Evaluating anti-cancer drugs in vitro is an important aspect of the drug development pipeline. When evaluating anti-cancer drugs, two different measurements are used: relative viability, which scores an amalgam of proliferative arrest and cell death, and fractional viability, which specifically scores the degree of cell killing. These two metrics are often used interchangeably despite measuring different aspects of a drug response. This study explored the relationship between drug-induced growth inhibition and cell death, and found that most drugs affect both proliferation and death, but in different proportions, and with different relative timing. This causes a non-uniform relationship between relative and fractional response measurements. To unify these measurements, I created a data visualization and analysis platform, called drug GRADE, which characterizes the degree to which death contributes to an observed drug response. GRADE captures drug- and genotype-specific responses, which are not captured using traditional pharmaco-metrics. Current in vitro anti-cancer drug evaluation practices measure drug responses with cancer cell lines in mono-culture. However, many cell types in the tumor microenvironment influence cancer’s drug response and disease progression. Therefore, current drug evaluation practices overlook complex cell-cell interactions that influence cancer’s drug response. In this study, I developed a high-throughput assay to study the effect of another cell type (cytotoxic T cells) on cancer viability in co-culture, in vitro. Further, I developed a reference framework to model the complex interaction between cancer cells and cytotoxic T cells, and to model how T cell-mediated cell death is modulated by anti-cancer drug treatment. Taken together, this study highlights two new methods which enable better in vitro evaluation of drug responses in cancer.