拉氧头孢对映异构体在儿童群体中的药动学研究和剂量优化

目的:建立拉氧头孢对映异构体在儿童患者中的群体药动学模型,研究拉氧头孢在儿童患者体内的药动学特点,为拉氧头孢在儿童患者中的个体化用药提供依据。方法:检测145例静脉滴注拉氧头孢患儿的血药浓度,收集患儿临床资料。采用非线性混合效应模型法建立拉氧头孢对映异构体在儿童患者群体中药动学模型,并用自举法、拟合优度图和正态化预测分布误差进行验证。采用蒙特卡洛模拟评价不同给药方案的合理性。结果:四房室模型可以较好描述拉氧头孢对映异构体在儿童患者体内的药动学特征。最终模型稳定,预测结果可靠。拉氧头孢R和S对映异构体的表观分布容积(V_d)分别为5.57 L和4.15 L,清除率(CL)分别为0.78 L·h^-1和1.32 L·h^-1。体质量对拉氧头孢异构体药动学参数有显著影响。结论:该研究成功建立了拉氧头孢对映异构体在儿童患者群体中的药动学模型,可为拉氧头孢的个体化用药提供参考。     

成年患者替考拉宁群体药动学研究

目的：构建中国成年患者替考拉宁（teicoplanin,TEC）群体药动学（population pharmacokinetics,PPK）模型,探讨TEC药动学参数的影响因素。方法：收集患者的用药信息、血药总浓度、性别、年龄、血清肌酐水平等信息,采用非线性混合效应模型法（nonlinear mixed effect model,NONMEM）建立替考拉宁PPK模型。用图形法、非参数自举法（bootstrap）、正态化预测分布误差法（normalized predictive distribution error,NPDE）进行模型评价。结果：共收集111例成年患者的149个替考拉宁血浆总浓度数据,建立了替考拉宁的一房室PPK模型：CL （L·h^-1）=1.26×（eGFR/82）^0.431,V（L）=83.1,协变量分析显示肌酐清除率（CKD-EPI公式）是影响替考拉宁清除率的重要因素,未发现影响替考拉宁表观分布容积的因素。经验证,最终模型具有良好的拟合优度、稳健率及预测性能。结论：临床可根据患者肌酐清除率（CKD-EPI公式）制定个体化给药方案。     

替考拉宁在特殊人群中药动学研究进展

替考拉宁是临床治疗耐甲氧西林金黄色葡萄球菌等耐药革兰阳性菌感染的首选药物之一。本文分别对近年来替考拉宁在老年人、儿童，重症感染、肾功能不全、低白蛋白血症、严重烧伤、血液肿瘤患者等特殊人群中的药动学研究进展进行综述，考察特殊病理生理状态对其疗效和安全性的影响，为临床合理用药提供参考。     

替考拉宁在不同人群中的药动学及给药方案分析

目的对替考拉宁在不同人群中的药动学及给药方案进行综述,以期为其在国内的临床合理应用提供参考。方法查阅国内外相关文献,归纳替考拉宁在健康志愿者、新生儿和儿童ICU患者、老年人、连续流动时腹膜透析的肾终末期患者、慢性肾功能衰竭患者等人群中的药动学及给药方案。结果与结论替考拉宁具有抗菌优势和低毒性等特点,因而在临床应用上有着广阔的前景,替考拉宁在国内人群中的药动学需要进一步研究。     

去甲万古霉素成人药动学数据外推至儿童群体和剂量优化

目的：获得去甲万古霉素在儿童群体中的药动学特征,优化给药方案以指导临床个体化用药。方法：将成人去甲万古霉素群体药动学（PPK）模型外推得到儿童模型;通过拟合优度图（goodness-of-fit）、可视化预测检验（VPC）及正态化预测分布误差（NPDE）验证外推模型的稳定性和预测性能。采用贝叶斯法获取个体药动学参数,通过蒙特卡洛模拟法评价和优化给药方案。结果：去甲万古霉素在儿童群体中药动学参数的群体均值分别为总体清除率（CL）0.11 L·kg^-1·h^-1、中央室分布容积（V₁）6.08 L、周边室分布容积（V₂）6.21 L、室间清除率（Q）2.32 L·h^-1。拟合优度、VPC和NPDE结果表明外推模型稳定性和预测性能均较好。蒙特卡洛模拟结果提示对于肾功能正常的患儿,去甲万古霉素用于治疗不同MIC（0.25,0.5,0.75和1 mg·L^-1）细菌感染时,要使体内暴露水平的目标获得概率（PTA）达到90%以上,对葡萄球菌属的理想日剂量应分别为16,32和48 mg·kg^-1及以上,对肠球菌属的理想日剂量应分别为16,24,32和40 mg·kg^-1。结论：本研究成功外推得到去甲万古霉素在儿童群体的药动学模型和参数,模拟结果显示,现行去甲万古霉素给药剂量可能偏低。     

