Modeling of Data for Tumor Growth and Chemotherapy


There is always a struggle between normal cells and foreign bodies inside us. We want to get rid of harmful bacteria, viruses, cancer cells, or anything in the body that hampers the proper functioning of the body. At times, there are blood clots formed and they prevent smooth flow of blood in the body leading to heart attack or stroke. Unfortunately, with a majority of traditional methods when a doctor treats a patient some harm is caused to the normal cells as well. Now we have a new way to combat the enemy within. It is target specific drug delivery.
Cancer cells have a very high growth rate. Thus, one needs to weed out all malignant cells as fast as possible. In the conventional chemotherapeutic treatment, an anticancer drug kills not only cancer cells but it also kills normal or healthy cells. The majority of the patients react severally to such drugs and it leads to vomiting, nausea, as well as loss of hair. If it becomes unbearable, another drug called rescue factor is given to the patient. This rescue factor nullifies the effect of the first drug and gives relief to the patient from the adverse drug reaction. However, administration of such a drug too soon hampers the effectiveness of the drug against cancer. On the other hand, delay in giving the rescue factors leads to patient suffering due to the drug reaction. It is indeed like walking on a fine edge sword. Research conducted at the University of Washington and Washington State University in 1985 showed that it is possible to schedule an optimal time and dosage to administer the drug for each patient using mathematical models (1).