A hallmark of the cancer tumor ecosystem is the rapid evolution of malignant cells which become resistant to treatment. Current treatment methods apply intense therapy to target the largest decrease in subclone populations. However, these treatment methods fail to account for the evolutionary dynamics of subclones, and therefore potentially expose patients to harmful side effects. In this project, we propose a model to account for the strategic interaction of the physician and the evolving subclones based on their resistance to therapy. Using this model, we describe treatment schedules that take advantage of inter-subclone competition for tumor ecosystem resources as well as prevent the most resistant subclones from dominating the tumor.