Systems toxicology: real world applications and opportunities

Hartung, Thomas and FitzGerald, Rex E and Jennings, Paul and Mirams, Gary R and Peitsch, Manuel C and Rostami-Hodjegan, Amin and Shah, Imran and Wilks, Martin F and Sturla, Shana J (2017) Systems toxicology: real world applications and opportunities. Chemical Research in Toxicology, 30 (4). pp. 870-882. ISSN 1520-5010

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Abstract

Systems Toxicology aims to change the basis of how adverse biological effects of xenobiotics are characterized from empirical end points to describing modes of action as adverse outcome pathways and perturbed networks. Toward this aim, Systems Toxicology entails the integration of in vitro and in vivo toxicity data with computational modeling. This evolving approach depends critically on data reliability and relevance, which in turn depends on the quality of experimental models and bioanalysis techniques used to generate toxicological data. Systems Toxicology involves the use of large-scale data streams ("big data"), such as those derived from omics measurements that require computational means for obtaining informative results. Thus, integrative analysis of multiple molecular measurements, particularly acquired by omics strategies, is a key approach in Systems Toxicology. In recent years, there have been significant advances centered on in vitro test systems and bioanalytical strategies, yet a frontier challenge concerns linking observed network perturbations to phenotypes, which will require understanding pathways and networks that give rise to adverse responses. This summary perspective from a 2016 Systems Toxicology meeting, an international conference held in the Alps of Switzerland, describes the limitations and opportunities of selected emerging applications in this rapidly advancing field. Systems Toxicology aims to change the basis of how adverse biological effects of xenobiotics are characterized, from empirical end points to pathways of toxicity. This requires the integration of in vitro and in vivo data with computational modeling. Test systems and bioanalytical technologies have made significant advances, but ensuring data reliability and relevance is an ongoing concern. The major challenge facing the new pathway approach is determining how to link observed network perturbations to phenotypic toxicity.

Item Type: Article
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Mathematical Sciences
Identification Number: 10.1021/acs.chemrestox.7b00003
Related URLs:
Depositing User: Mirams, Gary
Date Deposited: 09 May 2017 13:55
Last Modified: 09 May 2017 14:00
URI: http://eprints.nottingham.ac.uk/id/eprint/42654

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