Mathematical modelling and quantitative methods

被引:79
作者
Edler, L
Poirier, K
Dourson, M
Kleiner, J
Mileson, B
Nordmann, H
Renwick, A
Slob, W
Walton, K
Würtzen, G
机构
[1] ILSI Europe, B-1200 Brussels, Belgium
[2] German Canc Res Ctr, Deutsch Krebsforschungszentrum, Biostat Abt, D-69009 Heidelberg, Germany
[3] TERA, Toxicol Excellence Risk Assessment, Cincinnati, OH 45223 USA
[4] Technol Sci Grp Inc, Toxicol Ecotoxicol & Risk Assessment Div, Washington, DC 20036 USA
[5] Aiinomoto Switzerland AG, CH-6304 Zug, Switzerland
[6] Univ Southampton, Clin Pharmacol Grp, Southampton SO16 7PX, Hants, England
[7] Natl Inst Publ Hlth & Environm, RIVM, NL-3720 BA Bilthoven, Netherlands
[8] Coca Cola Nord & Balt, DK-2900 Copenhagen, Denmark
关键词
hazard characterisations; risk assessment; mathematical modelling; benchmark; probabilistic methods; toxicokinetic models; categorical regression;
D O I
10.1016/S0278-6915(01)00116-8
中图分类号
TS2 [食品工业];
学科分类号
0832 ;
摘要
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. (C) 2002 ILSI. Published by Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:283 / 326
页数:44
相关论文
共 50 条
  • [1] MODELLING OF FLOTATION PROCESSES BY CLASSICAL MATHEMATICAL METHODS - A REVIEW
    Jovanovic, Ivana
    Miljanovic, Igor
    ARCHIVES OF MINING SCIENCES, 2015, 60 (04) : 905 - 919
  • [2] STABILITY THEORY METHODS IN PROBLEMS OF MATHEMATICAL MODELLING COMPLEX MECHANICAL SYSTEMS
    Kuzmina, L. K.
    11TH WORLD CONGRESS ON COMPUTATIONAL MECHANICS; 5TH EUROPEAN CONFERENCE ON COMPUTATIONAL MECHANICS; 6TH EUROPEAN CONFERENCE ON COMPUTATIONAL FLUID DYNAMICS, VOLS II - IV, 2014, : 4464 - 4474
  • [3] Mathematical and Technical Quantitative Methods for Risk Assessment in Public Crisis Management
    Kisilowski, Marek
    ADVANCES IN SCIENCE AND TECHNOLOGY-RESEARCH JOURNAL, 2023, 17 (02) : 215 - 225
  • [4] Mathematical Modelling
    Vorhoelter, Katrin
    Greefrath, Gilbert
    Ferri, Rita Borromeo
    Leiss, Dominik
    Schukajlow, Stanislaw
    TRADITIONS IN GERMAN-SPEAKING MATHEMATICS EDUCATION RESEARCH, 2019, : 91 - 114
  • [5] Novel mathematical modelling methods of comprehensive mesh stiffness for spur and helical gears
    Tang, Xiaolin
    Zou, Liang
    Yang, Wei
    Huang, Yanjun
    Wang, Hong
    APPLIED MATHEMATICAL MODELLING, 2018, 64 : 524 - 540
  • [6] Geography's underworld: The military-industrial complex, mathematical modelling and the quantitative revolution
    Barnes, Trevor J.
    GEOFORUM, 2008, 39 (01) : 3 - 16
  • [7] The Use of Modern Methods of Mathematical Modelling to Backup Decision Making in Business Management
    Olesovsky, Vaclav
    INNOVATION MANAGEMENT AND SUSTAINABLE ECONOMIC COMPETITIVE ADVANTAGE: FROM REGIONAL DEVELOPMENT TO GLOBAL GROWTH, VOLS I - VI, 2015, 2015, : 1203 - 1210
  • [8] MATHEMATICAL MODELLING OF NANOSTRUCTURES
    Baowan, Duangkamon
    BULLETIN OF THE AUSTRALIAN MATHEMATICAL SOCIETY, 2008, 78 (02) : 351 - 352
  • [9] Mathematical Modelling of Angiogenesis
    Mark A.J. Chaplain
    Journal of Neuro-Oncology, 2000, 50 : 37 - 51
  • [10] Mathematical modelling of angiogenesis
    Chaplain, MAJ
    JOURNAL OF NEURO-ONCOLOGY, 2000, 50 (1-2) : 37 - 51