ArticlePloS one2021
A comparison among three maximal mathematical models of the glucose-insulin system.
Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- A Computational Glucoregulatory Model of Liver and Glucagon for the Evaluation of Therapeutics.ACS pharmacology & translational science · 2025Article
- Fatty acids and physical activity are critical for β-cell mass and insulin sensitivity: Pathways to T2D and prevention.Journal of theoretical biology · 2025Article
- "MoSpec": A customized and integrated system for model development, verification and validation.PloS one · 2025Article
- Chinese diabetes datasets for data-driven machine learning.Scientific data · 2023Article
- SPINA Carb: a simple mathematical model supporting fast in-vivo estimation of insulin sensitivity and beta cell function.Scientific reports · 2022Article
- Evaluation of blood glucose level control in type 1 diabetic patients using deep reinforcement learning.PloS one · 2022Article
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Authors and funding
4 authors.
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Abstract
The most well-known and widely used mathematical representations of the physiology of a diabetic individual are the Sorensen and Hovorka models as well as the UVAPadova Simulator. While the Hovorka model and the UVAPadova Simulator only describe the glucose metabolism of a subject with type 1 diabetes, the Sorensen model was formulated to simulate the behaviour of both normal and diabetic individuals. The UVAPadova model is the most known model, accepted by the FDA, with a high level of complexity. The Hovorka model is the simplest of the three models, well documented and used primarily for the development of control algorithms. The Sorensen model is the most complete, even though some modifications were required both to the model equations (adding useful compartments for modelling subcutaneous insulin delivery) and to the parameter values. In the present work several simulated experiments, such as IVGTTs and OGTTs, were used as tools to compare the three formulations in order to establish to what extent increasing complexity translates into richer and more correct physiological behaviour. All the equations and parameters used for carrying out the simulations are provided.
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