老年重症耐甲氧西林金黄色葡萄球菌感染患者替考拉宁的药动学研究和药效学评价

目的 探讨耐甲氧西林金黄色葡萄球菌（methicillin-resistant Staphylococcus aureus,MRSA）肺部感染老年患者替考拉宁的药动学差异与药效学评价。方法 研究纳入2018年9月—2019年8月诊断为MRSA肺部感染患者50例,治疗前下呼吸道痰液标本培养提示为MRSA感染并对替考拉宁敏感。所有患者予静脉输注替考拉宁,前3剂400 mg,每12 h给药1次,维持剂量400 mg每24 h给药1次。将达到稳态后第5次给药前测得C_min≤10 μg·mL^-1的患者维持剂量方案更改为600 mg qd。注射用替考拉宁400 mg或600 mg溶于100 mL 0.9%氯化钠注射液,给药时间为30 min,疗程为14~21 d。按规定时间采集静脉血2 mL,采用HPLC检测血药浓度,使用DAS 3.0软件处理,求出各例患者的药动学参数。将达稳态后第5次给药前测得C_min>10 μg·mL^-1的药动学参数设为A;对于C_min≤10 μg·mL^-1的患者,将维持剂量调整为600 mg qd,并将调整剂量后第5次给药前测得C_min>10 μg·mL^-1的药动学参数设为B。按照APACHE II评分和SOFA评分将患者分为重症和非重症2组。结合PK/PD原理,比较2组患者在C_min处于10~20 μg·mL^-1和20~30 μg·mL^-1以及AUC/MIC≥345和<345的临床治疗有效率、细菌清除率及不良反应发生情况。结果 替考拉宁药动学以二室模型描述最佳。负荷剂量相同时,维持剂量为400 mg的A组与维持剂量为600 mg的B组药动学参数比较如下：C_max[（32.28±15.16） mg·L^-1vs（65.73±28.96） mg·L^-1],t_1/2[（86.24±10.61） h vs（70.51±11.78） h],V_d[（2.73±1.32） L·kg^-1vs（2.58±1.02） L·kg^-1],CL[（0.11±0.05） L·h^-1·kg^-1vs（0.13±0.06） L·h^-1·kg^-1],AUC_（0~t）[（2 698.16±1 603.25） mg·h·L^-1vs（4 076.85±1 873.09） mg·h·L^-1],AUC_（0~∞）[（4 509.33±2 786.54） mg·h·L^-1vs（7 193.58±4 109.81） mg·h·L^-1],差异有统计学意义（P<0.05）。患者SOFA评分≤5和>5的临床有效率为65.71%和53.33%,细菌清除率分别为65.79%和47.37%。APACHEII评分≤15和>15的临床有效率分别为63.64%和58.82%,细菌清除率分别为63.16%和52.63%。结论 MRSA肺部感染老年患者替考拉宁的药动学存在较大差异,结合PK/PD原理,能够为个体化治疗提供科学的给药方案。     

基于药动学理论脓毒症患者替考拉宁个体化给药分析

目的 探讨临床药师利用药动学理论指导脓毒症患者替考拉宁个体化给药的可行性。方法 临床药师通过参与1例脓毒症抗感染治疗案例,结合监测结果和患者药动学分析,为临床提供药物处置对策和监护建议。结果 临床药师在2次会诊中,结合监测结果对患者进行抗菌药物药动学分析,提出替考拉宁个体化的处置对策和监护计划,保障个体化给药的实施。结论 临床药师对脓毒症患者药动学改变进行全面评估,配合治疗药物监测手段,能够辅助临床医生做好个体化用药工作。     

