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Toxicity Testing: Strategies to Determine Needs and Priorities (1984)

Chapter: 4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM

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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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Suggested Citation:"4. DETAILED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM." National Research Council. 1984. Toxicity Testing: Strategies to Determine Needs and Priorities. Washington, DC: The National Academies Press. doi: 10.17226/317.
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4 DETAI LED DESCRIPTION OF THE OPERATION OF AN ILLUSTRATIVE SYSTEM INTRODUCTION An illustrative priority-setting system has been developed to demonstrate the application of principles described in Chapter 2 and to demonstrate the feasibility of the approach to designing priority-setting systems. The system responds to the approach taken in Part 1, in that it uses the same classes of intended use and incorporates two of the toxicity tests used by the Committee on Sampling Strategies and the Committee on Toxicity Data Elements. The approaches differ in that the illustrative system is structured to be specific for a human health effect, whereas those two committees take a more general approach. ELEMENTS OF DESIGN Authors of priority-setting systems have several choices to make: goal of the system, universe of chemicals considered, structure of the system, and assessment. GOAL The goal chosen for this illustrative priority-setting and testing system is to assess accurately the public-health concern about all chemicals to which there is human exposure. This goal was chosen to reflect the wide range of chemicals of interest to NTP. A goal might be chosen to be oriented more toward regulation, such as minimizing the impact on human health caused by chemicals to which there is exposure. The Committee on Priority Mechanisms did not choose this goal, because NTP does not have regulatory authority and because NTP does testing for purposes other than regulation. UNIVERSE The universe of chemicals to be considered is defined to include all chemicals to which there is potential human exposure. The universe defined by the Committee on Sampling Strategies has five categories of intended use: food chemicals, drug ingredients, pesticide chemicals, cosmetic ingredients, and general industrial chemicals (TSCA Inventory) There are two additional categories: "other," such as pollutants; and "unknown." 237

ASSESSMENT The degree of public-health concern is a combination of degree of human exposure and degree of toxicity to humans. For purposes of designing this illustrative system, toxicity is limited to carcinogenesis. This health effect was chosen because of its severity and the high degree of public interest in it. Also, more effort has been devoted to discovering carcinogens; therefore, more data are available for designing the system. Both toxicity and exposure are expressed as high, medium, or low, because available information seems inadequate to define more than three levels. Toxicity, in this case carcinogenic potency, is defined in terms of TD50 (Ames et al., 1982~: high is a TD50 less than 102 ~g/kg-d, medium between 10~-and 106 ~g/kg-d, and low greater than 106 ~g/kg-d. His definition assumes a linear dose-response curve. The category of "low" toxicity also includes noncarcinogens. For exposure, high is greater than 107 person-grams per year (p-g/yr), medium is between 107 and 105 p-g/yr, and low is less than 105 p-g/yr. Note that, in this population-exposure formulation, large exposure of a small number of people could be equivalent to small exposure of a large number of people. Which situation is more important is a matter of social judgment. STRUCTURE A multistage structure was chosen, so that the system could handle many thousands of chemicals and fit the current institutional structure of the NTP selection system. A multistage structure provides for using small amounts of data to assess large numbers of chemicals in the early stages and examining fewer chemicals in depth in later stages. RULES FOR SELECTION The result of each stage is an assessment of the toxicity and exposure of each chemical considered in that stage and an estimate of confidence in each assessment. Having these assessments from each stage, it is still necessary to decide whether a chemical should receive further consideration or be removed from consideration. A mathematical model chooses rules for selection such that the errors in assessment are minimized, for a chosen amount of resources for selection and testing (Appendix B). That optimization model not only guided the Committee in designing the illustrative priority-setting scheme, but also allowed it to examine the values of and interactions among various indicators of exposure and 238

toxicity. Even the simplified model used for choosing the rules of the illustrative system validated some intuitive judgments about testing priorities and provided valuable additional insights; further development of the model may be justified to sharpen the rules for chemical selection in an operational priority-setting system and to modify them as additional information is gained by operating the system and conducting the tests it selects. DESIGN PARAMETERS Several characteristics of the universe were estimated and serve as data for the model used to develop the rules for the illustrative system. These estimates were based on fragmentary data and are intended to be replaced with better estimates based on data obtained from operating the system. The universe was estimated to consist of 70,000 discrete chemicals. The Committee on Priority Mechanisms intends that the definition of the universe be considered flexible and subject to change as needed. The estimate of 70,000 is not intended to become either a maximal or a minimal number of chemicals to be considered. On the basis of the above definitions of degree of exposure, the overall distribution of low, medium, and high exposure is 0.7, 0.2 and 0.1. On the basis of the definition of carcinogenic potencies, the estimated distribution of potency is 0.95 low, 0.04 medium, and 0.01 high. These estimates are only for purposes of designing the illustrative system and are highly speculative. Estimates of the proportion of carcinogens in a group of chemicals may vary widely (U.S. Congress, 1981), because of the definition of "carcinogen" and the group of chemicals considered. STAGE 1 me purpose of Stage 1 is to provide a mechanism for scanning the entire population of chemicals to be considered by the system. It is intended that this scanning could be performed in many ways: by category or combination of categories of intended use or by chemical structure. The scanning need not be performed in one year, but might be performed over a period of a few years. Stage 1 is limited to data in machine-readable data bases, so that human intervention is minimized. The Committee on Priority Mechanisms chose to use the data bases and searching capability of the Chemical Information System (CIS) developed by the National Library of Medicine (NLM) and EPA. This system was chosen because many chemicals of interest are already included in the data bases. In addition, the Structure and Nomenclature Search System of CIS provides a searching capability for chemical structures and thus makes possible a crude analysis of structure-activity relationships. 239

