群体药动学研究方法的比较和评价

群体药动学研究方法主要包括单纯集聚法、传统二步法、迭代二步法、非参数法、吉布斯取样法、混合效应模型法等。简介这些研究方法的原理及应用,重点介绍基于混合效应模型的NONMEM程序的应用,并详细介绍目前对NONMEM法的一些改进。     

群体药动学参数的估算与应用

群体药动学参数在给药个体化中,有着极其重要的地位.当病人明确诊断,选定药物后,首先根据群体药动学参数设计给药方案,如果群体代表性强,预报的血药浓度将接近期望值,不然会造成较大的误差。     

中国成年感染患者万古霉素群体药动学研究

目的 利用来自恩泽医疗中心3家医院的成年万古霉素治疗患者的治疗药物监测数据研究其群体药动学（population pharmacokinetics,PPK）模型,并利用所建药动学参数模型和该类群体患者治疗过程中的单点谷浓度经贝叶斯反馈参数估算法计算个体化药动学参数,建立个体化给药方案。方法 收集128例患者,共监测235个血清浓度,采用Kinetica软件的PPK模块中的一室静脉给药模型通过期望最大法（EM）和贝叶斯反馈拟合数据得到基础模型。利用逐步正向回归法研究消除速率常数（Kel和Vd）与患者个体协变量肌酐（Scr）、年龄（Age）、体质量（Wt）、性别（Sex）以及合并用药之间的关系,并拟合最终模型。利用内部自举法和外部验证法对模型进行评价。结果 本研究中最终模型公式为Kel=θ₁×（Scr）^θ₂×（Sex）^θ₃,V=θ₄×（Scr）^θ₅×（Age）^θ₆×（Wt）^θ₇（θ₁=0.18;θ₂=-0.19;θ₃=-0.31;θ₄=20.85;θ₅=-0.52;θ₆=-0.23;θ₇=0.98）。最终模型对应的CL和Vd群体典型值分别为5.0 L·h^-1和66.9 L,外部验证中贝叶斯预测平均误差分别为0.8 L·h^-1和9 L。结论 本研究通过所建立的万古霉素PPK模型,较好的反应出中国成年患者的万古霉素PPK特征,贝叶斯单点反馈误差较低,为提高治疗效果、减少不良反应以及实现个体化给药提供了重要的理论实验参考依据。     

群体药动学理论及其应用

群体药动学（ Population Pharmacokinetics,PPK）起因于对在新药研究早期阶段就有可能应用该药而未进行药动学（ PK）研究的人群的关切 [1～ 4].儿童、妇女、老人等特殊群体一般不作为新药Ⅰ期临床药动学研究对象,但这些群体的药动学特征在Ⅲ、Ⅳ期临床研究中对于给药方案的设计与修订至关重要,而其病理生理情况与Ⅰ期研究中的受试者有很大区别.     

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。     

成人万古霉素群体药动学的研究进展

目的:为临床合理应用万古霉素提供参考。方法:以"成人""万古霉素""群体药动学""群体药动学模型""Adults""Vancomycin""Population pharmacokinetic""PPK model"等为中英文关键词,在PubMed、中国知网、万方等数据库中组合检索自建库起至2019年10月31日发表的相关文献,对成人万古霉素群体药动学(PPK)的研究进展进行综述。结果与结论:共检索到相关文献166篇,其中有效文献25篇。目前已有研究在成年感染患者、危重症患者、接受肾脏替代治疗及血液滤过治疗的患者、神经外科患者、接受体外膜氧合治疗的患者、重症脓毒血症患者、血液肿瘤患者以及下呼吸道感染重症患者等群体中建立了万古霉素PPK模型。成人患者中,肌酐清除率与体质量是影响万古霉素药动学参数的主要因素,提示临床用药时应当关注患者肾功能与体质量;另外,是否感染及感染类型也对万古霉素的药动学参数有不同程度的影响。对于接受肾脏替代治疗及血液滤过治疗的患者,万古霉素的清除主要与其疗法的滤过率相关,提示临床应当根据所接受疗法的滤过率调整剂量;对于神经外科患者,脑脊液白蛋白与脑脊液引流量则是万古...     

