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High Throughput Screening (HTS) assays are used to rapidly identify promising drug candidates or leads from hundreds of thousands of compounds. Hence, it is important that the assay should be designed to discriminate responses from the active and inactive compounds and the background noise. We introduce the idea of a signal window which provides a degree of separation between signals. This allows one to correctly identify new molecular entities with desired level of activity (called "hits") in the presence of variability. The statistical criteria for setting and calculating signal windows are presented along with illustrative examples. Results show that the ideal signal window should be 2 standard deviations (SD) of the largest signal in screening assays, although a 1 SD window size is the minimum acceptable limit. When signal windows are set below 2 SD, the probability of missing "hits" increases significantly.

Design of Signal Windows in High Throughput Screening Assays for Drug Discovery