EXPOSURE DATA ELEMENTS The purpose of exposure data elements in all stages is to contribute to an attempt at estimating exposure on the basis of surrogate data--data that are related to exposure only incompletely or inaccurately. "Exposure" is a concept that embraces the quantities of material that reach people, the number of people exposed, the rates and patterns of exposure, the characteristics of the exposed population, and other factors. A fully developed system for priority-setting not only would take into account as many of these dimensions as feasible, but also would ensure that they interacted properly with the dimensions of toxicity. However, complexity may not be justified for screening decisions at early stages of the system, and it also obscures the logic of the illustrative system. Therefore, the committee conducted its analysis with a single exposure variable to which degree of hazard would be proportional for a constant degree of toxicity. If a linear dose-response relationship is assumed for toxicity as a first approximation, then exposure can be measured by the total mass of a substance that is ingested, inhaled, or otherwise taken in by all members of the population, in units of person-grams per year. This quantity can be estimated by summing the products of the per capita annual intakes and the number of persons for all exposed groups with different intakes. Two surrogates of exposure--class of intended use and production volume--are used to define the possible classifications of a Stage 1 exposure data element (Table 3~; each classification consists of a pair of subelement classes--use and production volume. The first is derived from the definitions of intended use devised for the select universe, and the second from the TSCA Inventory or other automated sources. We assume that, on the average, a higher fraction of food-chemical and drug production than of cosmetic, general TSCA chemical, or other (as yet undefined) chemical production eventually results in human exposure. New classes would need to be examined to test this assumption. Prime candidates for new classes are general environmental chemicals in air and water (including degradation products and "natural" pollutants) and food constituents and their products. If one accepts the exposure assumption, then the production volume required for a high probability of exposure should be lower for food chemicals and drugs than for chemicals in the other use classes. Table 3 lists an illustrative exposure classification, in which there is a decreasing probability that exposure is high; where the probabilities are identical, the list is in decreasing order of confidence in the estimates. The ability of the classifications to identify high-exposure chemicals cannot be determined without estimating the numbers of chemicals in the universe of concern that fit these classifications. Table 4 is a hypothetical classification and would need to be revised as data and experience accumulate. 240

TABLE 3 Illustrative Stage 1 Estimates of Probability of Exposure in Relation to Use and Production Probability That Exposure Is: UseaProduction, lb/yr Low Medium High F,D>104 0.40 0.40 0.20 P,C>105 0.40 0.40 0.20 G,O> 108 0.40 0.40 0.20 U> 106 0.40 0.40 0~20 G,O1o6_1o8 0.50 0.35 0.15 P,C104-105 0.50 0.35 0.15 U1o4_1o6 0.68 0.20 0.12 F,DU 0.68 0.20 0.12 F,D,U<104 0.73 0.18 0.09 P,C,G,O,UU 0.73 0.18 0.09 P,C< 104 0.75 0.17 0.08 G,O104-106 0.75 0.17 0.08 G,O<104 0.76 0.17 0.07 a F = food chemical. D = drug. P = pesticide. C = cosmetic. = general commerce (TSCA). Other (known, not previously classified). unclassified. 241

1 TABLE 4 Illustrative Estimates of Distr ibution of Production Volumes in Relation to Use Categories Frac tion Fr action by Production Volume, lb/yr of All Chem Use Class icals > 108 1o6 _ 1o8 105 _ 1o6 104 - 105 <104 ua b -- 0.001 0.003 Food 0. 12 Drug 0.10 Pesticide 0.05 Cosmetic 0.05 0.003 0.003 0.11 c 0.001 0.009 0.020 0.03 0.06 0.001 0.002 c 0.001 0.004 0.015 0.025 0.055 0.004 0.093 0.001 0.002 0.002 0.045 c 0.0002 0.006 0.005 0.013 0.026 b -- 0.001 0.001 c 0.001 0.002 0.003 __ 0.002 0.002 0~044 0.014 0.03 __ General 0.066 0.02 0.06 0.06 0.09 0.28 0.3 Other 0.01d 0 o o Unknown 0.01d 0 o o o o a In inventory, but without stated production volume. b Estimated distribution of production volumes listed in CIS. c Estimated distribution of production volumes if all were known. d At present--these categories will grow. 242 0 0.01 0 0.01

TOXICITY DATA ELEMENTS Two surrogates of toxicity, RTECS status and chemical class, are used in Stage 1. Each is used to estimate the likelihood that a substance may have toxic effects. These surrogates indicate that the likelihood that a given chemical or class of chemicals will have health effects is different from the likelihood that any substance in the universe of chemicals will have those health effects. Given the present state of knowledge, it is only slightly possible to assess the potential for an adverse response on the basis of chemical structure. But it would be desirable to use knowledge of structure-activity relationships (SARs) to identify potentially toxic substances by analyzing substructures that have been associated with adverse effects in humans or animals. Such an assessment is ordinarily based on expert knowledge, experience, and intuition and is used in considering the type of testing that may be required. A number of systems have been created to place SAR analysis on a more formal footing. They range from simple classifications of key types of substances to sophisticated statistical treatments that involve weighting of subgroups and from detailed treatments of specific health effects to general considerations of toxicity. These approaches have merit as research efforts, but none has evolved enough to provide a practical or accurate method for identifying potentially toxic chemicals. A more detailed review of the possible contribution of SAR analysis is given in Appendix D. To be usable in Stage 1, any data base used for SAR analysis must contain a large proportion of the universe of chemicals being considered. The data must also be susceptible to a search for chemical subgroups that can be associated with specific types of toxicity. The SANSS data base may provide a potentially useful data base. It can be searched for any of 271 functional groups containing at least two nonhydrogen atoms, any of 137 specific cyclic nuclei, and a number of hydrocarbon radicals. Each structural group or feature is described by a code that can be modified to allow for other structural features, such as the attachment of phenyl nuclei and aromaticity in ring structures. At the simplest level, the system provides a machine-readable way of identifying all the compounds in the system's collections that contain a specified structural group. The system may also be programed to identify structures with specified subgroups; thus, the code for phenols can be modified to produce separately monocyclic, dicyclic, and tricyclic phenols. And the system allows identification of compounds that have more than one specified functional group; this permits the identification, in lists of compounds that contain a given structure, of substances in which that structure is accompanied by another structure that might modify its biologic activity. 243