头孢哌酮钠舒巴坦钠在儿童群体中的药动学研究和剂量优化

目的： 考察头孢哌酮在儿童群体中的药动学特征,促进个体化用药。方法： 收集140例患儿的临床资料和血药浓度数据。采用非线性混合效应模型法建立头孢哌酮在儿童群体中的群体药动学模型,用拟合优度（Goodness-of-fit）、直观预测检验法（VPC）、正态化预测分布误差（NPDE）验证最终模型的预测性能。采用模拟试验评价不同用药方案的合理性。结果： 最终模型评价结果表明模型稳定、预测结果可靠,得到的头孢哌酮药动学参数为：表观分布容积（V_d）0.86 L,清除率（CL）0.38 L·h^-1。模型结构显示患儿的体质量及肾小球滤过率是影响药动学参数的显著性因素。基于此模型最终确定各年龄段儿童的最优给药方案为：针对大肠埃希菌,新生儿患者为30 mg·kg^-1,qid,静滴2 h;1个月~2岁患儿为20 mg·kg^-1,qid,静滴2 h;2~14岁患儿为10 mg·kg^-1,tid,静滴2 h;针对肺炎克雷伯菌,新生儿患者为10 mg·kg^-1,tid,静滴2 h;1个月~2岁患儿为10 mg·kg^-1,tid,静滴2 h;2~14岁患儿为10 mg·kg^-1,bid,静滴2 h。结论： 本研究成功建立了头孢哌酮在儿童患者中的药动学模型,并借此模型推导出不同年龄段患儿针对大肠埃希菌及肺炎克雷伯菌的最佳给药方案。     

替考拉宁的药动学和药效学特点及给药方案研究进展

摘要：替考拉宁是治疗严重革兰阳性菌感染的首选药物之一。替考拉宁半衰期长,蛋白结合率高,属于时间依赖性药物, 临床疗效与AUC/MIC相关。替考拉宁在不同人群中的药动学参数变异大,应监测替考拉宁谷浓度进行个体化用药方案的调整。 本文通过查阅国内外文献,对替考拉宁在危重症患者、肾功能不全、低蛋白血症、儿童、老年人等特殊人群的药动学、给药方 案进行综述,以期为临床提供参考。     

早产儿氟康唑群体药动学模型的外部验证和剂量优化

目的:验证现有的早产儿氟康唑群体药动学模型对外部数据的预测准确性,并对给药剂量进行优化,为早产儿的个体化给药提供参考.方法:通过文献检索,提取国内外已发表的关于氟康唑的早产儿群体药动学模型信息.收集30例使用氟康唑的早产儿临床资料和血药浓度数据,采用拟合优度法、可视化预测检验法(visual predictive ch...     

Population pharmacokinetics and dosing optimization of teicoplanin in children with malignant haematological disease

Aim

Children with haematological malignancy represent an identified subgroup of the paediatric population with specific pharmacokinetic parameters. In these patients, inadequate empirical antibacterial therapy may result in infection-related morbidity and increased mortality, making optimization of the dosing regimen essential. As paediatric data are limited, our aim was to evaluate the population pharmacokinetics of teicoplanin in order to define the appropriate dosing regimen in this high risk population.

Methods

The current dose of teicoplanin was evaluated in children with haematological malignancy. Population pharmacokinetics of teicoplanin were analyzed using nonmem software. The dosing regimen was optimized based on the final model.

Results

Eighty-five children (age range 0.5 to 16.9 years) were included. Therapeutic drug monitoring and opportunistic samples (n = 143) were available for analysis. With the current recommended dose of 10 mg kg^–1 day^–1, 41 children (48%) had sub-therapeutic steady-state trough concentrations (C_ss,min<10 mg l^–1). A two compartment pharmacokinetic model with first order elimination was developed. Systematic covariate analysis identified that bodyweight (size) and creatinine clearance significantly influenced teicoplanin clearance. The model was validated internally. Its predictive performance was further confirmed in an external validation. In order to reach the target AUC of 750 mg l^–1 h 18 mg kg^–1 was required for infants, 14 mg kg^–1 for children and 12 mg kg^–1 for adolescents. A patient-tailored dose regimen was further developed and reduced variability in AUC and C_ss,min values compared with the mg kg^–1 basis dose, making the modelling approach an important tool for dosing individualization.

Conclusions

This first population pharmacokinetic study of teicoplanin in children with haematological malignancy provided evidence-based support to individualize teicoplanin therapy in this vulnerable population.     

Population pharmacokinetics of teicoplanin in patients with endocarditis

Teicoplanin is a new glycopeptide antibiotic, active against aerobic and anaerobic gram-positive bacteria. The drug is intended for the treatment of systemic infections including endocarditis. In two U.S. clinical safety and efficacy trials, loading doses of 6 to 30 mg/kg doses of teicoplanin were administered initially to 197 patients, followed by once-a-day treatment of approximately the same doses over several weeks. Blood samples were collected sporadically during the study to monitor serum teicoplanin concentrations either by FPIA or microbiological assay. Nonlinear mixed-effects modeling was performed on these data to characterize the population pharmacokinetics of teicoplanin that were best described by a two-compartment model. Patient body weight, concomitant gram-positive drug treatment, and serum creatinine had significant influences on systemic clearance(CL) of the glycopeptide. In addition, body weight affected the volume of distribution of the central compartment(Vc). Other demographic factors such as age, gender, etc., had no effects. The FPIA assay method was more precise than the microbiological assay.     

