Miao Zhang, Shudong Zhang, Zhiheng Yu, Xueting Yao, Zihan Lei, Pangke Yan, Nan Wu, Xu Wang, Qin Hu, Dongyang Liu
HSK7653, an oral dipeptidyl peptidase-4 inhibitor administered every 2 weeks, is a candidate for the treatment of type 2 diabetes mellitus. The major elimination pathway of HSK7653 in vivo is renal excretion, and hepatic metabolism and fecal excretion of unchanged compound contribute less to the systemic clearance of HSK7653. Considering the disposition characteristics and the potential indication population of HSK7653, evaluating the HSK7653 exposure in patients with renal impairment and geriatric populations is a prerequisite for bringing more benefits to the patients. Here, a PBPK model was developed based on in vitro experimental results, such as dissolution, permeability, and metabolism, and the in vivo renal clearance, to evaluate the effects of physiological factors and food on HSK7653 exposure in specific populations, including adult and elder individuals with renal impairment and geriatric populations. Simulation results showed that the AUC of HSK7653 increased by 46%, 82%, and 129% in adult patients with mild, moderate, and severe renal impairment, and by 56%, 78%, and 101% in patients aged 65-75, 75-85 and 85-95 years, respectively. The AUC increased in the range of 62%-83%, 98%-133%, and 153%-195% in elderly patients (65-95 years) with mild, moderate, and severe renal impairment, respectively. Moreover, two different absorption model development methods (dissolution profile method and the diffusion layer model method) predicted that food had no effect on the exposure of the same simulated population. Since the predicted AUC of HSK7653 at the 10 mg dose in various specific populations was still within the relatively flat results of the exposure-response analysis, the 10 mg dose of HSK7653 was first used to explore the exposure in the renal impairment population (CTR20221952).
Adult
Aged
Humans
Diabetes Mellitus, Type 2
Renal Elimination
Dipeptidyl-Peptidase IV Inhibitors
Administration, Oral
Tablets
Models, Biological
Computer Simulation