群体药动学的研究进展及应用

目的：介绍群体药动学（PPK）近年来的研究进展及应用。方法：查阅近年来的文献，综述近年来群体药动学的研究进展及应用。结果：群体药动学的研究对临床合理用药、新药研究及评价有很大的指导意义。结论：PPK的研究方法已逐渐成为临床药动学研究的重要手段，并将发挥越来越重要的作用。     

丙泊酚群体药动学研究与临床个体化给药

丙泊酚为新型短效静脉全身麻醉药,其功能主治是全身麻醉的诱导和维持。临床用药时个体之间由于生理、病理及其他一些因素的不同,丙泊酚在体内处置方式存在差异,因而需要采用个体化给药的方式。综述年龄、体质量、性别、肝肾功能、合并用药等因素对个体化给药的影响及国内外对丙泊酚群体药动学所做的研究。     

中国成年患者万古霉素群体药动学研究

目的:利用万古霉素治疗药物监测(TDM)数据建立群体药动学(PPK)模型,用于估算个体化药动学参数。方法:选择使用万古霉素成年患者,详细记录用药、TDM数据以及病理生理资料。采用非线性混合效应模型(NONMEM)法建立万古霉素群体药动学模型。结果:169例患者数据来源于血液科及重症监护(ICU)病房等9个科室,共获得385个血药浓度数据,其中峰浓度39个,谷浓度346个。根据文献资料及TDM数据建立二室PPK模型,万古霉素清除率(CL)、中央室(V1)及外周室(V2)分布容积、室间清除率分别为4.08 L·h-1、21.7 L、65.3 L、5.95 L·h-1,患者肌酐清除率及体重分别对CL及V2具有显著影响。根据模型预测169位患者AUC0-24h为(450.1±231.8)mg·L-1·h。结论:本研究建立的万古霉素PPK模型可以用于中国成年患者个体化药动学参数估算。     

新生儿万古霉素群体药动学模型建立的必要性评价

目的:观察研究万古霉素在新生儿中的临床应用及血药谷浓度达标情况,评价新生儿万古霉素群体药动学模型建立的必要性。方法:回顾性收集苏州市立医院本部新生儿科2011年7月-2014年8月使用万古霉素的病史材料,对其感染部位、病原学检查、疗程、疗效、合并用药、血药浓度监测结果进行统计与分析。结果:入选71例患儿,90.14%为多部位混合感染,最常见的是呼吸道合并血流感染(43.66%);病原学送检率100%,首次培养阳性率80.28%,以葡萄球菌属为主(87.67%);万古霉素首次用药后血药谷浓度达标(10~20 mg·L^-1)率28.17%,未达标患者中有43.14%进行剂量调整,调整后达标率50%;万古霉素总临床有效率为90.14%,血药谷浓度未达标组的临床有效率为42.25%,达标组有效率为47.62%;首次经验性用药未进行剂量调整组万古霉素疗程为(13.41±4.41)d,经验性剂量调整组为(18.73±9.52)d(P=0.00188)。结论:万古霉素治疗新生儿感染疗效确切,但经验性用药后血药谷浓度达标率低,未达标者临床疗效差,经验性多次调整万古霉素用法显著延长患儿治疗时间,因此有必要建立新生儿万古霉素群体药动学模型以实现个体化给药治疗。     

迭代二步法估算阿米卡星的群体药动学参数

目的：用迭代二步法估算阿米卡星的群体药动学参数。方法：收集58例呼吸系统感染病人静脉滴注阿米卡星的临床血药浓度监测数据,用荧光偏振免疫法测定阿米卡星血药浓度。用迭代二步法估算阿米卡星的群体及个体药动学参数。比较性别、年龄、体重、肌酐清除率等因素对药动学参数的影响。结果：性别对药动学参数无影响,CL与CLcr呈正相关,Vd与体重呈正相关。结论：迭代二步法能较好地估算出阿米卡星的群体及个体药动学参数,用于优化给药方案及预测血药浓度可满足临床需要。     