About 80 of the SANSS specific functional-group codes are associated with one or more human health effects, as shown in Table 5. The groups are assumed to produce the ascribed effect either by direct action or after metabolic activation. The table is illustrative and should not be considered comprehensive or definitive. The estimated degree of association between a given chemical structure and a specific form of toxicity is indicated in the table as low (L), medium (M), or high tH). An association between a chemical structure and an effect and the degree of that association imply that chemicals that contain the structure are more likely to cause the particular health effect in question~than are randomly selected chemicals in the universe being considered. RTECS, published by the National Institute for Occupational Safety and Health, is the most comprehensive (but not the only) summary of information on the toxicity of chemicals that is available in easily accessible, computerized form. In the 1980 edition, positive results of toxicity testing of some 45,000 chemicals are reported. In general, negative results of toxicity testing are not reported, so RTECS is biased toward toxicity. But RTECS does report negative results of lifetime bioassays for carcinogenicity by NTP (and earlier by the National Cancer Institute). Consequently, mere listing in RTECS slightly raises the probability of high or moderate toxicity at the expense of the probability of low toxicity. RTECS also reports specific positive results, such as carcinogenicity, mutagenicity, teratogenicity, reproductive effects, and a variety of acute and other chronic toxicities. Nevertheless, in practice, even listing as a carcinogen carries with it a false-positive rate, because of the imperfect correlation in cancer hazards among different species, experimental uncertainties, faulty experimental procedures, or mere error. The absence of a CAR code implies that the substance may have proved negative in a bioassay, but the false-negative rate for such an assumption is high. Similar problems beset other toxicity codes. In a fully developed priority-setting system, each toxic effect of concern would be related to at least one RTECS code. Matrices of probability for a given effect would be constructed to show how the underlying prevalence rates are modified for appearance or nonappearance of particular codes, which are retrievable by computer search. In this report, we discuss only carcinogenicity, both because time was too limited to develop other "performance characteristics" and because the theory and data base for carcinogenicity are better developed than those for other kinds of toxicity. Six codes are thought to be related to carcinogenicity: NTP POS,* NTP NEG, CAR, NEO, ETA, and MUT (MTDS in the latest RTECS). NTP POS *Many RTECS codes refer to NCI-positive or -negative results, rather than to quantitative results of tests conducted according to NTP-approved protocols. 244

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means that an NTP test with an approved protocol has been conducted and that results were positive in at least one species, whereas NTP NEG means that the test results were negative in at least one species. If both NTP POS and NTP NEG are listed, we assume equivalence to CAR, which means that acceptable, but not necessarily NTP-approved, bioassays have been assessed as positive. NEO means that a bioassay of careful design produced tumors, but not necessarily malignant ones. ETA (equivocal tumorigenic agent) means that some test was reported as positive for carcinogenesis, but failed to meet RTECS criteria for CAR or NEO. MUT means that a substance was found mutagenic in at least one of several recognized assays. It is generally assumed that mutagenesis is a better-than-random predictor of human carcinogenesis. The order in which these findings suggest carcinogenic potential is shown in Table 6. For our study, we chose to consider NTP POS and CAR together, to consider MUT and NEO together, and to ignore ETA and NTP NEG. The estimated probabilities for the four remaining combinations are summarized in Table 7, which also shows the committee's arbitrary estimates of the proportions of chemicals in the universe with various carcinogenic potencies: 95% low, 4% medium, and 1% high. The estimated probabilities are based on reported false-positive and false-negative rates for the correlation between mutagenesis and animal carcinogenesis and on the committee's subjective assessments of animal-to-human extrapolation and of the certainty of RTECS criteria. Only about 10% of the TSCA (Hgeneral") chemicals appear in RTECS; we have assumed that chemicals in other categories appear more often (Table 8~. The 23% (100% - 77%) assumes that over half the food additives, drugs, cosmetics, and pesticides have had some reported toxicity information, even if only LDsos, reported to RTECS. (Note that, if substance showed both MUT and CAR, it would be assigned to CAR.) Use of the RTECS data element is simple. The list of chemicals constituting the inventory is compared with the RTECS data base, using CAS registry numbers as the matching field. The RTECS text is scanned for the chosen terms; for the present illustration, only NTP POS, CAR, MUT, and NEO would be sought. Depending on the results of this test, the chemical class, and the exposure data elements, a substance in question is either removed from current consideration or passed to Stage 2 with a recommendation for a specific minidossier on toxicity and exposure. The rules for the choice are summarized below. SELECTION RULES If a computer is to assist in making the decision regarding which of the substances screened in Stage 1 to pass on to Stage 2--and to which level of Stage 2--the criteria for the decision must be expressed as an algorithm selection rule that can be implemented by a computer. That is, 255

