Description

Mathematical modeling is a great tool in the medical field. Mathematical models help to simulate the dynamics of complex systems. Dynamic models typically are represented by differential equations. Mathematical models are used everywhere in cancer research. The number of cancer cells in a tumor is not easy to calculate due to continuous changes in time. So may have to calculate with the help of differential equations easily. Challenge of mathematical modeling is to produce simplest possible model.

Many of the researchers developed mathematical models that identify the most effective chemotherapeutic administration regimens using optimization and control techniques. In 1962 L.S. Pontryagin, etal. was developed the model for optimal control. A. Lotka and R. Fisher has been developed the mathematical theory life history evolution in 1970s. Panetta was developed an effective model for heterogeneous tumor and chemotherapeutic drug action in 1996. A.J.Coldman and J.M.Murray was developed the stochastic model of cancer treatment in 2000. L.G. de Pillis, etal. developed the system of ODE for variety of cancers and different treatments in between 2000 to 2013. In recent years so many authors developed them new models based on the above author's research.

In recent years most of the people were affected by different types of cancer. Some type of cancer is the curable disease when we detect in early stage. Rare type of cancer is the not fully curable disease but to controls the tumor growth and gives assumption of survival for some years. There are different types of treatments are available according to their stage of the disease. Stages were defined from their tumor size and disease spreading position of their disease. Main treatments of cancers are Surgery, Chemotherapy, Radiation therapy, Immunotherapy, Gene therapy and Hormone therapy. Mathematical modeling of tumor dynamics and treatment responses can be applied to identify better drug administration regimes. Using mathematical model for tumor growth and cancer treatments we can reduce the tumor size.

Now everyone must know about types of cancer and correct treatments for that. So select this area and developed the mathematical models for tumor dynamics and combinations of treatments. Collected the breast and colorectal cancer patient's details and fitted to our model then reduced the tumor burden. Also have find that which type of drug combinations are used for colorectal cancer and breast cancer treatments.

Here we used Mathematical Tools are Differential Equation, Ordinary Differential Equation (ODE), Formulation of differential equation, Growth model, optimal control, Equilibrium and Stability Analysis in ODE.