Abstarct: Breast cancer is the second leading cause of cancer deaths in women after lung cancer, and is the most common cancer in women after non-mextastatic skin cancer. According to World Health Organization (WHO) statistics, more than 1.2 million breast cancer patients are diagnosed each year and more than 500,000 die from the disease. Iran is no exception. As such, cancer accounts for 4.21% of all malignancies and is the most common cancer in Iranian women. As many as 24 out of every 10,000 Iranian women get the disease. Given the current situation, Iranian women develop the disease a decade earlier. Given this, diagnosis and treatment of the disease is important. One of the most important problems in the treatment of cancer is its timely diagnosis. There are many different methods of detection; biosensors are the best way to measure different biological parameters in the human body. In this study, two systems are examined, in the first system we detect the disease, and by using therapeutic immunity to modify the dynamics of the system and by using chemotherapy to guide the path of the system to the desired equilibrium point. Treatment was performed on three patients aged 8, 22 and 60 years, as the age of the patient was effective in providing treatment. The duration of treatment is shorter than in the young and elderly patient because of the stronger assumption of the immune system in the young and elderly patient, indicating the importance of immunotherapy along with chemotherapy. The next section discusses the relationship between blood glucose level and its effect on cancer treatment. In this way, biosensor modeling is performed using analytical and numerical solution of partial differential equations. The main rationale of this study is to evaluate the critical parameters and conditions that determine the biosensor response. Hence the solution of finite difference method 4 is dedicated to the digital solution of linear diffusion equations that are the basis of biosensor modeling. Then the results of the construction and laboratory data are compared with the modeling method. And we were able to optimize the sensor performance as much as possible by analyzing the parameters affecting the sensor output.