TABLE 6 Significance of Ranking of RTECS Codes for Carcinogenic Potential Code or Category NTP POS CAR MUT (MTDS) NEO ETA In RTECS, with no cancer code Not in RTECS NTP NEG 256 Meaning High probability positive Moderately high probability positive Moderate probability positive Moderate probability positive Moderately low probability positive Slight probability negative Moderate probability negative High probability negative

TABLE 7 Estimated Proportions of Chemicals with Given Carcinogenic Potency, by RTECS Code Code or Ca tegory Low Proportion with Carcinogenic Potency, 96 Medium High Chemicals in universe 95.04.0 1.0 Not in RTECS 97.42.3 0.3 In RTECS, with no cancer code 97.02.0 1.0 MUT (MTDS) or NEO 48. 040.3 11.7 CAR or NTP POS 55.033.0 12.0 TABLE 8 Estimated Proportions of Chemicals with RTECS Codes Related to Cancer Code or Category Not in RTECS In RTECS, with no cancer code MUT (MTDS I, not CAR CAR Proportion of Chemicals in Universe, 96 77 18 257

the computer must be given precise criteria for causing a chemical to be removed from consideration, considered later, or moved forward. The committee has shown how such rules can be developed from a mathematical model of the system and has made more subjective evaluations of the meanings of the various data elements. The rules are presented in Appendix B in the form of a hierarchic directory that is similar to a taxonomic field guide. By selecting an answer to a question on exposure, the reader (or, in Stage 1, the computer) is directed to a page on which other questions and their possible answers appear. When all Stage 1 questions have been answered, a decision may be made regarding the next step: do nothing (place the chemical on a list of chemicals to be considered later); go to Stage 2 and prepare some combination of high- or low-exposure and high- or low-toxicity minidossiers; or go to Stage 3 or 4 immediately. The model in Appendix B shows all chemicals as advancing to some level of Stage 2. However, a large class (Branch 1) is shown to require an inexpensive exposure minidossier and no toxicity information or testing whatsoever. The model predicts that a small amount of additional information would be useful in reducing the probability of misclassification of such chemicals by category of exposure. However, such information might be virtually meaningless to the NTP testing program; in effect, chemicals classified as low exposure and low toxicity would be on a dormant list, as far as NTP were concerned. STAGE 2 Data used in Stage 2 will include the data gathered in Stage 1, data submitted with nominations, or additional data that may be easily located in handbooks or machine-readable data bases. Two levels of possible data-gathering effort are envisaged for both toxicity and exposure. mese data are compiled into a dossier for toxicity and a dossier for exposure. Toxicity and exposure are estimated separately. EXPOSURE DATA ELEMENTS The data gathered in Stage 1 consist of: Annual production volume, if known. Use class. Reported types of toxicity, if any. Types of toxicity suspected from structure. Exposure and toxicity distributions. Recommended Stage 2 dossier budget. 258

me budget may or may not be split between exposure and toxicity. In any case, the exposure assessor for Stage 2 must decide the most cost-effective way to apply the budget on the basis of the fragmentary input data. The types of toxic effects of concern with regard to a chemical will have some influence on the development of the exposure dossier. If the effect is likely to have a very low threshold or no threshold, as might be assumed for carcinogens, then both low exposures of large numbers of people and high exposures of smaller numbers of people may be of interest. If a high threshold is likely, as with some of the reversible effects that are clinically significant only when severe (methemoglobinemia, perhaps), then only high exposures are important. Furthermore, if the effect is likely to be related principally to one route of exposure (for example, inhalation in the case of lung cancer), then a corresponding exposure data set can be emphasized. An initial check of regulatory and testing status should be made for every chemical. If a chemical is already being tested because of suspected toxicity, there is little benefit in gathering further information at this point. If production volume is reported as unknown, some attempt should be made to estimate it from such data bases as the Chemical Information System or SRI International's Directory of Chemical Producers. These sources may also supply information on uses, numbers of producers, and so on. If production volume is high, it may be important to estimate it more accurately, because for TSCA chemicals it may have a range of a factor of 100. Intended use is the principal determinant of the exposure search strategy. The broad Stage 1 use class should be both refined and augmented. For example, the type of pest (insect, fungus, nematode, weed, rodent, etc.) should be identified as a minimal refinement for pesticides. And such standard sources as the Kirk-Othmer Encyclopedia of Chemical Technology (1978) or the Merck Index (1976) should be consulted. These sources are far from complete or current, but they can aid further investigation. The finding that uses extend beyond the "intended" use defined by the Committee on Sampling Strategies data base will be the rule, rather than the exception, for chemicals of continuing interest. After further details as to use have been established, the dossier strategy may become fairly obvious. Each use class tends to have its own "standard" reference works or data base; Table 9 lists a few of these. Furthermore, some pieces of data become more or less relevant, depending on the use of the chemical. Table 10 indicates the relative importance of various kinds of data for the use class in question; an exposure assessor should find it easy to make the choices in a specific case. Budget constraints might imply that even a highly rated piece of 259