Evaluation of the autoinduction of ifosfamide metabolism by a population pharmacokinetic approach using NONMEM

AIMS: This study investigated the population pharmacokinetics of ifosfamide in 15 patients treated for soft tissue sarcoma with 9 or 12 g m-2 ifosfamide by means of a 72 h continuous i.v. infusion. METHODS: A model was developed using nonlinear mixed effects modelling (NONMEM) to describe the nonlinear pharmacokinetics of ifosfamide by linking the ifosfamide plasma concentrations to the extent of the autoinduction. RESULTS: The proposed model revealed the effect of autoinduction on the disposition of ifosfamide. The initial clearance, volume of distribution, rate constant for enzyme degradation, induction half-life of the enzyme and the ifosfamide concentration at 50% of the maximum inhibition of enzyme degradation were estimated at 2.94 +/- 0.27 l h-1, 43.5 +/- 2.9 l, 0.0546 +/- 0. 0078 h-1, 12.7 h and 30.7 +/- 4.8 microM, respectively. Interindividual variabilities of initial clearance, volume of distribution, rate constant for enzyme degradation were 24.5, 23.4 and 22.7%, respectively. Proportional and additive variability not explained by the model were 13.6% and 0.0763 microM, respectively. CONCLUSIONS: The absence of a lag time for the autoinduction of ifosfamide metabolism could be the result of an immediate inhibition of the enzymatic degradation of CYP3A4 by ifosfamide. By application of the autoinduction model individual pharmacokinetic profiles of patients were described with adequate precision. This model may therefore be used in the future development of a model to individualize dose selection in patients.     

A computationally efficient approach for the design of population pharmacokinetic studies

A computationally efficient procedure was devised for designing experiments in which population pharmacokinetic parameters are estimated. The method, referred to as the large-sample approach, evaluates the variances of parameter estimates for a population pharmacostatistical model. The procedure utilizes the NONMEM program and requires a single simulation that assumes many, say 1000, subjects. The approach reduced CPU time by about a factor of 50 when compared with the evaluation of the same variances by the direct simulation of experiments. The large-sample and simulation approaches yielded generally similar values for the variances of parameter estimates. The variances calculated by the large-sample approach were, in the case of a simple model, close to the expected variances. The proposed method identified correctly the imprecise parameter estimates but somewhat underestimated their variances.This work was supported by the Medical Research Council of Canada.     

Prospective evaluation of a D-optimal designed population pharmacokinetic study

Recently, methods for computing D-optimal designs for population pharmacokinetic studies have become available. However there are few publications that have prospectively evaluated the benefits of D-optimality in population or single-subject settings. This study compared a population optimal design with an empirical design for estimating the base pharmacokinetic model for enoxaparin in a stratified randomized setting. The population pharmacokinetic D-optimal design for enoxaparin was estimated using the PFIM function (MATLAB version 6.0.0.88). The optimal design was based on a one-compartment model with lognormal between subject variability and proportional residual variability and consisted of a single design with three sampling windows (0–30 min, 1.5–5 hr and 11–12 hr post-dose) for all patients. The empirical design consisted of three sample time windows per patient from a total of nine windows that collectively represented the entire dose interval. Each patient was assigned to have one blood sample taken from three different windows. Windows for blood sampling times were also provided for the optimal design. Ninety six patients were recruited into the study who were currently receiving enoxaparin therapy. Patients were randomly assigned to either the optimal or empirical sampling design, stratified for body mass index. The exact times of blood samples and doses were recorded. Analysis was undertaken using NONMEM (version 5). The empirical design supported a one compartment linear model with additive residual error, while the optimal design supported a two compartment linear model with additive residual error as did the model derived from the full data set. A posterior predictive check was performed where the models arising from the empirical and optimal designs were used to predict into the full data set. This revealed the optimal design derived model was superior to the empirical design model in terms of precision and was similar to the model developed from the full dataset. This study suggests optimal design techniques may be useful, even when the optimized design was based on a model that was misspecified in terms of the structural and statistical models and when the implementation of the optimal designed study deviated from the nominal design.     

