环孢素A在结缔组织病患者中的群体药代动力学研究

Population pharmacokinetics of cyclosporine A in patients with connective tissue disease

目的建立结缔组织病患者口服环孢素A的群体药代动力学模型,指导环孢素A个体化应用。方法回顾性收集环孢素A血药浓度数据,用非线性混合效应模型(NONMEM)法建立群体药代动力学模型,拟合优度图、自举法评价模型的预测性能,通过蒙特卡罗模拟推荐给药剂量。结果共收集119例结缔组织病患者的235个环孢素A血药浓度数据信息,患者总胆红素和总胆汁酸水平是影响环孢素A体内清除率的协变量。最终模型为:全身清除率=97.5×(TBIL/9.25)^(-1.61)×(TBA/4.77)^(-0.125);表观分布容积=3300 L(Fixed),其中,环孢素A的表观清除率的典型值为97.5 L·h^(-1),表观分布容积的群体典型值为3300 L。对于总胆红素<8μmol·L^(-1),总胆汁酸<6μmol·L^(-1)的患者,按照75 mg bid给药,血药浓度在治疗窗内的概率大于60%。结论用NONMEM法建立的结缔组织病患者的环孢素A群体药代动力学模型,经模型评价和验证,最终模型稳定且预测性能良好。可用于临床个体化给药方案的制定。

Objective To establish a population pharmacokinetic model of cyclosporine A in patients with connective tissue disease,and to guide the individualized application of cyclosporine A.Methods Methods Using the retrospectively collected data of blood concentration of cyclosporine A,a population pharmacokinetic model using nonlinear mixed effects model(NONMEM)was established.The stability and accuracy of the model were evaluated by using goodness of fit diagnostic map,bootstrap method and recommendation of drug dosage through Monte Carlo simulation.Results A total of 235 cyclosporine A blood concentration data of 119 patients were included in this study.The levels of total bilirubin and total bile acid were included in the model as covariates affecting pharmacokinetic parameters.The final model was established as clearance/bioavailability=97.5×(TBIL/9.25)^(-1.61)×(TBA/4.77)^(-0.125);apparent volume of distribution/bioavailability=3300 L(Fixed).The typical value of apparent clearance rate and volume of distribution were 97.5l L·h^(-1)and 3300 L.For patients with total bilirubin 8μmol·L^(-1)and total bile acid 6μmol·L^(-1),after given a dosing regimen of 75 mg bid,the probability of blood drug concentration in the treatment window could be more than 60%.Conclusion The population pharmacokinetic model of cyclosporine A in patients with connective tissue disease established by NONMEM method is stable and has good prediction performance after internal evaluation and external verification of the model.It can be used for the formulation of clinical individualized drug delivery scheme.