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9. Evaluation of EFSA training courses on principles in chemical and biological risk assessment

Author

Escher, Sylvia, Bruer, Gustav, Creutzenberg, Otto, Schlemminger, Karin, Schulz, Florian, Ziemann, Christina, Rorije, Emiel, Klaveren, Jacob van, Posthuma, Leo, Bokkers, Bas, Slob, Wout, Hanberg, Annika, Beronius, Anna, Baumann, Lisa, Zilliacus, Johanna, Bitsch, Annette, and Publica

Abstract

This report evaluates the training courses delivered under the contract OC/EFSA/SCER/2017/01 ‐ Lot 1. Within the period of January 2018 to February 2022 a total of 21 training courses were provided, eight on‐site training courses in Parma at EFSA, six virtual training courses during the Covid‐19 pandemic and seven eLearning courses comprising various numbers of modules. The courses covered different aspects of chemical and biological risk assessment and related tools, namely i) harmonisation of risk assessment methodologies for human health and ecological risk assessment of combined exposure to multiple chemicals (mixture assessment), ii) risk assessment of the application of nanoscience and nanotechnologies in agro/food/feed (nanotoxicity); iii) science‐based criteria for identifying endocrine disruptors in the context of EU legislation on pesticides and biocides (endocrine disruption); iv) principles on genotoxicity on scientific assessment (genotoxicity) and v) computational toxicology approaches and tools (in silico). All tutors were experts in their field and had previously performed training courses on these topics. The target participants of the training courses were members of EFSA’s Scientific Committee/Panels and their working groups as well as employees from national and international regulatory agencies associated with risk assessment of feed and food compounds. Members of the EFSA Networks as well as EFSA scientific staff also participated in the training courses. Courses were evaluated based on the feedback of participants and continuously improved also by integrating updated or new EFSA guidance documents.

Published
2022
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24. Endocrine effects of tetrabromobisphenol-A (TBBPA) in Wistar rats as tested in a one-generation reproduction study and a subacute toxicity study

Author

Van der Ven, Leo T.M., Van de Kuil, Ton, Verhoef, Aart, Verwer, Cynthia M., Lilienthal, Hellmuth, Leonards, Pim E.G., Schauer, Ute M.D., Cantón, Rocío F., Litens, Sabina, De Jong, Frank H., Visser, Theo J., Dekant, Wolfgang, Stern, Natalia, Håkansson, Helen, Slob, Wout, Van den Berg, Martin, Vos, Josephus G., and Piersma, Aldert H.

Published
2008
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30. Dose addition in chemical mixtures inducing craniofacial malformations in

Author

Zoupa, Maria, Zwart, Edwin P., Gremmer, Eric R, Nugraha, Ananditya, Compeer, Sharon, Slob, Wout, and van der Ven, Leo TM

Abstract

A challenge in cumulative risk assessment is to model hazard of mixtures. EFSA proposed to only combine chemicals linked to a defined endpoint, in so-called cumulative assessment groups, and use the dose-addition model as a default to predict combined effects. We investigated the effect of binary mixtures of compounds known to cause craniofacial malformations, by assessing the effect in the head skeleton (M-PQ angle) in 120hpf zebrafish embryos. We combined chemicals with similar mode of action (MOA), i.e. the triazoles cyproconazole, triadimefon and flusilazole; next, reference compounds cyproconazole or triadimefon were combined with dissimilar acting compounds, TCDD, thiram, VPA, prochloraz, fenpropimorph, PFOS, or endosulfan. These mixtures were designed as (near) equipotent combinations of the contributing compounds, in a range of cumulative concentrations. Dose-addition was assessed by evaluation of the overlap of responses of each of the 14 tested binary mixtures with those of the single compounds. All 10 test compounds induced an increase of the MPQ angle, with varying potency and specificity. Mixture responses as predicted by dose-addition did not deviate from the observed responses, supporting dose-addition as a valid assumption for mixture risk assessment. Importantly, dose-addition was found irrespective of MOA of contributing chemicals.

