The Use of Data, Not Defaults
The Red Book recognized the limitations of defaults and also recognized that any set of defaults, no matter how they were selected, would not likely be generally applicable to all risk assessments (NRC, 1983). Although substantial research might someday make it possible to justify generally applicable models for interspecies, high- to low-dose, or intraspecies extrapolations, the understanding needed to achieve such a goal remains unavailable and is not likely to be available for a very long time.
New research on a specific substance or exposure situation can lead to questions about the applicability of any given default to that substance or situation (NRC, 1983). Thus the report urged agencies conducting risk assessments to seek data that would supplant the need for a default—such as data on the toxicokinetic differences between animals and humans—and to allow scientific knowledge and data on specific substances to hold sway over defaults. This same point has been emphasized in subsequent reports (NRC, 1994, 2007, 2009; OMB and OSTP, 2007).
For instance, if enough scientific information exists about the differences in the metabolism or mode of action of a chemical in animals versus in humans, then scientifically derived extrapolation factors can be used rather than the defaults. Such factors, which EPA refers to as “data-derived extrapolation factors” (EPA, 2011a, p. ii), would be specific for a given chemical. If those factors more accurately reflect the differences between animals and humans than default adjustment factors, the use of such data-derived extrapolation factors would decrease the uncertainty in the risk assessment.
EPA agrees with the NRC report that specific knowledge should supplant the use of defaults when appropriate and it has adopted that as a general principle (EPA, 2005a). However, a 2006 GAO report concluded that “EPA is often reluctant to deviate from its established default assumptions” (GAO, 2006, p. 67). In other words, GAO concluded that although EPA in theory favors using new scientific information to supplant established defaults, in practice it uses defaults more often than not (GAO, 2006).
The continued reliance on defaults is, in part, due to a view that any research data used to deviate from defaults—such as data on the mode of action of a chemical that indicates that there are no adverse effects below a certain dose—will themselves have uncertainties. Unless those uncertainties are clearly much smaller than those associated with the default, assessors often think that the default should be retained (Haber et al., 2001; Meek et al., 2002). However, because the true uncertainties associated with the standard defaults are generally unknowable, such comparisons are problematic. In any event, the general question remains unanswered of just how convincing the data on specific substances—such as mode of action