Abstracts / Toxicology Letters 229S (2014) S4–S21 S7

plasm to the nucleus where it forms a heterodimer with the retinoicacid receptor. CAR-inducible genes play key roles in the metabolismof xenobiotics and endogenous compounds, regulation of trans-porters, and in energy metabolism by inhibiting gluconeogenesisand lipogenesis. CAR differs from other NRs in that it does notrequire a ligand in order to affect transcription. However, activa-tion of CAR can be affected by direct ligand binding or throughan indirect mechanism. PB, the classic non-genotoxic promoter ofrodent liver tumorigenesis, is an indirect activator of CAR. PB doesnot act as a promoter in CAR KO mice. This presentation will focuson the mechanism underlying activation of CAR, and major differ-ences between rodent CAR and human CAR that might account forthe ability of PB to act as a rodent, but not a human, carcinogen.Furthermore, the steps that can be taken to see if a non-genotoxicrodent liver tumorigen exhibits a PB-like, CAR-dependent, mode ofaction, indicating that it does not present a carcinogenic hazard tohumans, will be illustrated.

http://dx.doi.org/10.1016/j.toxlet.2014.06.049

Symposia 3: New approaches to characterising uncertainty inhazard and risk assessment

PS3.1-O1The future of the QSAR Toolbox: Moving to lessuncertainty in predictive toxicology

Romualdo Benigni ∗, Joop de Knecht

Organization for Economic Co-operation and Development (OECD),Paris, France

Classification of untested chemicals, which make up more than95% of all chemicals in the market, is not possible without someform of prediction based on a simplified alternative biologicalmodel or a simplified chemical structure–activity relationship. TheOECD QSAR Toolbox is a freely available software that implementsstructure-based approaches to the prediction of toxicological data:it exploits the possibility of combining chemical and biologicalinformation to assess the toxicity of a query chemical startingfrom the toxicity and structural data of analogue chemicals. Thereduction of uncertainty is a crucial issue. Uncertainty is part ofexperimental measures, and reverberates from data to modelingapproaches. In order to minimize the uncertainty proper to mod-eling and to provide transparent mechanistic justification to thepredictions, the OECD has developed the concept of Adverse Out-come Pathways (AOP). AOPs delineate the documented, plausible,and testable processes by which a chemical induces molecular per-turbations and the associated biological responses that describehow the molecular perturbations cause effects at the subcellular,cellular, tissue, organ, whole animal, and population levels of obser-vation. A priority of OECD for the near future is to implement AOPsinto the Toolbox, and provide the investigators with additionaltools to predict complex toxicological endpoints.

http://dx.doi.org/10.1016/j.toxlet.2014.06.051

PS3.1-O2The WHO guidance on evaluating uncertaintiesin hazard characterization: The basic approach

Wout Slob

RIVM, Bilthoven, The Netherlands

WHO recently published a guidance document on quantitativelyevaluating uncertainties in hazard characterization. The approachdiffers in two ways from the more traditional (“deterministic”)approaches of hazard characterization. First, rather than singlevalues for the Point of Departure (POD) and for the adjustmentfactors it uses uncertainty distributions, reflecting the assumed orestimated uncertainties in each of those aspects. Second, it quan-titatively defines the protection goals in terms of incidence (I) anddegree (M) of the critical effect in the human population. Whenthe hazard characterization aims to develop a health-based guid-ance value, traditional approaches result in a single value (e.g., RfD,ADI) for which the associated values for I and M are not quan-tified, while the uncertainty in that value remains unknown. Inthe probabilistic approach described by WHO the values of I andM are made explicit, while the uncertainty in the target humandose at these values of I and M is quantified. This additionalinformation may enable risk managers in making better-informeddecisions. Further, when they consider the overall uncertaintylarger than deemed desirable in view of the problem formulation,they may decide to ask for a more refined (higher tier) assess-ment. Some examples will be given how historical data may beused to inform generic uncertainty distribution for the typicaladjustment factors. Finally, the problem of uncertainties whichare hard to quantify due to a lack of relevant data is brieflydiscussed.

http://dx.doi.org/10.1016/j.toxlet.2014.06.052

PS3.1-O3Applying the WHO guidance on evaluatinguncertainties in hazard characterization: A casestudy on deoxynivalenol (DON)

Matthias Herzler

Federal Institute for Risk Assessment (BfR), Berlin, Germany

Recently, the WHO IPCS program has published a GuidanceDocument on ‘Evaluating and Expressing Uncertainty in HazardAssessment’. The basic idea behind this concept is to expressthe outcome of hazard characterization for human health, e.g. areference dose (RfD), as an interval or distribution rather thanas a point estimate. In this way, potential uncertainties may becommunicated more clearly, while at the same time the riskmanagement protection goals of the assessment, in particularthe degree of effect which is unwanted, and the percentile ofthe population to be protected, are made explicit in quantitativeterms.

In this presentation, the audience is walked step-by-stepthrough the practical application of the approach. At the exampleof the mycotoxin deoxynivalenol (DON), the concept of ‘approxi-mate probabilistic uncertainty analysis’ will be demonstrated fora number of hazard characterization aspects and with respectto different toxicological endpoints. It is shown that a first tieranalysis based on NOAELs/LOAELs will not return satisfactoryresults. Thus, a second tier analysis based on the benchmark dose(BMD) approach is performed. Finally, potential implications of theresults for risk management and options for further refinement arediscussed.

The presentation will also include a detailed overview of the var-ious features of the APROBA software, an easy-to-use spreadsheettool which is provided alongside the IPCS guidance.

http://dx.doi.org/10.1016/j.toxlet.2014.06.053