A population pharmacokinetic approach to ceftazidime use in burn patients: influence of glomerular filtration, gender and mechanical ventilation

AIMS: The aim of this study was to evaluate the disposition of ceftazidime in burn patients using a population pharmacokinetic approach, and to identify the clinical and biological parameters influencing its pharmacokinetics. METHODS: The development of the pharmacokinetic model was based on 237 serum ceftazidime concentrations from 50 burn patients. The determination of the pharmacokinetic parameters and the selection of covariates were performed using a nonlinear mixed-effect modelling method. RESULTS: A two-compartment model with first order elimination incorporating a proportional error model best fitted the data. Ceftazidime clearance (CL, l h(-1)) was significantly correlated with creatinine clearance (CL(CR)), and the distribution volume of the peripheral compartment (V2, l) was correlated with gender, mechanical ventilation and the CL(CR). The final model was defined by the following equations: Ceftazidime clearance was 6.1 and 5.7 l h(-1) for mechanically ventilated males and females, respectively, and 7.2 and 6.6 l h(-1) for nonventilated patients. The total volume of distribution was 31.6 and 49.4 l for mechanically ventilated males and females, respectively, and 22.8 and 28.1 l h (-1)for nonventilated patients. CONCLUSIONS: We have shown that gender, mechanical ventilation and CL(CR) significantly influence the disposition of ceftazidime in burn patients. Interindividual variability in the pharmacokinetics of ceftazidime was significant and emphasizes the need for therapeutic monitoring.     

Pharmacokinetic-pharmacodynamic evaluation of ceftazidime continuous infusion vs intermittent bolus injection in septicaemic melioidosis

AIMS: Experimental studies have suggested that constant intravenous infusion would be preferable to conventional intermittent bolus administration of beta-lactam antibiotics for serious Gram-negative infections. Severe melioidosis (Burkholderia pseudomallei infection) carries a mortality of 40% despite treatment with high dose ceftazidime. The aim of this study was to measure the pharmacokinetic and pharmacodynamic effects of continuous infusion of ceftazidime vs intermittent bolus dosing in septicaemic melioidosis. METHODS: Patients with suspected septicaemic melioidosis were randomised to receive ceftazidime 40 mg kg-1 8 hourly by bolus injection or 4 mg kg-1 h-1 by constant infusion following a 12 mg kg-1 priming dose to perform estimation of pharmacokinetic and pharmacodynamic parameters. RESULTS: Of the 34 patients studied 16 (59%) died. Twenty patients had cultures positive for B. pseudomallei of whom 12 (60%) died. The median MIC90 of B. pseudomallei was 2 mg l-1, giving a target concentration CT, of 8 mg l-1. The median (range) estimated total apparent volume of distribution, systemic clearance and terminal elimination half-lives of ceftazidime were 0.468 (0.241-0.573) l kg-1, 0.058 (0.005-0.159) l kg-1 h-1 and 7.74 (1.95-44.71) h, respectively. Clearance of ceftazidime and creatinine clearance were correlated closely (r = 0. 71; P < 0.001) and there was no evidence of significant nonrenal clearance. CONCLUSIONS: Simulations based on these data and the ceftazidime sensitivity of the B. pseudomallei isolates indicated that administration by constant infusion would allow significant dose reduction and cost saving. With conventional 8 h intermittent dosing to patients with normal renal function, plasma ceftazidime concentrations could fall below the target concentration but this would be unlikely with a constant infusion. Correction for renal failure which is common in these patients is Clearance = k * creatinine clearance where k = 0.072. Calculation of a loading dose gives median (range) values of loading dose, DL of 3.7 mg kg-1 (1. 9-4.6) and infusion rate I = 0.46 mg kg h-1 (0.04-1.3) (which equals 14.8 mg kg-1 day-1). A nomogram for adjustment in renal failure is given.     

