群体药物动力学简介

介绍了群体药物动力学的定义及统计理论、群体参数估计方法及在临床药理学与新药开发中的应用     

群体药代动力学在儿科抗癫痫药合理使用中的应用

癫痫（ epilepsy ）是一种常见的神经系统慢性疾病,对人类健康危害较大。世界卫生组织报告,全球约有5000万患者。国内流行病学研究结果表明,在中国癫痫的患病率为0．7％,每年新发患者达45万左右,癫痫患者中75％～80％起病于儿童期,10岁以下儿童的发病率为高峰,故小儿癫痫的治疗尤为重要。癫痫治疗的主要目的是控制发作,而药物治疗是控制发作的主要手段。临床常用的一线抗癫痫药物主要有苯妥英钠,苯巴比妥,卡马西平及丙戊酸钠等。但是抗癫痫药物具有显著的个体差异性,且药物必须维持在稳态有效血药浓度范围内,才能满意控制惊厥,因此抗癫痫长期以来都是治疗药物监测的重点。现将群体药代动力学在儿科抗癫闲药合理使用中的应用综述如下。     

儿童生理药代动力学模型及其在儿科药物研究中的应用

生理药代动力学(physiologically based pharmacokinetic, PBPK)模型是预测药物在特殊人群中的药代动力学、药效学和安全性的重要工具。尤其对于儿童这类不易开展临床试验的人群, PBPK模型的应用更是能有效促进儿科药物的开发以及儿童的临床用药。目前, PBPK模型在儿科药物开发中的主要应用有以下几种:临床试验设计、药物相互作用(drug-drug interaction, DDI)的风险评估和儿童给药剂量的确立等。本综述简介了儿童生理药动学模型在儿科药物研究中的优越性,总结了PBPK模型如何实现从成人到儿童的外推,儿童生理药动学模型的理论基础,建模过程及所要注意的重要生理参数,列举了目前PBPK模型在儿科药物研究中的一些应用实例。最后简述了儿童PBPK模型当前的局限性和未来发展方向。     

群体药代动力学及其儿科应用

药代动力学(Pharmacokinetics,PK)是研究药物在体内吸收、分布、代谢和排泄规律的科学,对于指导合理用药有重要意义。获得个体PK参数的方法是：在病人一次用药后,短时间内的不同时刻取7～10个血样,测定血药浓度并应用PK专业软件计算个体PK参数。此法取样多,痛苦大,经济负担重,不易为患者(尤其儿     

群体药物动力学研究

近年来,群体药物动力学已引起制剂工业以及美国食品药物管理局(U.S Food and Dring Adminis-tration,FDA)专家们的极大关注,不少FDA法规文件中都引用了群体药物动力学来评价药物的有效性和安全性.本文综述了群体药物动力学研究中的群体方法、实验设计、数据处理和分析以及模型的验证等内容,旨在为药品开发和规范管理提供参考.1 研究背景某些疾病的生理病理特征能有规律地改变剂量-浓度之间的关系.例如主要通过肾消除的药物,肾衰通常会引起病人稳态血药浓度的明显升高.群体药物动力学就是研究个体间血药浓度差异的来源和联系,目的在于揭示引起剂量-浓度关系改变的生理病理因素,确定这种改变的大小,以便拟定合适的临床用药剂量.传统药物动力学的研究对象通常是健康志愿者或经严格挑选的病人,且仅对他们的平均情况感兴趣.对于个体间的差异往往采用复杂的实验设计或     

群体药物动力学研究进展

本文综述了群体药物动力学近年来的发展,包括研究方法、模型建立与验证以及应用等.在研究方法中,以NONMEM模型法应用最广,而非参数期望值法也有其优点.模型的建立和验证是群体药动学研究的一项重要而复杂的工作,不同的模型采用不同的数据和方法来验证.群体药动学用应用范围在不断拓宽,已用于群体药动学分析、个体化给药、生物利用度研究、药效学研究和新药开发与临床评价等方面.     

