Pharmacokinetic modeling of valproate from clinical data in Serbian epileptic patients

The aim of this study was to define a population pharmacokinetic model that could estimate the clearance of valproate (VPA) in a Serbian epileptic population. For the analysis, 97 steady-state concentrations of VPA were used, collected from 93 patients with epilepsy during routine clinical care in our hospital. To build a final model, we selected the ADVAN1 program subroutine from the NONMEM library for estimating the drug clearance (CL) and determining the influence of different covariates. This is a one-compartment model with first-order elimination and without absorption. Estimation of the predictive performances of the final model was performed on a validation set consisting of 20 epileptic patients. Typical mean value of CL of VPA estimated by the base model in our population was 0.368 l h(-1). The results of the final model show that the CL of VPA increased linearly with total body weight (TBW) and patients' age, while carbamazepine (CBZ) comedication did not affect it significantly. Interindividual variability (coefficient of variation) for CL was 27.2%. Residual error, including intraindividual variability, was 29.68%. The results of the validation process and the analysis of prediction errors suggest a good predictive performance of the final population model. The defined model describes CL of VPA in terms of specific Serbian patient characteristics, using serum concentration data obtained from routine therapeutic drug monitoring.     

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 lamotrigine with data from therapeutic drug monitoring in German and Spanish patients with epilepsy

This study develops a population pharmacokinetic model for lamotrigine (LTG) in Spanish and German patients diagnosed with epilepsy. LTG steady-state plasma concentration data from therapeutic drug monitoring were collected retrospectively from 600 patients, with a total of 1699 plasma drug concentrations. The data were analyzed according to a one-compartment model using the nonlinear mixed effect modelling program. The influences of origin (Germany or Spain), sex, age, total body weight, and comedication with valproic acid (VPA), levetiracetam, and enzyme-inducing antiepileptic drugs (phenobarbital [PB], phenytoin [PHT], primidone [PRM], and carbamazepine [CBZ]) were investigated using step-wise generalized additive modelling. The final regression model for LTG clearance (CL) was as follows: CL(L/h) = 0.028*total body weight*e(-0.713*VPA)*e0.663*PHT*e0.588*(PB or PRM)*e0.467*CBZ*e0.864*IND, where IND refers to two or more inducers added to LTG treatment; this factor as well as VPA, PHT, PB, PRM, and CBZ take a value of zero or one according to their absence or presence, respectively. The administration of inducers led to a significant increase in mean LTG CL (values of 0.045-0.070 L/h/kg vs. 0.028 L/h/kg being reached in monotherapy), whereas VPA led to a significant decrease in CL (0.014 L/h/kg). Thus, comedication with these analyzed drugs can partly explain the interindividual variability in population LTG CL, which decreased from the basic model by more than 40%. The proposed model may be very useful for clinicians in establishing initial LTG dosage guidelines. However, the interindividual variability remaining in the final model (clearance coefficient of variation close to 30%) make these a priori dosage predictions imprecise and justifies the need for LTG plasma level monitoring to optimize dosage regimens. Thus, this final model allows easy implementation in clinical pharmacokinetic software and its application in dosage individualization using the Bayesian approach.     

Population pharmacokinetics of free carbamazepine in adult Omani epileptic patients

OBJECTIVE: The aim of this study was to define the pharmacokinetic profile of free carbamazepine (F-CBZ) in adult Omani epileptic patients in order to improve on dosing schedules through population pharmacokinetic analysis using the NONMEM program. METHOD: Steady-state trough F-CBZ serum concentrations, carbamazepine (CBZ) dosing history and associated information were collected prospectively. RESULTS: Forty-eight patients with two or more available F-CBZ serum concentrations (total of 149 dose/serum concentration pairs) met our inclusion criteria. Patients were taking CBZ (200-1200 mg/day) in monotherapy. The analysis assumed a one-compartmental open model with first-order absorption and elimination. The apparent clearance (CL/F) and apparent volume of distribution (V/F) and their interindividual variabilities were estimated using the program. The population estimates for clearance (CL; modelled independently of dose) and volume of distribution were 13.2 +/- 0.6 l/h and 525 +/- 44 1, respectively. However, CL increased as a function of dosing rate and consequently was modelled as a linear function of steady-state concentration. In order to validate these results, the predictions of the population model were tested against data from 13 further patients subjected to the same inclusion criteria but who were not included in the original analysis. The predictions were good, being unbiased (P=0.31), and had an average deviation from the observed values of 18%. CONCLUSION: In order to establish steady-state dosage regimens, a population pharmacokinetic model is proposed, based on the patient's dose, to estimate the individual CL for an Omani epileptic patient receiving CBZ in monotherapy.     