Population pharmacokinetics of eniporide and its metabolite in healthy subjects and patients with acute myocardial infarction

Eniporide (EMD 96 875) is a novel and selective inhibitor of the Na+-H+ exchange (NHE-1) inhibitor. The study objectives were to identify a structural model for population pharmacokinetic analysis of eniporide and its metabolite (EMD 112 843) using nonlinear mixed-effects modeling after short-term infusion (dose: 2.5-400 mg) in healthy subjects and patients undergoing myocardial reperfusion therapy. Pooled concentrations of eniporide and its metabolite from healthy subjects (n = 153; 4815 observations) and patients (n = 304; 1465 observations) were included in the pharmacokinetic analysis. Population estimates of clearance and volume of distribution of eniporide were 29.2 L/h (24.1% coefficient of variation [CV], healthy), 20.8 L/h (28.0% CV, patients) and 20.4 L (13.1% CV, healthy), 16.9 L (24.9% CV, patients), respectively. Statistical significance was achieved for the effect of age on clearance and creatinine clearance on volume of distribution of eniporide. The impact of the covariates on eniporide pharmacokinetics is minimal to warrant any dosage adjustments in patient population.     

Pharmacokinetics and effects of propofol 6% for short-term sedation in paediatric patients following cardiac surgery

AIMS: This paper describes the pharmacokinetics and effects of propofol in short-term sedated paediatric patients. METHODS: Six mechanically ventilated children aged 1-5 years received a 6 h continuous infusion of propofol 6% at the rate of 2 or 3 mg kg-1 h-1 for sedation following cardiac surgery. A total of seven arterial blood samples was collected at various time points during and after the infusion in each patient. Pharmacokinetic modelling was performed using NONMEM. Effects were assessed on the basis of the Ramsay sedation score as well as a subjective sedation scale. RESULTS: The data were best described by a two-compartment pharmacokinetic model. In the model, body weight was a significant covariate for clearance. Pharmacokinetic parameters in the weight-proportional model were clearance (CL) = 35 ml kg-1 min-1, volume of central compartment (V1) = 12 l, intercompartmental clearance (Q) = 0.35 l min-1 and volume of peripheral compartment (V2) = 24 l. The interindividual variabilities for these parameters were 8%, < 1%, 11% and 35%, respectively. Compared with the population pharmacokinetics in adults following cardiac surgery and when normalized for body weight, statistically significant differences were observed the parameters CL and V1 (35 vs 29 ml kg-1 min-1 and 0.78 vs 0.26 l kg-1P < 0.05), whereas the values for Q and V2 were similar (23 vs 18 ml kg-1 min-1 and 1.6 vs 1.8 l kg-1, P > 0.05). In children, the percentage of adequately sedated patients was similar compared with adults (50% vs 67%) despite considerably higher propofol concentrations (1.3 +/- 0.10 vs 0.51 +/- 0.035 mg l-1, mean +/- s.e. mean), suggesting a lower pharmacodynamic sensitivity to propofol in children. CONCLUSIONS: In children aged 1-5 years, a pharmacokinetic model for propofol was described using sparse data. In contrast to adults, body weight was a significant covariate for clearance in children. The model may serve as a useful basis to study the role of covariates in the pharmacokinetics and pharmacodynamics of propofol in paediatric patients of different ages.     

Population pharmacokinetics model and limited sampling strategy for intravenous vinorelbine derived from phase I clinical trials

AIMS: a) To characterize the pharmacokinetics of intravenous vinorelbine, b) to use a population analysis for the identification of patient covariates that might appreciably influence its disposition and c) to define a limited sampling strategy for further Bayesian estimation of individual pharmacokinetic parameters. METHODS: All data were collected from 64 patients (99 courses) entered in three different phase I trials that have been previously reported. All patients received vinorelbine as a 20 min infusion with dose levels ranging from 20-45 mg m-2. The population pharmacokinetic model was built in a sequential manner on a subset of two-thirds of the data, starting with a covariate-free model then progressing to a covariate model using the nonlinear-mixed effect methodology. The remaining one-third of the data were used to validate several sparse sampling designs. RESULTS: A linear three-compartment model characterized vinorelbine blood concentrations (n=1228). Two primary pharmacokinetic parameters (total clearance and volume of distribution) were related to various combinations of covariates. The relationship for total clearance (CLtotal (l h-1)=29.2xBSAx(1-0.0090 Plt)+6.7xWt/Crs) was dependent on the patient's body surface area (BSA), weight (Wt), serum creatinine (Crs) and platelet count before administration (Plt). The optimal limited sampling strategy consisted of a combination of three measured blood concentrations; the first immediately before the end of infusion or 20 min later, the second at either 1 h, 3 h or 6 h and the third at 24 h after drug administration. CONCLUSIONS: A population pharmacokinetic model and a limited sampling strategy for intravenous vinorelbine have been developed. This is the first population analysis performed on the basis of a large phase I database that has identified clinical covariates influencing the disposition of i.v. vinorelbine. The model can be used to obtain accurate Bayesian estimates of pharmacokinetic parameters in situations where extensive pharmacokinetic sampling is not feasable.     

