Establishing the level of safety concern for chemicals in food without the need for toxicity testing

Schilter, Benoı̂t; Benigni, Romualdo; Boobis, Alan R.; Chiodini, Alessandro; Cockburn, Andrew; Cronin, Mark T.D.; Piparo, Elena Lo; Modi, Sandeep; Thiel, Anette; Worth, Andrew

doi:10.1016/j.yrtph.2013.08.018

Cited by 51 publications

(34 citation statements)

References 68 publications

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“…These approaches have more precision than the TTC because they make comparisons within a smaller group of chemicals and could be accurate to within 3-5 orders of magnitude (OECD 2007, Schilter et al 2014. Depending on how this estimate contributes to the risk area on the matrix, more toxicity data may be required.…”

Section: Estimating Toxicitymentioning

confidence: 99%

Risk assessment in the 21st century: Roadmap and matrix

Embry¹,

Bachman²,

Bell³

et al. 2014

Critical Reviews in Toxicology

111

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The RISK21 integrated evaluation strategy is a problem formulation-based exposure-driven risk assessment roadmap that takes advantage of existing information to graphically represent the intersection of exposure and toxicity data on a highly visual matrix. This paper describes in detail the process for using the roadmap and matrix. The purpose of this methodology is to optimize the use of prior information and testing resources (animals, time, facilities, and personnel) to efficiently and transparently reach a risk and/or safety determination. Based on the particular problem, exposure and toxicity data should have sufficient precision to make such a decision. Estimates of exposure and toxicity, bounded by variability and/or uncertainty, are plotted on the X-and Y-axes of the RISK21 matrix, respectively. The resulting intersection is a highly visual representation of estimated risk. Decisions can then be made to increase precision in the exposure or toxicity estimates or declare that the available information is sufficient. RISK21 represents a step forward in the goal to introduce new methodologies into 21st century risk assessment. Indeed, because of its transparent and visual process, RISK21 has the potential to widen the scope of risk communication beyond those with technical expertise.

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Section: Estimating Toxicitymentioning

confidence: 99%

Risk assessment in the 21st century: Roadmap and matrix

Embry¹,

Bachman²,

Bell³

et al. 2014

Critical Reviews in Toxicology

111

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“…In the process of chemical risk assessment, the steps of hazard identification and hazard characterization refer to the qualitative description and dose-response analysis of toxic effects (Schilter et al, 2013). Traditionally, both have relied on in vivo animal studies.…”

Section: Introductionmentioning

confidence: 99%

“…In this context, the technique of chemical grouping and read-across has been promoted as a most promising and pragmatic alternative approach. It consists of identifying analogs of the chemical under investigation (grouping) and extrapolating its toxic properties using the available toxicological data to the analogs (read-across) (Patlewicz et al, 2014;Schilter et al, 2013;Wu et al, 2010). Finding adequate analogs is not straightforward and has to be based on a number of structural and biological features (OECD, 2011;Patlewicz et al, 2014;Schilter et al, 2013;Wu et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

Hazard assessment through hybrid in vitro / in silico approach: The case of zearalenone

Ehrlich

2015

ALTEX

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SummaryWithin the framework of reduction, refinement and replacement of animal experiments, new approaches for identification and characterization of chemical hazards have been developed. Grouping and read-across has been promoted as a most promising alternative approach. It uses existing toxicological information on a group of chemicals to make predictions on the toxicity of uncharacterized ones. In the present work, the feasibility of applying in vitro and in silico techniques to group chemicals for read-across was studied using the food mycotoxin zearalenone (ZEN) and metabolites as a case study. ZEN and its reduced metabolites are known to act through activation of the estrogen receptor α (ERα). The ranking of their estrogenic potencies appeared highly conserved across test systems including binding, in vitro and in vivo assays. This data suggests that activation of ERα may play a role in the molecular initiating event (MIE) and be predictive of adverse effects, and it provides the rationale to model receptor-binding for hazard identification. The investigation of receptor-ligand interactions through docking simulation proved to accurately rank estrogenic potencies of ZEN and reduced metabolites, showing the suitability of the model to address estrogenic potency for this group of compounds. Therefore, the model was further applied to biologically uncharacterized, commercially unavailable, oxidized ZEN metabolites (6α-, 6β-, 8α-, 8β-, 13-and 15-OH-ZEN). Except for 15-OH-ZEN, the data indicate that in general, the oxidized metabolites would be considered of lower estrogenic concern than ZEN and reduced metabolites.

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“…In silico tools are essentially computer models, able to make predictions for a non-evaluated compound based on knowledge extracted from a collection of structurally related substances with experimental toxicity data. Progressively acknowledged by regulatory bodies, in silico tools are gaining importance in toxicology not only as a first tier screening tool, but also for complementing in vivo and in vitro test results (for example, Buist et al 2013;Nendza et al 2013;Schilter et al 2014;Scholz et al 2013). Their widespread use, however, remains limited due to (1) the non-flexibility of the current regulatory framework, strictly describing the required experimental tests, (2) the oversupply of computer models while often uncertainty exists as to which model (combination) is most suitable to assess a given (type of) substance for a particular endpoint, and (3) the rather poor predictive capacity for toxicological endpoints other than Ames mutagenicity (Barber and Myatt 2016).…”

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confidence: 99%