Human risk assessment, extrapolation from

In animal experiments exposures can be carefully controlled, and dose-response curves can be formally estimated. Extrapolating such information to the human situation is often done for regulatory purposes. There are several models for estimating a lifetime cancer risk in humans based on extrapolation from animal data. These models, however, are premised on empirically unverified assumptions that limit their usefulness for quantitative purposes. While quantitative cancer risk assessment is widely used, it is by no means universally accepted. Using different models, one can arrive at estimates of potential cancer incidence in humans that vary by several orders of magnitude for a given level of exposure. Such variations make it rather difficult to place confidence intervals around benefits estimations for regulatory purposes. Furthermore, low dose risk estimation methods have not been developed for chronic health effects other than cancer. The... 

In section 2.3 of this chapter the present approach to characterisation of dose-response relationships was described. In most cases it is necessary to extrapolate from animal species that are used in testing to humans. It may also be necessary to extrapolate from experimental conditions to real human exposures. At the present time default assumptions (which are assumed to be conservative) are applied to convert experimental data into predictive human risk assessments. However, the rates at which a particular substance is adsorbed, distributed, metabolised and excreted can vary considerably between animal species and this can introduce considerable uncertainties into the risk assessment process. The aim of PB-PK models is to quantify these differences as far as possible and so to be able to make more reliable extrapolations. 

Basic problems of animal-to-human extrapolation are in the OTA s report (op. cit.) and comprehensively treated in Edward Calabrese, Principles of Animal Extrapolation (John Wiley and Sons New York, 1983). The particular problem of extrapolation of teratology data from animals to humans is concisely discussed by V. Frankos in his paper FDA perspectives in the use of teratology data for human risk assessment (Fundamental and Applied Toxicology, Vol. 5, 1985, pp 615-25). 

Finally, following the enumeration of pathologic diagnoses, the choice of the statistical model can, in itself, affect the conclusion. This is especially true in discerning a negative from a weak positive effect. Thus, before we even approach the area of human risk assessment, or extrapolation, the complex test required to determine whether or not a chemical is an animal carcinogen, i.e., the basis for the qualitative decision, is already encumbered by many possible errors of procedure or judgment. 

The following example is based on a risk assessment of di(2-ethylhexyl) phthalate (DEHP) performed by Arthur D. Little. The experimental dose-response data upon which the extrapolation is based are presented in Table II. DEHP was shown to produce a statistically significant increase in hepatocellular carcinoma when added to the diet of laboratory mice (14). Equivalent human doses were calculated using the methods described earlier, and the response was then extrapolated downward using each of the three models selected. The results of this extrapolation are shown in Table III for a range of human exposure levels from ten micrograms to one hundred milligrams per day. The risk is expressed as the number of excess lifetime cancers expected per million exposed population. 

In the case of noncarcinogenic substances, there exists a threshold this is an exposure with a dose below which there would not be adverse effect on the population that is exposed. This is the reference dose (RfD), and it is defined as the daily exposure of a human population without appreciable effects during a lifetime. The RfD value is calculated by dividing the no observed effect level (NOEL) by uncertainty factors. When NOEL is unknown, the lowest observed effect level (LOEL) is used. NOEL and LOEL are usually obtained in animal studies. The main uncertainty factor, usually tenfold, used to calculate the RfD are the following the variations in interspecies (from animal test to human), presence of sensitive individuals (child and old people), extrapolation from subchronic to chronic, and the use of LOEL instead of NOEL. Noncancer risk is assessed through the comparison of the dose exposed calculated in the exposure assessment and the RfD. The quotient between both, called in some studies as hazard quotient, is commonly calculated (Eq. 2). According to this equation, population with quotient >1 will be at risk to develop some specific effect related to the contaminant of concern. 

Estimates of exposure levels posing minimal risk to humans (MRLs) have been made, where data were believed reliable, for the most sensitive noncancer end point for each exposure duration. MRLs include adjustments to reflect human variability and, where appropriate, the uncertainty of extrapolating from laboratory animal data to humans. Although methods have been established to derive these levels (Barnes et al. 1987 EPA 1989a), uncertainties are associated with the techniques. Furthermore, ATSDR acknowledges additional uncertainties inherent in the application of these procedures to derive less than lifetime MRLs. As an example, acute inhalation MRLs may not be protective for health effects that are delayed in development or are acquired following repeated acute insults, such as hypersensitivity reactions, asthma, or chronic bronchitis. As these kinds of health effects data become available and methods to assess levels of significant human exposure improve, these MRLs will be revised. 

Immunotoxicology data most often available for use in risk assessment is derived from experimental animal studies. Although animal models provide an opportunity to establish more reliable exposure estimates and conduct more informative tests than human studies, the level of accuracy that can be achieved using such data in extrapolating to humans is often a matter of debate. In immunotoxicology testing, a set of tests usually referred to... 

