Population pharmacokinetics of digoxin in Korean patients

AIM: Digoxin possesses a narrow therapeutic index and shows a large inter-patient pharmacokinetic variability. The purpose of this study was to develop a population model for the pharmacokinetics of digoxin in Korean patients. METHODS: Plasma concentrations of digoxin after multiple administration at varying dosing schedules in Korean patients were used for population modeling. Data analysis was performed with the P-Pharm software. The data were best fitted by a one-compartment model. The effect of demographic and clinical factors like sex, age, weight, disease state, and renal function on the pharmacokinetic parameters of digoxin was investigated. RESULTS: The study indicated that the clearance of digoxin was influenced by creatinine clearance, while body weight and creatinine clearance were the covariates for its volume of distribution. The population mean estimates for CL and V were 4.4 l/h and 535 l, respectively. Absorption rate constant was lower in females and in the presence of concomitant drug treatment. CONCLUSION: A population pharmacokinetic model for the digoxin pharmacokinetics in a section of Korean patients was developed. The relationships between the pharmacokinetic parameters and the demographic data and the patient-specific covariates were established.     

Population pharmacokinetics of infliximab in patients with ankylosing spondylitis

The population pharmacokinetics of infliximab were characterized in patients with active ankylosing spondylitis (n = 274). Serum infliximab concentration data, from a 2-year period, were analyzed using NONMEM. A 2-compartment linear pharmacokinetic model was chosen to describe the pharmacokinetic characteristics of infliximab in serum. Population estimates (typical value +/- standard error) were obtained from the final covariate model: clearance (CL: 0.273 +/- 0.007 L/day), volume of distribution in the central compartment (V(1): 3.06 +/- 0.057 L), intercompartment clearance (Q: 1.72 +/- 0.48 L/day), and volume of distribution in the peripheral compartment (V(2): 2.94 +/- 0.17 L). Interindividual variability for CL and V(1) was 34.1% and 17.5%, respectively. White blood cell count at baseline and the antibody-to-infliximab status were significant covariates to CL; body surface area and sex were significant covariates to V(1). The CL for patients with a positive antibody-to-infliximab status was estimated to be 41.9% to 76.7% higher than for the remaining patients. Other covariates (baseline disease activity and the concomitant medication use of prednisolone, omeprazole, nonsteroidal anti-inflammatory drugs, or analgesics) did not affect infliximab pharmacokinetics. The development of antibodies to infliximab was associated with accelerated infliximab clearance and may represent a potential underlying mechanism for an inadequate response, or loss of response, to infliximab treatment.     

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 imatinib and the role of alpha-acid glycoprotein

AIMS: The aims of this observational study were to assess the variability in imatinib pharmacokinetics and to explore the relationship between its disposition and various biological covariates, especially plasma alpha1-acid glycoprotein concentrations. METHODS: A population pharmacokinetic analysis was performed using NONMEM based on 321 plasma samples from 59 patients with either chronic myeloid leukaemia or gastrointestinal stromal tumours. The influence of covariates on oral clearance and volume of distribution was examined. Furthermore, the in vivo intracellular pharmacokinetics of imatinib was explored in five patients. RESULTS: A one-compartment model with first-order absorption appropriately described the data, giving a mean (+/-SEM) oral clearance of 14.3 l h-1 (+/-1.0) and a volume of distribution of 347 l (+/-62). Oral clearance was influenced by body weight, age, sex and disease diagnosis. A large proportion of the interindividual variability (36% of clearance and 63% of volume of distribution) remained unexplained by these demographic covariates. Plasma alpha1-acid glycoprotein concentrations had a marked influence on total imatinib concentrations. Moreover, we observed an intra/extracellular ratio of 8, suggesting substantial uptake of the drug into the target cells. CONCLUSION: Because of the high pharmacokinetic variability of imatinib and the reported relationships between its plasma concentration and efficacy and toxicity, the usefulness of therapeutic drug monitoring as an aid to optimizing therapy should be further investigated. Ideally, such an approach should take account of either circulating alpha1-acid glycoprotein concentrations or free imatinib concentrations.     