用NONMEM法建立癫痫患者丙戊酸群体药代动力学模型

目的 建立丙戊酸(VPA)在癫痫患者中的群体药代动力学(PPK)模型,考察固定效应因素对VPA清除率(CL/F)的影响.方法 回顾性收集贵州省人民医院111名癫痫患者VPA稳态血药浓度数据及相应的人口学、合并用药及CYP2A6基因型等资料,随机将患者分成建模组(74名)及验证组(37名),使用建模组数据通过非线性混合效应模型(NONMEM)程序建立VPA的PPK模型.使用验证组数据来验证模型的准确度和精密度,比较基础模型和最终模型的平均预测误差(MPE)、平均绝对误差(MAE)、平均根方差(RMSE).结果 建立的最终模型包含了日用药剂量(DDO)及CYP2A6基因型,模型方程为:CL/F=0.363·DD00.525·1.29GENECYP2A6.最终模型有更好的精密度及准确度,基础模型MPE、MAE、RMSE值为- 10.63、14.40、22.55,最终模型相应值为-6.11、9.06、14.17.结论 本研究初步建立癫痫患者VPA的PPK模型,VPA清除率随日给药剂量的增大而增大,CYP2A6野生型(CYP2A6*1/*1)组患者较CYP2A6突变型(CYP2A6* 1/*4、CYP2A6* 4/*4)组患者有更高的VPA清除率.     

NONMEM法估算中国癫痫患者卡马西平的清除率

目的　考察中国癫痫患者卡马西平的群体药动学参数。方法　癫痫病例来自上海、北京两地 4所医院 ,采集服用卡马西平的 5 92例患者的稳态血药浓度 (n =70 3)。NONMEM程序估算分析时 ,采用一级吸收和消除的药动学模型并固定吸收速率、生物利用度和表观分布体积参数。结果　体重 (TBW )、剂量 (Dose)、合用丙戊酸钠 (VPA)且其日剂量大于 2 0mg·kg-1·d-1、苯妥英 (PHT)、苯巴比妥 (PB)和年龄大于 6 5岁的老年人 (ELDER)均为卡马西平清除率(CL)的影响因素。性别、合用氯硝西泮、妥吡酯不改变卡马西平的清除率。最终模型为 :CL(CL/F) (L/h) =1 32·Dose(g·kg-1·d-1) 0 42 1·TBW (kg) 0 .691·1 2 0 VPA·1 4 3PHT·1 14 PB·0 836 ELDER。讨论　根据中国癫痫患者的群体药动学模型 ,结合患者服用的剂量、体重和合并用药可估算其清除率 ,制定给药方案     

Population pharmacokinetics of carbamazepine in Chinese epilepsy patients

AIM: To investigate the pharmacokinetic profile of carbamazepine (CBZ) in Chinese epilepsy patients. MATERIALS AND METHODS: Serum samples through concentrations at steady state (n = 687) were collected prospectively from 585 patients during routine clinical care. Data were analyzed by the non-linear mixed-effect modeling (NONMEM) technique with a one-compartment model of first-order absorption and elimination. RESULTS: The important determinants of clearance (CL) were total body weight (TBW); dose; patient age over 65 years (E); and comedication with phenytoin (PHT), phenobarbital (PB), or valproic acid (VPA) when VPA daily dose was greater than 18 mg/kg. The final pharmacokinetic model for relative CL and apparent distribution volume (V) were: Equation CONCLUSION: A population pharmacokinetic model was proposed to estimate the individual CL for Chinese patients receiving CBZ in terms of patient's dose, TBW, and comedications to establish a priori dosage regimens.     

Population pharmacokinetics of tacrolimus in Asian paediatric liver transplant patients

