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

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

Population pharmacokinetics of total and unbound plasma cisplatin in adult patients

AIMS: To investigate the pharmacokinetics of unbound (ultrafilterable) and total plasma platinum using a population approach and to identify patient characteristics that may influence the disposition of the drug. METHODS: Pharmacokinetic and demographic data were collected from adult patients treated with 30-min daily infusions of cisplatin for various malignancies. Unbound and total platinum concentration-time data were analysed using a nonlinear mixed effects model. RESULTS: Data from 43 patients were available for analysis. A linear two-compartment model best described total and unbound platinum plasma concentration-time data. The mean population estimates for total and unbound drug were, respectively, 0.68 and 35.5 l h(-1) for clearance and 21.1 and 23.4 l for central distribution volume (V(1)). Unbound clearance (CL) was dependent on body surface area (BSA) and creatinine clearance, and V(1) was dependent on BSA. The elimination rate constant for plasma-bound platinum (modelled as metabolite formation) was 0.014 h(-1). The pharmacokinetic parameter, f(m)/V(m), a measure of the clearance of unbound platinum due to irreversible plasma binding, was related to serum protein concentration and to the inverse of dose per m(2). The covariate modelling of CL, V(1) and f(m)/V(m) improved the intersubject variabilities associated with these parameters. The final pharmacokinetic models were validated using 200 bootstrap samples from the original datasets. CONCLUSIONS: The results support the conventional dose adjustment of cisplatin based on BSA. They also support the need for a dose reduction in case of renal insufficiency.     

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.     

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.     

Memantine pharmacotherapy: a naturalistic study using a population pharmacokinetic approach

BACKGROUND AND OBJECTIVE: Memantine plasma concentrations show considerable interindividual variability. High memantine plasma concentrations are associated with the occurrence of neuropsychiatric adverse effects such as confusion. The objective of the present study was, therefore, to investigate the reasons for the observed variability of the pharmacokinetics of memantine in a representative patient population and to explore patient covariates on drug disposition. SUBJECTS: Fifty-six ambulatory Western European patients aged 50-91 years. METHODS: This prospective study used a full population pharmacokinetic sampling design. After at least 11 days of continuous memantine intake, the patients provided pharmacokinetic profiles, with six measurements each over a 12-hour period, with a total of 335 serum memantine concentrations. Covariates considered for inclusion in the models were: subject demographic factors (age, total bodyweight, gender), laboratory tests (urinary pH), total daily dose of memantine, memantine formulation type, comedication eliminated via tubular secretion and smoking history. The model development was conducted in three sequential steps. First, an adequate basic structural model was chosen (e.g. a one-, two- or three-compartment pharmacokinetic model). The data were analysed to estimate population pharmacokinetic parameters with the nonlinear mixed-effects model computer program NONMEM. Second, the effects of covariates were investigated on post hoc estimates using multivariate statistics. Third, the covariates with significant effects in the second step were used to build a final covariate pharmacokinetic model, again using NONMEM. RESULTS: A two-compartment model with first-order absorption satisfactorily described memantine pharmacokinetics. In the final regression model, total bodyweight, memantine formulation type (solution vs tablets) and concomitant medication eliminated via tubular secretion were all important determinants of the apparent clearance (CL/F). The final regression model was: CL/F (L/h) = (1.92 + 0.048 x BW (kg)) x 0.530(FRM) x 0.769(CMD) where FRM = 1 for patients receiving memantine solution, otherwise FRM = 0; CMD = 1 for patients receiving a comedication eliminated via tubular secretion, otherwise CMD = 0; and BW is bodyweight. Compared with the basic model, the final population pharmacokinetic model explained 61% of the interindividual variance of the apparent clearance. CONCLUSIONS: The population pharmacokinetic model that was developed identified a set of sources of variability in the apparent clearance of memantine, which can be used as a reference in order to optimise memantine therapy in Western European patients.     