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 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.     

Comparative population pharmacokinetics of lorazepam and midazolam during long-term continuous infusion in critically ill patients

AIMS: It is well established that there is a wide intra- and interindividual variability in dose requirements for lorazepam and midazolam in intensive care patients. The objective of this study was to compare the population pharmacokinetics of lorazepam and midazolam after long-term continuous infusion in mechanically ventilated critically ill patients. METHODS: Forty-nine critically ill patients randomly received either lorazepam (n = 28) or midazolam (n = 21) by continuous infusion for at least 24 h. Multiple blood samples were obtained for determination of the drug and metabolite concentrations by HPLC. Population pharmacokinetic models were developed using the Non-Linear Mixed Effect Modelling (NONMEM) program. The influence of selected covariates was investigated. The prospective performance of the models was evaluated on the basis of results in separate groups of patients for lorazepam (n = 31) and midazolam (n = 33). RESULTS: The pharmacokinetics of lorazepam were best described by a two-compartment model. Alcohol abuse, positive end expiratory pressure (PEEP) and age were identified as significant covariates. Total body clearance for patients without alcohol abuse was 4.13 - (PEEP - 5) x 0.42 l h-1, and 0.74 l h-1 for patients with alcohol abuse. The volume of distribution was 0.74 l, the steady state volume of distribution was 56 - (age - 58) x 2.1 l and the intercompartmental clearance was 10 l h-1. The proportional residual error was 15% and the median absolute prediction error was 13.6% with a bias of 1.5%. The pharmacokinetics of midazolam were best described by a two-compartment model with alcohol abuse, APACHE score and age as significant covariates. Total body clearance for patients without alcohol abuse was 11.3 - (age - 57) x 0.14 l h-1, and 7.27 - (age -57) x 0.14 l h-1 for patients with alcohol abuse. The volume of distribution was 7.15 l, the steady state volume of distribution was 431 l, and the intercompartmental clearance was 40.8 - (APACHE score - 26) x 2.75 l h-1. The proportional residual error was 31% with an additive residual error of 32 ng ml-1. The median absolute prediction error was 12.9% with a bias of 1.2%. The prospective performance in the lorazepam evaluation group was better with the covariate adjusted model, but in the midazolam evaluation group it was not better than with the simple model. In all models a tendency to overestimate the lower plasma concentrations was observed. CONCLUSIONS: The pharmacokinetics of both lorazepam and midazolam were well described by a two-compartment model. Inclusion of alcohol abuse and age as covariates improved both models. PEEP was identified as an additional covariate for lorazepam, and the APACHE score for midazolam. For both drugs there is a large interindividual variability in their pharmacokinetics when used for long-term sedation in critically ill patients. However, the intra-individual variability is much lower for lorazepam.     

A model for size and age changes in the pharmacokinetics of paracetamol in neonates, infants and children

AIMS: The aims of this study were to describe paracetamol pharmacokinetics in neonates and infants. METHODS: Infants in their first 3 months of life (n = 30) were randomised to sequentially receive one of three paracetamol formulations (dose 30-40 mg kg-1) over a 2 day period. The formulations were (a) elixir, (b) glycogelatin capsule suppository and (c) triglyceride base suppository. Approximately six blood samples were taken after each dose over the subsequent 10-16 h. Data were analysed using a nonlinear mixed effect model. These neonatal and infant data were then included with data from four published studies of paracetamol pharmacokinetics (n = 221) and age-related pharmacokinetic changes investigated. RESULTS: Population pharmacokinetic parameter estimates and their coefficients of variation (CV%) for a one compartment model with first order input, lag time and first order elimination were volume of distribution 69.9 (18%) l and clearance 13.0 (41%) l h-1 (standardized to a 70 kg person). The volume of distribution decreased exponentially with a half-life of 1.9 days from 120 l 70 kg-1 at birth to 69.9 l 70 kg-1 by 14 days. Clearance increased from birth (4.9 l h-1 70 kg-1) with a half-life of 3.25 months to reach 12.4 l h-1 70 kg-1 by 12 months. The absorption half-life (tabs) for the oral preparation was 0.13 (154%) h with a lag time (tlag) of 0.39 h (31%). Absorption parameters for the triglyceride base and capsule suppositories were tabs 1.34 (90%) h, tlag 0.14 h (31%) and tabs 0.65 (63%) h, tlag 0.54 h (31%), respectively. The tabs for elixir and capsule suppository in children under 3 months were 3.68 and 1.51 times greater than children over 3 months. The relative bioavailability of rectal formulations compared with elixir were 0.67 (30%) and 0.61 (23%) for the triglyceride base and capsule suppositories, respectively. CONCLUSIONS: Total body clearance of paracetamol at birth is 62% and volume of distribution 174% that of older children. A target concentration above 10 mg l-1 in approximately 50% subjects can be achieved by a dose from 45 mg kg-1 day-1 at birth and up to 90 mg kg-1 day-1 in 5-year-old children. A reduced dose of 75 mg kg-1 day-1 in an 8-year-old child is sufficient because clearance is a nonlinear function of weight.     

