The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index; none of the 7 sources its claims cite is checked for support yet.
The University of Virginia/Padova Type 1 Diabetes Simulator Matches the Glucose Traces of a Clinical Trial
Open accessAbstract
Background: In 2008, the Food and Drug Administration (FDA) accepted our type 1 diabetes mellitus (T1DM) simulator (S2008), equipped with 100 in silico adults, 100 adolescents, and 100 children, as a substitute for preclinical trials for certain insulin treatments, including closed-loop algorithms. Hypoglycemia was well described in the simulator, but recent closed-loop trials showed a much larger frequency of hypoglycemia events in patients compared with the in silico ones. In order to better describe the distribution of glucose concentration observed in clinical trials, the simulator has recently been updated, and modifications have been accepted by the FDA (S2013). The aim of this study is to assess the validity of the S2013 simulator against clinical data and compare its performance with that of the S2008. Subjects and Methods: The database consists of 24 T1DM subjects who received dinner (70.7±3.3 g of carbohydrate) and breakfast (52.9±0.1 g of carbohydrate) in two occasions (open- and closed-loop), for a total of 96 postmeal glucose profiles. Measured plasma glucose profiles were compared with those simulated in 100 in silico adults, and the continuous glucose error grid analysis (CG-EGA) was used to assess the validity of the simulated traces. Moreover, the most common outcome metrics have been compared. Results: The frequency of hypoglycemia episodes predicted by the S2013 well reproduces that observed during clinical trials as proven by the CG-EGA. In addition, the outcome metrics provided by the S2013 are similar to those observed in clinical trials in a set of T1DM subjects. Conclusions: We demonstrated that the virtual subjects of the S2013 are representative of the T1DM population observed in a clinical trial. We conclude that the S2013 is a valid tool usable to test the robustness of closed-loop control algorithms for artificial pancreas.
Overview
AI snapshot
Written from the paper’s full text.
TL;DR
The updated UVA/Padova type 1 diabetes simulator S2013 was assessed against clinical glucose data from 24 adults and compared with the earlier S2008. S2013 reproduced clinical glucose traces and hypoglycemia better, supporting its use for in silico testing of closed-loop algorithms.
Key findings
- CG-EGA accurate+benign percentages were 86.4% in hypoglycemia, 99.9% in euglycemia, and 99.2% in hyperglycemia for S2013, versus 40.7%, 99.8%, and 99.5% for S2008.
- S2013 outcome metrics were substantially similar to clinical data except for percentage of time in hypoglycemia (6.22±11.81 vs 4.04±7.93; P=0.006) and hypoglycemia area under the curve (5.00±14.50 vs 2.65±8.99 mg·h/dL; P=0.019); most S2008 metrics were significantly lower than clinical values (P<0.05).
- Hypoglycemia events numbered 37 in data, 32 with S2013, and 19 with S2008; hyperglycemia events were 72, 67, and 61, respectively.
- Real versus virtual parameter differences averaged 18% for body weight and 67% for carbohydrate ratio; a >50% carbohydrate-ratio difference occurred in 23 subjects, and 14 of them would have benefited from a ratio closer to the virtual one. No subject was matched by the same virtual patient at both dinner and breakfast.
Methods
- The clinical database included 24 T1DM adults from Virginia (n=11), Padova (n=7), and Montpellier (n=6), each studied during two 22-h admissions (open- and closed-loop), with dinner (70.7±3.3 g carbohydrate) and breakfast (52.9±0.1 g carbohydrate), yielding 96 postmeal traces plus 8 overnight portions with at least one hypoglycemic episode.
- Each measured plasma glucose profile was compared with 100 in silico adults undergoing the same meals, basal insulin, and boluses; the best FIT-matched simulated profile was evaluated by continuous glucose error grid analysis (CG-EGA).
- Outcome metrics were compared between clinical and simulated data using paired t tests or Wilcoxon signed rank tests, with significance at P=0.05; S2013 includes modified hypoglycemia glucose kinetics via the Low BG Risk Index, a glucagon counterregulation model, and refined virtual-subject generation.
Limitations
- Stated by the authors: the 24-subject dataset is not large despite 96 traces; only inpatient data were used, so outpatient free-living robustness is unproven; only adults were considered; the model does not yet account for intraindividual diurnal parameter variability; and glucagon secretion may not be appropriate for all long-duration T1DM patients.
