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New approach methods supporting read-across: Two neurotoxicity AOP-based IATA case studies
Author(s) -
Wanda van der Stel,
Giada Carta,
Julie Eakins,
Johannes Delp,
Ilinca Suciu,
Anna Forsby,
Andrea Cediel-Ulloa,
Kristina Attoff,
Florentina Troger,
Hennicke Kamp,
Iain Gardner,
Barbara Zdrazil,
Martijn J. Moné,
Gerhard Ecker,
Manuel Pastor,
José Carlos Gómez-Tamayo,
Andrew White,
Erik H.J. Danen,
Marcel Leist,
Paul Walker,
Paul Jennings,
Susanne Hougaard Bennekou,
Bob van de Water
Publication year - 2021
Publication title -
altex/alternatives to animal experimentation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.975
H-Index - 51
eISSN - 1868-8551
pISSN - 1868-596X
DOI - 10.14573/altex.2103051
Subject(s) - neurotoxicity , computer science , in silico , mitochondrial respiratory chain , toxicodynamics , computational biology , neuroscience , pharmacology , chemistry , biology , mitochondrion , toxicity , biochemistry , toxicokinetics , organic chemistry , pharmacokinetics , gene
Read-across approaches are considered key in moving away from in vivo animal testing towards addressing data-gaps using new approach methods (NAMs). Ample successful examples are still required to substantiate this strategy. Here we present and discuss the learnings from two OECD IATA endorsed read-across case studies. They involve two classes of pesticides – rotenoids and strobilurins – each having a defined mode-of-action that is assessed for its neurological hazard by means of an AOP-based testing strategy coupled to toxicokinetic simulations of human tissue concentrations. The endpoint in question is potential mitochondrial respiratory chain mediated neurotoxicity, specifically through inhibition of complex I or III. An AOP linking inhibition of mitochondrial respiratory chain complex I to the degeneration of dopaminergic neurons formed the basis for both cases but was deployed in two different regulatory contexts. The two cases also exemplify several different read-across concepts: analogue versus category approach, consolidated versus putative AOP, positive versus negative prediction (i.e., neurotoxicity versus low potential for neurotoxicity), and structural versus biological similarity. We applied a range of NAMs to explore the toxicodynamic properties of the compounds, e.g., in silico docking as well as in vitro assays and readouts – including transcriptomics – in various cell systems, all anchored to the relevant AOPs. Interestingly, although some of the data addressing certain elements of the read-across were associated with high uncertainty, their impact on the overall read-across conclusion remained limited. Coupled to the elaborate regulatory review that the two cases underwent, we propose some generic learnings of AOP-based testing strategies supporting read-across.

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