Population pharmacokinetics of doxorubicin, etoposide and ifosfamide in small cell lung cancer patients: results of a multicentre study

AIMS: To determine the population pharmacokinetic (PK) parameters of doxorubicin (Dox), etoposide (Eto) and ifosfamide (Ifo) in small cell lung cancer (SCLC) patients, to assess the potential relationship between those parameters and to estimate the impact of individual morphological and biological covariates on patients' PK parameters. METHODS: Twenty-four patients with either SCLC limited to the thorax or extensive SCLC entered the study. All but one received at least two 3 day courses of the standard AVI (Dox 50 mg m-2 day 1, Eto 120 mg m-2 day 1,2,3, Ifo 2000 mg m-2 day 1,2) regimen. Individual blood samples were collected during each course and data on 47 courses were available. Data were analysed with the NONMEM program. Dox, Eto and Ifo plasma concentrations were studied with multicompartment (3, 2 and 2, respectively) models. Inter-individual and interoccasion (course-to-course) variabilities were estimated. The influence of individual covariates (age, sex, stage of the disease, weight, height, body-surface area, serum creatinine, total protein, LDH, ASAT, ALAT, alkaline phosphatase, gamma-GT, bilirubin) on PK parameters was also assessed. Correlations between individual PK parameters of Dox, Eto and Ifo were explored by using Pearson's correlation coefficient. RESULTS: Multiple data were available for each patient. Dox clearance (CL) and volume of distribution (Vd) were 32.0 l h-1 and 9.3 l (Inter-individual variability: 17.2% and 19.2%). Eto CL (l h-1) and Vd were, respectively, 3.34-0.0083* serum creatinine (micromol l-1) and 6.38 l (interindividual variability: 15.6% and 18.7%). Ifo CL and Vd at day 1 were 5.6 l h-1 and 26.0 l (interindividual variability: 10.1% and 17.2%, respectively). Estimation of course-to-course variability improved the precision of PK models in some cases. No correlation was observed between the respective PK parameters of each drug. Of individual covariates tested, only serum creatinine correlated with Eto CL (r = -0.37, P < 0.001). Self-induction of the metabolism of Ifo was apparent (mean CL increase from day 1 to day 2 : 42%) and individually correlated with the CL value at day 1 (r = -0.61, P < 0.001). CONCLUSIONS: Assessment of potential relationships between individual systemic exposure of chemotherapy and therapeutic endpoints (tumour response, toxicity and survival) will be required to adjust drugs dosages based on individual PK parameters rather than questionable body-surface area. However, all three drugs in the AVI regimen should be monitored simultaneously.     

