Literature DB >> 11893400

Mathematical modelling and quantitative methods.

L Edler1, K Poirier, M Dourson, J Kleiner, B Mileson, H Nordmann, A Renwick, W Slob, K Walton, G Würtzen.   

Abstract

The present review reports on the mathematical methods and statistical techniques presently available for hazard characterisation. The state of the art of mathematical modelling and quantitative methods used currently for regulatory decision-making in Europe and additional potential methods for risk assessment of chemicals in food and diet are described. Existing practices of JECFA, FDA, EPA, etc., are examined for their similarities and differences. A framework is established for the development of new and improved quantitative methodologies. Areas for refinement, improvement and increase of efficiency of each method are identified in a gap analysis. Based on this critical evaluation, needs for future research are defined. It is concluded from our work that mathematical modelling of the dose-response relationship would improve the risk assessment process. An adequate characterisation of the dose-response relationship by mathematical modelling clearly requires the use of a sufficient number of dose groups to achieve a range of different response levels. This need not necessarily lead to an increase in the total number of animals in the study if an appropriate design is used. Chemical-specific data relating to the mode or mechanism of action and/or the toxicokinetics of the chemical should be used for dose-response characterisation whenever possible. It is concluded that a single method of hazard characterisation would not be suitable for all kinds of risk assessments, and that a range of different approaches is necessary so that the method used is the most appropriate for the data available and for the risk characterisation issue. Future refinements to dose-response characterisation should incorporate more clearly the extent of uncertainty and variability in the resulting output.

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Year:  2002        PMID: 11893400     DOI: 10.1016/s0278-6915(01)00116-8

Source DB:  PubMed          Journal:  Food Chem Toxicol        ISSN: 0278-6915            Impact factor:   6.023


  4 in total

1.  Two-Stage Experimental Design for Dose-Response Modeling in Toxicology Studies.

Authors:  Kai Wang; Feng Yang; Dale W Porter; Nianqiang Wu
Journal:  ACS Sustain Chem Eng       Date:  2013-06-27       Impact factor: 8.198

2.  Hierarchical Rank Aggregation with Applications to Nanotoxicology.

Authors:  Trina Patel; Donatello Telesca; Robert Rallo; Saji George; Tian Xia; André E Nel
Journal:  J Agric Biol Environ Stat       Date:  2013-06-01       Impact factor: 1.524

3.  Vitamins and minerals: issues associated with too low and too high population intakes.

Authors:  Janneke Verkaik-Kloosterman; Mary T McCann; Jeljer Hoekstra; Hans Verhagen
Journal:  Food Nutr Res       Date:  2012-04-02       Impact factor: 3.894

4.  A New Stochastic Kriging Method for Modeling Multi-Source Exposure-Response Data in Toxicology Studies.

Authors:  Kai Wang; Xi Chen; Feng Yang; Dale W Porter; Nianqiang Wu
Journal:  ACS Sustain Chem Eng       Date:  2014-05-20       Impact factor: 8.198

  4 in total

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