2014 - Alicante - Spain

PAGE 2014: Drug/Disease modeling - Endocrine
Siti Maisharah Sheikh Ghadzi

Are insulin measurements needed in glucose provocation studies? : Comparison of study power using Monte-Carlo Mapped Power (MCMP) method

Siti M. Sheikh Ghadzi, Mats O. Karlsson, Maria C. Kjellsson

Pharmacometrics Research Group, Department of Pharmaceutical Biosciences, Uppsala University

Objectives: Most glucose provocation studies are performed according to standard protocols, but the needs for insulin measurements have been questioned when performing the provocation with the aim to identify drug effects. In light of this, we performed a simulation study comparing the difference of study power between the uses of glucose plus insulin as opposed to only glucose in identifying hypothetical drug effects using model-based analysis and Monte Carlo Mapped Power (MCMP) method.

Methods: The design of the simulation study was a cross-over meal tolerance test (MTT) with two occasions and 500 subjects. Drug, 50 mg, was administered at time 0 of the second occasion and glucose, 75000 mg was administered at time 30 minutes on both occasions. Blood samples were taken at time 0 until 240-minute with 30 minutes interval. Complete datasets, including glucose and insulin, were simulated for the MCMP method using the Integrated Glucose-Insulin Meal Tolerance Test (IGI-MTT) Model with drug effects. The full dataset as well as datasets only including glucose were analysed using the IGI-MTT model with and without drug effects to assess power to detect drug effect. Six types of Emax shaped drug effects were investigated; drug effect on incretin activity, basal insulin secretion, insulin-independent glucose clearance, insulin-dependent glucose clearance, glucose production, and glucose absorption.

Results: The power to detect drug effects with a model-based approach was high for the tested magnitude of drug effects. The study power at 80% was higher with the use of both glucose plus insulin versus only glucose for all sites of drug actions, except insulin-independent glucose clearance. The largest difference in power between using insulin observation and not using insulin observation was seen in drug effect of basal insulin, followed by incretin activity and glucose absorption. No difference at 80% of study power detected for drug effect on insulin-independent glucose clearance. This indicated the need of insulin measurement in glucose provocation study, being dependent on the site of drug’s action.

Conclusions: The impact on power of not measuring insulin after an MTT will depend on site of action for the drug effect.

AcknowledgementsThis work was supported by the DDMoRe (www.ddmore.eu) project.

References: [1] Jauslin PM, Frey N, Karlsson MO. Modelling of 24-hour glucose and insulin profiles of patients with type 2 diabetes. J Clin Pharmacol. 2011;51(2):153-164 [2] Jauslin PM, Karlsson MO, Frey N. 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. J Clin Pharmacol . 2012; 52(12): 1861-1871 [3] Vong C, Bergstrand M, Nyberg J, Karlsson MO. Rapid sample size calculations for a defined likelihood ratio test-based power in mixed-rffects models. The AAPS Journal.2012; 14(2): 176-186.

Reference: PAGE 23 (2014) Abstr 3260 [www.page-meeting.org/?abstract=3260]
Poster: Drug/Disease modeling - Endocrine
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