in Health Risk Assessments
ARTHUR ROBERT GREGORY TECHTO
220 Ash Rd, Sterling,
June 29, 1989
Considerable scientific evidence has accumulated in the area ofrisk assessment. Using physiologically based pharmacokinetic models and biologically based dose-response models, more precise estimates of risk are becoming available. Uncertainty analysis performed at three steps of the process will enhance a clearer understanding of the assumptions being made regarding a public health decision. Recommendations are made on how uncertainty in risk assessmentscan be addressed and the types of future research that are required to this end. o 1990 Academic Press, Inc.
INTRODUCTION There is increasing reliance on quantitative risk assessment when decisions in public health affairs are to be made. This is occurring in both regulatory bodies and industry. The advantages for this approach have been reviewed (NAS, 1983; US. DHHS, 1986; Clayson et al., 1985; and Cothem et al., 1988) and are now generally accepted (U.S. EPA Guidelines, 1986). Nevertheless, the utility of risk assessment in risk management primarily resides in the adequacy of the data base. Wherever data gaps occur, assumptions must be made before the risk assessment process can be completed. When these assumptions are unrealistic or eventually prove to be incorrect, the risk assessment supports an interpretation diametrically opposed to reality (Breslow, 1986; Weintrub et al., 1989). Ideally, one would like to have only epidemiological data for the performance of risk assessments. Man is his own best experimental model. No cross-species extrapolation would be required. Unfortunately, epidemiological data are very expensive, often lack exact exposure measurements, and usually lack sufficient power to establish cause and effect. Thus, on pragmatic as well as ethical grounds, carcinogenic potency must primarily be determined in experimental animals, preferably, short-lived animals. It is a fact of life that they are the best we have to work with. Nevertheless, unless animal data have realistic relevance to the human situation, they are of little value for establishing hazard for man (Gregory, 1988). 191 0273-2300190
Copyright 0 I990 by Academic Press. Inc. All rights of reproduction in any form reserved.
Hazard identification (Does the agent cause the adverse ellect?)
(what Is the estimated ndeoftheadverse
Evaluation of public health, economic. social, 8 poWal consequences
1. Elements of risk assessment and risk management (adopted from NAS (1983))
This document will describe in detail the types of uncertainties encountered in making risk assessments and the interrelationships of the uncertainties of each of the four steps in the risk assessment process. It will also describe methodologies that may be utilized to reduce the uncertainty involved in making most risk assessments.
Depicted in Fig. 1 is an adopted version of the elements of the risk assessment process as reviewed by the National Academy of Sciences (NAS, 1983) and the interrelationships between risk assessment, risk management, and the data base. The data base is the foundation on which the four steps in risk assessments must be based. The inexactness or lack of appropriate data used for each step results in a proportional deficiency in the final quantitative risk assessment. Of even greater consequence is the fact that if a risk characterization (Step 4) provides no estimation of the uncertainty involved, such a risk characterization will undoubtedly contribute to the inadequacies of the ultimate management decisions and the public health actions taken. In the 1983 publication Risk Assessment in the Federal Government: Managing the Process, the Academy made two outstanding recommendations: (1) Guidelines for risk assessment must accommodate change as scientific evidence accumulates; and (2) uniform guidelines for risk assessment (except for exposure assessment) are feasible and desirable. Because scientific evidence has accumulated in risk assessment and because these should be applied uniformly to risk assessments, the next section addresses the “givens” now generally utilized in risk assessments.