中药复方冠心Ⅱ的群体药物动力学研究

目的:以群体药物动力学原理分析复方冠心Ⅱ不同组成条件对主要组分芍药苷及阿魏酸体内过程的影响。方法:将大鼠随机分组后分别静脉注射芍药苷(PPE)或阿魏酸(FA)提取物水溶液、灌胃给予PPE或FA水溶液及不同组成的水煎液,HPLC法测定血浆中芍药苷和阿魏酸浓度,以非线性混合效应模型(NONMEM)法分别对芍药苷和阿魏酸的血药浓度数据进行群体药物动力学解析。结果:芍药苷的体内药物动力学过程可用吸收相包含一级降解过程的二室口服吸收模型进行表述,参数CL1、V1、CL2、V2、Ka0和Ka1分别为0.509 L/h, 0.104 L,0.113 L/h,0.123 L,0.135/h及0.0135/h;阿魏酸的体内过程可用二室口服吸收模型表述,参数CL1、V1、CL2、V2,、Ka及F分别为0.295 L/h、0.025 L、0.0331 L/h、0.0518 L、0.110/h及0.40。模型化中对个体间差异进行了估计,并以给药组方因素(DF)作为固定效应对参数进行了校正。结论:群体药物动力学方法可以用于分析中药复方冠心Ⅱ中组方变化对其中指标成分的体内吸收和分布产生的影响,较以往的方法有一定的优越性。     

Population pharmacokinetic modeling for enterohepatic recirculation in Rhesus monkey.

Enterohepatic recirculation (EHR) occurs via biliary excretion and intestinal reabsorption of a drug. Drug recycling through EHR can lead to a change in pharmacokinetic (PK) properties, such as reduced clearance (CL), extended half-life (T(1/2)) and increased plasma exposure (AUC). As a result, EHR may prolong the pharmacological effect of drugs. In the present study, the compound (Cpd A) was found to exhibit EHR in Rhesus monkeys associated with a reduction in CL (from 3.8 to 0.33 Lh(-1), IV; from 2.3 to 0.4 Lh(-1), PO), and an increase in T(1/2) (from 0.9 to 18 h, IV) and in AUC (from 1.5 to 17.4 microg h/mL, IV; from 2.8 to 16.3 microg h/mL, PO), by comparing the PK in the monkeys via the interruption of EHR (bile-duct cannulation) with that in the intact monkeys. A population four-compartment model was constructed based on recirculation loops incorporating all possible inputs (bile secretion, a lag-time model for gall bladder emptying, routes and amounts of a single dose administration) to fully evaluate the EHR of Cpd A. The plasma concentrations versus time profiles predicted from the model had a good fit to the values observed in the subjects and were further simulated with 90% confidence interval to demonstrate its utility. Thus, the model could be applied as a useful tool to evaluate the drugs or compounds that undergo EHR in different species.     

Weight related differences in the pharmacokinetics of abacavir in HIV-infected patients

AIM: To study the possible influence of patient characteristics on abacavir pharmacokinetics. METHODS: A population pharmacokinetic model for abacavir was developed using data from 188 adult patients by the use of a nonlinear mixed effects modelling method performed with NONMEM. RESULTS: Abacavir pharmacokinetics was well described by a two-compartment open model with linear absorption and elimination. Typical population estimates for the absorption rate constant (Ka), the apparent central distribution volume (Vc/F), the apparent peripheral distribution volume (Vp/F), the apparent intercompartmental clearance (Q/F) and the apparent plasma clearance (CL/F) were 1.8 h(-1), 75 l, 23.6 l, 10 l h(-1) and 47.5 l h(-1), respectively. Apparent plasma clearance was positively related to bodyweight. Individual Bayesian estimates of CL/F were used to calculate abacavir AUC. The latter decreased from 10.7 +/- 5.0 to 5.7 +/- 1.6 mgh l(-1) when bodyweight increased from 36 to 102 kg. This drop in abacavir exposure could lead to suboptimal treatment for the heaviest patients, as antiviral efficacy of abacavir is known to be related to its AUC. A 400 mg abacavir dose would be necessary to achieve adequate exposure to abacavir in patients weighing more than 60 kg. CONCLUSIONS: The apparent plasma clearance of abacavir was positively related to bodyweight. The efficacy of the current recommended abacavir dosage for patients with high bodyweight should be evaluated in further studies.     

Population pharmacokinetics of doxorubicin in Indian cancer patients using NONMEM

The population pharmacokinetics of doxorubicin were evaluated based on a mixed-effect model using the NONMEM (VI) program. Doxorubicin in plasma was measured using high-performance liquid chromatography. Plasma concentration measurements (85 plasma samples) of doxorubicin from 28 patients with cancer receiving doxorubicin (with other co-medication) ranging from 20–120?mg by infusion over 1–2?h were analyzed according to a two-compartment model both in FO and FOCE methods. Additive proportional error model was used to describe inter-individual and residual variability. The influence of covariates such as age, body surface area, gender, and clinical laboratory values (SGOT, SGPT) on total body clearance (CL) and volume of distribution (Vd) were examined. No covariate was found to affect the CL and Vd of unchanged doxorubicin. The CL and Vd estimated by FO method were 1.42?L/h and 51.1?L, respectively, and FOCE method are 1.43?L/h and 51.4?L, respectively. The inter-individual variability for CL and Vd and residual variability were 45.8%, 36%, and 12.6%, respectively. The population means and inter-individual and residual variability of pharmacokinetics of doxorubicin were evaluated using the NONMEM program. The results of this study show that the population pharmacokinetic approach could be useful to manage doxorubicin cardio toxicity using sparse data in a clinical setting.     

