Zhang Xinyue, Xue Hao, Xu Jialei, Ren Ke, Qian Fangyi, Zhang Yifan, Dou Jingru, Shen Kai, Zhu Xiao, Xiang Xiaoqiang, He Qingfeng
Department of Clinical Pharmacy and Pharmacy Administration, School of Pharmaceutical Sciences, Fudan University, Shanghai, China.
Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China.
Pediatr Diabetes. 2025 Aug 7;2025:8857248. doi: 10.1155/pedi/8857248. eCollection 2025.
This study aimed to present a quantitative modeling and simulation approach for oral henagliflozin, a selective sodium-glucose cotransporter 2 (SGLT2) inhibitor primarily metabolized by uridine diphosphate-glucuronosyltransferase (UGT) enzymes. A physiologically-based pharmacokinetic (PBPK) model for henagliflozin was developed using in vitro metabolism and clinical pharmacokinetic (PK) data, with validation across multiple contexts, including healthy adults, and hepatic impairment populations. Additionally, empirical pharmacodynamic (PD) modeling was employed to optimize pediatric dosing based on exposure-response relationships for urinary glucose excretion (UGE). Predicting henagliflozin exposure in pediatric patients poses challenges due to UGT enzyme ontogeny and the scarcity of clinical PK data in younger age groups. Using twofold acceptance criteria, model-predicted and observed drug exposures and PK parameters (area under the curve and peak concentration) were compared in diverse scenarios, including monotherapy in healthy adults (single/multiple doses), hepatic impairment, and extrapolation to pediatric age groups. The PBPK model accurately captured observed exposures within a twofold range in both adults and adolescents, supporting the model's predictive utility. The verified PBPK and empirical PD models informed dosing recommendations in pediatric populations aged 1 month to 18 years, achieving henagliflozin exposures comparable to those in adult patients receiving a 5-10 mg dose. This study shows that PBPK and PD modeling effectively guide pediatric dosing of henagliflozin, reducing trial reliance and supporting real-world validation.
本研究旨在提出一种口服恩格列净的定量建模与模拟方法,恩格列净是一种选择性钠-葡萄糖协同转运蛋白2(SGLT2)抑制剂,主要由尿苷二磷酸葡萄糖醛酸转移酶(UGT)代谢。利用体外代谢和临床药代动力学(PK)数据,开发了恩格列净的基于生理的药代动力学(PBPK)模型,并在包括健康成年人和肝功能损害人群在内的多种情况下进行了验证。此外,采用经验药效学(PD)建模,根据尿糖排泄(UGE)的暴露-反应关系优化儿科给药方案。由于UGT酶的个体发育以及较年轻年龄组临床PK数据的匮乏,预测儿科患者的恩格列净暴露量具有挑战性。采用两倍接受标准,在多种情况下比较了模型预测和观察到的药物暴露量及PK参数(曲线下面积和峰浓度),包括健康成年人的单药治疗(单剂量/多剂量)、肝功能损害以及外推至儿科年龄组。该PBPK模型在成年人和青少年中均能在两倍范围内准确捕捉观察到的暴露量,支持了该模型的预测效用。经过验证的PBPK和经验PD模型为1个月至18岁儿科人群的给药建议提供了依据,使恩格列净的暴露量与接受5-10毫克剂量的成年患者相当。本研究表明,PBPK和PD建模有效地指导了恩格列净的儿科给药,减少了对试验的依赖并支持了实际验证。