TABLE 9 Selected Sources of Exposure Information by Use Class Food Chemicals - Carroll, M. D. 1983. Dietary Intake Source Data: United States, 1976-80. Hyattsville, Md.: U.S. Department of Health and Human Services, National Center for Health Statistics. 486 pp. (DHHS Publ. No. (PHS) 83-1681; Vital and Health Statistics Series 11, No. 231. Federation of American Societies for Experimental Biology. 1980. Reviews of GRAS Substances for Food and Drug Administration. For a list see FASEB, "Evaluation of GRAS Monographs (Scientific Literature Reviews)." (Available from NTIS, Springfield, Va., as PB-80-203789.) Furia, T. E., Ed. 1973 (v. 1), 1980 (v. 2~. Handbook of Food Additives, 2nd ed. Boca Raton, Fla.: CRC Press. [1,430 pp.] Furia, T. E., and N. Bellanca, Eds. 1975. Fenaroli's Handbook of Flavor Ingredients. Boca Raton, Fla.: CRC Press. 1,504 pp. National Academy of Sciences/National Research Council. 1965. Chemicals Used in Food Processing. Washington, D.C.: National Academy of Sciences. 294 pp. (NAS Publication 1274) U. S . Food and Drug Administration, Bureau of Foods. 1982. Toxicological Principles for the Safety Assessment of Direct Food Additives and Color Additives Used in Food. [245 pp.] Drugs Gilman, A. G., L. S. Goodman, and A. Gilman, Eds. 1980. Goodman and Gilman's me Pharmacologic Basis of Therapeutics, 6th ed. New York: Macmillan. 1,843 ppe IMS America, Rockville, Md. Computer data bases: U.S. Drugstore, U.S. HOspital, and National Prescription Audit. Opdyke, D. L. J. 1979. Monographs on Fragrance Raw Materials. Oxford: Pergamon Press. 732 pp. Physicians' Desk Reference, 36th ed. 1982. Oradell, N.J.: Medical Economics. 3,060 pp. [updated annually] 260

TABLE 9 (continued) Cosmetics Estrin' N. F., Pe A. Crosley, and Ce R. Haynes, Edse 1982. CTFA Cosmetic Ingredient Dictionary, 3rd ed e Washington, D aCe ~ The Cosmetic, Toiletry and Fragrance Association, Inc. 610 pp e U.S. Food and Drug Administration, Division of Cosmetics Technology, Washington, D eC ~ Frequency of the Use List gives nonquantitative information on presence of substances in cosmetics. Pesticides Gosselin, R. E., H. C. Hodge, R. P. Smith, and M. N. Gleason. 1976. Clinical Toxicology of Commercial Products, 4th ed. Baltimore: Williams & Wilkins. [1,791 pp.] Johnson, R. D., D. D. Manske, D. H. New, and D. S. Podrebarac. 1981. Pesticide, heavy metal, and other chemical residues in infant and toddler total diet samples (II): August 1975-July 1976. Pestic. Monit. J. 15:39-50. Johnson, R. D., D. D. Manske, and D. S. Podrebarac. 1981. Pesticide, metal, and other chemical residues in adult total diet samples {XII): August 1975-July 1976. Pestic. Monit. J. 15:54-69. Miller, S. A. 1982. Compliance Program Report of Findings: PY 79 Total Diet Studies--Adult. Washington, D.C.: U.S. Food and Drug Administration, Bureau of Foods. 48 pp. (Available from NTIS, Springfield, Va., as PB83-112722.) Commercial Chemicals Kirk-Othmer Encyclopedia of Chemical Technology, 3rd ed. (25 volumes projected) New York: John Wiley & Sons, v. 1, 1978 - . Lawler, G. M., Ed. 1977. Chemical Origins and Markets, 5th ed. Menlo Park, Calif.: SRI International. 118 pp. Sax, N. I. 1979. Dangerous Properties of Industrial Materials, 5th Ed. New York: Van Nostrand Reinhold. 1,118 pp. SRI International. Chemical Economics Handbook Program. SRI International, Menlo Park, Calif. [a continuously updated program] Synthetic Organic Chemicals: United States Production and Sales, 1980. 1981. Washington, D.C.: U.S. International Trade Commission. (USITC Publication 1183 [annual]) 261

TABLE 9 (continued) Consumer Products Gosselin, R. E., H. C. Hodge, R. P. Smith, and M. N. Gleason. 1976. Clinical Toxicology of Commercial Products, 4th ed. Baltimore: Williams & Wilkins. [1,791 pp.] Environmental Pollutants Anderson, D. Emission Factors for Trace Substances. 1973. Research Triangle Park, N.C.: U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards. 80 pp. (Report no. EPA-450/2-73-001) (Available from NTIS, Springfield, Va., as PB-230894.) Leo, A., C. Hansch, and D. Elkins. 1971. Partition coefficients and their uses. Chem. Rev. 71:525-616. STORET Water Quality Data Base. Produced by U.S. Environmental Protection Agency, Office of Water Regulations and Standards, Washington, D.C. Available through Freedom of Information Act request or through NTIS, Springfield, Va. Verschueren, K. 1977. Handbook of Environmental Data on Organic Chemicals. New York: Van Nostrand Reinhold. Occupational Exposures Clayton, G. D., and F. E. Clayton, Eds. 1978-1982. Patty's Industrial Hygiene and Toxicology, 3rd rev. ed. 3 vols. New York: Wiley. [5,864 pp.] Documentation of the Threshold Limit Values, 4th ed. 1980. Cincinnati, Ohio: American Conference of Governmental Industrial Hygienists, Inc. [various paging] (supplements issued each year) U.S. Department of Health, Education, and Welfare. 1974. National Occupational Hazard Survey, Vol. 1: Survey Manual. NIOSH Publ. No. 74-127. Public Health Service, Center for Disease Control, National Institute for Occupational Safety and Health, Cincinnati, Ohio. 202 PP U.S. Department of Health, Education, and Welfare. 1977. National Occupational Hazard Survey, Vol. 2: Data Editing and Data Base Development. NIOSH Publ. No. 77-213. Public Health Service, Center for Disease Control, National Institute for Occupational Safety and Health, Cincinnati, Ohio. 154 pp. 262

