PI-068

P. Gaitonde,1 P. Garhyan,2 J. Y. Chien,2 S. Schmidt1; 1University of Florida, Orlando, FL, 2Eli Lilly and Co., Indianapolis, IN

BACKGROUND: Type 2 Diabetes Mellitus (T2DM) is a chronic, progressive disease. The aim of the study was to develop and apply a drug-systems-disease model that integrate knowledge of patient’s disease status, mechanisms and magnitude of drug action and dynamic relationship of clinically relevant biomarkers to predict treatment effects of oral anti-hyperglycemic (OAH) drugs.
METHODS: The model was developed in NONMEM® using a large clinical dataset and three clinically used biomarkers; fasting plasma glucose (FPG), fasting serum insulin (FSI) and glycosylated hemoglobin (HbA1c). Baseline HOMA-B and HOMA-S measures were incorporated to reflect patient’s disease status at start of therapy. Biomarker degradation rates were fixed to reflect their respective biological half-lives. Mechanism and magnitude of drug-effect was incorporated based on pharmacology. It was linked to changes in β-cell function and insulin sensitivity and reflected as disease progression.
RESULTS: Dose and underlying biomarker dynamics were found to regulate the onset of treatment effect, whereas the wear-off of treatment-effect was governed by disease progression obtained based on 52-week studies and reflected by change in β-cell function and insulin sensitivity.
CONCLUSION: The developed drug-systems-disease model successfully characterized the effect of different OAH drugs using clinical biomarker data. The model will now be expanded to evaluate covariate effects, inter-individual differences in treatment response and to predict the impact of combination therapy.