- Evident from the text: the protocol did not include a physical activity session, so simulator validity under exercise is not tested.
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A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This analysis revealed that a difference between real and virtual CR >50% was present in 23 subjects.”
Strength:plain· not yet calibratedn = 23Tests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The results of the S2008 (Table 1, second row) show that the performance is similar to that of S2013 in euglycemia and hyperglycemia (percentage in accurate+benign zones: 99.8% in euglycemia and 99.5% in hyperglycemia) but worse in hypoglycemia (percentage in accurate+benign zones: 40.7%).”
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The frequency of hypoglycemia episodes predicted by the S2013 well reproduces that observed during clinical trials as proven by the CG-EGA.”
- Also stated in: § Discussion · boosted
“where the hypoglycemic episodes predicted by the simulator well reflect those observed in clinical trials (Fig. 2, left panel).”
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Also stated in: § Discussion · boosted
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The S2013 well reproduces the glucose patterns observed in clinical trials in all clinical zones, in particular the rapid falls in glucose level and the hypoglycemic episodes.”
- Also stated in: § Discussion · boosted
“Our results show that the S2013 well reproduces the glucose patterns in eu-, hyper-, and, above all, hypoglycemia, where the hypoglycemic episodes predicted by the simulator well reflect those observed in clinical trials (Fig. 2, left panel).”
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Also stated in: § Discussion · boosted
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For the S2008 (Table 2, third column), most of the outcome metrics are significantly lower in simulation (P<0.05).”
- Also stated in: § Discussion · plain
“Moreover, most of the in silico outcome metrics are significantly different from their clinical counterparts (Table 2, third column).”
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Also stated in: § Discussion · plain
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In fact, we found that none of the subjects was matched by the same virtual patient at dinner and breakfast.”
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The results of the S2008 (Table 1, second row) show that the performance is similar to that of S2013 in euglycemia and hyperglycemia (percentage in accurate+benign zones: 99.8% in euglycemia and 99.5% in hyperglycemia) but worse in hypoglycemia (percentage in accurate+benign zones: 40.7%).”
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesA conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The improvement presented above is confirmed by the analysis of the distribution of outcome metrics, reported in Table 2.”
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesA conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The higher difference found for CR is due to the fact that the virtual CR is the “optimal” one for a given patient.”
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesA conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We conclude that the S2013 is a valid tool usable to test the robustness of closed-loop control algorithms for artificial pancreas.”
- Also stated in: § Discussion · boosted
“In conclusion, this study proves the validity of the S2013 (Fig. 1B), which incorporates a novel nonlinear response to hypoglycemia and includes a counterregulation model.”
Load-bearingStrength:boosted· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Also stated in: § Discussion · boosted
- It may state two separate claims as one. 8
- Probably not a substantial claim. 6
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The average results of CG-EGA of the S2013 (Table 1, first row) are very good in hypo-, eu-, and hyperglycemia (percentage in accurate+benign zones: 86.4% in hypoglycemia, 99.9% in euglycemia and 99.2% in hyperglycemia).”
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We found that the percentage difference between subject and virtual parameters was 18% on average for body weight and 67% for CR.”
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In this case a match was always found except for eight traces, which, however, presented hypoglycemia, and thus the corresponding CR were suboptimal, as explained above.”
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The simulated profiles obtained with the S2008 reproduce quite well the data in euglycemia and hyperglycemia but not the hypoglycemic episodes.”
- Also stated in: § Discussion · plain
“On the other hand, we observed that the S2008 reproduces quite well the glucose patterns in euglycemia and hyperglycemia, but not the hypoglycemic episodes, which are difficult to predict (Fig. 2, right panel).”
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Also stated in: § Discussion · plain
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The outcome metrics of S2013 simulations (Table 2, second column) are substantially similar to those obtained from the data, except for the percentage of time in hypoglycemia and the area under the BG curve for hypoglycemia.”
- Also stated in: § Abstract · plain
“In addition, the outcome metrics provided by the S2013 are similar to those observed in clinical trials in a set of T1DM subjects.”
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Also stated in: § Abstract · plain
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The most important one is that the model does not yet take into account the intraindividual diurnal parameter variability.”
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Second, the dataset used for model assessment only includes inpatient data. Unfortunately, we do not have data to prove that the performance would be as robust in outpatient free-living individuals.”
