.025). Use of rescue anti-emetics and incidence of adverse events were comparable.

CONCLUSIONS

A two compartment mammillary model was used to describe ramosetron pharmacokinetics. Prophylactic anti-emetic efficacy of ramosetron was significantly better 24 and 48 h post-operatively than that of ondansetron, particularly when the Apfel score was ≥ 3.

Different treatment benefits were estimated by clinical trials performed in adults compared with those performed in children

OBJECTIVE

Our main objective was to see whether the therapeutic benefit observed in placebo controlled randomized controlled trials (RCTs) is different between adults and children.

STUDY DESIGN AND SETTING

We searched three electronic databases for meta-analyses that included double-blind, placebo-controlled RCTs with separate results for adults and children. The selected reviews were classified according to disease and drug used. The heterogeneity of treatment response between adults and children was measured using ratio of odds ratios (RORs).

RESULTS

We selected 89 meta-analyses and calculated RORs for 124 drugs. Heterogeneity in the direction of the treatment effect was observed in one drug and heterogeneity in the quantity of the treatment effect for 13 drugs, indicating significantly different treatment effect in adults when compared with children. RORs were not significantly different from 1 for 110 drugs. For 36 of these drugs, the treatment effect was confirmed in both populations.

CONCLUSION

We found different treatment benefits estimated by clinical trials performed in adults compared with those performed in children for 14 of 124 drugs. Data on dose adjustment and child age groups from RCTs were not adequately reported to investigate their influence on the treatment benefit dissimilarities.

The metabolism of the 5HT3 antagonists, ondansetron, alosetron and GR87442 II: investigation into the in vitro methods used to predict the in vivo hepatic clearance of ondansetron, alosetron and GR87442 in the rat, dog and human

The in vitro clearances of the 5HT3 antagonists, ondansetron, alosetron and GR87442 were investigated. Intrinsic clearances using either metabolite formation or substrate depletion methods were equivalent (R2 = 0.95). Hepatocytes from preclinical species were superior to microsomes for the prediction of hepatic clearance (CL(H)), whereas the predictions from human microsomes and hepatocytes were similar. Using a non-restrictive model, seven of the nine CL(H) predictions using hepatocytes were within 2-fold of the in vivo CL(H) values. If the unbound fraction was included, the clearance of the compounds was generally under-predicted by both in vitro models. However, for the most metabolically stable compound, GR87442, the non-restrictive model over-predicted CLp. This and the possibility of extrahepatic metabolism indicate that the restrictive model is more appropriate for prediction of CL(H). The rank order of metabolic stability correlated with that in vivo. All three compounds were more metabolically stable in human than in the preclinical animal species examined.

Population pharmacokinetics of melphalan in paediatric blood or marrow transplant recipients

AIM

To develop a population pharmacokinetic model for melphalan in children with malignant diseases and to evaluate limited sampling strategies for melphalan.

METHODS

Melphalan concentration data following a single intravenous dose were collected from 59 children with malignant diseases aged between 0.3 and 18 years. The data were split into two sets: the model development dataset (39 children, 571 concentration observations) and the model validation dataset (20 children, 277 concentration observations). Population pharmacokinetic modelling was performed with the NONMEM software. Stepwise multiple linear regression was used to develop a limited sampling model for melphalan.

RESULTS

A two-compartment model was fitted to the concentration-vs.-time data. The following covariate population pharmacokinetic models were obtained: (i) Clearance (l h(-1)) = 0.34.WT - 3.17.CPT + 0.0377.GFR, where WT = weight (kg), CPT = prior carboplatin therapy (0 = no, 1 = yes), and GFR = glomerular filtration rate (ml min(-1) 1.73 m(-2)); (ii) Volume of distribution (l) = 1.12 + 0.178.WT. Interpatient variability (coefficient of variation) was 27.3% for clearance and 33.8% for volume of distribution. There was insignificant bias and imprecision between observed and model-predicted melphalan concentrations in the validation dataset. A three-sample limited sampling model was developed which adequately predicted the area under the concentration-time curve (AUC) in the development and validation datasets.