Pharmacokinetic modelling of total and unbound plasma carboplatin--a population study in 75 children

AIMS: A compartmental open model was developed to describe the relationship between plasma unbound (C.) and bound (CT) carboplatin concentrations. A population pharmacokinetic study was then undertaken to investigate the effect of demographic covariates on unbound and bound carboplatin clearance and volume parameters. METHODS: Carboplatin and demographic data were collected from 75 children (1-17 years old, 10 children with unilateral nephrectomy) treated using 1-hour daily infusions for various malignancies. Concentration-time data, C(U) and C(T), from children with rich data were used to develop the model. The data from all children were then simultaneously analyzed using a population approach. RESULTS: The average population values for total unbound carboplatin clearance, CL(U), and distribution volume of unbound carboplatin, VI, were 3.87 l/h and 6.26 l/h, respectively. The clearance of plasma-bound carboplatin was comparatively low, 0.11 l/h. CL(U) was dependent on weight, nephrectomy status and serum creatinine. A constant fraction of CL(U), 0.17 l/h, included the disappearance of unbound compound due to irreversible plasma binding. V1 was dependent on body weight. The unbound plasma carboplatin fraction (fu) was simulated and rapidly decreased with post-infusion time. CONCLUSIONS: The body weight was a better predictor for unbound carboplatin clearance than body surface area, and UNP and SCr caused a reduction in clearance of unbound carboplatin, as previously reported. The rate ofcarboplatin plasma binding was low and not dependent on demographic patient characteristics. The f(U) of plasma carboplatin could be predicted as a function of time, infusion rate and covariates affecting CL(U), weight, UNP and SCr.     

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.     

Population pharmacokinetic modelling and estimation of dosing strategy for NXY-059, a nitrone being developed for stroke

BACKGROUND AND OBJECTIVES: NXY-059 (disufenton sodium, Cerovive, a nitrone with neuroprotective and free radical trapping properties (in experimental stroke) is under development for the treatment of acute stroke. The objectives of this study were to develop a population pharmacokinetic model for NXY-059 in acute stroke patients and to estimate individualised dosing strategies for NXY-059 using preclinical pharmacological and clinical pharmacokinetic information and knowledge of characteristics of the patient population. METHODS: NXY-059 was given as a continuous intravenous infusion for 72 hours, including a 1-hour loading infusion. Maintenance infusion rates were individualised based on creatinine clearance (CL(CR)). Population pharmacokinetic models were derived using NONMEM software. Optimal dosing strategies, individualised based on CL(CR) or bodyweight, were estimated using the population pharmacokinetic models, empirical covariate distributions relevant for the target population, and a target definition. Dosing strategies were selected based on target fulfillment criteria and parsimony. PATIENTS: Pharmacokinetic data from 179 patients with acute ischaemic or haemorrhagic stroke, included in two clinical studies, were used for the analyses. Patients were aged 34-92 years with varying degrees of renal impairment (estimated CL(CR) 20-143 mL/min). MAIN OUTCOME MEASURES AND RESULTS: The final population model based on data from both studies comprised a two-compartment model with unexplained interpatient variability for clearance (23% coefficient of variation [CV]) and central volume of distribution (40% CV). Part of the variability in clearance and volume of distribution was explained by CL(CR) and bodyweight, respectively. Typical clearance was estimated to 4.54 L/h in a patient with CL(CR) of 70 mL/min. The preferred dosing strategy for NXY-059 comprised an initial loading infusion (the same for all patients) followed by an individualised maintenance infusion on the basis of CL(CR) (three dosing categories) with cut-off values (at which infusion rates are incremented or decremented) of 50 and 80 mL/min. CONCLUSION: The results illustrate how an individualised dosing strategy, given a pharmacokinetic target, for NXY-059 was successfully optimised through estimation using the increasing pharmacokinetic and pharmacodynamic knowledge during a clinical drug development programme. The chosen dosing strategy of NXY-059 provides an easily adapted treatment regimen for acute stroke, resulting in early achievement of target plasma concentrations.     