AIMS: The purpose of this study was to describe the population pharmacokinetics of intravenous and oral tacrolimus (FK506) in 20 Asian paediatric patients, aged 1-14 years, following liver transplantation and to identify possible relationships between clinical covariates and population parameter estimates. METHODS: Details of drug dosage histories, sampling times and concentrations were collected retrospectively from routine therapeutic drug monitoring data accumulated for at least 4 days after surgery. Before analysis, patients were randomly allocated to either the population data set (n = 16) or a validation data set (n = 4). The population data set was comprised of 771 concentration measurements of patients admitted over the last 3 years. Population modelling using the nonlinear mixed-effects model (NONMEM) program was performed on the population data set, using a one-compartment model with first-order absorption and elimination. Population average parameter estimates of clearance (CL), volume of distribution (V) and oral bioavailability (F) were sought; a number of clinical and demographic variables were tested for their influence on these parameters. RESULTS: The final optimal population models related clearance to age, volume of distribution to body surface area and bioavailability to body weight and total bilirubin concentration. Predictive performance of this model evaluated using the validation data set, which comprised 86 concentrations, showed insignificant bias between observed and model-predicted blood tacrolimus concentrations. A final analysis performed in all 20 patients identified the following relationships: CL (l h-1) = 1.46 *[1 + 0. 339 * (AGE (years) -2.25)]; V (l) = 39.1 *[1 + 4.57 * (BSA (m2)-0. 49)]; F = 0.197 *[1 + 0.0887 * (WT (kg) -11.4)] and F = 0.197 *[1 + 0.0887 * (WT (kg) -11.4)] * [1.61], if the total bilirubin > or = 200 micromol l-1. The interpatient variabilities (CV%) in CL, V and F were 33.5%, 33.0% and 24.1%, respectively. The intrapatient variability (s.d.) among observed and model-predicted blood concentrations was 5.79 ng ml-1. CONCLUSIONS: In this study, the estimates of the pharmacokinetic parameters of tacrolimus agreed with those obtained from conventional pharmacokinetic studies. It also identified significant relationships in Asian paediatric liver transplant patients between the pharmacokinetics of tacrolimus and developmental characteristics of the patients.     

Population pharmacokinetics of valproate in Chinese children with epilepsy

Aim： The aim of the present study is to establish a population pharmacokinetic （PPK） model of valproate （VPA） in Chinese epileptic children to promote the reasonable use of anti-epileptic drugs. Methods： Sparse data of VPA serum concentrations from 417 epileptic children were collected. These patients were divided into 2 groups： the PPK model group （n=317） and the PPK valid group （n=100）. The PPK parameter values of VPA were calculated by NONMEM software using the data of the PPK model group. A basic model and a final model were set up. To validate the 2 models, the concentrations of PPK valid group were predicted by each model, respectively. The mean prediction error （MPE）, mean squared prediction error （MSPE）, root mean squared prediction error （RMSPE）, weight residues （WRES）, and the 95% confidence intervals （95% CI） were also calculated. Then, the values between the 2 models were compared. Results： The PPK of VPA was determined by a 1-compartment model with a first-order absorption process. The basic model was： Ka=3.09 （h^-1）, V/F=20.4 （L）, CL/F=0.296 （L/h）. The final model was： Ka=0.251＋2.24-（1-HS） （h^-l）, V/F=2.8 8＋0.157-WT （L）, CL/F=0.106^0.98.CO＋ 0.0157·AGE （L/h）. For the basic model, the MPE, MSPE, RMSPE, WRES, and the 95% CI were -23.53 （-30.36,-16.70）, 3728.96 （2872.72, 4585.20）, 39.62 （34.34, 44.90）, and-0.06 （-0.14, 0.02）, respectively. For the final model, the MPE, MSPE, RMSPE, WRES, and the 95% CI were -1.16 （-4.85, 2.53）, 1002.83 （1050.64,1143.61）, 23.04 （21.12, 24.96）, and 0.08 （-0.04, 0.20）, respectively. The final model was more optimal than the basic model. Conclusion： The PPK model of VPA in Chinese epileptic children was successfully established. It will be valuable to facilitate individualized dosage regimens.     

Population pharmacokinetics of amphotericin B in children with malignant diseases

AIMS: To construct a population pharmacokinetic model for the antifungal agent, amphotericin B (AmB), in children with malignant diseases. METHODS: A two compartment population pharmacokinetic model for AmB was developed using concentration-time data from 57 children aged between 9 months and 16 years who had received 1 mg kg(-1) day(-1) doses in either dextrose (doseform=1) or lipid emulsion (doseform=2). P-Pharm (version 1.5) was used to estimate the basic population parameters, to identify covariates with significant relationships with the pharmacokinetic parameters and to construct a Covariate model. The predictive performance of the Covariate model was assessed in an independent group of 26 children (the validation group). RESULTS: The Covariate model had population mean estimates for clearance (CL), volume of distribution into the central compartment (V) and the distributional rate constants (k12 and k21) of 0.88 l h(-1), 9.97 l, 0.27 h(-1) and 0.16 h(-1), respectively, and the intersubject variability of these parameters was 19%, 49%, 55% and 48%, respectively. The following covariate relationships were identified: CL (l h(-1)) = 0.053 + 0.0456 weight (0.75) (kg) + 0.242 doseform and V (l) = 7.11 + 0.107 weight (kg). Our Covariate model provided unbiased and precise predictions of AmB concentrations in the validation group of children: the mean prediction error was 0.0089 mg l(-1) (95% confidence interval: -0.0075, 0.0252 mg l(-1)) and the root mean square prediction error was 0.1245 mg l(-1) (95% confidence interval: 0.1131, 0.1349 mg l(-1)). CONCLUSIONS: A valid population pharmacokinetic model for AmB has been developed and may now be used in conjunction with AmB toxicity and efficacy data to develop dosing guidelines for safe and effective AmB therapy in children with malignancy.     

