Abstract Tumor/T-cell co-cultures in combination with large-scale genome-editing tools emerged as powerful tools for discovery of drivers of resistance to immunotherapies. Traditionally, chromium or lactate-dehydrogenase release and/or target cell viability counts before and after co-culture treatment are used as surrogate endpoint assays to estimate the selection pressure applied. These assays cannot dissect growth arrest, cell death, cell viability and target cell outgrowth, all of which occur as a consequence of released cytokines and direct tumor/T-cell interactions, hence, significantly impact the interpretation of small- and large-scale screens in co-culture models. These biases are particularly relevant when comparing cell lines or genotypes with different growth kinetics. Here, we use a dual reporter system and adopt pharmaco-mathematical principles to dissect these biases to create a growth-rate corrected co-culture metric (GRC), which normalizes T-cell mediated antiproliferative and cytotoxic effects in tumor target cells. We illustrate the value of this metric by comparing fast and slow-growing tumor cells in autologous patient-derived melanoma/T-cell co-culture pairs. At tumor-T-cell ratios resulting in a half maximal relative reduction of target cell counts compared to controls, the fast-proliferating cell line had not changed in absolute cell counts since baseline while the slow-growing cell line showed a 50% reduction. This indicates that in one instance (fast growing cell line) growth-retardation occurred due to a balance of immune editing and target cell proliferation, while in the other (slow-growing cell line) T-cell mediated killing resulted in net loss of tumor cells. Using GRC, these differences can be readily distinguished, and comparable selection conditions can be selected. This has important implications for large-scale screens with perturbations within cancer cells: drop-outs from a screen in the fast-growing cell line would not only contain perturbations that increase specific sensitivity to T-cell mediated cytotoxicity, but also perturbations causing a general loss in proliferation/survival fitness. In addition, some of the discrepancy in recently published screens may be explained by differences in models with varying proliferation rates and therefore selection conditions. In summary, the GRC metric enhances the interpretation of co-culture experiments and could contribute to improved selection of targets from large-scale screens investigating resistance to T-cell mediated toxicity for drug development. Citation Format: Johannes Christian Melms, Clarence Yapp, Caitlin Elizabeth Mills, Peter Sorger, Benjamin Izar. A growth rate corrected metric for cytotoxic co-culture systems [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2168.