Given: In our present state of knowledge about risk assessments, most analyses regard the following approaches as axiomatic. 1. Total human exposure cannot be completely measured, although the total exposure assessment methodology (TEAM) approach has succeeded in closely defining specific measurements of specific materials (Wallace, 1987). Even the best exposure measurements have residual uncertainty. 2. Physiologically based pharmacokinetics models provide the best approach for determining how the applied dose results in the delivered dose at the target organ. 3. Biologically based dose-response models provide the best approach for understanding and estimating the relationships between a delivered dose and the ultimate health effect. The relationships
are depicted in Fig. 2. EXPOSURE
Human exposure assessment necessarily establishes contact between the chemical and the portal of entry. Direct exposures can be quantitated using individual moni-
tors. However, in many cases, indirect measurements are all that are available. These indirect measurements can be either ambient or biological. If the measurements is ambient, a model (with its associated uncertainty) is usually utilized to estimate exposure. Activity, physical parameters, and microenvironments all must be incorporated into the model. Indirect biological measurements have also been used to estimate exposure from the rate of excretion in the urine or rate of metabolite formation. Such models depend on estimating the excretion and/or transformation rates. The direct measurement of a xenobiotic or radiation entry into the body involves real time measurements of exposure. Personal radiation badges are an example. Personal monitors that trap, analyze, and measure volatile substances are also available (Wallace, 1987). For some time poisons such as aflatoxin have been monitored in various appropriate food substrates. Such procedures have been used to estimate direct exposure of individuals (U.S. DHHS, 1986). One of the key findings of studies like the TEAM study was that exposure is not only different from individual to individual but that exposures tend to be in peaks of variable duration. Most animal experiments are done at constant exposure levels. Therefore, the question of how a series of short-term peak exposures would compare riskwise to a constant, but equivalent, lifetime exposure has engendered considerable interest (Clayson et al., 1985). Over the past several years, exposure assessors have approached the problem of assessing the exposure (contact between chemical and organism) or dose (amount entering the organism after contact) in three ways-one direct and two indirect. The direct measurement approach involves real time measurements of contact intensity through the use of a personal monitor such as radiation badges or active devices that pump and trap volatile chemicals, through analysis of the amounts and contamination levels of food and water ingested, and through methods to measure dermal exposure. The indirect methods can be either predictive, using models for pollutant behavior or human (ecological) behavior, or, under limited conditions, reconstructive, using body burden and knowledge of pharmacokinetics to back-calculate what the exposure must have been to result in the observed levels. All of these methods have strengths and weaknesses, and all have associated uncertainties for their intended uses (OSTP, 1985). Predictive exposure assessment techniques have been particularly appealing to regulatory agencies such as FDA and EPA, since they allow the evaluation of an impact to large populations over long periods of time. Predictive techniques need not only estimate (or measure) concentrations of pollutants but may also relate pollution levels to what is being contacted by the target populations. Humans are quite mobile in the environment and the assumption of constant levels of exposure over time for an individual or population is at best an approximation, and at worst a major misrepresentation of the actual situation. To measure human exposure, knowledge of human activity patterns must be known. However, ways to incorporate this information into risk assessments has long been a weak link in the process. It is thus the origin of much uncertainty in exposure assessment (U.S. EPA Proposed Guidelines, 1988). A second major area of uncertainty is how the data for exposure assessment are taken in the field. The methods used to collect the data are of particular importance if the data are to be used appropriately in the generation of a model to estimate further exposure. Of particular recent interest in this area, for example, is the question of how a series of short-term duration exposure peaks would differ in a risk context from equivalent
lifetime long-term exposures at fairly constant but lower levels, and how this information can best be measured in the field and incorporated into the exposure assessment. A third major area of concern in reducing uncertainty in exposure assessments is the inconsistency in assumptions used by various assessors for similar exposure situations. This often leads to two assessments of the same situation done by different assessors (for example, an Agency assessment of a Superfund site and an assessment sponsored by a potentially responsible party) which use different methodologies and assumptions, and thereby reach estimates of exposure or risk that are substantially different. Any program directed at improving exposure assessment must focus on three major areas of uncertainty: acquiring better information on human activity patterns as they relate to exposure estimates, improving methods to obtain exposure assessment data, and standardizing the ways these data are to be used. HUMAN