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“The simulator was successfully validated against data of different experiments performed in T1DM subjects, reproducing (1) distribution of insulin correction factors in the T1DM population of children and adults, (2) glucose traces in children with T1DM, and (3) glucose traces of induced moderate hypoglycemia observed in adults in clinical trials at the University of Virginia.1”
What the sources say
- Not checked yetcites [1] Kovatchev BP, Breton M, Dalla Man C, Cobelli C: In silico preclinical trials: a proof of concept in closed-loop control of type 1 diabetes. J Diabetes Sci Technol 2009;3:44–55 [DOI] [PMC free article] [PubMed] [Google Scholar] source
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What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Third, only the adult population has been considered in this article.”
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“However, it is important to stress that the simulator is not designed to do prospective studies on a given individual, given the large intrasubject variability of real life.”
What the sources say
- Not checked yetcites [3] Hinshaw L, Dalla Man C, Nandy DK, Saad A, Bharucha AE, Levine JA, Rizza RA, Basu R, Carter RE, Cobelli C, Kudva YC, Basu A: Diurnal pattern of insulin action in type 1 diabetes: implications for a closed loop system. Diabetes 2013;62:2223–2229 [DOI] [PMC free article] [PubMed] [Google Scholar] source
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“First, the dataset used for the assessment, consisting of 24 subjects, cannot be considered a large database, despite subjects being studied twice with two meals per trial for a total of 96 traces.”
Strength:plain· not yet calibratedn = 24Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In principle, if information on the exact timing of the meals and carbohydrates content is available, we are pretty confident that the method proposed here can be applied to outpatient free-living individuals.”
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“This database was not used for the update of S2013.”
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“However, it is likely that finding a match between real and simulated subjects is easier if only three or four BG values are available in a day, as happens in real life.”
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
The paper relies on this without support.
The virtual subjects well span the variability of the T1DM population observed in vivo.
“The virtual subjects well span the variability of the T1DM population observed in vivo.”
The paper relies on this without support.
Recent closed-loop trials showed a much larger frequency of hypoglycemia events in patients compared with the in silico ones.
“Hypoglycemia was well described in the simulator, but recent closed-loop trials showed a much larger frequency of hypoglycemia events in patients compared with the in silico ones.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“we used the University of Virginia (UVA)/Padova T1D simulator, which consists of a fully identified maximal model of glucose metabolism in T1D 18 and a virtual population of 100 adult PwDs displaying key metabolic behaviors observed in the general population of individuals with T1D.[18][19][20][21]”
From Time to Moderate and Severe Hyperglycemia and Ketonemia Following an Insulin Pump Occlusion (2024) · cites this paper as [20]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“unlike the S2008 simulator, the S2013 simulator overestimated the percent time spent in hypoglycemia significantly [7].”
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. [7]
Citations
Cites
The UVA/PADOVA Type 1 Diabetes Simulator: New Features
Man, C. D., Micheletto, F., Lv, D., Breton, M., Kovatchev, B., & Cobelli, C. (2014) · Journal of Diabetes Science and Technology · doi:10.1177/1932296813514502 · Cited by 791 · cited 3×
“updated version of the T1DM simulator (S2013), incorporating a model of counterregulation and a new description of glucose dynamics in hypoglycemia, has been developed.(2) Here our aim is to assess the validity of S2013 versus S2008 compared with T1DM data obtained in a clinical trial.”