Pharmacokinetics of ceftazidime and cefepime in burn patients: the importance of age and creatinine clearance

AIM: The standard dosage recommendations for beta-lactam antibiotics can result in very low drug levels in intensive care (IC) patients and burn patients in the absence of renal dysfunction. We studied the pharmacokinetic parameters and serum concentrations of ceftazidime (CF) and cefepime (CE) in burn patients and analyzed the modifications according to clinical and biological parameters and in particular age and creatinine clearance. MATERIAL AND METHODS: Two pharmacokinetic studies were carried out with daily doses of 1 g x 6 for CF (n = 17) and 2 g x 3 for CE (n = 13). Creatinine clearance (CL(CR)) was both estimated and measured. Blood was sampled at steady state after an initial and a subsequent antibiotic dose. C(max) (maximal) and C(min) (minimal) concentrations were measured by HPLC. The influence of clinical and biological data was analyzed using ANOVA, ANCOVA and stepwise multiple linear regression. RESULTS: The ratio of C(min) to the low MIC break point (4 mg/l) was lower than 4 in 52% of subjects receiving CF and in 80% of subjects receiving CE. The C(min) of CF was correlated with measured CL(CR) and was higher in mechanically ventilated patients than in non-ventilated patients. The clearance of CF was correlated with age. The C(min) of CE was correlated with age and drug clearance with measured CL(CR). Therefore dosage adjustment of these drugs in burn patients needs to take into account age, measured creatinine clearance and the danger of low concentrations occurring when the creatinine clearance is greater than 120 ml x min(-1). CONCLUSION: In burn patients, the pharmacokinetic disposition of CF and CE was much more variable than in healthy subjects. Age and CL(CR) were predictors of the disposition of these antibiotics. Shortening the dosage interval or using continuous infusions will prevent low serum levels and keep trough levels above the MIC for longer periods of time. In view of the lack of a bedside measurement technique for ceftazidime and cefepime levels, we suggest a more frequent use of measured CL(CR) in order to attain efficacious clinical concentrations.     

Comparison of propranolol and sotalol pharmacokinetics in obese subjects

Six obese subjects (mean +/- s.d. : 145.1 +/- 16.7% of ideal body weight) were randomly assigned to a single i.v. dose either of (+/-)-propranolol base (0.108 mg kg-1 of ideal body weight) or of (+/-)-sotalol base (1.06 mg kg-1 of ideal body weight). Each subject received the other drug 7 days later. Pharmacokinetic parameters were compared with those obtained previously in non-obese control subjects. In obese subjects, the pharmacokinetic data calculated for sotalol were comparable with those measured in controls (total body clearance = 9.4 +/- 2.9 L h-1; volume of distribution during the terminal phase = 79.8 +/- 19.8 L or 0.9 +/- 0.2 L kg-1; terminal half-life = 6.2 +/- 1.6 h). For propranolol, total clearance (44.3 +/- 15.9 L h-1) and volume of distribution (230.5 +/- 48.2 L or 2.7 +/- 0.7 L kg-1) were significantly less than control values. The terminal half-life (3.9 +/- 1.1 h), was not significantly increased. These results could be explained by altered tissue blood flow and a decreased metabolic capacity of the liver in obese subjects.     

Population pharmacokinetics of quinidine.

1. Population pharmacokinetic parameters of quinidine were determined based on 260 serum drug concentration measurements in 60 patients treated for arrhythmias with quinidine sulphate or quinidine bisulphate (Kinidin duriles) orally. 2. Quinidine kinetics were best described by a two compartment model with zero order absorption from the gastrointestinal tract. The pharmacokinetics are influenced by severe heart or liver failure and renal function impairment. No effect was found for mild or moderate heart failure, for age, for body weight or for coadministration of nifedipine. 3. Population pharmacokinetic parameters of quinidine (assuming 100% bioavailability of oral quinidine sulphate) were: nonrenal clearance for patients without severe heart and liver failure 12.6 l h-1, reduction in patients with severe heart or liver failure to 6.8 l h-1, renal clearance (l h-1) related to creatinine clearance (ml min-1), proportionality constant 0.0566, volume of distribution of the central compartment 161 l, maximum serum drug concentration 1.4 h after administration of quinidine sulphate and 6.0 h after administration of quinidine bisulphate. 4. The results were validated by predicting the serum drug concentration in a separate group of 30 patients. The model reliably predicted both the population average and the variability of the serum concentration of quinidine. 5. Using Monte Carlo computer simulations, an a priori dosing regimen was derived that should maximize the proportion of patients having quinidine serum concentrations within the recommended range (2-5 mg l-1): initial dose of 600 mg quinidine sulphate in all patients, 3 h later first maintenance dose of quinidine bisulphate.(ABSTRACT TRUNCATED AT 250 WORDS)     

Pharmacokinetic-pharmacodynamic evaluation of ceftazidime continuous infusion vs intermittent bolus injection in septicaemic melioidosis