Considerable work is needed to develop and validate human exposure models which can generate realistic predictions of exposure to chemicals using human activity patterns and source information. Human exposure models are used to measure the concentrations of pollutants that individuals experience in various microenvironments (microenvironmental exposures) and multiply these by the time spent in those microenvironments (human activity patterns) to provide the total dose experienced. Such models should address each of the microenvironments which people experience (e.g., homes, stores, schools, subways, buses, automobiles, workplace) and should include multiple routes of exposure (e.g., air, food, drinking water). In particular, they should take into account indoor and in-transit environments. The research problems to be addressed in human exposure model development lie not only in the development of improved exposure models based on existing data but also in validating these models (U.S. EPA, THERC, 1989). Developments in this area should proceed by first constructing human exposure models for particular families of important pollutants (e.g., respirable particles, volatile organic compounds, food additives) using the most complete data set available. To be useful, models must be validated by testing them under field conditions. Total human exposure field studies must be used to validate a variety of situations. Uncertainty ranges around the predictions should be characterized for specific models. Only after the uncertainty of the model has been characterized (validation phase) should the risk assessor utilize such models. Guidelines for model validation should include a discussion of the appropriateness of various exposure situations and the expected uncertainty of the models. In the past, models have lacked objective validity criteria in many cases even though relatively simple precision criteria are available to test such models (Burns, 1985). The U.S. EPA has published proposed guidelines for exposure-related measurements (U.S. EPA, 1988). This document addresses many of the areas discussed here and provides additional resource material on uncertainty in human exposure measurements and human exposure models. HUMAN
Field studies of human exposure, such as the TEAM studies, have shown that an individual’s activities are critical in explaining the exposures of the population to
environmental pollutants. Yet, considerable work is needed to improve the data base on parameters used to make indirect exposure estimates and to clarify how to use them. More information is needed on the ranges and distributions of parameters used in direct exposure assessments, such as ingestion rates, exposure durations, contact rates, and short-term versus long-term exposures. Guidance on such topics is especially important to be able to improve consistency in risk assessment. Guidance is also needed on how to apply these factors to create different scenarios including both typical and reasonable worst cases. Significant controversy exists about the amount of soil ingested by children (U.S. EPA, THERC, 1989). Since this is a very significant exposure route in many assessments, more field work is required to develop the data base needed to establish the relationship among these variables. Also, it has become clear that for many pollutants, short-term peaks are extraordinarily important contributors to exposure. In addition to the importance as contributors to exposure, short-term peaks may have considerable impact on the dose-response portion of the risk assessment. A number of single-dose exposures have now been shown to be capable of producing cancer (Moore et al., 1988; Gregory, 1988). Methods should be pursued for measuring the relative frequency and magnitude of short-term peaks and then incorporating this information in establishing the doseresponse relationships. These data could then be used to supply risk assessors with source parameters and methodologies to incorporate these parameters into exposure assessments. PHYSIOLOGICALLY
The trend over the last few years has been to base quantitative risk assessments on the “delivered dose.” This is the dose of proximate toxicant, whether the unchanged xenobiotic or its metabolite, at the tissue site of toxic action-rather than on the applied dose or ambient concentration. The determination of this delivered dose is in essence an extension of exposure assessment, in that the direct exposure of the actual target tissue is examined free of the various physiological fate and transport processes by which the body absorbs, distributes, transforms, and modifies compounds absorbed from its environment. Uncertainty can be reduced by further investigation into the effects of different conditions of exposure on the distribution pattern of the delivered dose using PB-Pk models. For example, examination of delivered dose could prove very useful in comparing the toxic results of exposures by different routes of administration. In this way, extraneous factors such as different degrees or rates of absorption can be accounted for, resulting in more meaningful comparisons. The ability to estimate target-site doses also is necessary for further information on the mechanistic biological modeling of toxicity. In risk assessment as often currently practiced, measurements of applied dose or exposure concentration are used merely as surrogates of the delivered dose since this frequently is unknown. The equivalencies among different conditions of exposure are mostly assumed and usually have little empirical support. This can represent a source of significant uncertainty (Conolly et al., 1988). Among the most critical uncertainties associated with extrapolation from experimental to actual conditions are assumptions about:
l route-to-route extrapolation comparability of exposure by different routes of administration (by accounting for differences in absorption, bioavailability, and firstpass metabolism); l chronic-to-acute extrapolation comparability of different regimes of exposure, such as the effect of repeated versus single dosing on dose delivery. The equality of episodic, peak, and chronic exposures totalling the same cumulative dose remains to be examined in detail; l high-to-low dose extrapolation proportionality between external exposure level and the resulting delivered dose for high exposure studies, compared to lower levels typical of environmental exposure (by accounting for sources of nonproportionality such as saturation of metabolism, utilization of different pathways of biotransformation, and nonlinear binding); and l species-to-species extrapolation scaling or translation of dose to determine exposures yielding equivalent doses in different species, especially when extrapolating toxic effects in experimental animals to those expected in humans. Gregory (1988) has shown that in some cases the extrapolation cannot be made at all because of qualitative differences in species.
