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Applications of quantitative HTS (qHTS) to facilitate assay pilot testing

Auld, Douglas, Hill, William, Smith, Thomas, Zhang, Ji, Kang, Zhao Bin, Ho, Pei-I, Ardayfio, Ophelia and Bowes, Scott (2014) Applications of quantitative HTS (qHTS) to facilitate assay pilot testing. Journal of Biomolecular Screening, 19 (5). pp. 651-660. ISSN 1087-05711552-454X

Official URL: http://jbx.sagepub.com/

Abstract

Pilot testing of an assay intended for high-throughput screening (HTS) is a necessary but often time consuming step in the assay optimization process. Typically, assay performance statistical factors such as Z-factor, repeatability, and hit rates are assessed at a single concentration, followed by validation of the hits at multiple concentrations after requesting additional compound sample. Oftentimes this involves iterative testing of small compound sets at different concentrations to evaluate the automated protocol and hit rates. One approach that enables flexible and rapid collection of both assay performance statistics and concentration-response curves against chemical libraries in a single experiment is quantitative HTS (qHTS). Here we investigated the application of qHTS to facilitate pilot testing of HTS assays using selected sets of 1,400 to 5,000 compounds. We describe the process for producing eight point concentration response curves using an inter-plate asymmetric dilution protocol where the first four concentrations are used to represent the range of typical single concentrations employed in HTS and the last four concentrations are used for robust curve fitting. We describe how this data can be rapidly analyzed to retrospectively determine the frequency of false positives, false negatives, hits, and confirmation rates as a function of screening concentration. This paradigm can facilitate testing of assay performance factors, choosing the optimal concentration for the large-scale HTS, and (when applied to annotated compound collections) the method provides pharmacological data for building robust target/pathway hypotheses in cell-based assays.

Item Type: Article
Date Deposited: 13 Oct 2015 13:13
Last Modified: 06 Jul 2016 23:45
URI: https://oak.novartis.com/id/eprint/10184

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