AIMS: Experimental studies have suggested that constant intravenous infusion would be preferable to conventional intermittent bolus administration of beta-lactam antibiotics for serious Gram-negative infections. Severe melioidosis (Burkholderia pseudomallei infection) carries a mortality over 40% despite treatment with high dose ceftazidime. The aim of this study was to measure the pharmacokinetic and pharmacodynamic effects of continuous infusion of ceftazidime vs intermittent bolus dosing in septicaemic melioidosis. METHODS: Patients with suspected septicaemic melioidosis were randomised to receive ceftazidime 40 mg kg(-1) 8 hourly by bolus injection or 4 mg kg(-1) h(-1) by constant infusion following a 12 mg kg(-1) priming dose and pharmacokinetic and pharmacodynamic parameters were compared. RESULTS: Of the 34 patients studied 16 (59%) died. Twenty patients had cultures positive for B. pseudomallei of whom 12 (60%) died. The median MIC90 of B. pseudomallei was 2 mg l(-1), giving a minimum target concentration (4*MIC) of 8 mg l(-1). The median (range) estimated total apparent volume of distribution, systemic clearance and terminal elimination half-lives of ceftazidime were 0.468 (0.241-0. 573) l kg(-1), 0.058 (0.005-0.159) l kg(-1) h(-1) and 7.74 (1.95-44.71) h, respectively. Clearance of ceftazidime and creatinine clearance were correlated closely (r = 0.71; P < 0.001) and there was no evidence of significant nonrenal clearance. CONCLUSIONS: Simulations based on these data and the ceftazidime sensitivity of the B. pseudomallei isolates indicated that administration by constant infusion would allow significant dose reduction and cost saving. With conventional 8 h intermittent dosing to patients with normal renal function, plasma ceftazidime concentrations could fall below the target concentration but this would be unlikely with a constant infusion. Correction for renal failure, which is common in patients with meliodosis is Clearance = k(*) creatinine clearance where k = 0.72. Calculation of a loading dose gives median (range) values of loading dose, DL of 18.7 mg kg(-1) (9.5-23) and infusion rate I = 3.5 mg k(-1) h(-1) (0.4-13) (which equals 84 mg kg(-1) day(-1)). A nomogram for adjustment in renal failure is given.     

Population pharmacokinetics of olmesartan following oral administration of its prodrug, olmesartan medoxomil: in healthy volunteers and hypertensive patients

BACKGROUND: Olmesartan medoxomil (CS-866) is a new orally active angiotensin II receptor antagonist that is highly selective for the AT1 receptor subtype. OBJECTIVE: To develop a population pharmacokinetic model for olmesartan (RNH-6270), the active metabolite of olmesartan medoxomil, in healthy volunteers and hypertensive patients, and to evaluate effects of covariates on the apparent oral clearance (CL/F), with particular emphasis on the effect of race. DESIGN: Retrospective analysis of data from 12 phase I-III trials in the US, Europe and Japan. PARTICIPANTS: Eighty-nine healthy volunteers and 383 hypertensive patients. METHODS: Nonlinear mixed-effects modelling was used to evaluate 7911 olmesartan plasma sample concentrations. The covariates included age, bodyweight, sex, race (Westerners [including Caucasians and Hispanics] versus Japanese), patient status (hypertensive patients versus healthy volunteers), serum creatinine level as an index of renal function and serum chemistry data as indices of hepatic function. RESULTS: The pharmacokinetic data of olmesartan were well described by a two-compartment linear model with first-order absorption and an absorption lag-time, parameterised in terms of CL/F (6.66 L/h for a typical male Western hypertensive patient), absorption rate constant (1.46h-1), elimination rate constant (0.193h-1), rate constant from the central to peripheral compartment (0.061h-1), rate constant from the peripheral to central compartment (0.079h-1) and absorption lag-time (0.427h). Analysis of covariates showed that age, bodyweight, sex, patient status and renal function were factors influencing the clearance of olmesartan. CONCLUSION: The population pharmacokinetic analysis of olmesartan showed that: (i) severe renal impairment (serum creatinine >265 micromol/L [approximately 3 mg/dL]) could cause a clearance decrease of > or =30%; (ii) older age, lower bodyweight and being female were determinants of lower clearance but their effects on olmesartan clearance were within 20%; (iii) no statistically significant difference in clearance was found between Westerners and Japanese.     

