Pathway-based predictive approaches for non-animal assessment of acute inhalation toxicity.
Pathway-based predictive approaches for non-animal assessment of acute inhalation toxicity.
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DOI:
10.1016/j.tiv.2018.06.009
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发表时间:
2018-10
期刊:
影响因子:
--
通讯作者:
Jarabek AM
中科院分区:
文献类型:
--
作者:
Clippinger AJ;Allen D;Behrsing H;BéruBé KA;Bolger MB;Casey W;DeLorme M;Gaça M;Gehen SC;Glover K;Hayden P;Hinderliter P;Hotchkiss JA;Iskandar A;Keyser B;Luettich K;Ma-Hock L;Maione AG;Makena P;Melbourne J;Milchak L;Ng SP;Paini A;Page K;Patlewicz G;Prieto P;Raabe H;Reinke EN;Roper C;Rose J;Sharma M;Spoo W;Thorne PS;Wilson DM;Jarabek AM
New approaches are needed to assess the effects of inhaled substances on human health. These approaches will be based on mechanisms of toxicity, an understanding of dosimetry, and the use of in silico modeling and in vitro test methods. Before these approaches can be implemented, there is a need to develop adverse outcome pathways (AOPs), identify and address gaps in our understanding of relevant parameters for model input and mechanisms, and optimize non-animal approaches that can be used to investigate key events in these AOPs. This paper describes the AOPs and the toolbox of in vitro and in silico models that can be used to assess the key events leading to toxicity following inhalation exposure. Because the optimal testing strategy will vary depending on the substance of interest, here we present a decision tree approach to identify an appropriate non-animal integrated testing strategy that incorporates consideration of a substance’s physicochemical properties, relevant mechanisms of toxicity, and available in silico models and in vitro test methods. This decision tree can facilitate standardization of the testing approaches. Case study examples are presented to provide a basis for proof-of-concept testing to illustrate the utility of non-animal approaches to predict the hazard to humans of inhaled substances.
影响因子:
4.1
作者:
Allen, Timothy E. H.;Goodman, Jonathan M.;Russell, Paul J.
通讯作者:
Russell, Paul J.
影响因子:
4.1
作者:
Ankley, Gerald T.;Bennett, Richard S.;Villeneuve, Daniel L.
通讯作者:
Villeneuve, Daniel L.