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Implications for Drug Characterization in Glucose Tolerance Tests Without Insulin: Simulation Study of Power and
S M Sheikh Ghadzi1,2, M O Karlsson1, M C Kjellsson1
1Department of Pharmaceutical Biosciences, Uppsala University, Sweden.
CPT: Pharmacometrics & Systems Pharmacology
|June 3, 2017
Summary
Excluding insulin from preclinical antihyperglycemic drug studies may reduce statistical power for detecting drug effects. However, model predictive performance remains unaffected, supporting continued use of glucose-provocation tests.
Area of Science:
- Pharmacometrics and Drug Development
- Endocrinology and Metabolism
Background:
- Antihyperglycemic drug development commonly uses glucose provocation tests.
- Pharmacometric analysis of provocation data enables powerful, small-scale studies.
- Insulin's availability can impact preclinical study power and predictive performance.
Purpose of the Study:
- To investigate the implications of model-based drug characterization without insulin.
- To assess the impact of excluding insulin on statistical power and predictive performance.
Main Methods:
- Simulated oral glucose tolerance tests using an integrated glucose-insulin model.
- Employed a crossover design with placebo and study compound.
- Implemented drug effects across seven mechanisms of action (MOA), individually and in combination.
Main Results:
- Exclusion of insulin significantly reduced the power to differentiate correct drug effects from competing ones.
- Detecting primary or secondary drug effects was notably impacted by the absence of insulin.
- Model predictive performance was not affected by the exclusion of insulin.
Conclusions:
- Model-based characterization of antihyperglycemic drugs without insulin may compromise statistical power.
- Despite reduced power, the predictive performance of the model remains reliable.
- Careful consideration of insulin's role is crucial for robust preclinical drug effect characterization.
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