The development of resistance to cancer therapy invariably limits the success of treatment. The conventional model for the development of resistance to therapy is built on a ‘somatic mutation theory’, meaning that the stochastic acquisition of mutations confer resistance-favored properties. However, an emerging paradigm implicates genetically similar, phenotypic variations capable of evading drug-induced death. Understanding and overcoming this newer model of ‘adaptive’ drug resistance requires an interdisciplinary approach that combines bioengineering techniques to both study and treat disease. Here, we describe the use of computational biology, nanotechnology and mechanistic molecular experimentation to develop novel therapeutic approaches for cancer treatment. This complex dissection of behavior reveals new biological phenomena, a distinct understanding of metabolic diversity and improved therapeutic approaches, reshaping our fundamental understanding of cancer.