Designs for population pharmacodynamics: Value of pharmacokinetic data and population analysis

Analyses of simulated data from pharmacokinetic/pharmacodynamic (PK/PD) studies varying with respect to the amount and timing of observations were undertaken to assess the value of these design choices. The simulation models assume mono- or biexponential drug disposition, andE _max-type pharmacodynamics. Data analysis uses a combined PK/PD population analysis or a hybrid, individual-PK/population-PD analysis. Assuming that the goal of the PK/PD studies is to estimate population PD, performance of designs is judged by comparing the precision of estimates of population mean PD parameters and of their interindividual variability. The simulations reveal that (i) PK data, even in small number (2 points per person from as few as 25–50% of persons) are very valuable for estimating population PD; (ii) designs involving more individuals, even if many are sparsely sampled, dominate designs calling for more complete study of fewer persons; (iii) the population analysis is generally superior to the hybrid analysis, especially when the PK model is misspecified (biexponential assumed to be monoexponential for analysis); (iv) varying sampling times and doses among subjects protects against the ill effects of model misspecification. In general, the results are quite encouraging about the usefulness of sparse data designs to estimate population dose response. Work supported in part by U.S. Department of Health, Education and Welfare, Grants GM26676, GM26691.     

NONMEM法建立大鼠外周和中枢左旋多巴群体药动学模型

目的:建立大鼠左旋多巴(levodopa, LD)群体药动学模型,考察LD药动学参数的影响因素。方法:14只大鼠随机分为高、低两个剂量组,单次灌胃给予多巴丝肼片。采用脑微透析技术收集大鼠纹状体细胞外液透析液,同时采集外周血;高效液相色谱-电化学法测定透析液及血浆LD浓度,并利用非线性混合效应模型(Nonlinear mixed effect model, NONMEM)进行群体药动学数据分析。结果:建立了包含大鼠个体间变异、个体自身变异及体质量、给药剂量等固定效应参数的统计学模型,原始数据估算的参数值均位于Bootstrap估算参数值的2.5%~97.5%范围内,视觉预测评估法显示建模大鼠外周血和中枢纹状体LD浓度基本位于90%百分位数范围之内,所建立的最终模型稳定、有效、且有较强的预测能力。体质量可影响LD药动参数K₃₂。结论:建立的群体药动学模型能较好地描述LD在大鼠中枢及外周血的药动学特点。大鼠给药剂量对LD药动参数无影响,体质量可影响LD药动参数。     

Estimation of population pharmacokinetic parameters in the presence of non-compliance

In population pharmacokinetic (PK) studies, patients' drug plasma profiles are routinely analyzed assuming that all patients took their drug at the times and in the amounts specified. However, patient non-compliance with the prescribed drug regimen is a leading source of failure to drug therapy. It has been reported that over 30% of patients routinely skip doses regardless of their disease, prognosis, or symptoms. This brings into question the assumption regarding full compliance for population PK analyses. This paper describes the estimation of population PK parameters in the presence and absence of non-compliance while either assuming full compliance or estimating compliance using a hierarchical Bayesian approach. Assessment of compliance for a given dose was limited to one of three possibilities: no dose was taken at the prescribed time, the prescribed dose was taken at the prescribed time, or twice the prescribed dose was taken at the prescribed time. Simulated data sets based on a one-compartment pharmacokinetic model with first order elimination were analyzed using WinBUGS* (Bayesian inference Using Gibbs Sampling) software. An initial feasibility simulation experiment, using a simple, but informative PK sampling design with bolus input of drug, was performed. A second simulation study was then carried out using a more realistic sampling design and first-order input of drug. The simulated sampling design included observations after known doses as well as after uncertain doses. Results from the feasibility study revealed that when compliance was estimated instead of being assumed to be 100%, the relative prediction error for clearance (CL) decreased from 0.25 to 0.10 for 60% compliance and from 0.6 to 0.2 for 35% compliance. Estimates of the interoccasion variability of clearance were improved by compliance estimation but still had substantial positive bias. Estimated of interindividual variability were relatively insensitive to compliance estimation. Estimates for volume of distribution (V) and its associated variances were not affected by incorporation of compliance estimates, perhaps due to the specific sampling design that was used. The design was relatively uninformative regarding V. In the more realistic study, estimates for CL, V and the difference between the absorption rate constant and the elimination rate constant (KA-K) were improved by the incorporation of compliance estimation. The median relative errors were reduced from 0.51 to -0.01 for CL, from 0.49 to 0.04 for V, and from 0.49 to -0.02 for Ka-K. The bias in interoccasion variances for V and CL appeared to be reduced by compliance estimation while estimates of interindividual variability were not affected in a systematic fashion. The bias in the residual error variance was decreased from a relative error of about 2 to close to 0. The use of hierarchical Bayesian modeling with the incorporation of compliance estimation decreased the bias in the typical value parameter but the effects on variance parameters were less consistent. The encouraging results of these simulation experiments will hopefully stimulate further evaluation of this methodology for the estimation of population pharmacokinetic parameters in the presence of potential patient noncompliance.     