One way to reduce the uncertainties related to scaling is to obtain data on doses at more biologically meaningful levels, i.e., delivered dose at the target issues. The examination of delivered dose still does not provide sufficient information for extrapolation in risk assessment, since the equivalency of effects across species is determined not only by relative dose delivery but also by species differences in sensitivity to a given delivered dose (Moore et al., 1988). Similarly, the extrapolation of effects to low doses or from acute-to-chronic exposures depends not only on the delivered dose differences in these circumstances but also on the relative toxicological effects of different levels and durations of tissue exposure to the proximate toxicant (OSTP, 1985; U.S. DHHS, 1986; Gaylor, 1989). Even when there is the capability of establishing internal or delivered doses at particular tissue sites, mechanisms of action may take prominence in establishing level of risk. The delivered dose may not be the essential factor. The quantitation of DNA adducts or other carcinogen “markers” may not suffice (Moore et al., 1988). For different mechanisms of action, the oncogenic or other noxious response may be a function of the quantity of metabolite formed, number of adducts or other covalent reactions produced with crucial cellular macromolecules, extent of reversible binding to specific ontogeny receptors, or a requisite threshold toxicant concentration for a specific duration of time. The rate and fidelity of DNA repair must also be considered. These factors vary considerably among species, strains, sexes, previous histories of exposure, and physiological condition ofthe subjects (Oser, 198 1; OSTP, 1985; Gregory, 1988). Although examination of delivered doses can remove a great deal of uncertainty from the various extrapolation processes in quantitative risk assessment, it should be considered a prerequisite and additional factors will also have to be considered. Nevertheless, it is clear that other biological factors cannot be addressed without first eliminating the confounding and obscuring effects of dose delivery and pharmacokinetics. Thus, further exploration in pharmacokinetics will be essential to performing more biologically rational risk assessments. High-to-low dose extrapolation has been the source of major uncertainties. This is partially because of a paucity of pharmacokinetics and pharmacodynamic data. In
quantitative risk assessment, extrapolation is often from the experimental chronic dose regimen used in an animal toxicological study to the expected human exposure. The doses must be compared not only on a total cumulative dose basis (the total mg/ kg) but on a time scale as well. Both the dose rate of administration and the dose level can affect the pharmacokinetics of a compound, and hence the amount delivered to the target site. High dose levels often include pathways that at lower dose levels do not contribute to metabolic conversions which are linked to the toxicity ofthe compound (Anderson et al., 1987). Further research is also needed to verify certain of the assumptions used in routeto-route extrapolation. Information may be only available on the toxicological effects associated with a particular route of exposure. Assessors may be able to utilize, to some extent, such data for the exposure route of interest if models could be developed and verified. Very little work has been reported in this area and considerable effort will have to be expended if it is to be utilized in the future. A further discussion of the particular research needs in this area will be the subject a subsequent paper. BIOLOGICALLY
In quantitative risk characterization dose-response with exposure estimates are used to calculate the incidence of a particular health effect at human exposure levels. Ideally, one would like to have human data available at the relevant exposure levels. But even when human data are available, considerable confounding variables may make extrapolation of the results uncertain. In most cases, however, the data available are at higher exposures, and based upon experiments in test species rather than obtained from human studies. As such, the risk assessor is required to select and apply an appropriate strategy (e.g., RfD’s or mathematical models) to perform a high-tolow dose extrapolation. The major uncertainty in quantitative risk assessment evolves from this often arbitrary selection process and a lack of testing for the bias that may guide selection. The final risk estimate may vary by orders of magnitude depending on the approach (model) applied (Purchase, 1985). The development and application of BB-DR models may substantially reduce the uncertainties in quantitative risk characterization. Under