Drug-response studies play an
important role in both preclinical and clinical research, but such
studies are complicated by differences in cell growth rates across
samples and conditions. To improve the value and reliability of such
studies, new metrics for parameterizing drug response were developed
in Nature Methods by Marc Hafner, Mario Niepel, and Peter
Sorger of the Harvard Medical School (HMS) LINCS Center. These new
metrics, such as GR50 and GRmax, are derived from normalized growth
rate inhibition (GR) values which are based on the ratio of growth
rates in the presence and absence of perturbagen. Largely
independent of cell division rate and assay duration, GR metrics are
more robust than IC50 and Emax for assessing cellular response to
drugs, RNAi, and other perturbations in which control cells divide
over the course of the assay.
|Learn More about GR metrics||Upload and analyze your own data||Browse datasets analyzed using GR metrics|
For offline computation, analysis, and visualization, see the Bioconductor R package GRmetrics.
Hafner M*, Niepel M*, Chung M, Sorger PK. (2016) Growth rate inhibition metrics correct for confounders in measuring sensitivity to cancer drugs. Nat Methods. doi: 10.1038/nmeth.3853.
Nick Clark1, Marc Hafner2, Michal Kouril1, Mario Niepel2, Elizabeth Williams2, Jeremy Muhlich2 and Mario Medvedovic1
1 LINCS-BD2K Data Coordination and Integration Center; 2 HMS LINCS Center, Harvard Medical School