Tumor Evolution Prediction Based on Mathematical Models

One of the most common causes of death throughout the world is cancer. The tumor growth modeling and even control therapy is a promising way to design an efficient, personalized cancer evolution prediction and treatment. This requires a model of the physiological process’ dynamics and a control law to design the therapy. The main goal of the present research is to incorporate the existing findings in a malignant tumor growth model, including tumor proliferation and necrosis, vascular and tumor volumes, serum efficiency rate, serum level dynamics and losses and even phagocytosis. The model’s validity is assessed using experimental data from literature.