the BB-DR approach, the essential physiological elements and processes, as well as their interactions, are described, Utilization of such information may also assist in the selection of the most biologically plausible strategy relevant to the risk assessment process. Such models may assist in accounting for variation in any key element as it differs within and among species under varying exposure conditions. The integration of biologic/mechanistic relevancy into the model process can also allow the risk assessor to examine the validity of some of the assumptions that are often applied in the risk assessment. The most noteworthy conclusion of a recent symposium on reducing uncertainty in risk assessment that was “the increased understanding of the underlying mechanisms . . . should be applied as fully as possible to the risk assessment process” (Kamrin, 1989). Thus, it is quite clear that risk assessors must learn to incorporate mechanistic data into dose-response models to more precisely predict human responses. INTER/INTRASPECIES
Considerable uncertainty exists as to the factors responsible for differences in response within and across species. Considerable work is needed to elucidate the critical
physiologic and mechanistic factors that contribute to the health effects of concern in the risk assessment process. Such research will improve the basis on which to adjust for intra- and interspecies variability in dose-response extrapolations. The extent to which effects observed in one species can be extrapolated to another is limited (Ames et al., 1987; Gold et al., 1989; Adamson and Sieber, 1983; OSTP, 1985; St. Hilaire, 1987; EPA Guidelines, 1986). One of the key elements in attempting extrapolation is to determine whether effects in animals are analogous (i.e., superficially similar) or homologous (i.e., resulting from a common mechanism of action) to those in humans. Research emphasis should be placed on evaluating species similarities and differences in both mechanism and expression of a given outcome. For example, the species and strains used in the NTP bioassays have never been validated using known human carcinogens (Gregory, 1990). As such, these efforts may confirm the existence of a homologous mechanism for inducing specific toxicities. The degree of homology in the expression of such disease (i.e., comparable outcome) may also lead to greater confidence in the risk characterization. Theoretically, the use of pharmacokinetic models should lead to the determination of the effective dose at a given target site. However, given equivalent target doses, we are still left with questions regarding interspecies differences in sensitivity that need to be addressed independently. Recent research has revealed that interspecies extrapolation can be very helpful or extremely misleading (Gregory, 1988; Reynolds et al., 1987; Spandidos and Anderson, 1989) since the oncogenes which suppress or enhance cancer are often species and/or strain specific (Spandidos and Anderson, 1989; Moore et al., 1988). For evaluation of carcinoma of the breast, for example, the Wistar-Furth rat is extremely sensitive, while the Copenhagen rat is completely resistant to all breast carcinogens tested thus far. The Fischer rat is intermediate in response (Moore et al., 1988). This, of course, does not mean that one can extrapolate all data from Fischer rats to humans, but these findings indicate that the choice of this strain to test carcinogens may well have been fortuitous. CONCLUSIONS The reliance on quantitative risk assessment to make public health decisions will continue. Potency estimates will continue to be based largely on experimental animal data. Therefore, it behooves us to utilize the data that are available in the best way possible. The use of physiologically based pharmacokinetic and the biologically based dose-response models will best accomplish this extrapolation with the least residual uncertainty. However, without further research into the validity of these models in the specific cases for which risk is estimated, uncertainty will continue to dominate the process. Research is especially needed to examine the relationships of external to internal dosings, pharmacokinetic transformation to effective levels, and the relationship of continuous dosing to sporadic (or even single) dosings. REFERENCES ADAMSON, R. H., AND SIEBER,S. M. (1983). Chemical carcinogenesis studies in nonhuman primates. In Organ and Species Specificity in Chemical Careinogenesis: Basic Life Sciences (R. Largenbach and S. Nesnow, Eds.), Vol. 24, pp. 129-156. Plenum, New York. AMES, B. M., MAGRAW, R., AND GOLD, L. (1987). Ranking possible carcinogenic hazards. Science 236, 271-280.
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