Evaluation of toxicity involves two steps: hazard identification and dose-response evaluation. Hazard identification includes a description of the specific forms of toxicity (neurotoxicity, carcinogenicity, etc.) that can be caused by a chemical…
Dose-response evaluation is a more complex examination… with particular emphasis on the quantitative relationship between dose and toxic response.
When epidemiologic studies are not available or not suitable, risk assessment may be based on studies of laboratory animals.
One advantage of animal studies is that they can be controlled, so establishing causation (assuming that the experiments are well conducted) is not in general difficult. Another advantage is that animals can be used to collect toxicity information on chemicals before their marketing, whereas epidemiologic data can be collected only after human exposure.
Laws in many countries require that some classes of chemicals (e.g., pesticides, food additives, and drugs) be subjected to toxicity testing in animals before marketing.
But laboratory animals are not human beings, and this obvious fact is one clear disadvantage of animal studies.
[I]nterpreting observations of toxicity in laboratory animals as generally applicable to humans usually requires two acts of extrapolation: interspecies extrapolation and extrapolation from high test doses to lower environmental doses.
Differences among animal species, or even among strains of the same species, in metabolic handling of a chemical, are not uncommon and can account for toxicity differences…
It has become customary to assume, under these circumstances, that in the absence of clear evidence that a particular toxic response is not relevant to human beings, any observation of toxicity in an animal species is potentially predictive of response in at least some humans.
[T]he standard procedure used by regulatory agencies for evaluating the dose-response aspects of toxicity involves identifying the highest exposure among all the available experimental studies at which no toxic effect was observed, the “no-observed-effect level” (NOEL) or “no-observed-adverse-effect level” (NOAEL).
The NOAEL is the highest exposure at which there is no statistically or biologically significant increase in the frequency of an adverse effect when compared with a control group. A similar value used is the lowest-observed-adverse-effect level (LOAEL), which is the lowest exposure at which there is a significant increase in an observable effect.
For example, if a chemical caused signs of liver damage in rats at a dosage of 5 mg/kg per day, but no observable effect at 1 mg/kg per day and no other study indicated adverse effects at 1 mg/kg per day or less, then 5 mg/kg per day would be the LOAEL and 1 mg/kg per day would be the NOAEL under the conditions tested in that study.
The experimental NOAEL is assumed to approximate the threshold [where toxic effects are unlikely].
To establish limits for human exposure, the experimental NOAEL is divided by one or more uncertainty factors, which are intended to account for the uncertainty associated with interspecies and intraspecies extrapolation [biological and physiological differences or variation] and other factors.
[I]f the NOAEL is derived from high-quality data in… humans, even a small safety factor (10 or less) might ensure safety, provided that the NOAEL was derived under conditions of exposure similar to those in the exposed population of interest and the study is otherwise sound. If, however, the NOAEL was derived from a less similar or less reliable laboratory-animal study, a larger uncertainty factor would be required.
There is no strong scientific basis for using the same constant uncertainty factor for all situations, but there are strong precedents for the use of some values (NRC, 1986). The regulatory agencies usually require values of 10,100, or 1,000 in different situations.
For example, a factor of 100 is usually applied when the NOAEL is derived from chronic toxicity studies (typically 2-year studies) that are considered to be of high quality and when the purpose is to protect members of the general population who could be exposed daily for a full lifetime (10 to account for interspecies [between different species] differences and 10 to account for intraspecies [within a species] differences).
Using the NOAEL/LOAEL/uncertainty-factor procedure yields an estimate of an exposure that is thought to “have a reasonable certainty of no harm.” Depending on the regulatory agency involved, the resulting estimate of “safe” exposure can be termed an acceptable daily intake, or ADI (Food and Drug Administration, FDA); a reference dose, or RfD (EPA); or a permissible exposure level, or PEL (Occupational Safety and Health Administration, OSHA).
The requirement for uncertainty factors stems in part from the belief that humans could be more sensitive to the toxic effects of a chemical than laboratory animals and the belief that variations in sensitivity are likely to exist within the human population.
Uncertainty factors are intended to accommodate scientific uncertainty, as well as uncertainties about dose delivered, human variations in sensitivity, and other matters.
EPA (1988a,b) later proposed guidelines for assessing male and female reproductive risks that incorporate the threshold default assumption “usually assumed for noncarcinogenic/nonmutagenic health effects,” as well as the agency’s new RfD [Reference Dose] approach to deriving acceptable intakes.
The total adjustment or uncertainty factor referred to in the proposed guidelines for use in obtaining an RfD [Reference Dose] from toxicity data “usually ranges” from 10 to 1,000. The adjustment incorporates (as needed) uncertainty factors (“often” 10) for “(1) situations in which the LOAEL must be used because a NOAEL was not established, (2) interspecies extrapolation, and (3) intraspecies adjustment for variable sensitivity among individuals.”
An additional modifying factor may be used to account for extrapolating between exposure durations (e.g., from acute to subchronic) or for NOAEL-LOAEL inadequacy due to scientific uncertainties in the available database.