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A Strategy to Define Applicability Domains for Read-Across

Pestana, C, Enoch, SJ, Firman, JW, Madden, JC, Spinu, N and Cronin, MTD (2022) A Strategy to Define Applicability Domains for Read-Across. Computational Toxicology, 22. ISSN 2468-1113

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Abstract

The definition, characterisation and assessment of the similarity between target and source molecules are cornerstones of the acceptance of a read-across prediction to fill a data gap for a toxicological endpoint. There is much guidance and many frameworks which are applicable in a regulatory context, but as yet no formalised process exists by which to determine whether or not the properties of an analogue (or chemicals within a category) fall within an appropriate domain from which a reliable read-across prediction can be made. This investigation has synthesised much of the existing knowledge in this area into a practical strategy to enable the domain of a read-across prediction to be defined, in terms of chemistry (structure and properties), toxicodynamics and toxicokinetics. The strategy is robust, comprehensive, flexible, and can be implemented readily. It enables the relative similarity and dissimilarity, between target and source molecules, for both the analogue and category approaches, to be analysed and provides a basis for alternative scenarios such as read-across based on formation of a common metabolite or biological profile to be defiend. Herein, the read-across domains for the repeated dose toxicity of a group of triazoles and imidazoles have been evaluated. The most challenging aspect to this approach will continue to be determining what is an “acceptable” degree of similarity when performing read-across for a specific purpose.

Item Type: Article
Subjects: Q Science > QH Natural history > QH426 Genetics
R Medicine > RA Public aspects of medicine > RA1190 Toxicology. Poisions
R Medicine > RS Pharmacy and materia medica
Divisions: Pharmacy & Biomolecular Sciences
Publisher: Elsevier
Date Deposited: 25 Feb 2022 09:20
Last Modified: 21 Mar 2022 15:52
DOI or Identification number: 10.1016/j.comtox.2022.100220
URI: https://researchonline.ljmu.ac.uk/id/eprint/16408

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