Growth rate inhibition metrics correct for confounders in measuring sensitivity to cancer drugs

Drug sensitivity and resistance are conventionally quantified by IC(50) or E(max) values, but these metrics are highly sensitive to the number of divisions taking place over the course of a response assay. The dependency of IC(50) and E(max) on division rate creates artefactual correlations between genotype and drug sensitivity while obscuring valuable biological insights and interfering with biomarker discovery. We derive alternative drug response metrics that are insensitive to division number. These are based on estimating the magnitude of drug-induced growth rate inhibition (GR) using endpoint or time-course assays. We show that GR(50) and GR(max) are superior to conventional metrics for assessing the effects of drugs in dividing cells. Moreover, adopting GR metrics requires only modest changes in experimental protocols. We expect GR metrics to improve the study of cell signaling and growth using drugs, discovery of drug response biomarkers, and identification of drugs effective on specific patient-derived tumor cells.