In this paper we argue for a naturalistic solution to some of the methodological controversies in regulatory science, on the basis of two case studies: toxicology and health claim regulation. We analyze the debates related to the scientific evidence that is considered necessary for regulatory decision making in each of those two fields, with a particular attention to the interactions between scientific and regulatory aspects. This analysis allows us to identify two general stances in the debate: a) one that argues (...) for more permissive standards of evidence and for methodological pluralism, and b) an opposing one that not only defends strict evidence requirements but also stipulates the use of one particular scientific methodologies for data generation. We argue that the real-world outcomes produced by alternative regulatory options are a vital piece of information that allows for the empirical assessment of these two stances. In particular, this information on outcomes makes it possible to analyze which standards of evidence and scientific methods generate the most useful knowledge as input for regulatory decision making. Our conclusion is that instead of an a priori selection of methodologies and standards, such decisions ought to be based on empirical evidence related to real-world outcomes. (shrink)

Mechanistic information is used in the field of risk assessment in order to clarify two controversial methodological issues, the selection of inference guides and the definition of standards of evidence. In this paper we present an analysis of the concept of mechanistic information in risk assessment by recurring to previous philosophical analyses of mechanistic explanation. Our conclusion is that the conceptual analysis of mechanistic explanation facilitates a better characterization of the concept of mechanistic information. However, it also shows that the (...) use of this kind of information in risk assessment is heavily influenced by pragmatic factors, which have not been sufficiently taken into account in philosophical analysis. Mechanistic models are like hypothesis that have to be validated empirically. Due to their dependence on the standards of evidence, they are subject to the same pragmatic factors. Therefore, recurring to mechanistic information does not lead to closure of the methodological controversies in risk assessment. (shrink)