Title of article :
Mathematical modelling and quantitative methods
Author/Authors :
Edler، نويسنده , , Diana L. and Poirier، نويسنده , , K. and Dourson، نويسنده , , M. and Kleiner، نويسنده , , J. and Mileson، نويسنده , , B. and Nordmann، نويسنده , , H. and Renwick، نويسنده , , A. Koos Slob، نويسنده , , W. and Walton، نويسنده , , K. and Würtzen، نويسنده , , G.، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2002
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.
Keywords :
Hazard characterisation , risk assessment , Benchmark , Toxicokinetic models , Probabilistic methods , Categorical regression , mathematical modelling
Journal title :
Food and Chemical Toxicology
Journal title :
Food and Chemical Toxicology