Control-relevant modeling in drug delivery

A physiological Intensive Control Insulin-Nutrition-Glucose (ICING) model validated in critically ill patients

“…Given the limited data available, it is crucial to maintain a model that is uniquely identifiable with bedside (glucose) measurements. Although the model presented in this study requires many population assumptions, and resulted in a much simpler structure compared to many others [33,34,35,100], it is able to accurately capture the highly dynamic response in critical illness. It is the authors' conclusion that given limited data in a noisy and highly variable environment, such as critical care, a model that requires the minimal number of parameters to be identified will potentially cope most successfully both mathematically and clinically.…”

“…Many studies have developed glucose-insulin models with varying degrees of complexity for a wide range of uses, primarily in research studies of insulin sensitivity [27,31,32,33,34,35,36]. A more comprehensive model review can be found in [28].…”

“…In addition, it should be uniquely identifiable, and the type and number of parameters to be identified should reflect the clinically available data that will provide validation. Finally, the most important aspect for a model to be used in model-based TGC is its predictive ability, where most studies provide only fitting error as validation [29,33,36,37]. This paper presents a more comprehensive model, ICING (Intensive Control Insulin-Nutrition-Glucose model), for the use of glycaemic control particularly in the ICU.…”

Modeling and Hemofiltration Treatment of Acute Inflammation

“…Model predictive control (MPC) is a popular control methodology for addressing biomedical systems control problems [34,35], based on its ability to robustly manage subject-model mismatch in a variety of disease case studies. MPC uses the predictive capacity of a model to manipulate inputs and guide a dynamic process towards a target trajectory [36].…”

Identification of Linear Dynamic Models for Type 1 Diabetes: A Simulation Study

“…For instance, the original model excluded exogenous insulin infusion as an input. Although it has been easily altered to include this input (Parker and Doyle III, 2001), the modified minimal model still does not include the dynamics of subcutaneous insulin infusion. A more recent model by Cobelli et al (1998) is significantly more detailed than the model of Bergman et al (1981), but its details are thus far unpublished.…”