Multi-level multi-scale metabolites simulation

Diabetes is a world-wide health problem with 415 millions of people suffering from the disease. Most diabetics are suffering from Type 2 Diabetes, which is preceded by insulin resistance in glucose utilizing tissues, such as adipose, liver, and muscle tissues. Diabetes is diagnosed when the insulin control of the glucose levels fails, which leads to high glucose levels in the blood. To better understand the insulin control of blood glucose, mathematical modeling has been used for many years to simulate the dynamics of glucose and insulin levels in the blood. Models have also been used to understand the intracellular insulin-signaling network in the insulin responding tissues. There have also been attempts to connect models from these different layers of control into a multi-level and multi-scale simulation model. However, to do such connections, several assumptions must be made about the comparability of the data from the different levels. Here, I aim for a deeper understanding of these assumptions and to use more advanced data for glucose uptake dynamics than in earlier work. I used data from the literature for the dynamics of glucose uptake in adipose and muscle tissues and improve the model in several steps to have a better agreement with these data. In particular, I refined the sub-division of the glucose uptake between the organs, to also account for liver uptake, a correction that implied a reduction by 50% for the muscle and adipose tissue glucose uptake. Unlike previous models, the updated model also describes blood flow. Finally, because of the connection to the intracellular level, the model can be used to simulate the response to anti-diabetic drugs.