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Identification of the primary mechanism of action of an insulin secretagogue from meal test data in healthy volunteers based on an integrated glucose-insulin model
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. (Pharmacometrics Group)
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. (Pharmacometrics Group)
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2013 (English)In: Journal of Pharmacokinetics and Pharmacodynamics, ISSN 1567-567X, E-ISSN 1573-8744, Vol. 40, no 1, 1-10 p.Article in journal (Refereed) Published
Abstract [en]

The integrated glucose–insulin (IGI) model is a previously developed semi-mechanistic model that incorporates control mechanisms for the regulation of glucose production, insulin secretion, and glucose uptake. It has been shown to adequately describe insulin and glucose profiles in both type 2 diabetics and healthy volunteers following various glucose tolerance tests. The aim of this study was to investigate the ability of the IGI model to correctly identify the primary mechanism of action of glibenclamide (Gb), based on meal tolerance test (MTT) data in healthy volunteers. IGI models with different mechanism of drug action were applied to data from eight healthy volunteers participating in a randomized crossover study with five single-dose tests (placebo and four drug arms). The study participants were given 3.5 mg of Gb, intravenously or orally, or 3.5 mg of the two main metabolites M1 and M2 intravenously, 0.5 h prior to a standardized breakfast with energy content of 1800 kJ. Simultaneous analysis of all data by nonlinear mixed effect modeling was performed using NONMEM®. Drug effects that increased insulin secretion resulted in the best model fit, thus identifying the primary mechanism of action of Gb and metabolites as insulin secretagogues. The model also quantified the combined effect of Gb, M1 and M2 to have a fourfold maximal increase on endogenous insulin secretion, with an EC50 of 169.1 ng mL−1 for Gb, 151.4 ng mL−1 for M1 and 267.1 ng mL−1 for M2. The semi-mechanistic IGI model was successfully applied to MTT data and identified the primary mechanism of action for Gb, quantifying its effects on glucose and insulin time profiles.

Place, publisher, year, edition, pages
Springer, 2013. Vol. 40, no 1, 1-10 p.
Keyword [en]
Glibenclamide, Semi-mechanistic, Meal tolerance test, Integrated glucose–insulin model, NONMEM
National Category
Endocrinology and Diabetes
Research subject
Pharmaceutical Science
Identifiers
URN: urn:nbn:se:uu:diva-187779DOI: 10.1007/s10928-012-9281-1ISI: 000313955700001PubMedID: 23179858OAI: oai:DiVA.org:uu-187779DiVA: diva2:575574
Available from: 2012-12-10 Created: 2012-12-10 Last updated: 2017-12-07Bibliographically approved
In thesis
1. Semi-mechanistic models of glucose homeostasis and disease progression in type 2 diabetes
Open this publication in new window or tab >>Semi-mechanistic models of glucose homeostasis and disease progression in type 2 diabetes
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Type 2 diabetes mellitus (T2DM) is a metabolic disorder characterized by consistently high blood glucose, resulting from a combination of insulin resistance and reduced capacity of β-cells to secret insulin. While the exact causes of T2DM is yet unknown, obesity is known to be a major risk factor as well as co-morbidity for T2DM. As the global prevalence of obesity continues to increase, the association between obesity and T2DM warrants further study. Traditionally, mathematical models to study T2DM were mostly empirical and thus fail to capture the dynamic relationship between glucose and insulin. More recently, mechanism-based population models to describe glucose-insulin homeostasis with a physiological basis were proposed and offered a substantial improvement over existing empirical models in terms of predictive ability.

The primary objectives of this thesis are (i) examining the predictive usefulness of semi-mechanistic models in T2DM by applying an existing population model to clinical data, and (ii) exploring the relationship between obesity and T2DM and describe it mathematically in a novel semi-mechanistic model to explain changes to the glucose-insulin homeostasis and disease progression of T2DM.

Through the use of non-linear mixed effects modelling, the primary mechanism of action of an antidiabetic drug has been correctly identified using the integrated glucose-insulin model, reinforcing the predictive potential of semi-mechanistic models in T2DM. A novel semi-mechanistic model has been developed that incorporated a relationship between weight change and insulin sensitivity to describe glucose, insulin and glycated hemoglobin simultaneously in a clinical setting. This model was also successfully adapted in a pre-clinical setting and was able to describe the pathogenesis of T2DM in rats, transitioning from healthy to severely diabetic.

This work has shown that a previously unutilized biomarker was found to be significant in affecting glucose homeostasis and disease progression in T2DM, and that pharmacometric models accounting for the effects of obesity in T2DM would offer a more complete physiological understanding of the disease.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2016. 78 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, ISSN 1651-6192 ; 210
Keyword
pharmacokinetics, pharmacodynamics, pharmacometrics, glucose homeostasis, insulin, type 2 diabetes, obesity, weight, visceral adipose tissue, HbA1c, non-linear mixed effects, modelling, disease progression, ZDSD rats
National Category
Endocrinology and Diabetes
Research subject
Pharmaceutical Science
Identifiers
urn:nbn:se:uu:diva-273709 (URN)978-91-554-9456-8 (ISBN)
Public defence
2016-03-04, B41, Biomedicinskt Centrum (BMC), Husargatan 3, Uppsala, 13:15 (English)
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Available from: 2016-02-05 Created: 2016-01-17 Last updated: 2016-02-12

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Choy, Stevevan der Walt, Jan-StefanKjellsson, MariaKarlsson, Mats

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