The effect of the choice of initial estimation for a tumor model parameter estimation problem

Cyber-medical systems provides lots of possibilities that help doctors plan more effective treatments. A reliable mathematical model that can be customized is essential for therapy optimization. We deal with a mathematical model that we use to optimize chemotherapy. We have parameter sets that we use to create virtual patients and create therapy with random doses. Then we use a non-linear function optimization procedure with different initial values, Whose task is to fit the unknown parameters. Our goal is to examine the extent to which the procedure is able to find the real parameters of the virtual patients in the neighborhood of the original parameters. We found that there are parameters in the model where the parameter can not be found if the initial estimation is far from the real value.