One-Day Bayesian Cloning of Type 1 Diabetes Subjects: Toward a Single-Day UVA/Padova Type 1 Diabetes Simulator
Abstract
OBJECTIVE: The UVA/Padova Type 1 Diabetes (T1DM) Simulator has been shown to be representative of a T1DM population observed in a clinical trial, but has not yet been identified on T1DM data. Moreover, the current version of the simulator is "single meal" while making it "single-day centric," i.e., by describing intraday variability, would be a step forward to create more realistic in silico scenarios. Here, we propose a Bayesian method for the identification of the model from plasma glucose and insulin concentrations only, by exploiting the prior model parameter distribution. METHODS: The database consists of 47 T1DM subjects, who received dinner, breakfast, and lunch (respectively, 80, 50, and 60 CHO grams) in three 23-h occasions (one open- and one closed-loop). The model is identified using the Bayesian Maximum a Posteriori technique, where the prior parameter distribution is that of the simulator. Diurnal variability of glucose absorption and insulin sensitivity is allowed. RESULTS: = 0.962 ± 0.027 ) and the posterior parameter distribution is similar to that included in the simulator. Absorption parameters at breakfast are significantly different from those at lunch and dinner, reflecting more rapid dynamics of glucose absorption. Insulin sensitivity varies in each individual but without a specific pattern. CONCLUSION: The incorporation of glucose absorption and insulin sensitivity diurnal variability into the simulator makes it more realistic. SIGNIFICANCE: The proposed method, applied to the increasing number of long-term artificial pancreas studies, will allow to describe week/month variability, thus further refining the simulator.
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The Hovorka model and the UVAPadova model were originally formulated to represent the physiological behaviour of T1DM individuals, and no modification is necessary for the purpose of the present work.
“On the contrary, the Hovorka model and the UVAPadova model were originally formulated to represent the physiological behaviour of T1DM individuals, and no modification is necessary for the purpose of the present work.”
From A comparison among three maximal mathematical models of the glucose-insulin system (2021) · cites this paper as [27]
Visentin et al. [8] found that insulin sensitivity was around 30% less than nominal values, showing that the insulin sensitivity of the S2013 simulator should be further modified to represent people with type 1 diabetes.
“They found that the insulin sensitivity was around 30% less than the nominal values, showing that the insulin sensitivity of the S2013 simulator should be further modified to represent people with type 1 diabetes.”
From A statistical virtual patient population for the glucoregulatory system in type 1 diabetes with integrated exercise model (2019) · cites this paper as Visentin et al. [8]
The Hovorka model and the UVAPadova Simulator describe only the glucose metabolism of a subject with type 1 diabetes.
“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.”
From A comparison among three maximal mathematical models of the glucose-insulin system (2021) · cites this paper as [27]
The formulation adopted in the UVAPadova model is marginally more complicated: if the parameter ka1 is set to zero and the parameter ka2 is set to the same value as the parameter kd, then the two formulations are equivalent.
“The formulation adopted in the UVAPadova model is marginally more complicated: if the parameter ka1 is set to zero and the parameter ka2 is set to same value as the parameter kd, then the two formulations are equivalent.”
From A comparison among three maximal mathematical models of the glucose-insulin system (2021) · cites this paper as [27]
The parameters of the Hovorka and UVA/Padova models are indicated for a diabetic individual.
“The parameters of the Hovorka and UVA/Padova models are instead indicated for a diabetic individual, but the more compact formulation of the Hovorka model requires fewer modifications to obtain a good fit.”
From A comparison among three maximal mathematical models of the glucose-insulin system (2021) · cites this paper as [27]
Cites
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Self-citationThe UVA/PADOVA Type 1 Diabetes Simulator: New Features
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“The UVA/Padova T1DM Simulator [5] has recently undergone a clinical validation by proving that the virtual subjects are representative of the T1DM population observed in a clinical trial [6], but, given the complexity of its model, it has never been identified in T1DM individuals so far.”
