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Optimal design of clinical tests for the identification of physiological models of type 1 diabetes mellitus in the presence of model uncertainty
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TLDR
In this article, the problem of the identification of single individual parameters in detailed dynamic models of glucose homeostasis is considered, and the optimal model-based design of experiment techniques are used to design a set of clinical tests that allow the model parameters to be estimated in a statistically sound way, while meeting constraints related to safety of the subject and ease of implementation.Abstract:
Type 1 diabetes mellitus is a disease affecting millions of people worldwide and causing the expenditure of millions of euros every year for health care. One of the most promising therapies derives from the use of an artificial pancreas, based on a control system able to maintain the normoglycaemia in the subject affected by diabetes. A dynamic simulation model of the glucose-insulin system can be useful in several circumstances for diabetes care, including testing of glucose sensors, insulin infusion algorithms, and decision support systems for diabetes. This paper considers the problem of the identification of single individual parameters in detailed dynamic models of glucose homeostasis. Optimal model-based design of experiment techniques are used to design a set of clinical tests that allow the model parameters to be estimated in a statistically sound way, while meeting constraints related to safety of the subject and ease of implementation. The model with the estimated set of parameters represents a specific subject and can thus be used for customized diabetes care solutions. Simulated results demonstrate how such an approach can improve the effectiveness of clinical tests and serve as a tool to devise safer and more efficient clinical protocols, thus providing a contribution to the development of an artificial pancreas.read more
Citations
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Journal ArticleDOI
Diabetes: Models, Signals, and Control
TL;DR: The control of diabetes is an interdisciplinary endeavor, which includes a significant biomedical engineering component, with traditions of success beginning in the early 1960s, and progressed to large-scale in silico experiments, and automated closed-loop control (artificial pancreas).
Journal ArticleDOI
Control-Relevant Models for Glucose Control Using A Priori Patient Characteristics
TL;DR: Control-relevant models are developed for T1DM, as opposed to models that minimize a prediction error, and the parameters of these models are chosen conservatively to minimize the likelihood of hypoglycemia events.
Journal ArticleDOI
Clinical Application of Emerging Sensor Technologies in Diabetes Management: Consensus Guidelines for Continuous Glucose Monitoring (CGM)
Irl B. Hirsch,Dana U. Armstrong,Richard M. Bergenstal,Bruce A. Buckingham,Belinda P Childs,William L. Clarke,Anne L. Peters,Howard Wolpert +7 more
TL;DR: It is concluded that routine use of CGM, with real-time data showing the rate and direction of glucose change, could revolutionize current approaches to evaluating and managing glycemia.
Journal ArticleDOI
Review and Analysis of Blood Glucose (BG) Models for Type 1 Diabetic Patients
TL;DR: Existing glucose-insulin dynamic models dating back from early 1960s are reviewed along with an overview of meal absorption and exercise effect models for BG regulation in type 1 diabetic patients.
Journal ArticleDOI
A backoff strategy for model‐based experiment design under parametric uncertainty
TL;DR: In this paper, a general methodology is proposed to formulate and solve the experiment design problem by explicitly taking into account the presence of parametric uncertainty, so as to ensure both feasibility and optimality of the planned experiment.
References
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Journal ArticleDOI
On the use of continuous glucose monitoring systems to design optimal clinical tests for the identification of type 1 diabetes models
TL;DR: The results suggest that, although the optimal design of a clinical test is simpler if continuous glucose measurements are made available through a CGMS, the noise level and formulation may make continuous measurements less suitable for model identification than their discrete counterparts.
Journal ArticleDOI
A revised Sorensen model: Simulating glycemic and insulinemic response to oral and intra-venous glucose load.
TL;DR: The goal of the present work is to revise the original Sorensen’s model, to clearly summarize its defining equations, to supplement it with a missing gastrio-intestinal glucose absorption and to make an implementation of the revised model available on-line to the scientific community.
Book ChapterDOI
Physiology-Based Interval Models: A Framework for Glucose Prediction Under Intra-patient Variability
Jorge Bondia,Josep Vehí +1 more
TL;DR: A review of physiological interval models applied to the prediction of blood glucose in type 1 diabetes glycemic control is presented and interval models are introduced as well as methods for simulation.