Literature DB >> 25160589

A semi-mechanistic model for the effects of a novel glucagon receptor antagonist on glucagon and the interaction between glucose, glucagon, and insulin applied to adaptive phase II design.

Joanna Z Peng1, William S Denney, Bret J Musser, Rong Liu, Kuenhi Tsai, Lanyan Fang, Marc L Reitman, Matthew D Troyer, Samuel S Engel, Lei Xu, Aubrey Stoch, Julie A Stone, Ken G Kowalski.   

Abstract

A potent novel compound (MK-3577) was developed for the treatment of type 2 diabetes mellitus (T2DM) through blocking the glucagon receptor. A semi-mechanistic model was developed to describe the drug effect on glucagon and the interaction between glucagon, insulin, and glucose in healthy subjects (N = 36) during a glucagon challenge study in which glucagon, octreotide (Sandostatin), and basal insulin were infused for 2 h starting from 3, 12, or 24 h postdose of a single 0-900 mg MK-3577 administration. The drug effect was modeled by using an inhibitory E max model (I max = 0.96 and IC50 = 13.9 nM) to reduce the ability of glucagon to increase the glucose production rate (GPROD). In addition, an E max model (E max = 0.79 and EC50 = 575 nM) to increase glucagon secretion by the drug was used to account for the increased glucagon concentrations prechallenge (via compensatory feedback). The model adequately captured the observed profiles of glucagon, glucose, and insulin pre- and postchallenge. The model was then adapted for the T2DM patient population. A linear model to correlate fasting plasma glucose (FPG) to weighted mean glucose (WMG) was developed and provided robust predictions to assist with the dose adjustment for the interim analysis of a phase IIa study.

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Year:  2014        PMID: 25160589      PMCID: PMC4389739          DOI: 10.1208/s12248-014-9648-x

Source DB:  PubMed          Journal:  AAPS J        ISSN: 1550-7416            Impact factor:   4.009


  20 in total

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4.  A mechanism-based disease progression model for comparison of long-term effects of pioglitazone, metformin and gliclazide on disease processes underlying Type 2 Diabetes Mellitus.

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8.  Pharmacokinetic and pharmacodynamic modeling of a monoclonal antibody antagonist of glucagon receptor in male ob/ob mice.

Authors:  Yvonne Y Lau; Peiming Ma; Leonid Gibiansky; Renee Komorowski; Jin Wang; George Wang; Hai Yan; Murielle M Véniant; Tarundeep Kakkar
Journal:  AAPS J       Date:  2009-10-23       Impact factor: 4.009

Review 9.  Clinical pharmacokinetics of octreotide. Therapeutic applications in patients with pituitary tumours.

Authors:  P Chanson; J Timsit; A G Harris
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  3 in total

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Journal:  Clin Pharmacokinet       Date:  2017-08       Impact factor: 6.447

2.  Cross-Validation of a Glucose-Insulin-Glucagon Pharmacodynamics Model for Simulation Using Data From Patients With Type 1 Diabetes.

Authors:  Sabrina Lyngbye Wendt; Ajenthen Ranjan; Jan Kloppenborg Møller; Signe Schmidt; Carsten Boye Knudsen; Jens Juul Holst; Sten Madsbad; Henrik Madsen; Kirsten Nørgaard; John Bagterp Jørgensen
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3.  Mathematical modeling of the glucagon challenge test.

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Journal:  J Pharmacokinet Pharmacodyn       Date:  2019-09-30       Impact factor: 2.745

  3 in total

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