Chemical Safety Assessment Using Read-Across: Assessing the Use of Novel Testing Methods to Strengthen the Evidence Base for Decision Making

Abstract

Background: Safety assessment for repeated dose toxicity is one of the largest challenges in the process to replace animal testing. This is also one of the proof of concept ambitions of SEURAT-1, the largest ever European Union research initiative on alternative testing, co-funded by the European Commission and Cosmetics Europe. This review is based on the discussion and outcome of a workshop organized on initiative of the SEURAT-1 consortium joined by a group of international experts with complementary knowledge to further develop traditional read-across and include new approach data.

Objectives: The aim of the suggested strategy for chemical read-across is to show how a traditional read-across based on structural similarities between source and target substance can be strengthened with additional evidence from new approach data--for example, information from in vitro molecular screening, "-omics" assays and computational models--to reach regulatory acceptance.

Methods: We identified four read-across scenarios that cover typical human health assessment situations. For each such decision context, we suggested several chemical groups as examples to prove when read-across between group members is possible, considering both chemical and biological similarities.

Conclusions: We agreed to carry out the complete read-across exercise for at least one chemical category per read-across scenario in the context of SEURAT-1, and the results of this exercise will be completed and presented by the end of the research initiative in December 2015.

Figure 1

Chemicals suggested for Category I.I: Perfluoroalkyl acids (PFAAs), identified by names, CAS (Chemical Abstracts Service) numbers, and molecular structures. The substance indicated “source” is the most data-rich substance in the category with known MoA.

Figure 2

Chemicals suggested for Category II.I: β-unsaturated alcohols (allylic alcohols), identified by names, CAS numbers, and molecular structures. The substance indicated “source” is the most data-rich substance in the category with known MoA.

Figure 3

Chemicals suggested for Category III.II: saturated alcohols, identified by names, CAS numbers, and molecular structures. The two substances indicated “source” are the most data-rich substances in the category with known MoA.

Figure 4

Chemicals suggested for Category IV.I: short-chain carboxylic acids (SCCAs), identified by names, CAS numbers, and molecular structures. The substance indicated “source” is the most data-rich substance in the category with known MoA.