chemical. Combinations of alleles might also have exaggerating or compensating effects.
Although it can be argued that the current approach of risk assessment appears to have worked reasonably well for hazard identification, many assumptions must be made before it can be applied. One such default assumption is that outcomes for rodent tests are relevant for human risk prediction. Such assumptions are generically used because information on the mechanisms of action for specific developmental toxicants is inadequate and because the lack of mechanistic information results in the use of default uncertainty factors. The most important limitation is the paucity of human data, and the lack of methodology to adequately assess humans. Mechanism of action can be pursued in animal models, but it is also the lack of an understanding of human development that hampers risk assessment.
For risk characterization, the bioassays used for regulatory assessment have provided limited dose-response information. The information is limited because the focus is on the effects of high doses at or near maternal toxicity to emphasize identification of hazards. That focus has provided little quantitative information on the dose-response relationship in the low-dose region, the region of greatest importance for extrapolation in human risk assessment. The lack of useful dose-response data has had several impacts. As mentioned previously, conservative use of uncertainty factors predominates for converting NOAELs and BMDs to RfDs for determination of acceptable safe exposure levels. The dominance of animal testing at high doses has also had the unfortunate consequence of providing minimal useful mechanistic information, because assessments are frequently conducted at doses where homeostatic mechanisms are overwhelmed (Nebert 1994), and mechanistic clues about critical toxicant-induced changes are hidden.
The lack of mechanistic information has also resulted in assumptions about sensitivity among humans. Present practice in risk assessment almost always makes use of a default factor of 10 to take into account the variability in sensitivity (i.e., there is a 10-fold difference in susceptibility of the most sensitive individual and the average individual). This assumption has been experimentally addressed for relatively few chemicals (for a review, see Neumann and Kimmel 1998). However, the default assumption could change as researchers gain more information about the underlying basis for responses to toxicants. To date, the greatest progress in characterizing human variability is from research on DMEs. With time, there will also be data on other factors that influence susceptibility. For example, as discussed in detail in Chapter 5, a particular allele of transforming growth factor conveys more than a 10-fold increase in risk of oral clefts in infants whose mothers smoke cigarettes (Hwang et al. 1995; Shaw et al.1996).