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Population Effects and Variability

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Computational Toxicology

Part of the book series: Methods in Molecular Biology ((MIMB,volume 929))

Abstract

Chemical risk assessment for human health requires a multidisciplinary approach through four steps: hazard identification and characterization, exposure assessment, and risk characterization. Hazard identification and characterization aim to identify the metabolism and elimination of the chemical (toxicokinetics) and the toxicological dose–response (toxicodynamics) and to derive a health-based guidance value for safe levels of exposure. Exposure assessment estimates human exposure as the product of the amount of the chemical in the matrix consumed and the consumption itself. Finally, risk characterization evaluates the risk of the exposure to human health by comparing the latter to with the health-based guidance value. Recently, many research efforts in computational toxicology have been put together to characterize population variability and uncertainty in each of the steps of risk assessment to move towards more quantitative and transparent risk assessment. This chapter focuses specifically on modeling population variability and effects for each step of risk assessment in order to provide an overview of the statistical and computational tools available to toxicologists and risk assessors. Three examples are given to illustrate the applicability of those tools: derivation of pathway-related uncertainty factors based on population variability, exposure to dioxins, dose–response modeling of cadmium.

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Acknowledgments

The views reflected in this review are the authors’ only and do not reflect the views of the European Food Safety Authority, the Technological university of Compiegne, the French Agency for Food, Environment, and Occupational Health Safety, the French National Institute of Agronomical Research (INRA), or the World Health organization.

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Authors and Affiliations

  1. Emerging Risks Unit, European Food Safety Authority, Parma, Italy

    Jean Lou Dorne

  2. LA-SER Europe Ltd, London, UK

    Billy Amzal

  3. Royallieu Research Center, Technological University of Compiegne, Compiegne, France

    Frédéric Bois

  4. INERIS, DRC/VIVA/METO, Verneuil en Halatte, France

    Frédéric Bois

  5. French Agency for Food, Environment and Occupational Health Safety (ANSES), Maisons-Alfort, France

    Amélie Crépet

  6. National Institute for Agronomic Research (INRA), Paris, France

    Jessica Tressou

  7. Department of Food Safety and Zoonoses, World Health Organization, Geneva, Switzerland

    Philippe Verger

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  1. Jean Lou Dorne
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  2. Billy Amzal
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  3. Frédéric Bois
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  4. Amélie Crépet
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  5. Jessica Tressou
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  6. Philippe Verger
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Correspondence to Jean Lou Dorne .

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Editors and Affiliations

  1. School of Biomedical Engineering, Chemical & Biological Engineering, Colorado State University, Campus Delivery 1370, Fort Collins, 80523-1370, Colorado, USA

    Brad Reisfeld

  2. , Chemical & Biological Engineering, Colorado State University, Campus Delivery 1370, Fort Collins, 80523-1370, Colorado, USA

    Arthur N. Mayeno

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Dorne, J.L., Amzal, B., Bois, F., Crépet, A., Tressou, J., Verger, P. (2012). Population Effects and Variability. In: Reisfeld, B., Mayeno, A. (eds) Computational Toxicology. Methods in Molecular Biology, vol 929. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-62703-050-2_20

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  • DOI: https://doi.org/10.1007/978-1-62703-050-2_20

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