Literature DB >> 27518632

Accounting Artifacts in High-Throughput Toxicity Assays.

Jui-Hua Hsieh1.   

Abstract

Compound activity identification is the primary goal in high-throughput screening (HTS) assays. However, assay artifacts including both systematic (e.g., compound auto-fluorescence) and nonsystematic (e.g., noise) complicate activity interpretation. In addition, other than the traditional potency parameter, half-maximal effect concentration (EC50), additional activity parameters (e.g., point-of-departure, POD) could be derived from HTS data for activity profiling. A data analysis pipeline has been developed to handle the artifacts and to provide compound activity characterization with either binary or continuous metrics. This chapter outlines the steps in the pipeline using Tox21 glucocorticoid receptor (GR) β-lactamase assays, including the formats to identify either agonists or antagonists, as well as the counter-screen assays for identifying artifacts as examples. The steps can be applied to other lower-throughput assays with concentration-response data.

Entities:  

Keywords:  Assay artifacts; Concentration-response data; Data analysis pipeline; HTS; Point-of-departure; Tox21; qHTS

Mesh:

Substances:

Year:  2016        PMID: 27518632     DOI: 10.1007/978-1-4939-6346-1_15

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  7 in total

1.  An Intuitive Approach for Predicting Potential Human Health Risk with the Tox21 10k Library.

Authors:  Nisha S Sipes; John F Wambaugh; Robert Pearce; Scott S Auerbach; Barbara A Wetmore; Jui-Hua Hsieh; Andrew J Shapiro; Daniel Svoboda; Michael J DeVito; Stephen S Ferguson
Journal:  Environ Sci Technol       Date:  2017-09-06       Impact factor: 9.028

2.  Application of Benchmark Concentration (BMC) Analysis on Zebrafish Data: A New Perspective for Quantifying Toxicity in Alternative Animal Models.

Authors:  Jui-Hua Hsieh; Kristen Ryan; Alexander Sedykh; Ja-An Lin; Andrew J Shapiro; Frederick Parham; Mamta Behl
Journal:  Toxicol Sci       Date:  2019-01-01       Impact factor: 4.849

3.  Identifying Compounds with Genotoxicity Potential Using Tox21 High-Throughput Screening Assays.

Authors:  Jui-Hua Hsieh; Stephanie L Smith-Roe; Ruili Huang; Alexander Sedykh; Keith R Shockley; Scott S Auerbach; B Alex Merrick; Menghang Xia; Raymond R Tice; Kristine L Witt
Journal:  Chem Res Toxicol       Date:  2019-06-18       Impact factor: 3.739

4.  From viability to cell death: Claims with insufficient evidence in high-impact cell culture studies.

Authors:  Ali Burak Özkaya; Caner Geyik
Journal:  PLoS One       Date:  2022-02-22       Impact factor: 3.240

5.  Nonionic Ethoxylated Surfactants Induce Adipogenesis in 3T3-L1 Cells.

Authors:  Christopher D Kassotis; Erin M Kollitz; Patrick Lee Ferguson; Heather M Stapleton
Journal:  Toxicol Sci       Date:  2018-03-01       Impact factor: 4.849

Review 6.  Benchmarking Data Sets from PubChem BioAssay Data: Current Scenario and Room for Improvement.

Authors:  Viet-Khoa Tran-Nguyen; Didier Rognan
Journal:  Int J Mol Sci       Date:  2020-06-19       Impact factor: 5.923

7.  Identifying Attributes That Influence In Vitro-to-In Vivo Concordance by Comparing In Vitro Tox21 Bioactivity Versus In Vivo DrugMatrix Transcriptomic Responses Across 130 Chemicals.

Authors:  William D Klaren; Caroline Ring; Mark A Harris; Chad M Thompson; Susan Borghoff; Nisha S Sipes; Jui-Hua Hsieh; Scott S Auerbach; Julia E Rager
Journal:  Toxicol Sci       Date:  2019-01-01       Impact factor: 4.849

  7 in total

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