Evaluation of Four Semi‐Mechanistic Models for Predicting Glycemic Control With a Glucagon Receptor Antagonist in People With Type 2 Diabetes
ABSTRACT Glycated hemoglobin (HbA1c) is the gold standard for measuring long‐term glycemic efficacy over at least 3 months in Type 2 diabetes (T2D). Being able to predict HbA1c using glucose response from studies of less than 3 months would be useful. Four semi‐mechanistic HbA1c models (ADOPT, FFH,...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-08-01
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| Series: | CPT: Pharmacometrics & Systems Pharmacology |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/psp4.70058 |
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| Summary: | ABSTRACT Glycated hemoglobin (HbA1c) is the gold standard for measuring long‐term glycemic efficacy over at least 3 months in Type 2 diabetes (T2D). Being able to predict HbA1c using glucose response from studies of less than 3 months would be useful. Four semi‐mechanistic HbA1c models (ADOPT, FFH, FHH, and IGRH) were evaluated for their predictive performance of longer‐term HbA1c at 24 weeks of treatment using glucose and HbA1c data up to 4 weeks of treatment. A novel glucagon receptor antagonist (LY2409021) was evaluated in T2D patients for glycemic control. The models were built using LY2409021 pharmacokinetics, glucose, and HbA1c data from a 4‐week Phase 1b study. Predictive performance of the models was assessed based on comparing model‐estimated and observed HbA1c values from a 24‐week Phase 2b study. Metrics for predictive performance included: (a) mean change from baseline HbA1c (ΔHbA1c) at Week 24 between observed and simulated values; (b) mean prediction error (MPE) for bias; and (c) root mean squared error (RMSE) for precision. Overall, the FHH and IGRH models closely predicted the mean ΔHbA1c at Week 24 within 0.1% difference from the observed values in the Phase 2b study. Both models also had reasonable bias (absolute MPE < 0.1%) and precision (RMSE < 0.3%) estimates. Conversely, the ADOPT and FFH models over‐predicted the mean reduction in HbA1c by 0.288% and 0.153%, respectively. The FHH and IGRH models featured transit compartments for modeling long delays between glucose and HbA1c. Thus, these models better represented the physiology and provided superior predictive performance. |
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| ISSN: | 2163-8306 |