Zapke Sonja E, Willmann Stefan, Grebe Scott-Oliver, Menke Kristin, Thürmann Petra A, Schmiedl Sven
Department of Clinical Pharmacology, School of Medicine, Faculty of Health, Witten/Herdecke University, Witten, Germany.
Bayer AG, Research and Development, Clinical Pharmacometrics, Wuppertal, Germany.
Front Pharmacol. 2021 May 14;12:630904. doi: 10.3389/fphar.2021.630904. eCollection 2021.
This study compared simulations of a physiologically based pharmacokinetic (PBPK) model implemented for cyclosporine with drug levels from therapeutic drug monitoring to evaluate the predictive performance of a PBPK model in a clinical population. Based on a literature search model parameters were determined. After calibrating the model using the pharmacokinetic profiles of healthy volunteers, 356 cyclosporine trough levels of 32 renal transplant outpatients were predicted based on their biometric parameters. Model performance was assessed by calculating absolute and relative deviations of predicted and observed trough levels. The median absolute deviation was 6 ng/ml (interquartile range: 30 to 31 ng/ml, minimum = -379 ng/ml, maximum = 139 ng/ml). 86% of predicted cyclosporine trough levels deviated less than twofold from observed values. The high intra-individual variability of observed cyclosporine levels was not fully covered by the PBPK model. Perspectively, consideration of clinical and additional patient-related factors may improve the model's performance. In summary, the current study has shown that PBPK modeling may offer valuable contributions for pharmacokinetic research in clinical drug therapy.
本研究将为环孢素实施的基于生理的药代动力学(PBPK)模型模拟结果与治疗药物监测中的药物水平进行比较,以评估PBPK模型在临床人群中的预测性能。基于文献检索确定模型参数。在使用健康志愿者的药代动力学曲线校准模型后,根据32名肾移植门诊患者的生物特征参数预测了他们的356次环孢素谷浓度。通过计算预测谷浓度与观察谷浓度的绝对偏差和相对偏差来评估模型性能。中位绝对偏差为6 ng/ml(四分位间距:30至31 ng/ml,最小值 = -379 ng/ml,最大值 = 139 ng/ml)。86%的预测环孢素谷浓度与观察值的偏差小于两倍。PBPK模型并未完全涵盖观察到的环孢素水平的高个体内变异性。从长远来看,考虑临床和其他与患者相关的因素可能会改善模型性能。总之,当前研究表明PBPK建模可能为临床药物治疗中的药代动力学研究做出有价值的贡献。