Pharmacokinetics of lamotrigine in paediatric and young adult epileptic patients—nonlinear mixed effects modelling approach

Purpose

The purpose of the study was to examine and describe adjunctive lamotrigine (LTG) pharmacokinetics in paediatric and young adult patients using a nonlinear mixed effects modelling (NONMEM) approach.

Methods

The study included 53 patients (age range 3–35 years) who were concomitantly treated with carbamazepine (CBZ) and/or valproic acid (VPA). A total of 70 blood samples corresponding to trough levels were available for analysis. Data were modelled, and the final model was evaluated using NONMEM and auxiliary software tools.

Results

The final LTG population model included the effects of concomitant drugs and patient’s weight (WT) which stratified the population into three groups: ≤25 kg, >25 to <60 kg and ≥60 kg. Based on the final model, the estimated LTG oral clearance (CL/F) for a typical patient weighing ≤25 kg, >25 to <60 kg or ≥60 kg who was concomitantly treated with CBZ was estimated to be 3.28, 4.23, or 7.15 l/h, respectively. If a patient was concomitantly treated with CBZ + VPA, the CL/F decreased on average by 69.5 % relative to LTG + CBZ co-therapy. VPA was found to decrease the LTG CL/F by 87.6 % compared to co-therapy with only CBZ.

Conclusion

The LTG population pharmacokinetic model developed in this study may be a reliable method for individualising the LTG dosing regimen in paediatric and young adult patients on combination therapy during therapeutic drug monitoring.     

Effects of <Emphasis Type="Italic">CYP2C19</Emphasis> and <Emphasis Type="Italic">CYP2C9</Emphasis> genotypes on pharmacokinetic variability of valproic acid in Chinese epileptic patients: nonlinear mixed-effect modeling

Purpose

To evaluate the effects of CYP2C19 and CYP2C9 genotypes on the pharmacokinetic variability of valproic acid (VPA) in epileptic patients using a population pharmacokinetic (PPK) approach.

Methods

VPA concentrations were measured in 287 epileptic patients, who were genotyped for CYP2C19*2/*3 and CYP2C9*3. Patients who were on monotherapy with VPA were divided into two groups, a PPK-model group (n?=?177) and a PPK-valid group (n?=?110). The PPK parameter values for VPA were calculated in the PPK-model group by using the NONMEM software. Ultimately, a biological model and a final model were established. Each model was then used to independently predict the concentrations of the PPK-valid group to validate the two models.

Results

There was a significant effect of the CYP2C19 and CYP2C9 genotypes on the pharmacokinetic (PK) variability (P?<?0.01) in the final PPK model of CL/F. The interindividual CL was calculated according to the final model: CL/F?=?0.0951?×?(1?+?e^{0.0267?×?(3???genotype)})?+?0.0071?×?age (L/h). The coefficient of variation (CV) (omega CL/F) of the final model was 29.3%, while that of the biological model was 31.7%. Based on the genotype, the individual PK parameters can be calculated more accurately than before.

Conclusion

The CYP2C19 and CYP2C9 genotypes significantly influenced the PK variability of VPA, as quantified by NONMEM software.

