Models of Glucose Metabolism and Control in Diabetes
Claudio Cobelli
University of Padova, Italy
Diabetes is one of the major chronic diseases, i.e. together with its complications it accounts for more than 10% of national healthcare expenditure. Modeling can enhance understanding of this disease in quantitative terms and is becoming an increasingly important aid in diagnosis, prognosis and in planning of therapy. In recent years the scope of modeling in relation to carbohydrate metabolism and diabetes has seen dramatic expansion such that it is now being applied across the spectrum from populations of patients (public health) to whole-body, to organ and to molecular level. I will discuss recent developments mostly concentrating on whole-body and organ modeling. At whole-body level I will discuss models to assess the efficacy of homeostatic control , e.g insulin sensitivity, beta-cell function, hepatic insulin extraction and their interplay, and of system fluxes, from dynamic intravenous (IVGTT) or oral (OGTT/meal) experiments, possibly also including tracers. At organ level models to assess key processes like glucose transport and phosphorylation in skeletal muscle, a key target tissue, from PET tracer experiments will be presented. Aspects of model validation will be addressed. A variety of studies will be reviewed where models have provided unique information on nonaccessible parameters/signals, thus enhancing the understanding of the physiology and pathophysiology of glucose metabolism, like obesity and diabetes. Population modeling will also be discussed viz a viz individual modeling strategies . In addition to parsimonious "models to measure" there is the need to develop in silico large scale simulation models. These models can help when it is either not possible, appropriate, convenient or desirable to perform a particular experiment on the system. Thanks to a recent large scale clinical trial a new in silico model has been developed which is capable of generating realistic synthetic subjects. I will discuss its use in the context of a JDRF artificial pancreas project.
