Drug Clinical Trial Center, Peking University Third Hospital, Beijing, 100191, China.
School of Pharmaceutical Sciences, Tsinghua University, Beijing, 100084, China.
Br J Clin Pharmacol. 2021 Jul;87(7):2711-2722. doi: 10.1111/bcp.14609. Epub 2021 May 18.
This study aims to develop and verify a physiologically based pharmacokinetic (PBPK) population model for the Chinese geriatric population in Simcyp.
Firstly, physiological information for the Chinese geriatric population was collected and later employed to develop the Chinese geriatric population model by recalibration of corresponding physiological parameters in the Chinese adult population model available in Simcyp (i.e., Chinese healthy volunteer model). Secondly, drug-dependent parameters were collected for six drugs with different elimination pathways (i.e., metabolized by CYP1A2, CYP3A4 or renal excretion). The drug models were then developed and verified by clinical data from Chinese adults, Caucasian adults and Caucasian elderly subjects to ensure that drug-dependent parameters are correctly inputted. Finally, the tested drug models in combination with the newly developed Chinese geriatric population model were applied to simulate drug concentration in Chinese elderly subjects. The predicted results were then compared with the observations to evaluate model prediction performance.
Ninety-eight per cent of predicted AUC, 95% of predicted C , and 100% of predicted CL values were within two-fold of the observed values, indicating all drug models were properly developed. The drug models, combined with the newly developed population model, were then used to predict pharmacokinetics in Chinese elderly subjects aged 60-93. The predicted AUC, C , and CL values were all within two-fold of the observed values.
The population model for the Chinese elderly subjects appears to adequately predict the concentration of the drug that was metabolized by CYP1A2, CYP3A4 or eliminated by renal clearance.
本研究旨在 Simcyp 中开发和验证适用于中国老年人群体的基于生理学的药代动力学（PBPK）群体模型。
首先，收集中国老年人群体的生理学信息，然后通过重新校准 Simcyp 中可用的中国成年人群体模型（即中国健康志愿者模型）中的相应生理学参数来开发中国老年人群体模型。其次，收集了六种具有不同消除途径的药物（即由 CYP1A2、CYP3A4 代谢或经肾脏排泄）的药物依赖性参数。然后，通过中国成年人、白种成年人和白种老年人的临床数据来开发和验证药物模型，以确保药物依赖性参数正确输入。最后，将新开发的中国老年人群体模型与经过测试的药物模型结合起来，用于模拟中国老年受试者的药物浓度。将预测结果与观察结果进行比较，以评估模型预测性能。
98%的预测 AUC、95%的预测 C 和 100%的预测 CL 值在观察值的两倍以内，表明所有药物模型均得到了正确开发。然后，将药物模型与新开发的人群模型结合起来，用于预测年龄在 60-93 岁的中国老年受试者的药代动力学。预测的 AUC、C 和 CL 值均在观察值的两倍以内。
该人群模型似乎能够充分预测由 CYP1A2、CYP3A4 代谢或经肾脏清除的药物的浓度。