Quantitative justification for target concentration intervention--parameter variability and predictive performance using population pharmacokinetic models for aminoglycosides

AIMS: [1] To quantify the random and predictable components of variability for aminoglycoside clearance and volume of distribution [2] To investigate models for predicting aminoglycoside clearance in patients with low serum creatinine concentrations [3] To evaluate the predictive performance of initial dosing strategies for achieving an aminoglycoside target concentration. METHODS: Aminoglycoside demographic, dosing and concentration data were collected from 697 adult patients (> or =20 years old) as part of standard clinical care using a target concentration intervention approach for dose individualization. It was assumed that aminoglycoside clearance had a renal and a nonrenal component, with the renal component being linearly related to predicted creatinine clearance. RESULTS: A two compartment pharmacokinetic model best described the aminoglycoside data. The addition of weight, age, sex and serum creatinine as covariates reduced the random component of between subject variability (BSVR) in clearance (CL) from 94% to 36% of population parameter variability (PPV). The final pharmacokinetic parameter estimates for the model with the best predictive performance were: CL, 4.7 l h(-1) 70 kg(-1); intercompartmental clearance (CLic), 1 l h(-1) 70 kg(-1); volume of central compartment (V1), 19.5 l 70 kg(-1); volume of peripheral compartment (V2) 11.2 l 70 kg(-1). CONCLUSIONS: Using a fixed dose of aminoglycoside will achieve 35% of typical patients within 80-125% of a required dose. Covariate guided predictions increase this up to 61%. However, because we have shown that random within subject variability (WSVR) in clearance is less than safe and effective variability (SEV), target concentration intervention can potentially achieve safe and effective doses in 90% of patients.     

Pharmacokinetics of cefoxitin in patients with normal or impaired renal function

The pharmacokinetics of cefoxitin have been determined after a single i.v. injection of 15 mg/kg body weight in 10 patients with normal renal function and 20 patients with varying degrees of renal impairment. The kinetics of the antibiotic followed an open two-compartment model. In patients with normal renal function the following pharmacokinetic parameters were found: alpha = 8.66 h-1 beta = 1.21 h-1 K12 = 3.47 h-1 K21 = 3.17 h-1 K13 = 3.15 h-1 Vc = 4.24 l. Vp = 4.87 l. Vdss = 9.11 l. In the patients with renal impairment there was a significant decrease in alpha, beta, K12, K21 and K13, and an increase in the apparent volume of distribution. The degree of plasma protein binding in patients with normal renal function was 73.6% and this was diminished in patients with renal impairment. A linear relationship between K13 of cefoxitin and creatinine clearance was demonstrated. The dosage regimen for patients with renal impairment should be adjusted by modifying the dosage interval whilst maintaining the amount administered.     

The pharmacokinetics of high dose metoclopramide in patients with neoplastic disease.

High dose metoclopramide infusions (10 mg/kg) were administered to nineteen patients with bronchial carcinoma who were receiving intravenous cyclophosphamide as single agent chemotherapy. Considerable interindividual variability in metoclopramide disposition was observed. Mean clearance was 0.33 +/- 0.13 (s.d.) l h-1 kg-1, mean volume of distribution at steady state was 3.8 +/- 1.2 (s.d.) l/kg and mean elimination half-life was 8.3 +/- 4.4 (s.d.) h. These results were significantly different from mean values previously reported for young healthy volunteers given conventional doses (0.70 l h-1 kg-1, 2.2 l/kg and 2.6 h respectively). Significant correlations were found between serum urea, serum creatinine and metoclopramide clearance. The metoclopramide regimens were well tolerated and, with the exception of two patients, were completely effective in the prevention of nausea and vomiting. To achieve and maintain target serum metoclopramide concentrations of 1 microgram/ml, we now administer a loading infusion of 3.61 mg/kg over 30 min followed by a maintenance infusion of 0.36 mg kg-1 h-1 for 10 h. Cyclophosphamide is normally administered concurrently with the second infusion. For patients with evidence of mild renal impairment, the maintenance infusion rate of metoclopramide hydrochloride should be adjusted according to the predicted individual clearance value; CL (l h-1 kg-1) = 0.57 - [0.036 X urea (mmol/l)].     

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 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.