TABLE 9 (Gontinued) U.S. Department of Health, Education, and Welfare. 1978. National Occupational Hazard Survey, Vol. 3: Survey Analysis and Supplemental Tables. NIOSH Publ. No. 78-114. Public Health Service, Center for Disease Control, National Institute for Occupational Safety and Health, Cincinnati, Ohio. 799 pp. Solvents Scheflan, L., and M. B. Jacobs. Van Nostrand. General 1983. Handbook of Solvents. New York: IARC Monographs on the Evaluation of the Carcinogenic Risk of Chemicals to Humans. Lyon: International Agency for Research on Cancer, v. 17, 1978 - . (Continues IARC Monographs on the Evaluation of the Carcinogenic Risk of Chemicals to Man, v. 1, 1972 - v. 16, 1978. Minerals Yearbook 1981. 1982. Washington, D.C.: U.S. Department of the Interior, Bureau of Mines. (revised annually) SOCMA Handbook: Commercial Organic Chemical Names. D.C.: American Chemical Society. 1966. Washington, Toxicology Data Bank (TDB). Computer data base available from National Library of Medicine, Specialized Information Services, Toxicology Information Program, Bethesda, Md. Windholz, M., S. Budavari, L. Y. Stroumtsos, and M. N. Fertig, Eds. 1976. me Merck Index. An Encyclopedia of Chemicals and Drugs, 9th ed. Rahway, N.J.: Merck & Co. 1,313 pp. 263

TABLE 10 Data Needs for Use Classesa Data u' v o o u, u, .H us o v to .~ v . - vet en o a o in v .5 .~ u, H in o Pi o ·~ W o o o U2 .~ U] o V Production volume Production locations Fraction used as intermediate Detailed uses Volume by use Measured concentrations Molecular weight Structural diagram Solubility in water Partition coefficient Melting point Boiling point Vapor presure Reactivity National Occupational Hazard Survey Regulatory status 2 1 2 2 2 2 2 2 2 l 2 3 2 2 3 3 2 2 2 1 1 2 1 1 1 1 1 1 1 1 1 1 1 3 1 1 2 2 2 2 3 2 3 2 2 2 1 1 2 1 1 2 2 2 2 3 2 2 2 3 2 2 2 2 2 2 2 3 3 2 2 3 3 2 2 2 2 1 1 1 2 3 2 2 _ 2 3 3 a 3 = highly desirable; 2 = desirable; 1 = useful; -- = irrelevant. 264

information may never be found--or even sought. Nevertheless, the assessor should record whether the search was made and, if so, what was found; and extra, easily available data should be retained in the dossier if little extra expense is involved. Once the dossier is assembled--by the assessor or by an information- retrieval specialist--the assessor should review its contents (usually between 1 and 10 pages). The assessor should then mentally integrate the information and make a judgment about degree of exposure, using toxicologic relevance for the effects of concern, as well as a mental model of the substance's progress from production to eventual human exposure. - When the material has been assimilated, the assessor is asked to make two judgments: degree of concern about exposure and degree of confidence in or reliability of that judgment. The checklist in Figure 7 could be used to record those judgments. The assessor could record an explicit probability distribution if he or she does not choose to use the "standard" distribution corresponding to the choice of concern and confidence made earlier. The distribution of degrees of exposure estimated by the committee is shown for comparison; the assessor should make his or her own estimates. If the assessor has not entered an explicit distribution, the codes for concern and confidence will be entered into the information system, and a corresponding exposure distribution will be generated. Hypothetical distributions (L-M-H) are shown in Table 11. if the estimated concern about exposure is low and confidence in the estimate is low, then the probability distribution is 75-17-8--where 75 is the probability (in percent) that the true exposure is low, 17 the probability that it is medium, and 8 the probability that it is high; and so on. TABLE 11 Hypothetical Estimates of Probability Distributions of Degree of Exposure Generated in Stage 2 in Relation to Estimated Degrees of Concern and Confidence Estimated Degree of Exposurea Low Medium High aSee text for explanation. Degree of Confidence in Estimate (Estimated Probability Distribution of True Exposure), % Low Medium 75-17-8 50-35-15 30-40-30 265 80-15-5 45-40-15 25-40-35 High 85-12-3 40-45-15 20-40-40

Stage-2 Exposure Assessment CAS or other identifier Substance name Decree of Concern (Circle one) L - No evidence of special features suggesting significant exposure M - Evidence suggesting that exposures may be greater than for typical substances H - Evidence suggests that exposures may be significantly greater than for typical substances Explanation: (point out reason for considering exposure to be medium or high) Degree of Confidence (Circle one) L - Evidence spotty and uncertain; poor understanding of exposure process M - Evidence moderately available, but still often missing, uncertain, or difficult to interpres H - Evidence missing only for a few of the less important kinds of information; implications of information generally clear; quantitative exposure estimates may be possible Explanation: explain reason for medium or high confidence Probability Distribution Indicate on the histogram below (for comparison with the "standard" distribution) your estimates of the probability that exposure to the chemical is low, medium, or high. 1.0 · ~ e e ~e 7 5 ~e~ e ee e ~ ~ ~ e ~ 2 · · ~· · · ~· · · L ~H FIGURE 7 Sample checklist for Stage 2 exposure assessment, to be filled out by assessor reviewing dossier. 266

