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基于生理的药代动力学建模预测钠-葡萄糖协同转运蛋白2抑制剂恩格列净在人体内的药代动力学

Physiologically Based Pharmacokinetic Modelling to Predict Pharmacokinetics of Enavogliflozin, a Sodium-Dependent Glucose Transporter 2 Inhibitor, in Humans.

作者信息

Kim Min-Soo, Song Yoo-Kyung, Choi Ji-Soo, Ji Hye Young, Yang Eunsuk, Park Joon Seok, Kim Hyung Sik, Kim Min-Joo, Cho In-Kyung, Chung Suk-Jae, Chae Yoon-Jee, Lee Kyeong-Ryoon

机构信息

College of Pharmacy, Seoul National University, Seoul 08826, Republic of Korea.

Laboratory Animal Resource Center, Korea Research Institute of Bioscience and Biotechnology, Cheongju 28116, Republic of Korea.

出版信息

Pharmaceutics. 2023 Mar 14;15(3):942. doi: 10.3390/pharmaceutics15030942.

Abstract

Enavogliflozin is a sodium-dependent glucose cotransporter 2 (SGLT2) inhibitor approved for clinical use in South Korea. As SGLT2 inhibitors are a treatment option for patients with diabetes, enavogliflozin is expected to be prescribed in various populations. Physiologically based pharmacokinetic (PBPK) modelling can rationally predict the concentration-time profiles under altered physiological conditions. In previous studies, one of the metabolites (M1) appeared to have a metabolic ratio between 0.20 and 0.25. In this study, PBPK models for enavogliflozin and M1 were developed using published clinical trial data. The PBPK model for enavogliflozin incorporated a non-linear urinary excretion in a mechanistically arranged kidney model and a non-linear formation of M1 in the liver. The PBPK model was evaluated, and the simulated pharmacokinetic characteristics were in a two-fold range from those of the observations. The pharmacokinetic parameters of enavogliflozin were predicted using the PBPK model under pathophysiological conditions. PBPK models for enavogliflozin and M1 were developed and validated, and they seemed useful for logical prediction.

摘要

恩格列净是一种钠依赖性葡萄糖协同转运蛋白2(SGLT2)抑制剂,已在韩国获批用于临床。由于SGLT2抑制剂是糖尿病患者的一种治疗选择,预计恩格列净将被处方给不同人群。基于生理的药代动力学(PBPK)模型可以合理预测生理条件改变下的浓度-时间曲线。在先前的研究中,其中一种代谢物(M1)的代谢比似乎在0.20至0.25之间。在本研究中,利用已发表的临床试验数据建立了恩格列净和M1的PBPK模型。恩格列净的PBPK模型在机械排列的肾脏模型中纳入了非线性尿液排泄,并在肝脏中纳入了M1的非线性形成。对该PBPK模型进行了评估,模拟的药代动力学特征与观察结果的范围相差两倍。在病理生理条件下,使用PBPK模型预测了恩格列净的药代动力学参数。建立并验证了恩格列净和M1的PBPK模型,它们似乎对逻辑预测有用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4e13/10058973/a100972ec878/pharmaceutics-15-00942-g001.jpg

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