Open Access
December 2012 Toxicity profiling of engineered nanomaterials via multivariate dose-response surface modeling
Trina Patel, Donatello Telesca, Saji George, André E. Nel
Ann. Appl. Stat. 6(4): 1707-1729 (December 2012). DOI: 10.1214/12-AOAS563


New generation in vitro high-throughput screening (HTS) assays for the assessment of engineered nanomaterials provide an opportunity to learn how these particles interact at the cellular level, particularly in relation to injury pathways. These types of assays are often characterized by small sample sizes, high measurement error and high dimensionality, as multiple cytotoxicity outcomes are measured across an array of doses and durations of exposure. In this paper we propose a probability model for the toxicity profiling of engineered nanomaterials. A hierarchical structure is used to account for the multivariate nature of the data by modeling dependence between outcomes and thereby combining information across cytotoxicity pathways. In this framework we are able to provide a flexible surface-response model that provides inference and generalizations of various classical risk assessment parameters. We discuss applications of this model to data on eight nanoparticles evaluated in relation to four cytotoxicity parameters.


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Trina Patel. Donatello Telesca. Saji George. André E. Nel. "Toxicity profiling of engineered nanomaterials via multivariate dose-response surface modeling." Ann. Appl. Stat. 6 (4) 1707 - 1729, December 2012.


Published: December 2012
First available in Project Euclid: 27 December 2012

zbMATH: 1257.62109
MathSciNet: MR3058681
Digital Object Identifier: 10.1214/12-AOAS563

Keywords: Additive models , dose-response models , hierarchical models , multivariate , nanotoxicology

Rights: Copyright © 2012 Institute of Mathematical Statistics

Vol.6 • No. 4 • December 2012
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