Skip to Main Content
Model reduction is an important step in modeling before the model can be deployed for practical applications. Its application to complex biological systems is often very useful. In this work, a minimal model expounding the glucose insulin interactions is considered and scaling analysis is applied to reduce the number of parameters and scale them to ~O(1). FSIVGTT is one of the diagnostic procedures to check the diabetic condition of an individual. Here, in silico studies are done to characterize the sampling times of existing FSIVGTT. In this regard, global sensitivity analysis is performed on the reduced parametric model to unravel the key parameters influencing the glucose and insulin concentration at the sampling times of FSIVGTT. Overall, this analysis can be beneficial to medical community in designing experiments for implementing novel and efficient diagnostic protocols.