Department of Pharmacy, The First People's Hospital of Changzhou, The Third Affiliated Hospital of Soochow University, Changzhou, Jiang Su, 213003, China.
BMC Cancer. 2024 Nov 1;24(1):1346. doi: 10.1186/s12885-024-13118-4.
This study aimed to develop a population pharmacokinetic (PPK) model for oral apatinib in Chinese oncology patients and investigate the factors influencing the pharmacokinetics of apatinib.
We gathered 199 blood concentration monitoring data points from 91 inpatient oncology participants receiving oral apatinib at the Third Affiliated Hospital of Soochow University. Covariates, such as age, gender, body weight, and indices of liver and renal function, were examined to assess their influence on the pharmacokinetic parameters of apatinib. The PPK model was developed using the nonlinear mixed-effects modeling procedure (NONMEM), and model validation was conducted using the bootstrap method and normalized prediction distribution error (NPDE) method.
The structural model adopted a one-compartment structure with first-order elimination. Notably, aspartate aminotransferase (AST) and the co-administered drug type emerged as primary covariates affecting apatinib clearance (CL/F). The finalized model was expressed as CL/F (L/h) = 56.7 × (AST/26.6) × θ, when apatinib was combined with monoclonal antibodies, θ was 1; when combined with paclitaxel, θ was 0.58; when combined with other drugs (e.g., platinum, capecitabine, or the combination of tegafur, gimeracil, and oteracil potassium), θ was 1.60; When used as monotherapy, θ was 1.38. V/F = 674 L, and the absorption rate constant (Ka) was fixed at 0.08 h. Bootstrap results affirmed the model's reliability and stability, while NPDE outcomes attested to the model's fit.
Our study successfully established a PPK model for apatinib in oncology patients, revealing that liver function status and co-administered drug types significantly impacted apatinib CL/F. This finding underscored the potential necessity for dose adjustments to optimize efficacy, particularly in patients undergoing different chemotherapy regimens involving apatinib.
本研究旨在建立中国肿瘤患者口服阿帕替尼的群体药代动力学（PPK）模型，并探讨影响阿帕替尼药代动力学的因素。
我们收集了 91 名在苏州大学附属第三医院接受口服阿帕替尼治疗的住院肿瘤患者的 199 个血药浓度监测数据点。检查了年龄、性别、体重和肝肾功能指标等协变量，以评估它们对阿帕替尼药代动力学参数的影响。采用非线性混合效应模型（NONMEM）程序建立 PPK 模型，并采用 bootstrap 方法和归一化预测分布误差（NPDE）方法进行模型验证。
结构模型采用一室模型和一级消除。值得注意的是，天冬氨酸氨基转移酶（AST）和联合用药类型是影响阿帕替尼清除率（CL/F）的主要协变量。最终模型表示为 CL/F（L/h）=56.7×（AST/26.6）×θ，当阿帕替尼与单克隆抗体联合使用时，θ为 1；与紫杉醇联合使用时，θ为 0.58；与其他药物（如铂类、卡培他滨或替加氟、吉美嘧啶、奥替拉西钾联合）联合使用时，θ为 1.60；单用时，θ为 1.38。V/F=674 L，吸收速率常数（Ka）固定为 0.08 h。Bootstrap 结果证实了模型的可靠性和稳定性，而 NPDE 结果证明了模型的拟合度。
本研究成功建立了肿瘤患者阿帕替尼的 PPK 模型，表明肝功能状态和联合用药类型显著影响阿帕替尼 CL/F。这一发现强调了在不同化疗方案中使用阿帕替尼时，需要调整剂量以优化疗效，特别是在患者中。
