Utility of in vivo metabolomics to support read-across for UVCB substances under REACH.

Structure-based grouping of chemicals for targeted testing and read-across is an efficient way to reduce resources and animal usage. For substances of unknown or variable composition, complex reaction products, or biological materials (UVCBs), structure-based grouping is virtually impossible. Biology-based approaches such as metabolomics could provide a solution. Here, 15 steam-cracked distillates, registered in the EU through the Lower Olefins Aromatics Reach Consortium (LOA), as well as six of the major substance constituents, were tested in a 14-day rat oral gavage study, in line with the fundamental elements of the OECD 407 guideline, in combination with plasma metabolomics. Beyond signs of clinical toxicity, reduced body weight (gain), and food consumption, pathological investigations demonstrated the liver, thyroid, kidneys (males only), and hematological system to be the target organs. These targets were confirmed by metabolome pattern recognition, with no additional targets being identified. While classical toxicological parameters did not allow for a clear distinction between the substances, univariate and multivariate statistical analysis of the respective metabolomes allowed for the identification of several subclusters of biologically most similar substances. These groups were partly associated with the dominant (> 50%) constituents of these UVCBs, i.e., indene and dicyclopentadiene. Despite minor differences in clustering results based on the two statistical analyses, a proposal can be made for the grouping of these UVCBs. Both analyses correctly clustered the chemically most similar compounds, increasing the confidence that this biological approach may provide a solution for the grouping of UVCBs.

Metabolomics as read-across tool: A case study with phenoxy herbicides.

New technologies, such as metabolomics, can address chemical grouping and read across from a biological perspective. In a virtual case study, we selected MCPP as target substance and MCPA and 2,4-DP as source substances with the goal to waive a 90-day study with MCPP. In order to develop a convincing case to show how biological data can substantiate read across, we used metabolomics on blood samples from the 28-day studies to show the qualitative and quantitative similarity of the substances. The 28-day metabolome evaluation of source substances and the target substance indicate liver and kidneys as target organs. 2,4-DP was identified as the best source substance. Using the information of the 90-day 2,4-DP study, we predicted MCPP's toxicity profile at 2500 ppm: reduced food consumption and body weight gain, liver and kidney weight increases with clinical-pathology changes and a moderate red blood cell parameter reduction. NOEL prediction for MCPP was below that of 2,4-DP (<500 ppm), and similar to that of MCPA (≥150 ppm). Qualitatively, these predictions are comparable to the results of the real MCPP 90-day study in rats (reduced food consumption and body weight gain, weight increases and clinical-pathology changes in liver and kidneys, reduced red blood cells values). Quantitatively, the predicted NOAEL (150 ppm) is similar to the actual study (NOEL = 75 ppm, NOAEL ≤ 500 ppm). Thus, the 90-day rat toxicity study of MCPP could have been waived and substituted by the 90-day results of 2,4-DP by using metabolome data of 28 day studies.