The scope of an evidence-based toxicology (EBT) is likely to cover prospective and retrospective systematic evaluations of in vitro, in vivo, and human data for risk assessment and management, and to provide high quality evidence relevant to human health and environmental issues. EBT toolboxes should therefore contain data-generating systems, methods for qualifying data, biological and ecological models, data mining methods (able at different levels even to integrate physical and chemical information), and expert judgment, possibly integrated into formal decision-making processes.
In EBT, high importance would be attached to framing the correct question, and both the relevance of questions and criteria of relevance would be important. Criteria for the inclusion and exclusion of studies should be developed, including those for novel methodologies, such as toxicogenomics. Methods to validate assays predicting human effects would also need to pass formal standards, designed using models from other scientific disciplines if not already available. Weighing schemes need to be developed and quality criteria for these weighing schemes established. Their use should address compound class-specific methods, and common scaling to integrate in vivo and in vitro dose-response data. Finally, guidelines would be needed and prominently published on a broad consensus basis.
It may be possible to break down the process of EBT-based decision-making into modules, including information retrieval, information generation (accounting for data gaps, acute vs chronic effects, rare vs frequent effects, and species and strains of animal), data scoring, data integration, data interpretation, uncertainty assessment, decision-making, and decision documentation as suggested by the charge questions for this break-out group. Evidence-based tools could be applied to each of these modules independently, but, in general, the modules should be assessed in an interconnected manner, depending on the endpoints relevant for risk assessment, and multi-layered tests should be applied conditionally to the observations.
GRIESINGER Claudius;
HOFFMANN Sebastian;
KINSNER-OVASKAINEN Agnieszka;
COECKE Sandra;
HARTUNG Thomas;
2010-01-25
SAGE PUBLICATIONS LTD
JRC56787
0960-3271,
https://publications.jrc.ec.europa.eu/repository/handle/JRC56787,
10.1177/0960327109105779,
