加药
医学
药理学
药效学
药代动力学
二肽基肽酶
二肽基肽酶-4
非金属
人口
利格列汀
2型糖尿病
内科学
糖尿病
内分泌学
化学
生物化学
环境卫生
酶
作者
Cheng Cui,Fangrui Cao,Iok Ian Kong,WU Qing-he,Fangqiong Li,Haiyan Li,Dongyang Liu
摘要
Abstract Aim To employ a model‐informed drug development approach in facilitating decision making and expediting the clinical progress of cofrogliptin (HSK7653), a novel ultralong‐acting dipeptidyl peptidase‐4 (DPP‐4) inhibitor, for the treatment of type 2 diabetes (T2D) via a biweekly dosing regimen. Methods Firstly, a population pharmacokinetics and pharmacodynamics (PopPKPD) model was developed using PK and PD data from a single ascending dose study to simulate the PK and PD time profiles of HSK7653 after multiple doses. Secondly, model‐based meta‐analysis (MBMA) was performed on published clinical studies of Eastern Asian subjects for all DPP‐4 inhibitors. We hypothesized a consistent relationship between PK and DPP‐4 inhibition in both healthy individuals and in those with T2D, establishing a quantitative correlation between DPP‐4 inhibition and HbA1c. Finally, the predicted PK/DPP‐4 inhibition/HbA1c profiles were validated by T2D patients in late clinical trials. Results The PK/DPP‐4 inhibition/HbA1c profiles of T2D patients treated with HSK7653 matched the modelled data. Our PopPKPD and MBMA models predict multiple ascending dosing PK and PD characteristics from single ascending dosing data, as well as the long‐term efficacy in T2D patients, based on healthy subjects. Conclusions Successful waiver approval for the phase 2b dose‐finding study was achieved through model‐informed recommendations, facilitating the clinical development of HSK7653 and other DPP‐4 inhibitors.
科研通智能强力驱动
Strongly Powered by AbleSci AI