群体药代动力学在儿科临床药理学研究中的应用

儿童是一特殊人群,他们的各种生理指标与成人有很大的不同。但在临床实践中,人们往往是参照成人剂量来指导儿童的用药,这严重的威胁着儿童的身体健康,个体化给药方案的建立刻不容缓。在这一方面,群体药代动力学是其强有力的工具。     

重视儿科的药物临床试验

儿童是一个极为特殊的群体,在这个具动力学成长特点的复杂群体里,药物治疗的太多未知参数等待进一步科学探索.     

群体药物动力学在治疗药物监测中的应用

群体药物动力学(population pharmacokinetics,PopPK)是研究患者群体在给予临床相应剂量的某种药物后,个体间药物浓度差异的来源及相关性的学科。群体中个体差异的来源可分为2类:一类是固定效应,指通常在一定时段内较为固定,可以受研究者控制的变异,如性别、年龄、身高、体重种族、基因多态     

群体药物动力学在个体化给药中的应用进展

目的群体药物动力学(population pharmacokinetics,PopPK)可综合评价药动学在个体间及个体内的各种变异,并应用Bayesian反馈法,较为准确地预测个体的药动学参数。目前群体药动学已广泛应用在治疗药物监测中,以实现临床个体化给药。本文阐述了群体药物动力学的概况,并对群体药物动力学在个体化给药中的应用进展进行综述。     

Population pharmacokinetics of Cyclosporine and its clinical application

A population pharmaeokinetic model of eyelosporine （CsA） for clinical renal transplant patients was constructed to adjust CsA＇ s administration individually. A total of 2, 548 retrospective drug monitoring data were collected from 120 Chinese renal transplant patients receiving CsA. Population modeling was performed with NONMEM by a one-compartment model with first-order absorption and elimination. Six significant eovariates were included in the final model. It is postoperative days （POD）, total bilirubin level （TBIL）, current body weight （CBW）, age, concurrent metabolic inhibitors of CsA （INHI）, and hematocrit （HCT）. The population means for CL/F （28.5 L/h）, V/F （volume of distribution, 133 L）, and inter-patient vari-Fability （CV% = 19.7%） for CL/F were estimated. The model was further validated internally and externally, and was demonstrated to be effeetive and robust. Moreover, in order to put the result of population pharmaeokinetie studies into elinical praetiee, a database with the name of C- TDM for post renal transplantation patients based on the population model was established. Up on the availability of the information from elinic, the precision of the plasma concentration predieted with C-TDM was elassified into 3 levels,[第一段]     

群体药代动力学及其在新药研究中的应用

近年来新药临床研究越来越重视群体药代动力学的应用。群体药代动力学可以定量地描述病理、生理、合并用药等多种因素对药物代谢的影响，可将PK参数中的各种变异区分开，指导用药方案的调整，从而增强对新药有效性和安全性的评价。本文对群体药代动力学的研究方法及其在新药研究中的应用进行综述．     

群体药动学及其应用研究进展

概述了群体药动学的研究方法,着重介绍了群体药动学的原理、步骤及应用。近年来群体药动学应用范围不断拓宽,极大地推进了个体化用药的发展,已成为临床药代动力学研究的重要手段。     

Population pharmacokinetics of clozapine and its primary metabolite norclozapine in Chinese patients with schizophrenia

Aim:

To develop a combined population pharmacokinetic model (PPK) to assess the magnitude and variability of exposure to both clozapine and its primary metabolite norclozapine in Chinese patients with refractory schizophrenia via sparse sampling with a focus on the effects of covariates on the pharmacokinetic parameters.

Methods:

Relevant patient concentration data (eg, demographic data, medication history, dosage regimen, time of last dose, sampling time, concentrations of clozapine and norclozapine, etc) were collected using a standardized data collection form. The demographic characteristics of the patients, including sex, age, weight, body surface area, smoking status, and information on concomitant medications as well as biochemical and hematological test results were recorded. Persons who had smoked 5 or more cigarettes per day within the last week were defined as smokers. The concentrations of clozapine and norclozapine were measured using a HPLC system equipped with a UV detector. PPK analysis was performed using NONMEM. Age, weight, sex, and smoking status were evaluated as main covariates. The model was internally validated using normalized prediction distribution errors.