Published
2020

41. Biostatistical Methodology in Carcinogenicity Studies

Author

Fairweather, William R., Bhattacharyya, Amit, Ceuppens, Peter P., Heimann, Guenter, Hothorn, Ludwig A., Kodell, Ralph L., Lin, Karl K., Mager, Harry, Middleton, Brian J., Slob, Wout, Soper, Keith A., Stallard, Nigel, Ventre, John, and Wright, Jane

Published
1998
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48. A unified probabilistic framework for dose-response assessment of human health effects

Author

Chiu, Weihsueh A. and Slob, Wout

Subjects
Risk management -- Methods, Chemicals -- Usage -- Safety and security measures, Risk management, Environmental issues, Health
Abstract

BACKGROUND: When chemical health hazards have been identified, probabilistic dose-response assessment ('hazard characterization') quantifies uncertainty and/or variability in toxicity as a function of human exposure. Existing probabilistic approaches differ for different types of endpoints or modes-of-action, lacking a unifying framework. OBJECTIVES: We developed a unified framework for probabilistic dose-response assessment. METHODS: We established a framework based on four principles: a) individual and population dose responses are distinct; b) dose-response relationships for all (including quantal) endpoints can be recast as relating to an underlying continuous measure of response at the individual level; c) for effects relevant to humans, 'effect metrics' can be specified to define 'toxicologically equivalent' sizes for this underlying individual response; and d) dose-response assessment requires making adjustments and accounting for uncertainty and variability. We then derived a step-by-step probabilistic approach for dose-response assessment of animal toxicology data similar to how nonprobabilistic reference doses are derived, illustrating the approach with example non-cancer and cancer datasets. RESULTS: Probabilistically derived exposure limits are based on estimating a 'target human dose' ([HD.sub.M.sup.I]), which requires risk management-informed choices for the magnitude (M) of individual effect being protected against, the remaining incidence (I) of individuals with effects ≥ M in the population, and the percent confidence. In the example datasets, probabilistically derived 90% confidence intervals for [HD.sub.M.sup.I] values span a 40- to 60-fold range, where I = 1% of the population experiences ≥ M = 1%-10% effect sizes. CONCLUSIONS: Although some implementation challenges remain, this unified probabilistic framework can provide substantially more complete and transparent characterization of chemical hazards and support better-informed risk management decisions. Environ Health Perspect 123:1241-1254; http://dx.doi.org/10.1289/ehp.1409385, Introduction The process of identifying human health hazards of chemicals has evolved substantially over time with advances in weight of evidence determination, mode of action (MOA), and systematic review (e.g., [...]

Published
2015
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50. APROBA-Plus: A probabilistic tool to evaluate and express uncertainty in hazard characterization and exposure assessment of substances

Author

Bokkers, Bas G H, Mengelers, Marcel J, Bakker, Martine I, Chiu, Weihsueh A, and Slob, Wout

Subjects
Models, Statistical, Animals, Humans, Food Contamination, Risk Assessment, Hazardous Substances
Abstract

To facilitate the application of probabilistic risk assessment, the WHO released the APROBA tool. This tool applies lognormal uncertainty distributions to the different aspects of the hazard characterization, resulting in a probabilistic health-based guidance value. The current paper describes an extension, APROBA-Plus, which combines the output from the probabilistic hazard characterization with the probabilistic exposure to rapidly characterize risk and its uncertainty. The uncertainty in exposure is graphically compared with the uncertainty in the target human dose, i.e. the dose that complies with the specified protection goals. APROBA-Plus is applied to several case studies, resulting in distinct outcomes and illustrating that APROBA-Plus could serve as a standard extension of routine risk assessments. By visualizing the uncertainties, APROBA-Plus provides a more transparent and informative outcome than the more usual deterministic approaches, so that risk managers can make better informed decisions. For example, APROBA-Plus can help in deciding whether risk-reducing measures are warranted or that a refined risk assessment would first be needed. If the latter, the tool can be used to prioritize possible refinements. APROBA-Plus may also be used to rank substances into different risk categories, based on potential health risks without being compromised by different levels of conservatism that may be associated with point estimates of risk.

Published
2018

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