CONCLUSIONS

A population pharmacokinetic model for melphalan has been developed and validated and may now be used in conjunction with pharmacodynamic data to develop safe and effective dosing guidelines in children with malignant diseases.

DI. Ondansetron does not reduce the shivering threshold in healthy volunteers

BACKGROUND

Ondansetron, a serotonin-3 receptor antagonist, reduces postoperative shivering. Drugs that reduce shivering usually impair central thermoregulatory control, and may thus be useful for preventing shivering during induction of therapeutic hypothermia. We determined, therefore, whether ondansetron reduces the major autonomic thermoregulatory response thresholds (triggering core temperatures) in humans.

METHODS

Control (placebo) and ondansetron infusions at the target plasma concentration of 250 ng ml(-1) were studied in healthy volunteers on two different days. Each day, skin and core temperatures were increased to provoke sweating; then reduced to elicit peripheral vasoconstriction and shivering. We determined the core-temperature sweating, vasoconstriction and shivering thresholds after compensating for changes in mean-skin temperature. Data were analysed using t-tests and presented as means (sds); P<0.05 was taken as significant.

RESULTS

Ondensetron plasma concentrations were 278 (57), 234 (55) and 243 (58) ng ml(-1) at the sweating, vasoconstriction and shivering thresholds, respectively; these corresponded to approximately 50 mg of ondansetron which is approximately 10 times the dose used for postoperative nausea and vomiting. Ondansetron did not change the sweating (control 37.4 (0.4) degrees C, ondansetron 37.6 (0.3) degrees C, P=0.16), vasoconstriction (37.0 (0.5) degrees C vs 37.1 (0.3) degrees C; P=0.70), or shivering threshold (36.3 (0.5) degrees C vs 36.3 (0.6) degrees C; P=0.76). No sedation was observed on either study day.

CONCLUSIONS

/b>. Ondansetron appears to have little potential for facilitating induction of therapeutic hypothermia.

Population pharmacokinetics of raltitrexed in patients with advanced solid tumours

AIMS

To investigate the population pharmacokinetics of raltitrexed in patients with advanced solid tumours and to identify patient covariates contributing to the interpatient variability in the pharmacokinetics of raltitrexed.

METHODS

Patient covariate and concentration-time data were collected from patients receiving 0.1-4.5 mg m(-2) raltitrexed during the early clinical trials of raltitrexed. Data were fitted using nonlinear mixed effects modelling to generate population mean estimates for clearance (CL) and central volume of distribution (V). The relationship between individual estimates of the pharmacokinetic parameters and patient covariates was examined and the influence of significant covariates on the population parameter estimates and their variance was investigated using stepwise multiple linear regression. The performance of the developed model was tested using an independent validation dataset. All patient data were pooled in the total cohort to refine the population pharmacokinetic model for raltitrexed.

RESULTS

three-compartment pharmacokinetic model was used to fit the concentration-time data of raltitrexed. Estimated creatinine clearance (CL(CR)) was found to influence significantly the CL of raltitrexed and explained 35% of variability in this parameter, whilst body weight (WT) and serum albumin concentrations (ALB) accounted for 56% of the variability in V. Satisfactory prediction (mean prediction error 0.17 micro g l(-1) and root mean square prediction error 4.99 micro g l(-1)) of the observed raltitrexed concentrations was obtained in the model validation step. The final population mean estimates were 2.17 l h(-1)[95% confidence interval (CI) 2.06, 2.28] and 6.36 l (95% CI 6.02, 6.70) for CL and V, respectively. Interpatient variability in the pharmacokinetic parameters was reduced (CL 28%, V 25%) when influential covariates were included in the final model. The following covariate relationships with raltitrexed parameters were described by the final population model: CL (l h(-1)) = 0.54 + 0.02 CL(CR) (ml min(-1)) and V (l) = 6.64 + 0.08 WT (kg) - 0.16 ALB (g l(-1)).

CONCLUSIONS

A population pharmacokinetic model has been developed for raltitrexed in patients with advanced cancer. Pharmacokinetic parameters of raltitrexed are markedly influenced by the patient's renal function, body weight and serum albumin levels, which may be taken into account in dose individualization. The use of influential covariates to guide anticancer dosage selection may result in less variability in drug exposure and potentially a better clinical outcome.