The estimates of degree of exposure and of confidence in those estimates have similar implications, whether they are made using a dossier resulting from a minimal or a moderate effort to search for data. However, the number of estimates scored as deserving low confidence should be lower for the dossier resulting from the moderate data search, and the number of estimates deserving high confidence should be higher, as indicated in Table 12. TABLE 12 Hypothetical Percentages of Chemicals as Estimated by Assessor to Have Given Degrees of Concern and Confidence in Estimate Degree of Effort to Concern Degree of Search about Exposure, % Confidence, % for Data Low Med. High Low Med. High Minimal 50 35 15 80 15 5 Moderate 50 35 15 65 25 10 m e distribution of degrees of confidence reflects the presumed enrichment between Stages 1 and 2, at least from the perspective of the assessor. TOXICITY DATA ELEMENTS Toxicity data elements are analogous to exposure data elements, except for the content of the information. The Stage 1 information is reviewed for relevance to Stage 2 data-gathering decisions. The Stage 1 exposure inputs influence the choice of toxicity information to seek: use in food implies that toxicity through oral exposure would be most relevant; industrial use implies more concern for inhalation and for higher exposures of fewer people (that makes effects with thresholds more significant than they might otherwise be); and cosmetic use implies repeated dermal exposure. As with exposure, the toxicity output of Stage 1 will suggest the effects of greatest interest, but again--as with uses--additional effects should be recorded as they are discovered. All easily accessible data bases should be searched for reported toxicity-test results, whether positive or negative: RTECS, Chemical Information System (CIS), Toxicology Data Bank (TDB), Environmental Mutagen Information Center (EPIC), Environmental Teratogen Information Center (ETIC), and so on. Major compendia should also be consulted, such as those in Tables 9 and 13. Chemical structure should be reviewed to see whether 267

TABLE 13 Selected Sources of Toxicity Information by Effect Mutagenicity Environmental Mutagen Information Center (EMI-C). Computer data base available from EMIC, Oak Ridge National Laboratory, Tenn., and as subtile of TOXLINE. Carcinogenicity Survey of Compounds Which Have Been Tested for Carcinogenic Activity 2nu ed. 1951. Bethesda, Md.: U.S. National Cancer Institute. (Public Health Service Publication No. 149) (Additional volumes cover later literature: Supplement 1; Supplement 2; 1961-67 volume, sections I and II; 1968-69 volume; 1970-71 volume; 1972-73 volume; 1978 volume) IARC Monographs on the Evaluation of Carcinogenic Risk of Chemicals to Humans. 1978-present. Lyon: International Agency for Research on Cancer. v. 17. (Continues IARC Monographs on the Evaluation of Carcinogenic Risk of Chemicals to Man, v. 1, 1972- v. 16, 1978.) Teratogenicity Shepard, T. H. 1980. Catalog of Teratogenic Agents, 3rd ed. Baltimore: Johns Hopkins University Press. Environmental Teratogen Information Center {ETIC). Computer data base available from ETIC, Research Triangle Park, N.C., and as a subtile of TOXLINE. Neurotoxic itY Spencer, P. S., and H. H. Schaumburg, Eds. 1980. Experimental and Clinical Neurotoxicology. Baltimore: Williams & Wilkins. Skin effects Maibach, H. I., and G. A. Gellin, Eds. 1982. Occupational and Industrial Dermatology. Chicago: Year Book Medical Publishers, Tnc. Marzolli, F. N., and H. I. Maibach, Eds. 1983. Dermatotoxicology, 2nd ed Washington, D.C.: Hemisphere Publishing Corp. 268

Eve effects Grant, W. M. 1974. Toxicology of the Eye, 2nd ed. Springfield, Ill.: Charles C Thomas. Liver effects Zimmerman, H. J. 1978. Hepatotoxicity: The Adverse Effects of Drugs and other Chemicals on the Liver. New York: Appleton-Century- Crofts. Other effects Documentation of the Threshold Limit Values, 4th ed. 1980. Cincinnati, Ohio: American Conference of Governmental Industrial Hygienists, Inc. (Supplements issued each year) Registry of Toxic Effects of Chemical Substances, 1980 edition. 1982. Cincinnati, Ohio: U.S. National Institute for Occupational Safety and Health. (More recent updates available as microfiche from NIOSH or as computer data base from National Library of Medicine, Bethesda, Md., or from Chemical Information Systems, Inc., Baltimore, Md.) 269

predicted Stage 1 effects still appear consistent with structure and whether any other possibilities are suggested. If the budget for the toxicity dossier permits, a beginning search of bibliographic information, such as the number of entries in TOXLINE, may be conducted. Table 13 shows some standard sources by category of effect. The search for toxicity data and preparation of the toxicity dossier may require more effort than the corresponding work for exposure, but the toxicity dossier may well include little information other than that pertaining to chemical structure. It is reviewed by the toxicity assessor, and a record almost identical with Figure 7 is completed (except that the word "toxicity" is substituted for "exposure" everywhere). A separate record is completed for each major human health effect of continuing concern. For each health effect, the appropriate table of estimated probability distributions should be consulted. The hypothetical distributions for carcinogenicity shown in Table 14 are consistent with the assumption that 90% of the chemicals considered in Stage 2 are noncarcinogens, 7% are weak carcinogens, and 3% are strong carcinogens. Finally, the distribution of chemicals by degrees of concern and confidence, as assigned by the assessor in Stage 2 for toxicity (carcinogenicity), might look as follows: Effort Degree of Degree of to Search Concern, ~Confidence, ~ for Data Low Med. High Low Med. High Minimal 80 15 5 80 15 5 Moderate 80 15 5 70 20 10 SELECTION RULES The Stage 2 rules (Appendix B) specify what action is to be taken in Stage 3 on the basis of the degrees of concern about exposure and toxicity estimated in Stage 2. Depending on the relative values for exposure and toxicity, the Stage 2 rules specify either that a dossier should be prepared in Stage 3 or that it should not be (i.e., consideration of the chemical should be deferred). More detailed rules could be developed to cover degree. of confidence, as well as degree of concern, but these are not illustrated in Appendix B. STAGE 3 . me input to Stage 3 from Stage 2 will consist of the following: · Stage 2 exposure dossier! if written. · Stage 2 toxicity dossier, if written. 270

