On the Prediction of Statistical Parameters in High-Throughput Screening Using Resampling Techniques

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A severe drawback in the high-throughput screening (HTS) process is the unintentional (random) presence of false positives and negatives. Their rates depend, among others, on the screening process being applied and the target class. Although false positives can be sorted out in subsequent process steps, their occurrence can lead to increased project cost. More fundamentally, it is not possible to rescue false nonhits. In this article, we investigate the prediction of the primary hit rate, hit confirmation rate, and false-positive and false-negative rates. Results for approximately 2800 compounds are considered that are tested as a pilot screen ahead of the primary screening work. This pilot screen is done at several concentrations and in replicates. The rates are predicted as a function of the proposed hit threshold by having the replicates serve as each other’s confirmers, and confidence limits to the prediction are attached by means of a resampling scheme. A comparison of the rates resulting from the resampling with the primary hit rate and the confirmation rates obtained during the screening campaign shows how accurate this method is. Hence, the “optimal” compound concentration for the screen as well as the optimal hit threshold corresponding to low false rates can be determined prior to starting the subsequent screening campaign.