PRINCIPLES OF TOXICOLOGY

460 RISK ASSESSMENT
leading to important differences in apparent dose–response relationships (i.e., those based strictly on
applied dose). One approach used to enhance extrapolation among species is PBPK modeling. Using
PBPK models, scientists are able to predict target organ doses of a chemical (or a critical metabolite,
if that is important for toxicity) in test species and humans. With this information, corrections can be
made for pharmacokinetic differences among species, leading to better extrapolation of dose–response
relationships. The principal limitation of PBPK analyses is that they are very data-intensive, and PBPK
models have been constructed and validated for only a few chemicals.
Since PBPK models are rarely available, simpler approaches to extrapolating doses must be used
in most situations. One of the simplest approaches is to convey doses per unit body weight. Larger
animals (or humans) are assumed to require larger doses to produce the same toxic effect in direct
proportion to their body weight. This is the dose metric most commonly used when extrapolating
information on noncancer health effects among species. Interestingly, a different dose metric has been
used traditionally for extrapolating dose–carcinogenicity relationships. In this situation, doses have
usually been scaled according to the surface area of the animal. Since surface area for most species is
a function of body weight, and can be approximated by body weight raised to the 0.67 power, this
function has been used to convert doses used in animal studies (e.g., rodent cancer bioassays) to
equivalent human doses. In biology, empirical observations suggest that many biochemical and
physiological processes seem to scale among species according to surface area, while differences in
others seem to correspond more closely to changes in weight. The correct scaling for doses is not
entirely obvious, and could conceivably be different for different chemical classes or toxicological
effects. Recently, there have been recommendations that scaling for carcinogen doses use a factor
intermediate between body weight (or body weight raised to the power of 1) and surface area (body
weight raised to the power of 0.67); that is, body weight raised to the power of 0.75.
Does the choice of scaling factor really make a difference? To illustrate the answer, consider the
extrapolation of dose information between a mouse and a human. If a dose for a noncancer effect in a
mouse were converted to a human dose based on surface area, rather than on body weight as is
customary, the SHD dose would be reduced by a factor of 12–14. On the other hand, switching from
surface area scaling to body weight scaling for carcinogenicity data would result in a 12–14-fold
decrease in cancer risks estimated from the same dose–response information. The difference in use of
body weight versus surface area for extrapolating between rats and humans is not as large—about
6-fold—but still might be considered significant.
18.5 RISK CHARACTERIZATION
The purpose of the risk characterization step is to integrate information provided by the hazard
identification, dose–response assessment, and exposure assessment in order to develop risk estimates.
Risk information may be conveyed in a qualitative manner, quantitative manner, or both. A qualitative
assessment may describe the hazard posed by chemicals of concern, discuss opportunities for exposure,
and reach some general conclusions that the risks are likely to be high or low, but would not provide
numerical estimates of risk. A quantitative risk characterization, on the other hand, includes numerical
risk values. Theoretically, there are many ways that numerical risks could be calculated depending on
the specific questions being addressed in the risk assessment. For example, risks could be expressed
as an individual’s excess lifetime risk of developing a particular health effect as a result of chemical
exposure. Risks could also be expressed on a population basis (e.g., estimated number of extra cases
of a disease per year attributable to chemical exposure), or as the relative risk of an exposed population
versus an unexposed population. Other ways of expressing risks, or health impacts, could be in terms
of loss of life expectancy or lost days of work.
As discussed in Section 18.4, the most common means of expressing cancer risk associated with
chemical exposure is in the form of individual excess lifetime cancer risk. When calculated for
regulatory purposes, these values are intended to represent upper-bound estimates. That is, a cancer
risk of one in one million means that an individual chosen at random from the exposed population is