Literature DB >> 22380769

Population PK/PD analysis of metformin using the signal transduction model.

Jung-woo Chae1, In-hwan Baek, Byung-yo Lee, Seong-kwon Cho, Kwang-il Kwon.   

Abstract

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT: Metformin, a biguanide glucose lowering agent, is commonly used to manage type 2 diabetes. The molecular mechanisms of metformin have not been fully identified, but turnover of biomarkers such as glucose and signalling pathways or translocation of glucose transporters are closely related to the glucose-lowering effects of metformin. The PK/PD of metformin have been investigated in healthy humans and patients with type 2 diabetes mellitus and modelling has been performed using an indirect response model. WHAT THIS STUDY ADDS: The purpose of this investigation was to develop a population PK/PD model for metformin using a signal transduction model in healthy humans and predict the PK/PD profile in patients with type 2 diabetes. The aim was to compare a previous model (a biophase model) with the signal transduction model, and use a more appropriate model to follow the actions of metformin. Additionally, our developed model was appropriate to predict the time course of plasma metformin and fasting plasma glucose (FPG) concentrations in patients with type 2 diabetes. To our knowledge, this is the first published population PK/PD analysis using the signal transduction model for metformin. AIMS To develop a population pharmacokinetic (PK) and pharmacodynamic (PD) model for metformin (500 mg) using the signal transduction model in healthy humans and to predict the PK/PD profile in patients with type 2 diabetes.
METHODS: Following the oral administration of 500 mg metformin to healthy humans, plasma concentrations of metformin were measured using LC-MS/MS. A sequential modelling approach using NONMEM VI was used to facilitate data analysis. Monte Carlo simulation was performed to predict the antihyperglycaemic effect in patients with type 2 diabetes.
RESULTS: Forty-two healthy humans were included in the study. Population mean estimates (relative standard error, RSE) of apparent clearance, apparent volume of distribution and the absorption rate constant were 52.6 l h(-1) (4.18%), 113 l (56.6%) and 0.41 h(-1) , respectively. Covariate analyses revealed that creatinine clearance (CL(CR) ) significantly influenced metformin: CL/F= 52.6 × (CL(cr) /106.5)(0.782) . The signal transduction model was applied to describe the antihyperglycaemic effect of metformin. The population means for efficacy, potency, transit time and the Hill coefficient were estimated to be 19.8 (3.17%), 3.68 µg ml(-1) (3.89%), 0.5 h (2.89%) and 0.547 (9.05%), respectively. The developed model was used to predict the antihyperglycaemic effect in patients with type 2 diabetes. The predicted plasma glucose concentration value was similar to previous values.
CONCLUSIONS: The population signal transduction model was developed and evaluated for metformin use in healthy volunteers. Model evaluation by non-parametric bootstrap analysis suggested that the proposed model was robust and parameter values were estimated with good precision.
© 2012 The Authors. British Journal of Clinical Pharmacology © 2012 The British Pharmacological Society.

Entities:  

Mesh:

Substances:

Year:  2012        PMID: 22380769      PMCID: PMC3495146          DOI: 10.1111/j.1365-2125.2012.04260.x

Source DB:  PubMed          Journal:  Br J Clin Pharmacol        ISSN: 0306-5251            Impact factor:   4.335


  29 in total

1.  A signal transduction pharmacodynamic model of the kinetics of the parasympathomimetic activity of low-dose scopolamine and atropine in rats.

Authors:  Itay Perlstein; David Stepensky; Wojciech Krzyzanski; Amnon Hoffman
Journal:  J Pharm Sci       Date:  2002-12       Impact factor: 3.534

2.  Model appropriateness and population pharmacokinetic modeling.

Authors:  Ene I Ette; Paul J Williams; Yong Ho Kim; James R Lane; Mei-Jen Liu; Edmund V Capparelli
Journal:  J Clin Pharmacol       Date:  2003-06       Impact factor: 3.126

Review 3.  Metformin.