The science policy components of risk assessment have led to what have come to be called default assumptions. A default is a specific, automatically applied choice, from among several that are available (in this case it might be, for example, a model for extrapolating animal dose-response data to humans), when such a choice is needed to complete some undertaking (e.g., a risk assessment). We turn in the next chapter to the conduct of risk assessment and the ways in which default assumptions are used under current regulatory guidelines. We might say we have arrived at the central subject of this book. 

If dose-response data from an animal study are selected as the principal basis for assessing risk, how are they to be applied (extrapolated) to the human population that is the subject of the risk assessment This is the problem of interspecies extrapolation. 

As mentioned previously, the assessment of hazard and risk to humans from exposure to chemical substances is generally based on the extrapolation from data obtained in smdies with experimental animals. In the absence of comparative data in humans, a basic assumption for toxicological risk assessment is that effects observed in laboratory animals are relevant for humans, i.e., would also be expressed in humans. In assessing the risk to humans, an assessment factor is applied to take account of uncertainties in the differences in sensitivity to the test substance between the species, i.e., to account for interspecies variability (Section 5.3). If data are available from more than one species or strain, the hazard and risk assessment is generally based on the most susceptible of these except where data strongly indicate that a particular species is more similar to man than the others with respect to toxicokinetics and/or toxicodynamics. Two main aspects of toxicity, toxicokinetics and toxicodynamics, account for the namre and extent of differences between species in their sensitivity to xenobiotics this is addressed in detail in Chapter 5. 

The assessment factors generally apphed in the estabhshment of a tolerable intake from the NOAEL, or LOAEL, for the critical effect(s) are apphed in order to compensate for rmcertainties inherent to extrapolation of experimental animals data to a given human situation, and for rmcertainties in the toxicological database, i.e., in cases where the substance-specific knowledge required for risk assessment is not available. As a consequence of the variabihty in the extent and nature of different databases for chemical substances, the range of assessment factors apphed in the establishment of a tolerable intake has been wide (1-10,000), although a value of 100 has been used most often. An overview of different approaches in using assessment factors, historically and currently, is provided in Section 5.2. 

Data from studies in experimental animals are the typical starting points for hazard and risk assessments of chemical substances and thus differences in sensitivity between experimental animals and humans need to be addressed, with the default assumption that humans are more sensitive than experimental animals. The rationale for extrapolation of toxicity data across species is founded in the commonality of anatomic characteristics and the universality of physiological functions and biochemical reactions, despite the great diversity of sizes, shapes, and forms of mammalian species. 

Risk assessments are usually based on data from studies in animals of similar age. In addition, the animals are initially healthy and are fed with the same feed, etc. The NOAEL from animal smdies is extrapolated to a tolerable intake that is considered to be without appreciable health risk for the general population. This raises the questions whether it is possible to generalize to the average human population or whether there is any particular vulnerable subpopulation that should be taken into consideration in the risk assessment. 

The first step, extrapolation of data from experimental animals to the human simation, is similar to the interspecies extrapolation described in detail for threshold effects (Section 5.3). The second step, evaluation of a carcinogen s mechanism(s) or mode of action(s), is very important for the choice of model for the risk assessment, i.e., non-threshold or threshold this issue is addressed in Section 4.9. The third step, quantitative dose-response assessment, is the main focus of this chapter and is addressed in more detail in the following text. 

The most widely used of the many mathematical models proposed for extrapolation of carcinogenicity data from animal studies to low-dose human exposures (i.e., low-dose extrapolation) is the LMS model. This has, in effect, become the default approach for quantitative risk assessment and has been used by, e.g., the US-EPA for many years as well as by the WHO in relation to derivation of drinking-water guideline values for potential carcinogens (WHO 1996) (see Section 9.2.1.2 for drinking-water guideline values). 

Assessment of the carcinogenic risk to humans from a review of animal data is complicated by the results of pharmacokinetic studies that have associated methylene chloride carcinogenicity with a specific metabolic pathway. This glutathione S-mediated pathway appears to proceed slowly in humans compared with mice and only at high exposure doses. Therefore, extrapolation from high dose to low dose and between species may not provide accurate risk assessment of human exposure. 

There are of course many mathematically complex ways to perform a risk assessment, but first key questions about the biological data must be resolved. The most sensitive endpoint must be defined along with relevant toxicity and dose-response data. A standard risk assessment approach that is often used is the so-called divide by 10 rule . Dividing the dose by 10 applies a safety factor to ensure that even the most sensitive individuals are protected. Animal studies are typically used to establish a dose-response curve and the most sensitive endpoint. From the dose-response curve a NOAEL dose or no observed adverse effect level is derived. This is the dose at which there appears to be no adverse effects in the animal studies at a particular endpoint, which could be cancer, liver damage, or a neuro-behavioral effect. This dose is then divided by 10 if the animal data are in any way thought to be inadequate. For example, there may be a great deal of variability, or there were adverse effects at the lowest dose, or there were only tests of short-term exposure to the chemical. An additional factor of 10 is used when extrapolating from animals to humans. Last, a factor of 10 is used to account for variability in the human population or to account for sensitive individuals such as children or the elderly. The final number is the reference dose (RfD) or acceptable daily intake (ADI). This process is summarized below. 

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