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Dose-Response Modeling of High-Throughput Screening Data
Fred Parham*,
Chris Austin,
Noel Southall,
Ruili Huang,
Raymond Tice,
and
Christopher Portier
* To whom correspondence should be addressed. E-mail: parham{at}niehs.nih.gov.
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Abstract |
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The National Toxicology Program is developing a high-throughput screening (HTS) program to set testing priorities for compounds of interest, to identify mechanisms of action, and potentially to develop predictive models for human toxicity. This program will generate extensive data on the activity of large numbers of chemicals in a wide variety of biochemical- and cell-based assays. The first step in relating patterns of response among batteries of HTS assays to in vivo toxicity is to distinguish between positive and negative compounds in individual assays. Here, the authors report on a statistical approach developed to identify compounds positive or negative in an HTS cytotoxicity assay based on data collected from screening 1353 compounds for concentration-response effects in 9 human and 4 rodent cell types. In this approach, the authors develop methods to normalize the data (removing bias due to the location of the compound on the 1536-well plates used in the assay) and to analyze for concentration-response relationships. Various statistical tests for identifying significant concentration-response relationships and for addressing reproducibility are developed and presented. (Journal of Biomolecular Screening XXXX:xx-xx)
First published on October 14, 2009
Journal of Biomolecular Screening 2009, doi:10.1177/1087057109349355
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