Wang Kun, Pan Chaohsuan, Xu Fengyan, Tse Archie N, Sheng Yucheng
Shanghai Qiangshi Information Technology Co., Ltd., Shanghai, China.
Cstone Pharmaceuticals (Suzhou) Co., Ltd., Shanghai, China.
Br J Clin Pharmacol. 2025 Mar;91(3):748-760. doi: 10.1111/bcp.16276. Epub 2024 Oct 10.
The aim of this study was to develop a population pharmacokinetics model for sugemalimab, a monoclonal antibody that targets programmed death-ligand 1 (PD-L1), using data from Phase I-III trials and to assess clinical factors affecting sugemalimab exposure.
A nonlinear mixed-effect modelling approach was employed to analyse pooled data from nine studies involving 1628 subjects to characterize the PopPK of sugemalimab. This investigation examined the influence of various covariates on sugemalimab pharmacokinetics (PK), encompassing demographics, baseline hepatic and renal function-related covariates, and others (including anti-drug antibody [ADA], combination treatment, Eastern Cooperative Oncology Group [ECOG] performance score, tumour burden and tumour type). Estimation accuracy and predictive ability of the final model were evaluated using various methods. The influence of covariates on sugemalimab exposure was assessed by simulation from the final model.
A two-compartment model with first-order elimination and time-varying clearance effectively described the PK of sugemalimab. Covariate analyses revealed significant relationships between sugemalimab clearance and body weight, albumin, gender, ADA, tumour burden and tumour type. The statistically significant covariates on central volume were body weight, albumin, gender and tumour type. No significant relationships were found in the final model for age, race, alanine aminotransferase, aspartate aminotransferase, creatinine, total bilirubin, alkaline phosphatase, combination treatment, creatinine clearance, ECOG, renal function or hepatic function. All significant covariates demonstrated less than a 20% effect on sugemalimab exposure.
The PopPK model adequately described the pharmacokinetic profile of sugemalimab with no clinically meaningful impact observed on its exposure across all covariates. Dose adjustment does not appear to be necessary.
本研究旨在利用I-III期试验数据,为靶向程序性死亡配体1(PD-L1)的单克隆抗体苏金单抗开发群体药代动力学模型,并评估影响苏金单抗暴露的临床因素。
采用非线性混合效应建模方法,分析来自9项研究的1628名受试者的汇总数据,以表征苏金单抗的群体药代动力学。本研究考察了各种协变量对苏金单抗药代动力学(PK)的影响,包括人口统计学、基线肝肾功能相关协变量以及其他因素(包括抗药物抗体[ADA]、联合治疗、东部肿瘤协作组[ECOG]体能状态评分、肿瘤负荷和肿瘤类型)。使用多种方法评估最终模型的估计准确性和预测能力。通过最终模型的模拟评估协变量对苏金单抗暴露的影响。
具有一级消除和时变清除率的二室模型有效地描述了苏金单抗的药代动力学。协变量分析显示,苏金单抗清除率与体重、白蛋白、性别、ADA、肿瘤负荷和肿瘤类型之间存在显著关系。对中央室容积有统计学意义的协变量是体重、白蛋白、性别和肿瘤类型。在最终模型中,未发现年龄、种族、丙氨酸氨基转移酶、天冬氨酸氨基转移酶、肌酐、总胆红素、碱性磷酸酶、联合治疗、肌酐清除率、ECOG、肾功能或肝功能有显著关系。所有显著的协变量对苏金单抗暴露的影响均小于20%。
群体药代动力学模型充分描述了苏金单抗的药代动力学特征,在所有协变量上均未观察到对其暴露有临床意义的影响。似乎无需进行剂量调整。