Literature DB >> 18936283

Model-based development of a PPARgamma agonist, rivoglitazone, to aid dose selection and optimize clinical trial designs.

Shashank Rohatagi1, Timothy J Carrothers, Jinyan Jin, William J Jusko, Tatiana Khariton, Joseph Walker, Kenneth Truitt, Daniel E Salazar.   

Abstract

A model-based approach was implemented for the development of the proliferator-activated receptor gamma (PPARgamma) agonist rivoglitazone. Population pharmacokinetic and pharmacodynamic models were developed using data collected from 2 phase I and 2 phase II studies in healthy volunteers and participants with type 2 diabetes mellitus. A 2-compartment model with first-order absorption and elimination and an absorption time lag best described rivoglitazone pharmacokinetics. Modified indirect-response models were used to characterize changes in fasting plasma glucose, HbA(1c), and hemodilution as a function of rivoglitazone plasma concentrations. In addition, differences in hemodilution among participants correlated with the incidence of edema. Current use of oral antidiabetic medication was a significant covariate for the fasting plasma glucose-HbA(1c) exposure-response model. Using a learn-and-confirm process, models developed prior to the second phase II study were able to make valid predictions for exposures and response variables in that study. In future studies, seamless designs can be supported by models such as those developed here.

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Year:  2008        PMID: 18936283     DOI: 10.1177/0091270008323260

Source DB:  PubMed          Journal:  J Clin Pharmacol        ISSN: 0091-2700            Impact factor:   3.126


  6 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

Review 2.  Peroxisome proliferator-activated receptor γ (PPARγ): A master gatekeeper in CNS injury and repair.

Authors:  Wei Cai; Tuo Yang; Huan Liu; Lijuan Han; Kai Zhang; Xiaoming Hu; Xuejing Zhang; Ke-Jie Yin; Yanqin Gao; Michael V L Bennett; Rehana K Leak; Jun Chen
Journal:  Prog Neurobiol       Date:  2017-10-12       Impact factor: 11.685

Review 3.  Paracrine and endocrine effects of adipose tissue on cancer development and progression.

Authors:  Jiyoung Park; David M Euhus; Philipp E Scherer
Journal:  Endocr Rev       Date:  2011-06-02       Impact factor: 19.871

4.  Evaluation of the long-term durability and glycemic control of fasting plasma glucose and glycosylated hemoglobin for pioglitazone in Japanese patients with type 2 diabetes.

Authors:  Frances Stringer; Joost DeJongh; Kazuaki Enya; Emiko Koumura; Meindert Danhof; Kohei Kaku
Journal:  Diabetes Technol Ther       Date:  2014-12-22       Impact factor: 6.118

5.  Pharmacometric Approaches to Guide Dose Selection of the Novel GPR40 Agonist TAK-875 in Subjects With Type 2 Diabetes Mellitus.

Authors:  H Naik; J Lu; C Cao; M Pfister; M Vakilynejad; E Leifke
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2013-01-09

6.  Clinical Trial Simulation to Inform Phase 2: Comparison of Concentrated vs. Distributed First-in-Patient Study Designs in Psoriasis.

Authors:  M G Dodds; D H Salinger; J Mandema; J P Gibbs; M A Gibbs
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2013-07-24
  6 in total

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