Population pharmacokinetic analysis of meloxicam in rheumatoid arthritis patients

AIM: To perform a nonlinear mixed effect modelling (NONMEM) population pharmacokinetic analysis of meloxicam plasma concentrations in rheumatoid arthritis (RA) patients participating in three clinical trials, and to evaluate the effects of age, weight, gender and concomitant medications on meloxicam pharmacokinetics. METHODS: Meloxicam was administered to RA patients once daily for 3 weeks or 6 months at doses between 7.5 and 60 mg. Plasma samples were obtained at least 7 days after the first dose and meloxicam plasma concentrations were quantified by h.p.l.c. RESULTS: NONMEM analysis was conducted on plasma samples derived from 586 patients. A one-compartmental model was found to describe the data adequately. For a typical subject in the population, a clearance of 0.377 l h-1 (95% confidence interval (CI) 0.0304-0.449) in males and 0.347 l h-1 (95% CI 0.274-0.419) in females was obtained. The volume of distribution was estimated to be 14.9 l. The findings were corroborated by subsequent analysis using WinBUGS. Analysis of covariates showed that age and gender both significantly (P < 0.005) affected clearance. The effect of age was relatively small and a dose adjustment of <10% was deemed unnecessary. Differences between males and females were attributed to differences in weight. No clinically relevant drug-drug interactions were found, although sulphasalazine and glucocorticoids both significantly (P < 0.005) affected meloxicam clearance (+19% and - 12%, respectively). The mechanisms by which these agents affect meloxicam clearance remain to be elucidated. CONCLUSIONS: The population pharmacokinetic meloxicam data from patients with RA gave similar results to those obtained from phase I trials. However, uncommon drug interactions may not be detected in phase I trials because of the small number of observations made.     

Population pharmacokinetics of lamotrigine.

The present study estimated the population pharmacokinetics of lamotrigine in patients receiving oral lamotrigine therapy with drug concentration monitoring, and determined intersubject and intrasubject variability. A total of 129 patients were analyzed from two clinical sites. Of these, 124 patients provided sparse data (198 concentration-time points); nine patients (four from a previous group plus five from the current group) provided rich data (431 points). The population analysis was conducted using P-PHARM (SIMED Scientific Software, Cedex, France), a nonlinear mixed-effect modeling program. A single exponential elimination model (first-order absorption) with heteroscedastic weighting was used. Apparent clearance (CL/F) and volume of distribution (V/F) were the pharmacokinetic parameters estimated. Covariate analysis was performed to determine which factors explained any of the variability associated with lamotrigine clearance. Population estimates of CL/F and V/F for lamotrigine generated in the final model were 2.14 +/- 0.81 L/h and 78.1 +/- 5.1 L/kg. Intersubject and intrasubject variability for clearance was 38% and 38%, respectively. The covariates of concomitant valproate and phenytoin therapy accounted for 42% of the intersubject variability of clearance. Age, gender, clinic site, and other concomitant antiepileptic drugs did not influence clearance. This study of the population pharmacokinetics of lamotrigine in patients using the drug clinically provides useful data and should lead to better dosage individualization for lamotrigine.     

Amiodarone does not affect digoxin kinetics in the rabbit

It has been reported that amiodarone may interact with digoxin in man. We investigated the effects of amiodarone pretreatment (35 mg kg-1 day-1) on the pharmacokinetics of a single dose of digoxin (50 micrograms kg-1) in 6 rabbits. Total body clearance of digoxin was 138.84 +/- 44.67 and 147.99 +/- 29.17 ml min-1, serum half life 187.9 +/- 60.9 and 181.34 +/- 25.57 min and volume of distribution 35.4 +/- 8.54 and 37.8 +/- 3.9 litres before and after amiodarone treatment, respectively. None of these changes were statistically significant. We conclude that the presence of an amiodarone-induced change in digoxin pharmacokinetics in the rabbit was not evident and that other animal models will be necessary for studying this interaction.     

Pharmacokinetic and pharmacodynamic interactions between the novel calcium sensitiser levosimendan and warfarin