Population pharmacokinetics of meropenem in critically ill patients undergoing continuous renal replacement therapy

BACKGROUND AND OBJECTIVE: Meropenem is a carbapenem antibacterial frequently prescribed for the treatment of severe infections in critically ill patients, including those receiving continuous renal replacement therapy (CRRT). The objective of this study was to develop a population pharmacokinetic model of meropenem in critically ill patients undergoing CRRT. PATIENTS AND METHODS: A prospective, open-label study was conducted in 20 patients undergoing CRRT. Blood and dialysate-ultrafiltrate samples were obtained after administration of 500 mg, 1000 mg or 2000 mg of meropenem every 6 or 8 hours by intravenous infusion. The data were analysed under the population approach using NONMEM version V software. Age, bodyweight, dialysate plus ultrafiltrate flow, creatinine clearance (CL(CR)), the unbound drug fraction in plasma, the type of membrane, CRRT and the patient type (whether septic or severely polytraumatized) were the covariates studied. RESULTS: The pharmacokinetics of meropenem in plasma were best described by a two-compartment model. CL(CR) was found to have a significant correlation with the apparent total clearance (CL) of the drug during the development of the covariate model. However, the influence of CL(CR) on CL differed between septic and polytraumatized patients (CL = 6.63 + 0.064 x CL(CR) for septic patients and CL = 6.63 + 0.72 x CL(CR) for polytraumatized patients). The volume of distribution of the central compartment (V(1)) was also dependent on the patient type, with values of 15.7 L for septic patients and 69.5 L for polytraumatized patients. The population clearance was 15 L/h, and the population apparent volume of distribution of the peripheral compartment was 19.8 L. From the base to the final model, the interindividual variabilities in CL and the V(1) were significantly reduced. When computer simulations were carried out and efficacy indexes were calculated, it was shown that polytraumatized patients and septic patients with conserved renal function may not achieve adequate efficacy indexes to deal with specific infections. Continuous infusion of meropenem is recommended for critically septic patients and polytraumatized patients when pathogens with a minimum inhibitory concentration (MIC) of > or =4 mg/L are isolated. Infections caused by pathogens with an MIC of > or =8 mg/L should not be treated with meropenem in polytraumatized patients without or with moderate renal failure because excessive doses of meropenem would be necessary. CONCLUSION: A population pharmacokinetic model of meropenem in intensive care patients undergoing CRRT was developed and validated. CL(CR) and the patient type (whether septic or polytraumatized) were identified as significant covariates. The population pharmacokinetic model developed in the present study has been employed to recommend continuous infusion protocols in patients treated with CRRT.     

Time-dependent clearance of mycophenolic acid in renal transplant recipients

AIMS: Pharmacokinetic studies of the immunosuppressive compound mycophenolic acid (MPA) have shown a structural decrease in clearance (CL) over time after renal transplantation. The aim of this study was to characterize the time-dependent CL of MPA by means of a population pharmacokinetic meta-analysis, and to test whether it can be described by covariate effects. METHODS: One thousand eight hundred and ninety-four MPA concentration-time profiles from 468 renal transplant patients (range 1-9 profiles per patient) were analyzed retrospectively by nonlinear mixed effect modelling. Sampling occasions ranged from day 1-10 years after transplantation. RESULTS: The pharmacokinetics of MPA were described by a two-compartment model with time-lagged first order absorption, and a first-order term for time-dependent CL. The model predicted the mean CL to decrease from 35 l h(-1) (CV = 44%) in the first week after transplantation to 17 l h(-1) (CV = 38%) after 6 months. In a covariate model without a term for time-dependent CL, changes during the first 6 months after transplantation in creatinine clearance from 19 to 71 ml min(-1), in albumin concentration from 35 to 40 g l(-1), in haemoglobin from 9.7 to 12 g dl(-1) and in cyclosporin predose concentration from 225 to 100 ng ml(-1) corresponded with a decrease of CL from 32 to 19 l h(-1). Creatinine clearance, albumin concentration, haemoglobin and cyclosporin predose concentration explained, respectively, 19%, 12%, 4% and 3% of the within-patient variability in MPA CL. CONCLUSIONS: By monitoring creatinine clearance, albumin concentration, haemoglobin and cyclosporin predose concentration, changes in MPA exposure over time can be predicted. Such information can be used to optimize therapy with mycophenolate mofetil.     