Population pharmacokinetics of weekly docetaxel in patients with advanced cancer

AIMS

Previous pharmacokinetic studies of the 3-weekly regimen (100 mg m(-2) every 3 weeks) of docetaxel have shown that docetaxel clearance is affected by liver function, body surface area, age, serum alpha1-acid glycoprotein and cytochrome P450 3A4 (CYP3A4) activity. However, the pharmacokinetics of a weekly docetaxel (40 mg m(-2) week(-1)) schedule are not well characterized. The aims of this study were (a) to investigate the pharmacokinetics of docetaxel (40 mg m(-2) week(-1)) using sparse concentration-time data collected from patients with advanced cancer and (b) to utilize a population pharmacokinetic approach to identify patient covariates that significantly influence the clearance of docetaxel when administered according to this regimen.

METHODS

A two-compartment pharmacokinetic model was used to describe the docetaxel concentration-time data from 54 patients with advanced cancer. The mean population and individual posterior Bayesian estimates of docetaxel clearance were estimated using P-PHARM. The relationships between docetaxel clearance and 21 covariates were investigated. This included estimates of CYP3A4 function in each patient using the erythromycin breath test (1/tmax). Significant covariates were included into the final population pharmacokinetic model. Pharmacokinetic models were validated using a data splitting approach with a dataset consisting of 16 patients.

RESULTS

Significant relationships were found between docetaxel clearance and 1/tmax (erythromycin breath test parameter) and several of the liver function enzymes and CL was best described by the equation; CL = 21.51 + 217 (1/tmax) - 0.13 (ALT). This final population pharmacokinetic model provided both precise and unbiased predictions of docetaxel concentrations in a validation group of patients and an estimate of the population mean (95% confidence interval) clearance of docetaxel was 30.13 l h(-1) (12.54, 46.04 l h(-1)) with an intersubject variability 30%.

CONCLUSIONS

A population pharmacokinetic model has been developed and validated for weekly docetaxel (40 mg m(-2)) in patients with advanced cancer. These results indicate that CYP3A4 activity and hepatic function have an impact on the pharmacokinetics of docetaxel when administered weekly.

Clinical pharmacokinetic/pharmacodynamic and physiologically based pharmacokinetic modeling in new drug development: the capecitabine experience

Preclinical studies, along with Phase I, II, and III clinical trials demonstrate the pharmacokinetics, pharmacodynamics, safety and efficacy of a new drug under well controlled circumstances in relatively homogeneous populations. However, these types of studies generally do not answer important questions about variability in specific factors that predict pharmacokinetic and pharmacodynamic (PKPD) activity, in turn affecting safety and efficacy. Semi-physiological and clinical PKPD modeling and simulation offer the possibility of utilizing data obtained in the laboratory and the clinic to make accurate characterizations and predictions of PKPD activity in the target population, based on variability in predictive factors. Capecitabine is an orally administered pro-drug of 5-fluorouracil (5-FU), designed to exploit tissue-specific differences in metabolic enzyme activities in order to enhance efficacy and safety. It undergoes extensive metabolism in multiple physiologic compartments, and presents particular challenges for predicting pharmacokinetic and pharmacodynamic activity in humans. Clinical and physiologically based pharmacokinetic (PBPK) and pharmacodynamic models were developed to characterize the activity of capecitabine and its metabolites, and the clinical consequences under varying physiological conditions such as creatinine clearance or activity of key metabolic enzymes. The results of the modeling investigations were consistent with capecitabine's rational design as a triple pro-drug of 5-FU. This paper reviews and discusses the PKPD and PBPK modeling approaches used in capecitabine development to provide a more thorough understanding of what the key predictors of its PBPK activity are, and how variability in these predictors may affect its PKPD, and ultimately, clinical outcomes.