OBJECTIVE: To study the effects of possible interactions between levosimendan and warfarin on pharmacokinetics and pharmacodynamics. Furthermore, the effects of levosimendan on blood coagulation were investigated. METHODS: Open, randomised cross-over design with two treatment phases was used. During one phase, levosimendan (0.5 mg four times daily) was given orally to ten healthy subjects for 9 days. On the fourth treatment day with levosimendan, a single oral dose of warfarin (25 mg) was given. Pharmacokinetic parameters of levosimendan from the third and fourth treatment days were compared with each other. During the other treatment phase the subjects received only a single dose of warfarin. Pharmacokinetic parameters of warfarin alone were compared with those determined after concomitant administration of levosimendan. Changes in blood coagulation parameters were evaluated after levosimendan and warfarin alone and after concomitant administration. RESULTS: Warfarin did not change the pharmacokinetics of levosimendan. The distribution volume of warfarin was higher and elimination half-life shorter after concomitant levosimendan administration than after warfarin alone. However, concomitant levosimendan administration did not potentiate the effects of warfarin on blood coagulation assessed using activated partial thromboplastin time (APTT) and thromboplastin time (TT-SPA). Levosimendan alone for 3 days did not change APTT or TT-SPA values. There were no changes in the protein binding of levosimendan or warfarin upon concomitant administration. Continuous treatment with oral levosimendan caused headache, which was probably due to cerebral vasodilation. CONCLUSIONS: Concomitant levosimendan administration did not potentiate the effect of warfarin on blood coagulation after a single dose. Levosimendan itself had no effects on blood coagulation.     

The effect of age on digoxin pharmacokinetics in Fischer-344 rats

Digoxin protein binding and pharmacokinetics were studied in 4-, 14-, and 25-month-old male Fischer-344 rats to determine if there were age-dependent changes in digoxin disposition. Serum protein binding did not differ among age groups. The average percentage unbound digoxin for all animals was 61.3 +/- 5.3% (means +/- SD, n = 15). For pharmacokinetic studies, [3H]digoxin and 1 mg/kg unlabeled digoxin were administered as an intravenous bolus dose to animals from each age group. The [3H]digoxin terminal elimination half-life was 2.0, 2.3, and 2.5 hr, respectively. The steady-state volume of distribution in the three age groups was 1.51, 1.49, and 1.27 liters/kg, respectively. Total body clearance for the three age groups was 14.2, 12.1, and 7.5 ml/min/kg, respectively. Analysis of variance of these data followed by Duncan's multiple range test indicated a significant decrease in clearance in the aged rats (25-month-old, p less than 0.05). This age-dependent decrease in clearance suggested that digoxin pharmacokinetics could be a significant factor in age-related alterations in digoxin cardiotoxicity in the rat, as it is in humans, and that the Fischer-344 rat could be a useful model for studies of digoxin pharmacokinetic changes with age.     

Study on the interaction of the dopamine agonist alpha-dihydroergocryptine with the pharmacokinetics of digoxin

AIM: The study was carried out to explore the potential for pharmacokinetic interaction of a single oral dose of alpha-dihydroergocryptine (CAS 14271-05-7, DHEC, Almirid) with digoxin. METHODS: The serum pharmacokinetics of digoxin were analysed after the administration of single oral doses of 0.5 mg digoxin administered either alone or concomitantly with 20 mg DHEC according to a randomised, non-blinded, two-period cross-over design, with study periods 2 weeks apart. Twelve healthy male subjects, 23 to 39 years of age were enrolled and were investigated in accordance with the protocol. Venous blood was sampled up to 48 h after dosing. Concentrations of digoxin in serum were determined by a competitive radioimmunoassay. RESULTS: The mean Cmax were 1.97 +/- 0.87 (after a median tmax of 1 h) and 2.05 +/- 0.95 ng/ml (after a median tmax of 0.83 h) after the administration of digoxin with (test) and without (reference) concomitant DHEC, respectively; the corresponding estimated treatment ratio for test: reference was 0.939, 95% CI: 0.781 to 1.129. The mean AUC(0-48) were 13.6 +/- 5.0 ng.h/ml and 13.3 +/- 4.7 ng.h/ml for the test and reference treatment, respectively; the corresponding estimated treatment ratio for test: reference was 1.011, 95% CI: 0.866 to 1.142. In addition, no clinically significant changes were observed by ECG monitoring. The tolerability of digoxin alone was good, significantly more adverse events occurred when co-administered with DHEC; these corresponded with the known adverse reaction profile and were of moderate intensity. No premature study termination was thus necessary. CONCLUSION: The present study did not demonstrate clinically relevant interaction of a single dose of DHEC on the pharmacokinetics of digoxin. On the basis of these observations there is no indication for an a priori adjustment of the dose of digoxin when concomitant treatment with DHEC is initiated.     

