Modeling approaches to type 2 diabetes.
The incidence of type 2 diabetes is increasing rapidly, but clinical maintenance of normoglycemia remains challenging. The systemic, multifactorial character of diabetes is a key reason its treatment is so difficult. In the past 25 years, a number of mathematical and computational models have been developed to study this disease. These models offer promise in identifying the underlying disease pathophysiology in individual patients and in understanding the general pathophysiology characterizing the disease in large populations. To exploit these models most effectively, it is necessary to understand both the strengths and limitations of each model. This review outlines a selection of the models available for the study of diabetes, with a particular focus on the types of problems for which each model is well suited and the limitations that restrict how each model can be used.
Kansal
Anuraag R
AR
Entelos, Inc., Foster City, California 94404, USA. kansal@entelos.com
D003198:Computer Simulation; D003924:Diabetes Mellitus, Type 2 / Q000378:metabolism / Q000503:physiopathology*; D005947:Glucose / Q000378:metabolism; D006706:Homeostasis / Q000502:physiology; D006801:Humans; D007328:Insulin; D008954:Models, Biological
D007328:Insulin; D005947:Glucose