Pharmacy Service, University Hospital of Salamanca, Salamanca, Spain.
Ther Drug Monit. 2011 Oct;33(5):573-82. doi: 10.1097/FTD.0b013e31822d578b.
A relationship between plasma concentrations and viral suppression in patients receiving lopinavir (LPV)/ritonavir (RTV) has been observed. Therefore, it is important to increase our knowledge about factors that determine interpatient variability in LPV pharmacokinetics (PK).
The study, designed to develop and validate population PK models for LPV and RTV, involved 263 ambulatory patients treated with 400/100 mg of LPV/RTV twice daily. A database of 1110 concentrations of LPV and RTV (647 from a single time-point and 463 from 73 full PK profiles) was available. Concentrations were determined at steady state using high-performance liquid chromatography with ultraviolet detection. PK analysis was performed with NONMEM software. Age, gender, height, total body weight, body mass index, RTV trough concentration (RTC), hepatitis C virus coinfection, total bilirubin, hospital of origin, formulation and concomitant administration of efavirenz (EFV), saquinavir (SQV), atazanavir (ATV), and tenofovir were analyzed as possible covariates influencing LPV/RTV kinetic behavior.
Population models were developed with 954 drug plasma concentrations from 201 patients, and the validation was conducted in the remaining 62 patients (156 concentrations). A 1-compartment model with first-order absorption (including lag-time) and elimination best described the PK. Proportional error models for interindividual and residual variability were used. The final models for the drugs oral clearance (CL/F) were as follows: CL/F(LPV)(L/h)=0.216·BMI·0.81(RTC)·1.25(EFV)·0.84(ATV); CL/F(RTV)(L/h) = 8.00·1.34(SQV)·1.77(EFV)·1.35(ATV). The predictive performance of the final population PK models was tested using standardized mean prediction errors, showing values of 0.03 ± 0.74 and 0.05 ± 0.91 for LPV and RTV, and normalized prediction distribution error, confirming the suitability of both models.
These validated models could be implemented in clinical PK software and applied to dose individualization using a Bayesian approach for both drugs.
在接受洛匹那韦（LPV）/利托那韦（RTV）治疗的患者中，观察到血浆浓度与病毒抑制之间存在关系。因此，增加我们对决定 LPV 药代动力学（PK）个体间变异性的因素的了解非常重要。
本研究旨在开发和验证 LPV 和 RTV 的群体 PK 模型，共纳入 263 例接受 400/100mg LPV/RTV 每日两次治疗的门诊患者。有 1110 个 LPV 和 RTV 浓度（647 个来自单点，463 个来自 73 个完整 PK 谱）的数据库。使用高效液相色谱法结合紫外检测法在稳态时测定浓度。使用 NONMEM 软件进行 PK 分析。年龄、性别、身高、总体重、体重指数、RTV 谷浓度（RTC）、丙型肝炎病毒合并感染、总胆红素、原籍医院、制剂和同时使用依非韦伦（EFV）、沙奎那韦（SQV）、阿扎那韦（ATV）和替诺福韦被分析为可能影响 LPV/RTV 动力学行为的协变量。
从 201 例患者的 954 个药物血浆浓度中建立了群体模型，并在其余 62 例患者（156 个浓度）中进行了验证。一个具有一级吸收（包括滞后时间）和消除的 1 室模型最好地描述了 PK。用于个体间和残留变异性的比例误差模型被使用。两种药物口服清除率（CL/F）的最终模型如下：CL/F（LPV）（L/h）=0.216·BMI·0.81（RTC）·1.25（EFV）·0.84（ATV）；CL/F（RTV）（L/h）=8.00·1.34（SQV）·1.77（EFV）·1.35（ATV）。使用标准化平均预测误差测试最终群体 PK 模型的预测性能，显示 LPV 和 RTV 的值分别为 0.03±0.74 和 0.05±0.91，归一化预测分布误差，证实了这两种模型的适用性。
这些经过验证的模型可以在临床 PK 软件中实现，并应用于两种药物的贝叶斯方法个体化剂量。
