You are here:
Computational Toxicology
Citation:
SINGH, A. V., R. J. KAVLOCK, A. M. RICHARD, AND C. YANG. Computational Toxicology. Second Edition, Chapter 21, Knudsen, T., Daston,GP (ed.), Comprehensive Toxicology. Elsevier Ltd, Oxford, Uk, 12:307-337, (2010).
Impact/Purpose:
Scientific advances are driven not only by new experimental technologies and fundamental insights, but also by finding new ways to harness and explore multiple dimensions of existing data. Computational toxicology, Internet resources, and the informatics advances presented in this chapter clearly have a great deal to offer to the developmental toxicology field, but they must be anchored to accurate and useful representations of fundamental biological processes, in vivo data, and ultimately human adverse outcomes. One of the key challenges aheadwill be to engage toxicologists and risk assessors to use and further develop these capabilities, and to optimally integrate these tools and approaches into the developmental toxicology screening and assessment workflow.
Description:
‘Computational toxicology’ is a broad term that encompasses all manner of computer-facilitated informatics, data-mining, and modeling endeavors in relation to toxicology, including exposure modeling, physiologically based pharmacokinetic (PBPK) modeling, dose-response modeling, and so on. Computable databases are enabling retrospective analysis, data mining, structure–activity relationship (SAR) studies, and model development. In addition, broadly applied chemical structure standards and chemoinformatics approaches are enabling comparison and cross-referencing of chemical data across previously disjointed areas of regulatory interest (e.g.,environmental, industrial, pharmaceutical, and food-use chemicals). In tandem with these informatics advances, a systems biology framework is being constructed through text mining, concept mining, and the integration of a large amount of mechanistic data in developmental biology and genetics. All these approaches are highly data-dependent and informatics- intensive and, together, they represent the next phase in evolution of predictive toxicology. Such technologies are beginning to be applied in earnest to the field of developmental toxicology and offer the promise of new insights and capabilities for the research and risk assessment community. This chapter will provide a background and overview of recent advances in informatics-based computational toxicology approaches, from both biological and chemical perspectives, that are poised to significantly impact the field of developmental toxicology.