Phase I population pharmacokinetics of irofulven

Our aim was to develop a population pharmacokinetic model for irofulven and to assess covariates that might affect irofulven pharmacokinetics. Irofulven was administered by 5- or 30-min i.v. infusion to cancer patients during a phase I study. Blood samples were collected over 4 h. Plasma samples were analyzed to quantitate irofulven by high-performance liquid chromatography. Population pharmacokinetic analysis was performed using a non-linear mixed effects modeling program, MP2. Fifty-nine patients were available for pharmacokinetic analysis. Irofulven plasma concentration-time profiles were best described by a two-compartment pharmacokinetic model. Clearance and central volume of distribution were not significantly influenced by individual characteristics, i.e. body weight (BW), body surface area (BSA), age and gender. Final parameter estimates of clearance and central volume of distribution were 616 l/h and 37 l, respectively, resulting in a very short terminal half-life of less than 10 min. A relatively high level of variability was observed in irofulven pharmacokinetics, which was mainly due to a significant residual variability, 39%. For a 30-min irofulven infusion, the optimal sampling schedule for clearance estimation using the Bayesian method was the three time points 0.35-0.45, 0.80 and 1-1.2 h from the beginning of a 30-min infusion. We conclude that after i.v. infusion of irofulven, plasma clearance was high and not dependent upon patient age, gender, BSA or BW.     

Population pharmacokinetics of platinum after nedaplatin administration and model validation in adult patients

AIMS: The pharmacokinetics of unbound platinum after administration of an anticancer drug nedaplatin, cis-diammineglycolateplatinum were examined using population analysis. The relevant covariates and the extent of inter- and intra-individual variability were evaluated. METHODS: In order to clarify the pharmacokinetic profile of nedaplatin, unbound platinum concentrations (789 points) in plasma after intravenous infusion of nedaplatin were obtained from 183 courses for 141 patients. Plasma concentration data were analysed by nonlinear mixed effect modelling using NONMEM to evaluate the population mean parameters and variances for inter- and intra-individual random effects. The final population model was validated by parameter sensitivity analysis using objective function mapping, the bootstrap resampling and a data-splitting technique, i.e. the Jackknife method, and the predictive performance of the final model was evaluated. RESULTS: A two-compartment pharmacokinetic model with zero-order input and first order elimination described the current data well. The significant covariates were creatinine clearance (CLcr) for clearance of platinum (CL) [population mean [95% confidence interval (CI)] CL (l h(-1)) = 4.47 (3.27, 5.67) + 0.0738 (0.0581, 0.0896) x CLcr (CLcr: ml min(-1))] and body weight (BW: kg) for volume of distribution of platinum (Vc) [Vc (l) = 12.0 (7.5, 16.5) + 0.163 (0.081, 0.246) x BW]. Inter-individual variations (CV%, 95% CI) for CL and Vc were 25.5% (20.7, 29.6) and 21.4% (17.0, 24.1), respectively, and intra-individual variation (CV%, 95% CI) was 12.6% (10.5, 14.4). The effects of pretreatment with nedaplatin or other platinum agents on clearance and volume of distribution were also tested, but no significant effect was found. The relationship between the observed and predicted unbound platinum concentration by empirical Bayesian prediction showed good correlation with no bias, suggesting that the final model explains well the observed data in the patients. The mean prediction error and root mean square prediction error (95% CI) were - 0.0164 micro g ml(-1) (- 0.4379, 0.4051) and 0.2155 micro g ml(-1) (not calculable, 0.6523), respectively. The values of mean, standard error and 95% CI for objective function mapping, the bootstrap resampling, the Jackknife estimates and the final model coincided well. CONCLUSIONS: A population pharmacokinetic model was developed for unbound platinum after intravenous infusion of nedaplatin. Only creatinine clearance was found to be a significant covariate of clearance, and BW was found to be a significant covariate of volume of distribution. These population pharmacokinetic estimates are useful for setting initial dosing of nedaplatin using its population mean and can also be used for setting appropriate dosage regimens using empirical Bayesian forecasting.     