Population pharmacokinetics of tobramycin.

1. Population pharmacokinetic parameters of tobramycin were determined in a heterogenous group of 97 patients using serum samples drawn for the routine monitoring of tobramycin concentrations, following multiple dosing regimens. 2. To describe the accumulation kinetics of tobramycin a two-compartment pharmacokinetic model was required. The best fit to the data was obtained when drug clearance (1 h-1) was related linearly to creatinine clearance (proportionality constant: 0.059 +/- 0.002 x CLcr (ml min-1)) and initial volume of distribution (1) was related linearly to body weight (proportionality constant: 0.327 +/- 0.014 x body weight (kg)). The intersubject variability in these two parameters was 32% and 3%, respectively, whilst the residual or intrasubject variability amounted to 21% of the tobramycin concentration. The terminal half-life of tobramycin, 26.6 +/- 9.4 h, was appreciably shorter than previously reported. 3. The population pharmacokinetic model was validated against data obtained from 34 independent patients and the predicted and observed concentrations were found to be in good agreement. The population pharmacokinetic model was used to design a priori dosing recommendations for tobramycin.     

A population pharmacokinetic study of tacrolimus in healthy Chinese volunteers and liver transplant patients

Aim:

To develop a population pharmacokinetic (PopPK) model of tacrolimus in healthy Chinese volunteers and liver transplant recipients for investigating the difference between the populations, and for potential individualized medication.

Methods:

A set of 1100 sparse trough concentration data points from 112 orthotopic liver transplant recipients, as well as 851 dense data points from 40 healthy volunteers receiving a single dose of tacrolimus (2 mg, po) were collected. PopPK model of tacrolimus was constructed using the program NONMEM. Related covariates such as age, hepatic and renal functions that were potentially associated with tacrolimus disposition were evaluated. The final model was validated using bootstrapping and a visual predictive check.

Results:

A two-compartment model of tacrolimus could best describe the data from the two populations. The final model including two covariates, population (liver transplant recipients or volunteers) and serum ALT (alanine aminotransferase) level, was verified and adequately described the pharmacokinetic characteristics of tacrolimus. The estimates of V2/F, Q/F and V3/F were 22.7 L, 76.3 L/h and 916 L, respectively. The estimated CL/F in the volunteers and liver transplant recipients was 32.8 and 18.4 L/h, respectively. Serum ALT level was inversely related to CL/F, whereas age did not influence CL/F. Thus, the elderly (≥65 years) and adult (<65 years) groups in the liver transplant recipients showed no significant difference in the clearance of tacrolimus.

Conclusion:

Compared with using the sparse data only, the integrating modeling technique combining sparse data from the patients and dense data from the healthy volunteers improved the PopPK analysis of tacrolimus.     

Population pharmacokinetics of oxaliplatin (85 mg/m2) in combination with 5-fluorouracil in patients with advanced colorectal cancer

Pharmacokinetic (PK) studies of oxaliplatin, using a dose regimen of 85 mg/m, are lacking. A PK model may be used in future studies to investigate the relationship between pharmacokinetics and dose limiting toxicity. The purpose of this study was to construct a population PK model to describe platinum (Pt) concentrations in plasma in 33 patients with colorectal cancer. The secondary objective was to determine the relationship between the amount of Pt in 24-hour urine and the amount of Pt in fractionated urine collection periods. Plasma and urine samples were collected from patients during their first oxaliplatin treatment course. Population PK analysis was performed with WinNonMix. The model that best described the Pt concentrations in plasma was a two-compartment PK model. The elimination clearance (CL) and the elimination clearance of the peripheral compartment (CL2) (median +/- SE) were 25.2 +/- 6.3 L/hr and 68 +/- 24.8 L/hr, respectively. The median volume of distribution (V1) was determined to be 41.6 +/- 9.4 L and the median volume of distribution of the peripheral compartment (V2) was 452.5 +/- 96.4 L. The relationship between the cumulative amount of Pt in urine in the first 12 hours compared with the amount of Pt in 24 hours urine was reflected by a correlation coefficient (r2) of 0.95. The cumulative Pt concentration in urine in the first 10 hours and the first 8 hours compared with 24 hours was reflected by correlation coefficients r2 = 0.93 and r2 = 0.897, respectively. This PK model could be useful in identifying predictors for PK and pharmacodynamic variability to individualize dosing. The results of this study suggest that fractionated urine samples can replace 24-hour urine collection.