Results:

A total of 809 clozapine concentration data sets and 808 norclozapine concentration data sets from 162 inpatients (74 males, 88 females) at multiple mental health sites in China were included. The one-compartment pharmacokinetic model with mixture error could best describe the concentration-time profiles of clozapine and norclozapine. The population-predicted clearance of clozapine and norclozapine in female nonsmokers were 21.9 and 32.7 L/h, respectively. The population-predicted volumes of distribution for clozapine and norclozapine were 526 and 624 L, respectively. Smoking was significantly associated with increases in the clearance (clozapine by 45%; norclozapine by 54.3%). The clearance was significantly greater in males than in females (clozapine by 20.8%; norclozapine by 24.2%). The clearance of clozapine and norclozapine did not differ significantly between Chinese patients and American patients.

Conclusion:

Smoking and male were significantly associated with a lower exposure to clozapine and norclozapine due to higher clearance. This model can be used in individualized drug dosing and therapeutic drug monitoring.     

Population pharmacokinetics of ceftazidime in burn patients

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

Population pharmacokinetics of oseltamivir in non-pregnant and pregnant women

Aims

Physiological changes in pregnancy are expected to alter the pharmacokinetics of various drugs. The objective of this study was to evaluate systematically the pharmacokinetics of oseltamivir (OS), a drug used in the treatment of influenza during pregnancy.

Methods

A multicentre steady-state pharmacokinetic study of OS was performed in 35 non-pregnant and 29 pregnant women. Plasma concentration–time profiles were analyzed using both non-compartmental and population pharmacokinetic modelling (pop PK) and simulation approaches. A one compartment population pharmacokinetic model with first order absorption and elimination adequately described the pharmacokinetics of OS.

Results

The systemic exposure of oseltamivir carboxylate (OC, active metabolite of OS) was reduced approximately 30 (19–36)% (P < 0.001) in pregnant women. Pregnancy significantly (P < 0.001) influenced the clearance (CL/F) and volume of distribution (V/F) of OC. Both non-compartmental and population pharmacokinetic approaches documented approximately 45 (23–62)% increase in clearance (CL/F) of OC during pregnancy.

Conclusion

Based on the decrease in exposure of the active metabolite, the currently recommended doses of OS may need to be increased modestly in pregnant women in order to achieve comparable exposure with that of non-pregnant women.     

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 imipramine in children

Summary The population pharmacokinetics of imipramine (IMI) and its active metabolite desipramine (DMI) have been evaluated using 177 IMI and DMI serum levels from 49 enuretic children (6–13 y) on IMI treatment. Standard two stage (STS) and maximum likelihood (ML) methods were used to estimate fixed and random effect parameters of IMI. Simultaneous estimation of the drug and metabolite parameters was carried out by the STS method.The mean value of the elimination constant of the drug and metabolite were 0.0425 h^–1 and 0.0359, h^–1 respectively. Significantly higher variability was found in the pharmacokinetic parameters of the metabolite. According to these estimated pharmacokinetic parameters, the recommended dose for enuretic children should be 1.7 mg · kg^–1 · day^–. The population pharmacokinetic parameters obtained in the study permit dosage individualisation using a bayesian algorithm.     

用NONMEM法建立西酞普兰群体药代动力学模型

目的建立中国人西酞普兰(抗抑郁药)的群体药代动力学(PPK)模型,为临床个体化给药提供参考。方法用群体药代动力学方法,对西酞普兰生物等效性研究中23例受试者的血药浓度和临床资料进行分析,用NON-MEM软件求算西酞普兰的PPK参数值,建立西酞普兰的PPK模型,并进行模型验证。结果经NONMEM法处理,所有因素中,年龄、体重以及CYP2C19基因型对中央隔室清除率有显著性的影响;体重对分布容积有显著性的影响。年龄和体重的增加对清除率影响分别为-0.39L·h-1.a-1和0.18L.h-1·kg-1。结论用NONMEM软件拟合获得的西酞普兰群体药代动力学最终模型,经验证稳定可靠。