Population pharmacokinetics of ceftazidime in burn patients

AIM: The aim of this study was to characterize, via a population pharmacokinetic approach, the pharmacokinetics of ceftazidime in burn patients who were not in the acute post-injury phase. METHODS: The development of the pharmacokinetic model was based on data from therapeutic drug monitoring (41 patients, 94 samples). The estimation of population pharmacokinetic parameters and the selection of covariates (age, gender, body weight, size of burn and creatinine plasma concentration) that could affect the pharmacokinetics were performed with a nonlinear mixed effect modelling method. RESULTS: No relationship between covariates and the pharmacokinetic parameters was established with the exception of an inverse-linear relationship between creatinine plasma concentration and ceftazidime total clearance. The total clearance of ceftazidime was 2.72 l h-1[coefficient variation (CV) = 56.3%] and the distribution volume of the central compartment was 0.28 l kg-1 (CV = 13.2%) The transfer rate constants (k12, k 21) between the central and peripheral compartments were 0.06718 h-1 (CV = 87.2%) and 0.001823 h-1 (CV = 82.7%), respectively. From these parameters, the total ceftazidime volume of distribution (10.64 l kg-1) was calculated. CONCLUSION: The population parameters were different from those obtained in a previous study performed in fewer patients and in the early period after burn injury. In our study, the lower ceftazidime clearance could be explained by the relative decrease in ceftazidime elimination in relation to the burn area, and the higher ceftazidime volume of distribution in the presence of interstitial oedema, which could act as a reservoir from which ceftazidime returns slowly to the circulation.     

Pharmacokinetics and excretion balance of OR-1896, a pharmacologically active metabolite of levosimendan, in healthy men

OBJECTIVE: To investigate the pharmacokinetics and excretion balance of [(14)C]-OR-1896, a pharmacologically active metabolite of levosimendan, in six healthy male subjects. In addition, pharmacokinetic parameters of total radiocarbon and the deacetylated congener, OR-1855, were determined. METHODS: OR-1896 was administered as a single intravenous infusion of 200 microg of [(14)C]-OR-1896 (specific activity 8.6 MBq/mg) over 10 min. The pharmacokinetic parameters were calculated by three-compartmental methods. RESULTS: During the 14-day collection of urine and faeces, excretion (+/-S.D.) averaged 94.2+/-1.4% of the [(14)C]-OR-1896 dose. Mean recovery of radiocarbon in urine was 86.8+/-1.9% and in faeces 7.4+/-1.5%. Mean terminal elimination half-life of OR-1896 (t(1/2)) was 70.0+/-44.9 h. Maximum concentrations of OR-1855 were approximately 30% to that of OR-1896. Total clearance and the volume of distribution of OR-1896 were 2.0+/-0.4 l/h and 175.6+/-74.5l, respectively. Renal clearances of OR-1896 and OR-1855 were 0.9+/-0.4 l/h and (5.4+/-2.3)x10(-4) l/h, respectively. CONCLUSIONS: This study provides data to demonstrate that nearly one half of OR-1896 is eliminated unchanged into urine and that the active metabolites metabolite of levosimendan remain in the body longer than levosimendan. The remaining half of OR-1896 dose is eliminated through other metabolic routes, partially through interconversion back to OR-1855 with further metabolism of OR-1855. Given the fact that the pharmacological activity and potency of OR-1896 is similar to levosimendan, these results emphasize the clinical significance of OR-1896 and its contribution to the long-lasting effects of levosimendan.     

Population-based investigation of relative clearance of digoxin in Japanese neonates and infants by multiple-trough screen analysis

OBJECTIVE: The steady-state concentrations of digoxin at trough levels were studied to establish the role of patient characteristics in estimating doses for digoxin using routine therapeutic drug monitoring data. METHOD: The data (n = 448) showing steady state after repetitive oral administration in 172 hospitalized neonates and infants were analyzed using Nonlinear Mixed Effect Model (NONMEM), a computer program designed to analyze pharmacokinetics in study populations by allowing pooling of data. Analysis of the pharmacokinetics of digoxin was accomplished using a simple steady-state pharmacokinetic model. The effects of a variety of developmental and demographic factors on the clearance of digoxin were investigated. RESULTS: Estimates generated using NONMEM indicated that clearance of digoxin (l.h-1) was influenced by the demographic variables of age, total body weight, serum creatinine, the coadministration of spironolactone, and the presence or absence of congestive heart failure. The interindividual variability in digoxin clearance was modeled with proportional errors with an estimated coefficient of variation of 32.1%, and the residual variability was 28.9%. In the validation set of 66 patients, the performance (bias, precision) of the final population model was good (mean prediction error -0.04 ng.ml-1; mean absolute prediction error 0.20 ng.ml-1).     

