Literature DB >> 27108678

Quantitative prediction of human pharmacokinetics and pharmacodynamics of imigliptin, a novel DPP-4 inhibitor, using allometric scaling, IVIVE and PK/PD modeling methods.

Dongyang Liu1, Xifeng Ma2, Yang Liu1, Huimin Zhou2, Chongtie Shi2, Frank Wu2, Ji Jiang1, Pei Hu3.   

Abstract

PURPOSE: To predict the pharmacokinetic/pharmacodynamic (PK/PD) profiles of imigliptin, a novel DPP-4 inhibitor, in first-in-human (FIH) study based on the data from preclinical species.
METHODS: Imigliptin was intravenously and orally administered to rats, dogs, and monkeys to assess their PK/PD properties. DPP-4 activity was the PD biomarker. PK/PD profiles of sitagliptin and alogliptin in rats and humans were obtained and digitized from literatures. PK/PD profiles of all dose levels for each drug in each species were analyzed using modeling approach. Human CL, Vss and PK profiles of imigliptin were then predicted using Allometric Scaling (AS), in vitro in vivo extrapolation (IVIVE), and the steady-state plasma drug concentration - mean residence time (Css-MRT) methods. In vitro EC50 corrected by fu and in vivo EC50 in rats corrected by interspecies difference of sitagliptin and alogliptin were utilized separately to predict imigliptin human EC50. The prediction by integrating all above methods was evaluated by comparing observed and simulated PK/PD profiles in healthy subjects.
RESULTS: Full PK/PD profiles in animal were summarized for imigliptin, sitagliptin and alogliptin. Imigliptin CL, Vss, and Fa were predicted to be 19.1L/h, 247L, and 0.81 in humans, respectively. Predicted imigliptin AUCs, AUECs, and Emax in humans were within 0.8-1.2 times of observed values whereas other predicted PK/PD parameters were within 0.5-1.5 times of observed values.
CONCLUSIONS: By integrating available preclinical and clinical data, FIH PK/PD profiles of imigliptin could be accurately predicted.
Copyright © 2016 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  First-in-human; Imigliptin; Pharmacodynamics; Pharmacokinetics; Prediction

Mesh:

Substances:

Year:  2016        PMID: 27108678     DOI: 10.1016/j.ejps.2016.04.020

Source DB:  PubMed          Journal:  Eur J Pharm Sci        ISSN: 0928-0987            Impact factor:   4.384


  3 in total

1.  Translational Modeling and Simulation in Supporting Early-Phase Clinical Development of New Drug: A Learn-Research-Confirm Process.

Authors:  Dongyang Liu; Yi Zhang; Ji Jiang; John Choi; Xuening Li; Dalong Zhu; Dawei Xiao; Yanhua Ding; Hongwei Fan; Li Chen; Pei Hu
Journal:  Clin Pharmacokinet       Date:  2017-08       Impact factor: 6.447

2.  Dipeptidyl-Peptidase-IV Inhibitors, Imigliptin and Alogliptin, Improve Beta-Cell Function in Type 2 Diabetes.

Authors:  Xu Liu; Yang Liu; Hongzhong Liu; Haiyan Li; Jianhong Yang; Pei Hu; Xinhua Xiao; Dongyang Liu
Journal:  Front Endocrinol (Lausanne)       Date:  2021-09-20       Impact factor: 5.555

Review 3.  Current trends in drug metabolism and pharmacokinetics.

Authors:  Yuhua Li; Qiang Meng; Mengbi Yang; Dongyang Liu; Xiangyu Hou; Lan Tang; Xin Wang; Yuanfeng Lyu; Xiaoyan Chen; Kexin Liu; Ai-Ming Yu; Zhong Zuo; Huichang Bi
Journal:  Acta Pharm Sin B       Date:  2019-10-18       Impact factor: 11.413

  3 in total

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