     

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 Pharmacokinetics of Carbamazepine in Indian Epileptic Patients

The aim of this study was to describe the population pharmacokinetics of carbamazepine in Indian epileptic patient population. The covariates evaluated were total body weight, height, age, dose, and gender. A total of 307 steady state serum concentrations were collected from 84 patients and analyzed. Population pharmacokinetic parameters were calculated using NONMEM, with one compartment first order absorption and elimination. The absorption rate was set at a fixed value of 1.2 h^?1. Exponential interindividual error and additive residual error model were developed. The model that was found to best describe the data following FO method was: Apparent Clearance (CL/F) (L/h)= 0.785 + 1.16 * (TBW/41.2) ** 0.75 * EXP (0.0976); Apparent Volume (V/F) (L) = 24.8 + 21.4 *(TBW/41.2)* EXP (0.740). Similarly the model found to best describe the data following FOCE method was CL/F (L/h) = 0.632 + 1.63 * (TBW/41.2) ** 0.75 * EXP (2.35E-12); V/F (L) = 31.8 + 56.9 *(TBW/41.2)* EXP (0.180).The final model estimates of CL/F and V/F estimated by FO method were 0.05 L/h/kg and 1.7 L/kg respectively and by FOCE method are 0.043 L/h/kg 1.43L/kg respectively. The typical body weight used for this population was 40 kg.     

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.     

Bayesian estimation of six different sets of carbamazepine pharmacokinetic parameters in Egyptian adult epileptic patients.

The individualization of carbamazepine (CBZ) dosage regimen based on estimation of pharmacokinetic (PK) parameters and measurement of serum drug concentration in epileptic patients can help to control epilepsy. In a retrospective study, the predictive performance of six different sets of CBZ PK parameters selected according to the literature was evaluated in 60 adult epileptic patients. Patients were administered controlled release CBZ (dose range: 200-1200 mg day(-1)) as monotherapy and one steady state serum concentration of the drug was available for each patient. The Bayesian Program of Abbott (PKS system; Abbott Laboratories, Wiesbaden, Germany) was used in the prediction process. Predictive measures included estimation of mean prediction error (mpe) for bias, mean squared prediction error (mspe) and root mean squared prediction error (rmspe) for precision. The analysis showed that three of the investigated six sets achieved the best predictive performance in Egyptian patients and consequently, the PK parameters of any of these three sets can be used by the Bayesian approach as prior information for CBZ dose optimization among the Egyptian adult population.     

Population estimation of valproic acid clearance in adult patients using routine clinical pharmacokinetic data

The aim of the present study was to estimate valproic acid (VPA) clearance values for adult patients with epilepsy, using serum concentrations gathered during their routine clinical care. Retrospective steady state serum concentrations data (n=534) collected from 208 adult patients receiving VPA were studied. Data were analysed according to a one-compartment model using the NONMEM program. The influence of VPA daily dose (Dose), gender, age, total body weight (TBW), and comedication with carbamazepine (CBZ), phenytoin (PHT) and phenobarbital (PB) were investigated. The results of the population pharmacokinetics analysis were validated in a group of 30 epileptic patients. The final regression model for VPA clearance (Cl) was: $?rm Cl?left (?rm L/h ?right )=0?rm. 004?times TBW?times Dose ?0.304??rm ?times 1.363?,?rm CBZ?times 1. 541?,?rm PHT?times 1.397?,?rm PB.$ The inter-individual variability in VPA clearance, described by a proportional error model, had a variation coefficient (CV) of 23.4% and the residual variability, described using an additive model, was 11.4 mg/L. These results show that VPA clearance increased linearly with TBW, but increases nonlinearly with increasing VPA daily dose. Concomitant administration of CBZ, PHT and PB led to a significant increase in VPA clearance. The model predictions in the validation group were found to have satisfactory precision and bias. In conclusion, inter-individual variability in VPA clearance can be partly explained by TBW, daily dose and bitherapy with CBZ, DPH or PB. Inclusion of these factors allows this variability to be reduced by 37.23% which may be very useful for clinicians when establishing the initial VPA dosage regimen. However, the magnitude of inter-individual plus residual variabilities, remaining in the final model, render these dosage predictions imprecise and justify the need for VPA serum level monitoring in order to individualize dosage regimens more accurately.     

Population pharmacokinetic study of cyclosporine based on NONMEM in Chinese liver transplant recipients