Unaltered etanercept pharmacokinetics with concurrent methotrexate in patients with rheumatoid arthritis

The purpose of this study was to evaluate the potential impact of concurrent weekly oral methotrexate administration on the pharmacokinetics of etanercept in patients with rheumatoid arthritis (RA) in a phase 3B trial. As part of a double-blind randomized trial of 682 patients with rheumatoid arthritis who received etanercept (25 mg subcutaneously twice weekly), methotrexate (weekly oral dose, median weekly dose: 20 mg), or etanercept (25 mg subcutaneously twice weekly) plus methotrexate (weekly oral dose, median weekly dose: 20 mg), serum etanercept concentrations were measured in a subset of patients. Serum samples for 98 randomly selected patients (48 receiving etanercept-alone treatment, 50 receiving etanercept plus methotrexate combination treatment) were analyzed to assess the pharmacokinetics of etanercept. A single blood sample was drawn from each patient at baseline and at the week 24 visit. Given the variable sampling time for patients in both groups, a population pharmacokinetic analysis using NONMEM was conducted for etanercept. A final covariate population pharmacokinetic model was constructed based on previously obtained etanercept data from both healthy subjects (n = 53) and patients with RA (n = 212) in 10 prior clinical trials. The predictive performance of the final model was assessed by both bootstrap and data-splitting validation approaches. The final model was then used to estimate Bayesian pharmacokinetic parameters for the patients in both treatments in the current trial. The potential effect of the concurrent administration of methotrexate on the pharmacokinetics of etanercept was examined by comparing the clearance values between 2 treatments using statistical criteria. A population 2-compartment model with first-order elimination from the central compartment and with either zero-order (intravenous administration) or first-order (subcutaneous administration) input was selected based on the data from the prior 10 etanercept clinical studies. The following pharmacokinetic parameters (typical value +/- standard error) were estimated: clearance (CL: 0.072 +/- 0.005 L/h), volume of distribution in the central compartment (V(c): 5.97 +/- 0.45 L), volume of distribution in the peripheral compartment (V(p): 2.05 +/- 0.32 L), intercompartment clearance (Q: 0.0645 +/- 0.0093 L/h), first-order absorption rate constant (k(a): 0.0282 +/- 0.0039 1/h), and absolute bioavailability for subcutaneous administration (F: 0.626 +/- 0.056). Interindividual variability of the pharmacokinetic parameters was quantified for CL (25.1%), V(c) (41.7%), k(a) (53.1%), and F (24.2%). Residual variability consisted of combined additive (11.4 ng/mL) and proportional error (49.9%). Both age (< 17 years) and body weight (< 60 kg) were found to be important covariates on CL. The results of both validation tests indicated the adequate predictive performance of the population model. Based on the bioequivalence criteria, the Bayesian-estimated clearance for patients receiving etanercept alone (mean: 0.070 L/h) was comparable to that for patients receiving a combination of etanercept and methotrexate (mean = 0.066 L/h). The pharmacokinetics of etanercept were not altered by the concurrent administration of methotrexate in patients with rheumatoid arthritis. Thus, no etanercept dose adjustment is needed for patients taking concurrent methotrexate.     

Population pharmacokinetics of digoxin in Japanese patients: a 2-compartment pharmacokinetic model.

OBJECTIVE: To clarify the observed variability of digoxin disposition by performing a population pharmacokinetic analysis in a Japanese population. DESIGN: Retrospective analysis of clinical pharmacokinetic data. PATIENTS AND PARTICIPANTS: Data were obtained from 106 patients with heart failure and atrial fibrillation (43 males and 63 females). METHODS: Digoxin concentrations in serum were measured by fluorescence polarisation immunoassay. Population pharmacokinetic analysis was performed using a 2-compartment open pharmacokinetic model with the computer program NONMEM. RESULTS: 246 serum concentrations were obtained. Final pharmacokinetic parameters were: CL (L/h) = (0.036 x TBW + 0.112 x CL(CR)) x 0.77SPI x 0.784CCB, V1 = 1.83 L/kg, V2 = 22.6 L/kg and Q = 0.629 L/h/kg, where CL is total body clearance, V1 and V2 are the apparent volumes of distribution in the central and peripheral compartments, Q is intercompartmental clearance, TBW is total bodyweight (in kg), CL(CR) is creatinine clearance (in ml/min), SPI = 1 for concomitant administration of spironolactone (and zero otherwise) and CCB = 1 for concomitant administration of calcium antagonists (and zero otherwise). Concomitant administration of digoxin and spironolactone resulted in a 23% decrease in digoxin clearance. Concomitant administration of digoxin and calcium antagonists (diltiazem, nicardipine, nifedipine or verapamil) resulted in a 21.6% decrease in digoxin clearance. CONCLUSIONS: The estimated population parameter values may assist clinicians in the individualisation of digoxin dosage regimens.     

