Acute myeloid leukemia (AML) is a rapidly fatal disease that can quickly be brought into complete remission, but with high relapse rates. The genetic evolution of the disease has been defined, but the basis for resistance to therapy and effective strategies to overcome it are lacking. This project seeks to take advantage of well-defined murine models where an analogous form of highly lethal, human AML can be temporarily brought into remission by traditional chemotherapy agents. Combining these basic features with novel strategies for quantitatively assessing oncological behavior and cell growth patterns, this project will provide multidimensional datasets for mathematical modeling of disease progression and susceptibility to therapeutic approaches. Ultimately, these models will be used to predict and test unique vulnerabilities of the disease that can be exploited therapeutically to reduce AML relapse.