ArticleJournal of diabetes science and technology2014
The UVA/PADOVA Type 1 Diabetes Simulator: New Features.
Article in Journal of diabetes science and technology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 171 papers.
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Who cites it
171 citing papers in PubMed.
- Methods for Insulin Bolus Adjustment Based on the Continuous Glucose Monitoring Trend Arrows in Type 1 Diabetes: Performance and Safety Assessment in an In Silico Clinical Trial.Journal of diabetes science and technology · 2023Trial
- Artificial Pancreas: Clinical Study in Latin America Without Premeal Insulin Boluses.Journal of diabetes science and technology · 2018Trial
- Analyzing the Potential of Advanced Insulin Dosing Strategies in Patients With Type 2 Diabetes: Results From a Hybrid In Silico Study.Journal of diabetes science and technology · 2018Trial
- A Human Glucoregulatory Model for the Rational Design and Evaluation of Diabetes Therapeutics.ACS pharmacology & translational science · 2026Article
- Article
- Trustworthy AI for personalized glycemic control: a systematic review and critical appraisal of multimodal forecasting and safety-critical closed-loop control.Reviews in endocrine & metabolic disorders · 2026Review
- Artificial Intelligence for Blood Glucose Level Prediction in Type 1 Diabetes: Methods, Evaluation, and Emerging Advances.Sensors (Basel, Switzerland) · 2026Review
- Recent Advances in Modeling and Prediction of Blood Glucose in Type 1 Diabetes.Delaware journal of public health · 2026Article
- Patient-specific deep offline artificial pancreas for blood glucose regulation in type 1 diabetes.Smart health (Amsterdam, Netherlands) · 2026Article
- A Wearable, Dual Closed-loop Insulin Delivery System for Precision Diabetes Management.Advanced materials (Deerfield Beach, Fla.) · 2026Article
- Cross-fusion of digital twins and artificial intelligence in diabetes: from mechanistic elucidation to full-cycle precision management.Frontiers in endocrinology · 2026Review
- A backstepping control of artificial pancreas for type 1 diabetes based on sub-fixed-time stability.Frontiers in endocrinology · 2026Article
- Distinct insulin sensitivity profiles revealed by clustering based on continuous glucose monitoring data in people living with type 1 diabetes.Frontiers in endocrinology · 2026Article
- Toward Trustworthy Diabetes Technologies: A Dynamic Platform for Safety and Security Evaluation.BME frontiers · 2026Article
- Pre-Ramadan time-below-range stratifies the simulated pump basal-rate dose-response during Ramadan fasting: a five-policy paired virtual-patient study.Frontiers in endocrinology · 2026Article
- Knowledgeable Language Models as Black-Box Optimizers for Personalized Medicine.... International Conference on Learning Representations · 2026Article
- A closed-loop microneedle-integrated physiological model for predictive glycemic management.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Modeling the effect of glucagon on endogenous glucose production in healthy individuals under meal-like conditions.American journal of physiology. Regulatory, integrative and comparative physiology · 2025Article
- What do LLMs value? An evaluation framework for revealing subjective trade-offs in assessment of glycemic control.Proceedings of machine learning research · 2025Article
- Harnessing Nonlinear Mechanics to Transform Medical Diagnostics.Applied mechanics reviews · 2025Article
111 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recent studies have provided new insights into nonlinearities of insulin action in the hypoglycemic range and into glucagon kinetics as it relates to response to hypoglycemia. Based on these data, we developed a new version of the UVA/PADOVA Type 1 Diabetes Simulator, which was submitted to FDA in 2013 (S2013). The model of glucose kinetics in hypoglycemia has been improved, implementing the notion that insulin-dependent utilization increases nonlinearly when glucose decreases below a certain threshold. In addition, glucagon kinetics and secretion and action models have been incorporated into the simulator: glucagon kinetics is a single compartment; glucagon secretion is controlled by plasma insulin, plasma glucose below a certain threshold, and glucose rate of change; and plasma glucagon stimulates with some delay endogenous glucose production. A refined statistical strategy for virtual patient generation has been adopted as well. Finally, new rules for determining insulin to carbs ratio (CR) and correction factor (CF) of the virtual patients have been implemented to better comply with clinical definitions. S2013 shows a better performance in describing hypoglycemic events. In addition, the new virtual subjects span well the real type 1 diabetes mellitus population as demonstrated by good agreement between real and simulated distribution of patient-specific parameters, such as CR and CF. S2013 provides a more reliable framework for in silico trials, for testing glucose sensors and insulin augmented pump prediction methods, and for closed-loop single/dual hormone controller design, testing, and validation.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.