Population pharmacokinetics of tipifarnib in healthy subjects and adult cancer patients

AIMS: To characterize the population pharmacokinetics of tipifarnib. METHODS: A total of 1083 subjects treated orally with a solution, capsule or tablet formulations of tipifarnib, given as a single dose or as multiple twice-daily doses (range 25-1300 mg) were combined with data from 1, 2 and 24 h intravenous infusions. A total of 3445 concentrations in the index data set were fitted by an open three-compartment linear disposition model with sequential zero-order input into the depot compartment, followed by a first-order absorption process, and lag time, using NONMEM V. The effect of patient covariates on tipifarnib pharmacokinetics was explored. The model was evaluated using goodness of fit plots and relative error measurements for 3894 concentrations in the test data set. Computer simulations were undertaken to evaluate the effect of covariates on tipifarnib pharmacokinetics. RESULTS: Tipifarnib oral bioavailability (26.7%) did not differ between the formulations. The absorption rate from the solution was faster than from the solid forms. Whereas the absorption rate and systemic clearance were more rapid in healthy subjects, the extent of absorption and the steady-state volume of distribution were comparable in cancer patients and healthy subjects. Systemic clearance in cancer patients (21.9 l h-1) exhibited a statistically significant relationship with total bilirubin. The typical volume of the central compartment in cancer patients (54.6 l 70 kg-1) was directly proportional to body weight. The clinical relevance of these covariates in cancer patients is questionable as there was a substantial overlap in simulated concentration-time profiles across a wide range of covariate values. CONCLUSIONS: A population PK approach has been used to integrate data gathered during clinical development and to characterize the pharmacokinetics of tipifarnib. Individualization of dose based on body weight or total bilirubin concentration in adult cancer patients is not warranted.     

Pharmacokinetics of progesterone in ovariectomized rats after single dose intravenous administration.

The pharmacokinetics of progesterone were characterized in ovariectomized female rats. Progesterone was administered intravenously at a dose of 500 micrograms kg-1. Serum progesterone concentrations were determined by radioimmunoassay. Serum concentrations of progesterone were best described by a two-compartment model with elimination from the central compartment. The distribution and elimination phase half-lives were 0.13 +/- 0.024 (mean +/- SD) and 1.21 +/- 0.21 h, respectively. Elimination of the steroid was rapid with a total clearance of 2.75 +/- 0.42 l h-1 kg-1. Progesterone was widely distributed in the rat with a steady state volume of distribution of 2.36 +/- 0.23 l kg-1, a volume of the central compartment of 0.86 +/- 0.24 l kg-1 and a volume of the peripheral compartment of 1.50 +/- 0.19 l kg-1. The results of this study suggest that the ovariectomized female rat is a suitable animal model for examining the pharmacokinetics of progesterone.     

Effect of itraconazole on digoxin clearance in patients with congestive heart failure

We showed a digoxin-itraconazole interaction in three patients in whom digoxin serum concentrations were increased. Their electrocardiograms revealed arrhythmias such as ventricular premature contraction, atrioventricular block, and ST depression. The elimination half-life of digoxin in case 3 patient who continued itraconazole therapy was 8.4 days, which was estimated by nonlinear least squares method from the serum concentrations of digoxin versus time curve. In order to evaluate the influence of itraconazole on pharmacokinetic parameters of digoxin, we estimated digoxin clearance by the Bayesian method using the population pharmacokinetic parameters in Japanese patients. During the concomitant use of itraconazole and digoxin, the digoxin clearance in all patients decreased to 50.5 +/- 8.8% (mean +/- S.D.) of the clearance without itraconazole. When digoxin and itraconazole are used concomitantly, careful monitoring of digoxin serum concentrations is necessary. Based on our results of digoxin clearance evaluation, the dose of digoxin should be reduced to 50% of original dose after itraconazole is started, and digoxin serum concentration might be controlled at the same level before the concomitant use.