Can Toxicity for Different Species Be Correlated?: The Concept and Emerging Applications of Interspecies Quantitative Structure-Toxicity Relationship (i-QSTR) Modeling

Can Toxicity for Different Species Be Correlated?: The Concept and Emerging Applications of Interspecies Quantitative Structure-Toxicity Relationship (i-QSTR) Modeling

Supratik Kar, Rudra Narayan Das, Kunal Roy, Jerzy Leszczynski
ISBN13: 9781522516293|ISBN10: 1522516298|EISBN13: 9781522516309
DOI: 10.4018/978-1-5225-1629-3.ch015
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MLA

Kar, Supratik, et al. "Can Toxicity for Different Species Be Correlated?: The Concept and Emerging Applications of Interspecies Quantitative Structure-Toxicity Relationship (i-QSTR) Modeling." Agri-Food Supply Chain Management: Breakthroughs in Research and Practice, edited by Information Resources Management Association, IGI Global, 2017, pp. 339-371. https://doi.org/10.4018/978-1-5225-1629-3.ch015

APA

Kar, S., Das, R. N., Roy, K., & Leszczynski, J. (2017). Can Toxicity for Different Species Be Correlated?: The Concept and Emerging Applications of Interspecies Quantitative Structure-Toxicity Relationship (i-QSTR) Modeling. In I. Management Association (Ed.), Agri-Food Supply Chain Management: Breakthroughs in Research and Practice (pp. 339-371). IGI Global. https://doi.org/10.4018/978-1-5225-1629-3.ch015

Chicago

Kar, Supratik, et al. "Can Toxicity for Different Species Be Correlated?: The Concept and Emerging Applications of Interspecies Quantitative Structure-Toxicity Relationship (i-QSTR) Modeling." In Agri-Food Supply Chain Management: Breakthroughs in Research and Practice, edited by Information Resources Management Association, 339-371. Hershey, PA: IGI Global, 2017. https://doi.org/10.4018/978-1-5225-1629-3.ch015

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Abstract

Experimental evaluation of the toxicity of a compound is an expensive practice, and it requires sacrifice of a large number of animals. As a consequence, in silico techniques for predictive toxicology are taking the central stage of attention of the scientific community. Interspecies quantitative structure-toxicity relationship (i-QSTR) modeling provides a tool for estimation of contaminant's sensitivity with known levels of uncertainty for a diverse pool of species. It is capable of extrapolating data for one toxicity endpoint to another toxicity endpoint when the data for the second species are unavailable. The emerging i-QSTR approach can overcome the cost of multiple toxicity tests, improve the understanding of the mechanism of toxic action (MOA) of chemicals for different organisms and endpoints and is very useful in order to fill the data gaps where toxicity value for a particular compound is absent for a specific endpoint.

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