Population pharmacokinetic analysis of the major metabolites of capecitabine

Capecitabine has been developed as an orally administered tumor selective fluoropyrimidine for use in the treatment of breast and colorectal cancer. The metabolic pathway for capecitabine includes 5'-deoxy-5-fluorocytidine (5'-DFCR) and 5'-deoxy-5-fluorouridine (5'-DFUR), which is then converted to the pharmacologically active agent 5-fluorouracil (5-FU). A previous analysis showed that systemic exposure to 5'-DFUR and alpha-fluoro-beta-alanine (FBAL), a catabolite of 5-FU, was predictive of dose limiting toxicities. Therefore, a multi-response population pharmacokinetic (PK) model for the description of plasma concentrations of 5'-DFUR, 5-FU and FBAL following oral administration of capecitabine was developed using NONMEM. PK data from a bioequivalence study in 24 patients with various solid tumors were used to develop the PK structural part of the population PK model. The 5'-DFUR, 5-FU and FBAL plasma concentrations were described by a linear disposition PK model with first order absorption and lag time. Sparse plasma concentration data from 54 phase II breast cancer patients were added to the bioequivalence data and the influence of covariates on the apparent oral clearances of 5'-DFUR, 5-FU and FBAL and on the apparent volume of distribution of FBAL was investigated. This was conducted by including all significant (p < 0.05) single covariate-PK parameter pairs in the full PK model, followed by one by one deletion (p < 0.001) from the population model. Statistically significant effects were found for the influence of gender, body surface area and total bilirubin on 5'-DFUR clearance and the influence of creatinine clearance on FBAL clearance. However, none of these effects were considered to have clinical relevance.

Population pharmacokinetics of amphotericin B in children with malignant diseases

AIMS

To construct a population pharmacokinetic model for the antifungal agent, amphotericin B (AmB), in children with malignant diseases.

METHODS

A two compartment population pharmacokinetic model for AmB was developed using concentration-time data from 57 children aged between 9 months and 16 years who had received 1 mg kg(-1) day(-1) doses in either dextrose (doseform=1) or lipid emulsion (doseform=2). P-Pharm (version 1.5) was used to estimate the basic population parameters, to identify covariates with significant relationships with the pharmacokinetic parameters and to construct a Covariate model. The predictive performance of the Covariate model was assessed in an independent group of 26 children (the validation group).

RESULTS

The Covariate model had population mean estimates for clearance (CL), volume of distribution into the central compartment (V) and the distributional rate constants (k12 and k21) of 0.88 l h(-1), 9.97 l, 0.27 h(-1) and 0.16 h(-1), respectively, and the intersubject variability of these parameters was 19%, 49%, 55% and 48%, respectively. The following covariate relationships were identified: CL (l h(-1)) = 0.053 + 0.0456 weight (0.75) (kg) + 0.242 doseform and V (l) = 7.11 + 0.107 weight (kg). Our Covariate model provided unbiased and precise predictions of AmB concentrations in the validation group of children: the mean prediction error was 0.0089 mg l(-1) (95% confidence interval: -0.0075, 0.0252 mg l(-1)) and the root mean square prediction error was 0.1245 mg l(-1) (95% confidence interval: 0.1131, 0.1349 mg l(-1)).

CONCLUSIONS

A valid population pharmacokinetic model for AmB has been developed and may now be used in conjunction with AmB toxicity and efficacy data to develop dosing guidelines for safe and effective AmB therapy in children with malignancy.

Pharmacokinetic/pharmacodynamic modeling in drug development

We propose a framework for considering the role of pharmacokinetic/pharmacodynamic modeling in drug development and an appraisal of its current and potential impact on that activity. After some introduction, definitions, and background information on drug development, we discuss subject-matter models that underlie pharmacokinetic/pharmacodynamic modeling and show how they determine appropriate statistical models. We discuss the broad role modeling can play in drug development, enhancing primarily the "learning" steps, i.e. acquiring the information needed for the label and for planning efficient confirmatory clinical trials. Examples of past applications of modeling to drug development are presented in tabular form, followed by a discussion of some practical issues in application. Modeling will not reach its potential utility until it is manifest as a visible and separate work unit within a drug development program. We suggest that that work unit is the "in numero" study: a protocol-driven exercise designed to extract additional information, and/or answer a specific drug-development question, through an integrated model-based (meta-) analysis of existent raw data, often pooled across separate (clinical) studies.