MethodInfluentialSelf-citation<i>In Silico</i> Preclinical Trials: A Proof of Concept in Closed-Loop Control of Type 1 Diabetes
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Self-citationEffects of Age and Sex on Postprandial Glucose Metabolism
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Self-citationSimulation Environment to Evaluate Closed-Loop Insulin Delivery Systems in Type 1 Diabetes
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Self-citationCircadian Variability of Insulin Sensitivity: Physiological Input for In Silico Artificial Pancreas
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“A clinical validation of the UVA/Padova T1DM simulator has been reported [6], where it has been shown that the virtual adult population of the simulator is representative of a T1DM population observed in a clinical trial by comparing 96 measured postprandial glucose profiles with those simulated in 100 in silico subje…”
MethodSelf-citationDay and Night Closed-Loop Control in Adults With Type 1 Diabetes
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The UVA/Padova Type 1 Diabetes Simulator Goes From Single Meal to Single Day
Visentin, R., Campos-Náñez, E., Schiavon, M., Lv, D., Vettoretti, M., Breton, M., Kovatchev, B. P., Dalla Man, C., & Cobelli, C. (2018) · Journal of Diabetes Science and Technology · doi:10.1177/1932296818757747 · Cited by 280 · see citing works
Self-citationContinuous glucose monitoring sensors: past, present and future algorithmic challenges
Facchinetti, A. (2016) · Sensors · doi:10.3390/s16122093 · Cited by 176 · see citing works
Resalat, N., El Youssef, J., Tyler, N., Castle, J., & Jacobs, P. G. (2019) · PLOS ONE · doi:10.1371/journal.pone.0217301 · Cited by 78 · see citing works
A comparison among three maximal mathematical models of the glucose-insulin system
Pompa, M., Panunzi, S., Borri, A., & De Gaetano, A. (2021) · PLOS ONE · doi:10.1371/journal.pone.0257789 · Cited by 24 · see citing works
“1: Meal Simulation Model of the Glucose-Insulin System (2007) [22] 2: GIM, Simulation Software of Meal Glucose–Insulin Model (2007) [25] 3: One-Day Bayesian Cloning of Type 1 Diabetes Subjects: Towards a Single-Day UVA/Padova Type 1 Diabetes Simulator (2016) [27] 4: The UVA/Padova Type I Diabetes Simulator Goes From S…”
MethodVisentin, R., Schiavon, M., Giegerich, C., Klabunde, T., Man, C. D., & Cobelli, C. (2019) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2019.2897851 · Cited by 22 · see citing works
Self-citation
- Authors
- Visentin, R., Man, C. D., & Cobelli, C.
- Affiliations
- University of Padua (IT)
- Venue
- IEEE Transactions on Biomedical Engineering
- Published
- 2016-11
- Volume
- 63
- Issue
- 11
- Pages
- 2416-2424
- ISSN
- 0018-9294 (ISSN-L)
- 1558-2531
- OpenAlex
- W2314840118
- Cited by
- 86
- References
- 15
- Citations by year
- 2026: 6 · 2025: 3 · 2024: 11 · 2023: 8 · 2022: 4 · 2021: 10 · 2020: 6 · 2019: 14 · 2018: 15 · 2017: 7 · 2016: 2
- FWCI
- 12.72
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Biomedical Engineering (publishedVersion)
- PubMed (publishedVersion)
- Padua Research Archive (University of Padova) (submittedVersion)
- Funders
- Italian Ministero dell’Università e della Ricerca Scientifica
- AP@Home
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Health Sciences › Medicine › Surgery › Pancreatic function and diabetes
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Diabetes and associated disorders
- Keywords
- type 1 diabetes, maximum a posteriori estimation, plasma glucose, insulin, glucose absorption, insulin sensitivity, diurnal variation, artificial pancreas, in silico modeling
- MeSH terms
- Adult, Bayes Theorem, Blood Glucose, Circadian Rhythm, Computer Simulation, Diabetes Mellitus, Type 1, Humans, Insulin, Insulin Resistance, Middle Aged, Pancreas, Artificial
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