A population pharmacokinetic study of cyclosporine (CsA) was performed in liver transplant recipients. A total of 3731 retrospective drug monitoring data points at predose (C0) and 2 hours postdose (C2) were collected from 124 liver transplant recipients receiving CsA microemulsion. Population pharmacokinetic analysis was performed using the program NONMEM (nonlinear mixed-effect modeling). Various covariates potentially related to CsA pharmacokinetics were explored, and the final model was validated by a bootstrap method and by assessing the predictive performance using empiric Bayesian estimates. A one-compartment model with first-order absorption was considered. Population parameters of apparent clearance (CL/F) and volume of distribution were estimated as 23.1 L/h and 105 L, respectively. CL/F was influenced by four covariates: duration of CsA therapy (DT), hematocrit (HCT), and concurrent prednisone dose (PR). The final model for CL/F was fitted as follows: CL/F = 23.1 + 0.5 × (DT/200) - 0.07 × HCT + 0.04 × PR. The interindividual variability in CL/F, volume of distribution, and Ka calculated as coefficient of variation were 15.1%, 9.3%, and 66.0%, respectively. The intraindividual variability was 18.6%. The model fitted well with the observed data, and the bootstrap method guaranteed robustness of the population pharmacokinetic study model. Model validation was performed by a visual predictive check. Moreover, simulation was conducted to facilitate the individualized treatment based on patient information and the final model. The model to characterize population pharmacokinetic study of CsA provided better clinical individualization of CsA dosing in liver transplant recipients based on patient information and to assess patients' suitability for CsA therapy.     

Population pharmacokinetics of cyclosporine in cardiopulmonary transplant recipients

A population pharmacokinetic analysis of cyclosporine (CsA) was performed, and the influence of covariates on CsA oral clearance and relative bioavailability was investigated. Data from 48 recipients of heart-lung (n = 21) or single (n = 18) or double (n = 9) lung transplant were included in the study. Patients received oral CsA as either a conventional formulation (Sandimmune) or a microemulsion (Neoral). Steady-state CsA concentrations were measured before and at approximately 2 and 6 hours after the morning dose of CsA at the end of weeks 1, 2, 3, 4, 13, 26, 39, and 52 posttransplantation. A total of 1004 CsA concentration observations were analyzed using mixed effects-modeling (NONMEM). A 1-compartment pharmacokinetic model and first-order oral absorption were used to fit the data. The absorption rate constants were fixed at 0.25 L/h for Sandimmune and 1.35 L/h for Neoral formulations. Oral clearance (CL/F) was estimated to be 22.1 L/h (95% confidence intervals [CI] 19.5-24.7 L/h). Itraconazole (ITRA), cystic fibrosis (CF), and weight (WT) were identified as significant covariates for CL/F according to the final model: CL/F = 22.1 - 11.3 x ITRA + 23.5 x CF + 0.129 x (WT - 58.7) L/h; where ITRA = 1 if the patient was taking concomitant itraconazole, otherwise 0; CF = 1 if the patient had cystic fibrosis, otherwise CF = 0; and WT is patient weight in kilograms. The relative oral bioavailability of Sandimmune to Neoral was 0.82. The bioavailability of both preparations increased during the first month posttransplantation. Age, gender, and type of transplant (single, double, or heart-lung) were not identified as significant covariates for CsA clearance. The population pharmacokinetic model developed identified some sources of variability in CsA pharmacokinetics; however, an appreciable degree of variability is still present in this patient population.     

Population estimation of the effects of cytochrome P450 2C9 and 2C19 polymorphisms on phenobarbital clearance in Japanese

A nonlinear mixed-effect modeling (NONMEM) program was used to evaluate the effects of cytochrome P450 (CYP) 2C9 and CYP2C19 polymorphisms on the phenobarbital (PB) population clearance for Japanese epileptics. The pharmacokinetics of the 260 PB concentrations at a steady-state obtained from 79 patients was described with a one-compartment open pharmacokinetic model with first-order elimination. The covariates screened included the total body weight (BW), age, gender, PB daily dose, CYP2C9 and CYP2C19 genotypes, the coadministered antiepileptic drugs (AEDs), and complications. The final model of PB apparent clearance was as follows: CL = 0.23 x (BW/40)0.21 x 0.52CYP2C9*1/*3 x 0.68VPA x 0.85PHT x 0.85SMID x (1 + etaCL) where CL = the clearance of PB; CYP2C9*1/*3 = 1, otherwise 0; VPA = 1 if valproic acid is coadministered, otherwise 0; PHT = 1 if phenytoin is coadministered, otherwise 0; SMID = 1 if complications of severe or profound mental retardation with a significant behavior impairment are presented, otherwise 0; and etaCL = the independent random error distributed normally with the mean zero and variance equal to omegaP2. The total clearance of PB decreased by 48% in patients with CYP2C9*1/*3 genotype in comparison with those with CYP2C9*1/*1 genotype (P < 0.001). An effect of CYP2C19 polymorphisms was not detected. To our knowledge, this is the first report to demonstrate that the CYP2C9 genotype affects the PB metabolism in routine care, but the results should be further verified in other ethnic populations.