Dose-Response Modeling of High-Throughput Screening Data

被引:20
|
作者
Parham, Fred [1 ]
Austin, Chris [2 ]
Southall, Noel [2 ]
Huang, Ruili [2 ]
Tice, Raymond [3 ]
Portier, Christopher [1 ]
机构
[1] NIEHS, NIH, Res Triangle Pk, NC 27709 USA
[2] NHGRI, NIH, Chem Genom Ctr, Bethesda, MD 20892 USA
[3] NIEHS, NIH, Natl Toxicol Program, Res Triangle Pk, NC 27709 USA
关键词
high-throughput screening; dose response; statistical modeling; viability assay;
D O I
10.1177/1087057109349355
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
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 2009:1216-1227)
引用
收藏
页码:1216 / 1227
页数:12
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