Identification of the Mechanism of Action of a Glucokinase Activator From Oral Glucose Tolerance Test Data in Type 2 Diabetic Patients Based on an Integrated Glucose‐Insulin Model

Dr Petra M. Jauslin PhD

Corresponding Author

Department of Translational Research Sciences, Modeling and Simulation Group, F. Hoffmann‐La Roche Inc, Basel, Switzerland

Division of Pharmacokinetics and Drug Therapy, Department of Pharmaceutical Biosciences, University of Uppsala, Sweden

Address for correspondence: Petra M. Jauslin, F. Hoffmann‐La Roche Inc, Pharma Research and Early Development, Translational Research Sciences, Building 670 / Room 321, Postfach, CH‐4070 Basel, Switzerland; e‐mail:

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Prof Mats O. Karlsson PhD

Division of Pharmacokinetics and Drug Therapy, Department of Pharmaceutical Biosciences, University of Uppsala, Sweden

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Dr Nicolas Frey PharmD

Department of Translational Research Sciences, Modeling and Simulation Group, F. Hoffmann‐La Roche Inc, Basel, Switzerland

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First published: 07 March 2013
Cited by: 13

Abstract

A mechanistic drug‐disease model was developed on the basis of a previously published integrated glucose‐insulin model by Jauslin et al. A glucokinase activator was used as a test compound to evaluate the model's ability to identify a drug's mechanism of action and estimate its effects on glucose and insulin profiles following oral glucose tolerance tests. A kinetic‐pharmacodynamic approach was chosen to describe the drug's pharmacodynamic effects in a dose‐response‐time model. Four possible mechanisms of action of antidiabetic drugs were evaluated, and the corresponding affected model parameters were identified: insulin secretion, glucose production, insulin effect on glucose elimination, and insulin‐independent glucose elimination. Inclusion of drug effects in the model at these sites of action was first tested one‐by‐one and then in combination. The results demonstrate the ability of this model to identify the dual mechanism of action of a glucokinase activator and describe and predict its effects: Estimating a stimulating drug effect on insulin secretion and an inhibiting effect on glucose output resulted in a significantly better model fit than any other combination of effect sites. The model may be used for dose finding in early clinical drug development and for gaining more insight into a drug candidate's mechanism of action.

Number of times cited according to CrossRef: 13

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