基于NONMEM法建立紫杉醇群体药动学模型

目的：建立国人紫杉醇（paclitaxel,PTX）群体药动学（population pharmacokinetic,PPK）模型,为制定个体化给药方案提供理论支持。方法：收集138例接受紫杉醇治疗的肿瘤患者（建模组105例,验证组33例）210个血样,HPLC法测定紫杉醇血药浓度,PCR-RFLP法检测MDR1 C3435T。应用非线性混合效应模型（NONMEM）法,考察MDR1 C3435T基因多态性、合并用药及病理生理因素对紫杉醇药动学参数的影响,建立紫杉醇PPK模型。对模型进行拟合优度诊断、自举法（Bootstrap）内部验证,正态预测分布误差法（NPDE）及外部验证考察模型预测能力。结果：紫杉醇清除率（CL）和表观分布容积（V_d）的群体典型值分别为64.7 L·h^-1和1 240 L,患者内生肌酐清除率（CLcr）和给药速率（RATE）显著影响紫杉醇清除率。最终模型Bootstrap法验证结果与模型计算值相符,拟合优度、准确度及精密度均优于最简模型。结论：紫杉醇PPK最终模型稳定、有效,可结合Bayesian反馈法为临床优化给药方案提供科学依据。     

A population pharmacokinetic study of alminoprofen penetration into synovial fluid

The pharmacokinetics of alminoprofen in plasma and synovial fluid (SF) at steady state (300 mg t.i.d.) was studied in 45 patients with knee effusion. Plasma and SF samples, one each per patient, were obtained. Six groups were made according to the time of sampling after ingestion of the 13th dose: 1h (n = 7), 2h (n = 7), 4h (n = 7), 6h (n = 10), 8h (n = 6), 12h (n = 8). A three-compartment model was used to describe alminoprofen kinetics in plasma and SF, with two parameterizations, a ‘classical’ and a ‘physiological’ one. The non-linear mixed effect model approach was used to estimate the mean and variance of the pharmacokinetic parameters. The mean ±SE of the estimates (coefficient of variation of interindividual variability as a percentage) were volume of distribution, 11.0 ± 1.711 (12%); elimination rate constant, 0.236 ± 0.025 h^?1 (18%); absorption rate constant 2.80 ± 0.31 h^?1 (464%), clearance of influx into SF, 0.29 ± 0.14 mL min^?1; clearance of efflux into plasma, 0.56 ± 0.25 mL min^?1. These two clearances were not significantly different, which indicates that passive diffusion occurs in both directions. The mean ±SD alminoprofen concentration versus time curve in plasma and SF at steady state was simulated and showed that the mean ±SD maximal concentration in SF was 8.1 ± 6.3 mg L^?1 and was obtained 4h after dose administration.     

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.