MethodInfluentialSelf-citationIn Silico Preclinical Trials: A Proof of Concept in Closed-Loop Control of Type 1 Diabetes
Kovatchev, B. P., Breton, M., Dalla Man, C., & Cobelli, C. (2009) · Journal of Diabetes Science and Technology · doi:10.1177/193229680900300106 · Cited by 760
Self-citationEvaluating the Accuracy of Continuous Glucose-Monitoring Sensors
Kovatchev, B. P., Gonder-Frederick, L. A., Cox, D. J., & Clarke, W. L. (2004) · Diabetes Care · doi:10.2337/diacare.27.8.1922 · Cited by 312
Self-citationKovatchev, B. P., Cox, D. J., Gonder-Frederick, L. A., Young-Hyman, D. L., Schlundt, D. G., & Clarke, W. L. (1998) · Diabetes Care · doi:10.2337/diacare.21.11.1870 · Cited by 309
Self-citationThe Original Clarke Error Grid Analysis (EGA)
Clarke, W. L. (2005) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2005.7.776 · Cited by 282
Kovatchev, B., Cobelli, C., Renard, E., Anderson, S., Breton, M., Patek, S., Clarke, W., Bruttomesso, D., Maran, A., Costa, S., et al. (2010) · Journal of Diabetes Science and Technology · doi:10.1177/193229681000400611 · Cited by 200
Self-citationKovatchev, B. P., Straume, M., Cox, D. J., & Farhy, L. S. (2000) · Computational and Mathematical Methods in Medicine · doi:10.1080/10273660008833060 · Cited by 125
Self-citationDiurnal Pattern of Insulin Action in Type 1 Diabetes
Hinshaw, L., Dalla Man, C., Nandy, D. K., Saad, A., Bharucha, A. E., Levine, J. A., Rizza, R. A., Basu, R., Carter, R. E., Cobelli, C., et al. (2013) · Diabetes · doi:10.2337/db12-1759 · Cited by 125
Self-citationKovatchev, B. P., Cox, D. J., Gonder-Frederick, L. A., & Clarke, W. L. (2002) · Diabetes Technology & Therapeutics · doi:10.1089/152091502760098438 · Cited by 85
Self-citationKovatchev, B. P., Farhy, L. S., Cox, D. J., Straume, M., Yankov, V. I., Gonder-Frederick, L. A., & Clarke, W. L. (1999) · Computational and Mathematical Methods in Medicine · doi:10.1080/10273669908833028 · Cited by 17
Self-citation
Flagged first, then by citations
Research works printed but not linked: 1
- Micheletto F, , Dalla Man C, , Vella A, , Cobelli C: A model of glucagon secretion and action in healthy subjects [abstract A105]. In: Book of Abstracts. 10th Diabetes Technology Meeting. Bethesda, MD: Diabetes Technology Society, 2010.
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Items 101–105 of 105
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Aganj, I., Bryant, N. K., Panaro, L. (., Caravan, P. D., Gaglia, J. L., & Fischl, B. R. (2026) · medRxiv · doi:10.64898/2026.07.27.26359073
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Vallée, A. (2026) · JAMIA Open · doi:10.1093/jamiaopen/ooag160 · Cited by 1
In silico methodologies in computational medicine: From complex disease modeling to virtual clinics
Italia, M., Otero, J. G., Azzimonti, L., García‐Aznar, J. M., Dercole, F., & Belmonte-Beitia, J. (2026) · Biophysics Reviews · doi:10.1063/5.0285118
Predicting phase 3 clinical trial outcomes with an evidence-driven large language model
Zhang, W., Meng, X., Jia, X., Yu, E., Lan, J., Wang, T., Chen, G., Guo, Y., Liu, Y., Chu, X., et al. (2026) · The Innovation · doi:10.1016/j.xinn.2026.101574
Metadata
- Authors
- Visentin, R., Dalla Man, C., Kovatchev, B., & Cobelli, C.
- Affiliations
- University of Padua (IT)
- University of Padova
- University of Virginia (US)
- Corresponding author
- Cobelli, Claudio
- Venue
- Diabetes Technology & Therapeutics
- Publisher
- SAGE Publications
- Published
- 2014-07
- Volume
- 16
- Issue
- 7
- Pages
- 428-434
- ISSN
- 1520-9156 (ISSN-L)
- 1557-8593
- PMC
- PMC4074748
- OpenAlex
- W2322662949
- Semantic Scholar
- 5acb44cd926a9e47ea60993621f01f2ed7c79a9d
- Cited by
- 103
- References
- 11
- Citations by year
- 2026: 7 · 2025: 8 · 2024: 7 · 2023: 12 · 2022: 6 · 2021: 9 · 2020: 9 · 2019: 9 · 2018: 12 · 2017: 15 · 2016: 6 · 2015: 1 · 2014: 2
- FWCI
- 6.44
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Diabetes Technology & Therapeutics (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Padua Research Archive (University of Padova) (submittedVersion, other-oa)
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Treatment and Management
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Diabetes and associated disorders
- Keywords
- type 1 diabetes, artificial pancreas, hypoglycemia, glucose profile, postprandial blood glucose
- MeSH terms
- Adolescent, Adult, Algorithms, Blood Glucose, Clinical Trials as Topic, Computer Simulation, Diabetes Mellitus, Type 1, Female, Humans, Hypoglycemia, Hypoglycemic Agents, Insulin, Insulin Infusion Systems, Male, United States, Blood Glucose Self-Monitoring, Reproducibility of Results
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