Authors:  C J Bailey; R C Turner
Journal:  N Engl J Med       Date:  1996-02-29       Impact factor: 91.245

Review 4.  Clinical pharmacokinetics of metformin.

Authors:  A J Scheen
Journal:  Clin Pharmacokinet       Date:  1996-05       Impact factor: 6.447

5.  Evaluating pharmacokinetic/pharmacodynamic models using the posterior predictive check.

Authors:  Y Yano; S L Beal; L B Sheiner
Journal:  J Pharmacokinet Pharmacodyn       Date:  2001-04       Impact factor: 2.745

Review 6.  Pharmacokinetic/pharmacodynamic modelling in diabetes mellitus.

Authors:  Cornelia B Landersdorfer; William J Jusko
Journal:  Clin Pharmacokinet       Date:  2008       Impact factor: 6.447

7.  Pharmacokinetic-pharmacodynamic modeling for the relationship between glucose-lowering effect and plasma concentration of metformin in volunteers.

Authors:  Shin Hwa Lee; Kwang-il Kwon
Journal:  Arch Pharm Res       Date:  2004-07       Impact factor: 4.946

8.  Rapid and sensitive liquid chromatography-tandem mass spectrometric method for the quantitation of metformin in human plasma.

Authors:  Yingwu Wang; Yunbiao Tang; Jingkai Gu; J Paul Fawcett; Xu Bai
Journal:  J Chromatogr B Analyt Technol Biomed Life Sci       Date:  2004-09-05       Impact factor: 3.205

Review 9.  Metformin. A review of its pharmacological properties and therapeutic use in non-insulin-dependent diabetes mellitus.

Authors:  C J Dunn; D H Peters
Journal:  Drugs       Date:  1995-05       Impact factor: 9.546

10.  Efficacy of metformin in patients with non-insulin-dependent diabetes mellitus. The Multicenter Metformin Study Group.

Authors:  R A DeFronzo; A M Goodman
Journal:  N Engl J Med       Date:  1995-08-31       Impact factor: 91.245

View more
  5 in total

1.  Effects of SLC22A1 Polymorphisms on Metformin-Induced Reductions in Adiposity and Metformin Pharmacokinetics in Obese Children With Insulin Resistance.

Authors:  Wai Johnn Sam; Orsolya Roza; Yuen Yi Hon; Raul M Alfaro; Karim A Calis; James C Reynolds; Jack A Yanovski
Journal:  J Clin Pharmacol       Date:  2016-08-23       Impact factor: 3.126

2.  Limited sampling strategy for determining metformin area under the plasma concentration-time curve.

Authors:  Ana Beatriz Santoro; Tore Bjerregaard Stage; Claudio José Struchiner; Mette Marie Hougaard Christensen; Kim Brosen; Guilherme Suarez-Kurtz
Journal:  Br J Clin Pharmacol       Date:  2016-07-24       Impact factor: 4.335

3.  A distributed delay approach for modeling delayed outcomes in pharmacokinetics and pharmacodynamics studies.

Authors:  Shuhua Hu; Michael Dunlavey; Serge Guzy; Nathan Teuscher
Journal:  J Pharmacokinet Pharmacodyn       Date:  2018-01-24       Impact factor: 2.745

Review 4.  A marriage of two "Methusalem" drugs for the treatment of psoriasis?: Arguments for a pilot trial with metformin as add-on for methotrexate.

Authors:  Hartmut Glossmann; Norbert Reider
Journal:  Dermatoendocrinol       Date:  2013-04-01

Review 5.  Recycling the Purpose of Old Drugs to Treat Ovarian Cancer.

Authors:  Mariana Nunes; Miguel Henriques Abreu; Carla Bartosch; Sara Ricardo
Journal:  Int J Mol Sci       Date:  2020-10-20       Impact factor: 5.923

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.