Metabolomics as read-across tool: An example with 3-aminopropanol and 2-aminoethanol.

Read-across and grouping is one of the most commonly used alternative approaches for data gap filling in registrations submitted under the REACH Regulation as defined by the European Chemicals Agency (ECHA) in their 'Read-Across Assessment Framework' (RAAF, 2017). At the same time, the application of read-across is rejected by ECHA frequently due to various reasons. As a major reason hereof, applicants fail to reduce the level of 'remaining uncertainty' intrinsical to every read-across approach compared to testing a substance experimentally. Recently, the use of metabolomics to support read-across cases with biological information has been reported in a case study with phenoxy herbicides (Ravenzwaay et al., 2016). In the present case-study a 'weight-of-evidence' read-across approach from 2-aminoethanol (MEA = 'source') to 3-aminopropanol (3AP = 'target') with metabolomics as 'supporting evidence' reducing the remaining uncertainties is reported. We demonstrate the high structural similarity of the two analogous substances based on the available data and we report how metabolome data add confidence concerning mechanistic similarity in this read-across approach. Finally, the herein described read-across case supported by metabolomics is used to cover the data gaps in repeated dose and reproductive toxicity endpoint of 3AP via weight of evidence for the REACH-registration.
(Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)