Population pharmacokinetics of lamotrigine in Chinese children with epilepsy

Aim:

To establish a population pharmacokinetics (PPK) model for lamotrigine (LTG) in Chinese children with epilepsy in order to formulate an individualized dosage guideline.

Methods:

LTG steady-state plasma concentration data from therapeutic drug monitoring (TDM) were collected retrospectively from 284 patients, with a total of 404 plasma drug concentrations. LTG concentrations were determined using a HPLC method. The patients were divided into 2 groups: PPK model group (n=116) and PPK valid group (n=168). A PPK model of LTG was established with NONMEM based on the data from PPK model group according to a one-compartment model with first order absorption and elimination. To validate the basic and final model, the plasma drug concentrations of the patients in PPK model group and PPK valid group were predicted by the two models.

Results:

The final regression model for LTG was as follows: CL (L/h)=1.01^*(TBW/27.87)^0.635*e^−0.753*VPA*e^0.868*CBZ*e^0.633*PB, Vd (L)= 16.7^*(TBW/27.87). The final PPK model was demonstrated to be stable and effective in the prediction of serum LTG concentrations by an internal and external approach validation.

Conclusion:

A PPK model of LTG in Chinese children with epilepsy was successfully established with NONMEM. LTG concentrations can be predicted accurately by this model. The model may be very useful for establishing initial LTG dosage guidelines.     

Population pharmacokinetics modeling of levetiracetam in Chinese children with epilepsy

Aim:

To establish a population pharmacokinetics (PPK) model of levetiracetam in Chinese children with epilepsy.

Methods:

A total of 418 samples from 361 epileptic children in Peking University First Hospital were analyzed. These patients were divided into two groups: the PPK model group (n=311) and the PPK validation group (n=50). Levetiracetam concentrations were determined by HPLC. The PPK model of levetiracetam was established using NONMEM, according to a one-compartment model with first-order absorption and elimination. To validate the model, 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 calculated.

Results:

A regression equation of the basic model of levetiracetam was obtained, with clearance (CL/F)=0.988 L/h, volume of distribution (V/F)=12.3 L, and K_a=1.95 h⁻¹. The final model was as follows: K_a=1.56 h⁻¹, V/F=12.1 (L), CL/F=1.04×(WEIG/25)^0.583 (L/h). For the basic model, the MPE, MSPE, RMSPE, WRES, and the 95%CI were 9.834 (−0.587–197.720), 50.919 (0.012–1286.429), 1.680 (0.021–34.184), and 0.0621 (−1.100–1.980). For the final model, the MPE, MSPE, RMSPE, WRES, and the 95% CI were 0.199 (−0.369–0.563), 0.002082 (0.00001–0.01054), 0.0293 (0.001−0.110), and 0.153 (−0.030–1.950).

Conclusion:

A one-compartment model with first-order absorption adequately described the levetiracetam concentrations. Body weight was identified as a significant covariate for levetiracetam clearance in this study. This model will be valuable to facilitate individualized dosage regimens.     

Covariate effects and population pharmacokinetics of lamivudine in HIV-infected children

Aim

Lamivudine is used as first line therapy in HIV-infected children. Yet, like many other paediatric drugs, its dose rationale has been based on limited clinical data, without thorough understanding of the effects of growth on drug disposition. Here we use lamivudine to show how a comprehensive population pharmacokinetic model can account for the influence of demographic covariates on exposure (i.e. AUC and C_max).

Methods

Data from three paediatric trials were used to describe the pharmacokinetics across the overall population. Modelling was based on a non-linear mixed effects approach. A stepwise procedure was used for covariate model building.

Results

A one compartment model with first order elimination best described the pharmacokinetics of lamivudine in children. The effect of weight on clearance (CL) and volume of distribution (V) was characterized by an exponential function, with exponents of 0.705 and 0.635, respectively. For a child with median body weight (17.6 kg), CL and V were 16.5 (95% CI 15.2, 17.7) l h⁻¹ and 46.0 (95% CI 42.4, 49.5) l, respectively. There were no differences between formulations (tablet and solution). The predicted AUC(0,12 h) after twice daily doses of 4 mg kg⁻¹ ranged from 4.44 mg l⁻¹ h for children <14 kg to 7.25 mg l⁻¹ h for children >30 kg.

Conclusions

The use of meta-analysis is critical to identify the correct covariate-parameter relationships, which must be assessed before a model is applied for predictive purposes (e.g. defining dosing recommendations for children). In contrast to prior modelling efforts, we show that the covariate distribution in the target population must be considered.