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Journal Articles Computational Toxicology Year : 2017

Ab initio chemical safety assessment : A workflow based on exposure considerations and non-animal methods

Abstract

We describe and illustrate a workflow for chemical safety assessment that completely avoids animal testing. The workflow, which was developed within the SEURAT-1 initiative, is designed to be applicable to cosmetic ingredients as well as to other types of chemicals, e.g. active ingredients in plant protection products, biocides or pharmaceuticals. The aim of this work was to develop a workflow to assess chemical safety without relying on any animal testing, but instead constructing a hypothesis based on existing data, in silico modelling, biokinetic considerations and then by targeted non-animal testing. For illustrative purposes, we consider a hypothetical new ingredient x as a new component in a body lotion formulation. The workflow is divided into tiers in which points of departure are established through in vitro testing and in silico prediction, as the basis for estimating a safe external dose in a repeated use scenario. The workflow includes a series of possible exit (decision) points, with increasing levels of confidence, based on the sequential application of the Threshold of Toxicological (TTC) approach, read-across, followed by an “ab initio” assessment, in which chemical safety is determined entirely by new in vitro testing and in vitro to in vivo extrapolation by means of mathematical modelling. We believe that this workflow could be applied as a tool to inform targeted and toxicologically relevant in vitro testing, where necessary, and to gain confidence in safety decision making without the need for animal testing.

Domains

Toxicology
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Dates and versions

ineris-01863939 , version 1 (29-08-2018)

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Elisabet Berggren, Andrew White, Gladys Ouedraogo, Alicia Paini, Andrea-Nicole Richarz, et al.. Ab initio chemical safety assessment : A workflow based on exposure considerations and non-animal methods. Computational Toxicology, 2017, 4, pp.31-44. ⟨10.1016/j.comtox.2017.10.001⟩. ⟨ineris-01863939⟩

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