Clinical Pharmacology and Quantitative Pharmacology, Clinical Pharmacology and Safety Science, R&D, AstraZeneca, Cambridge, UK.
IntiQuan GmbH, Basel, Switzerland.
J Clin Pharmacol. 2024 Nov;64(11):1419-1431. doi: 10.1002/jcph.2492. Epub 2024 Jul 19.
Adavosertib (AZD1775) is a potent small-molecule inhibitor of Wee1 kinase. This analysis utilized pharmacokinetic data from 8 Phase I/II studies of adavosertib to characterize the population pharmacokinetics of adavosertib in patients (n = 538) with solid tumors and evaluate the impact of covariates on exposure. A nonlinear mixed-effects modeling approach was employed to estimate population and individual parameters from the clinical trial data. The model for time dependency of apparent clearance (CL) was developed in a stepwise manner and the final model validated by visual predictive checks (VPCs). Using an adavosertib dose of 300 mg once daily on a 5 days on/2 days off dosing schedule given 2 weeks out of a 3-week cycle, simulation analyses evaluated the impact of covariates on the following exposure metrics at steady state: maximum concentration during a 21-day cycle, area under the curve (AUC) during a 21-day cycle, AUC during the second week of a treatment cycle, and AUC on day 12 of a treatment cycle. The final model was a linear 2-compartment model with lag time into the dosing compartment and first-order absorption into the central compartment, time-varying CL, and random effects on all model parameters. VPCs and steady-state observations confirmed that the final model satisfied all the requirements for reliable simulation of randomly sampled Phase I and II populations with different covariate characteristics. Simulation-based analyses revealed that body weight, renal impairment status, and race were key factors determining the variability of drug-exposure metrics.
阿得沃替布(adavosertib,AZD1775)是一种有效的 Wee1 激酶小分子抑制剂。该分析利用了 8 项阿得沃替布 I/II 期研究的药代动力学数据,旨在对接受阿得沃替布治疗的实体瘤患者(n=538)的阿得沃替布群体药代动力学进行特征描述,并评估协变量对暴露量的影响。采用非线性混合效应模型分析方法,从临床试验数据中估算群体和个体参数。采用逐步法建立表观清除率(CL)时间依赖性模型,并通过可视化预测检查(VPC)验证最终模型。采用 2 周 3 周给药周期方案,以 300mg 剂量每天 1 次、每 5 天给药 2 天的方案给药,模拟分析评估了协变量对稳态时以下暴露量指标的影响:21 天周期内的最大浓度、21 天周期内的曲线下面积(AUC)、治疗周期第 2 周的 AUC 和治疗周期第 12 天的 AUC。最终模型是一个线性 2 室模型,具有给药间隔的滞后时间和进入中央室的 1 阶吸收,时变 CL,以及所有模型参数的随机效应。VPC 和稳态观察结果证实,最终模型满足对具有不同协变量特征的随机抽样 I/II 期人群进行可靠模拟的所有要求。基于模拟的分析结果表明,体重、肾功能损害状况和种族是决定药物暴露量指标变异性的关键因素。