Modeling the Effect of Chemotherapy on Melanoma B16F10 in Mice Using Cellular Automata and Genetic Algorithm in Tapered Dosage of FBS and Cisplatin

Purpose: Plans for all types of therapies for cancer need to be updated according to new achievements in science and technology. Building models of in vitro cancer cell growth may make a predictive view for physicians about the behavior of these cells in the real world. Methods: In this study using experimental data which acquired from cultured cells and taking photos using a digital microscope lens, we designed a Cellular Automata model of death and growth of melanoma cancer cells in the presence of different concentration of FBS and different dose of Cisplatin as a chemotherapy drug. Results: This model is based oncellular automata although we used a genetic algorithm for this model.This combined model casts a dynamic in model and made which is adoptive based on the alternation of the environment. In the end, we achieved up to 75% prediction accuracy about the behavior of these cells. Conclusion: The proposed model showed approximately good results to predict tumor growth in the presence of different dosages of chemotherapy drug and it can make a perspective of tumor growth for us.