A novel integrated QSP model of in vivo human glucose regulation to support the development of a glucagon/GLP-1 dual agonist.
CPT Pharmacometrics Syst Pharmacol · 2022
Last updated 2026-05-28A new computer model was created to study how drugs that target GLP-1 and glucagon receptors affect blood sugar control and weight loss in people with type 2 diabetes. The model, tested with data from drugs like liraglutide, dulaglutide, and semaglutide, accurately predicts how these drugs work by influencing insulin release, food intake, and digestion speed after meals.
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| Journal | CPT Pharmacometrics Syst Pharmacol, 2022 |
|---|---|
| Citations | 11 |
| Relative citation ratio | 1.24 |
| NIH percentile | 58 |
| Molecules | — |
| Conditions studied | Type 2 Diabetes |
Abstract
Glucagon-like peptide-1 (GLP-1) receptor agonists (GLP-1RAs) and dual GLP-1/glucagon receptor agonists improve glycaemic control and cause significant weight loss in patients with type 2 diabetes. These effects are driven in part by augmenting glucose-stimulated insulin release (incretin effect), reducing caloric intake and delayed gastric emptying. We developed and externally validated a novel integrated quantitative systems pharmacology (QSP) model to gain quantitative insight into the relative contributions and mechanisms of drugs modulating glucose regulatory pathways. This model (4GI model) incorporates known feedback mechanisms among glucose, GLP-1, glucagon, glucose-dependent insulinotropic peptide (GIP), and insulin after glucose provocation (i.e., food intake) and drug intervention utilizing published nonpharmacological and pharmacological (liraglutide, a GLP-1RA) data. The resulting model accurately describes the aforementioned mechanisms and independently predicts the effects of the GLP-1RAs (dulaglutide and semaglutide) on system dynamics. Therefore, the validated 4GI model represents a quantitative decision-making tool to support the advancement of novel therapeutics and combination strategies modulating these pathways.
Verbatim abstract via PubMed 34889083 ↗