· Distributions for high, medium, and low exposure and toxicity {by effect) derived from the subjective judgments of the Stage 2 assessors. · Recommendations regarding need for a Stage 3 exposure dossier, toxicity dossier, or both. · Agency nomination of substances for specific tests, with supporting documentation that may exceed the information content of the best Stage 2 dossier. TABLE 14 Hypothetical Estimates of Probability Distributions of Carcinogenic Potency as Generated in Stage 2, in Relation to Assigned Degree of Concern about Carcinogenicity and Degree of Confidence in Assignment Degree of Concern about Carcino- genicity Degree of Confidence in Estimate (Estimated Probability Distribution of True Potency), ~ Low Medium High Low 95- 3- 2 96-3- 1 97-2- 1 Medium 80-15- 5 65-30- 5 50-45- 5 High 50-35-15 40-40-20 30-40-30 For illustrative purposes, the Committee on Priority Mechanisms has assumed that the standard budget for preparation and review of Stage 3 dossiers would be $1,000 for exposure and $1,000 for toxicity. We also assumed that the Stage 3 dossier managers would adjust budgets for specific substances according to the perceived availability of and need for information; thus, some dossiers would require only a few hundred dollars, whereas others might require twice the standard budget. And we assumed that dossiers will automatically be prepared for both toxicity and exposure for all agency-nominated substance, but that the supporting documentation might supply much of the needed information. 271

EXPOSURE DATA ELEMENTS The procedure for processing exposure information in Stage 3 is nearly identical with that in Stage 2. First, the dossier manager determines what types of information need to be sought for what types of substances. (The bases for selection of the information to be sought include use, structure, effects of concern, physical and chemical properties, and other information in the Stage 2 dossier.) A list of possible information categories appears in Table 9. Next, the dossier information is sought and assembled under the direction of the manager. The dossiers then go in batches of, say, 20-50 to an expert committee* for review. (The committee would presumably assign primary reviewers for each substance, but it should be encouraged to form its own procedural rules.) The committee attempts to reach a consensus regarding the degree of concern and confidence about exposure, as in Stage 2. Difficulty in reaching a consents about degree of concern is a good reason to assign a low - degree of confidence. Elowever, we assume that the criteria for high and medium confidence will be more stringent than those for the same (Again, if the committee felt comfortable about doing so, probability distribution for exposure directly.) The decision should documented on forms similar to those shown for Stage 2 in Figure 3, but with more room for explanations. terms in Stage 2. it might generate a - be If the committee does not generate an explicit probability distribution for exposure, one can be selected from Table 15, using the degrees of concern and confidence shown. TABLE 15 Hypothetical Estimates of Probability Distributions of Degree of Exposure Generated in Stage 3, in Relation to Assigned Degree of Confidence in Assignment Degree of Exposure Low Medium High Degree of Confidence in Estimate (Estimated Probability Distribution of True Exposure), % Low Medium High 80-15-5 45-40-15 20-40-35 85-12-3 40-50-10 15-40-45 90-9-1 35-60-5 10-35-55 *Separate exposure and toxicity co~runittees may be useful, but a single committee could serve if instructed to keep the assessments separate. 272

It is difficult to predict the distribution of ratings generated by the Stage 3 process, because of uncertainties as to how the committee will assess the dossiers. Hypothetical initial assumptions of the distribution of the assignments are as follows: Degree of Concern, ~ Degree of Confidence, % Low Medium High Low Medium High Stage 3 exposure dossier 25 50 25 50 30 20 TOXICITY DATA ELEMENTS As in Stage 2, the toxicity dossier should be oriented toward the effects suggested as being of greatest concern, but should present any other information on observed or suspected effects that turns up in the course of the search. As with exposure, the Stage 3 toxicity dossier strategy should be designed to yield the information of most use to the expert committee that will be reviewing the dossiers. Information on obscure details of biochemistry and on effects whose clinical significance has not been interpreted probably is not useful. However, it is possible in Stage 3 to include information that would be difficult to process in earlier stages, such as known or suspected synergism with other chemicals; in such cases, it may prove useful to search for information on joint exposures to the chemical of concern and those with which it acts synergistically. The expert committee on toxicity will assess the dossiers and make judgments about degree of concern and degree of confidence for each effect of interest. Although such judgments will normally be limited to the effects nominated by agencies or indicated on Stage 2 dossiers, any other effect of serious concern that becomes evident may also be assessed. If the committee does not generate an explicit probability distribution for toxicity, one can be selected from Table 16, in which an illustrative set of distributions for carcinogenic potency is presented. 273

TABLE 16 Hypothetical Estimates of Probability Distributions of Carcinogenic Potency as Generated in Stage 3, in Relation to Assigned Degree of Concern about Carcinogenicity and Degree of Confidence in Assignment Degree of Toxicity Low Medium High Degree of Confidence in Estimate (Estimated Probability Distribution of True Toxicity), % Low Medium High 96-3-1 97-2-1 98-1 1 75-21-4 57-40-3 40-57-3 40-40-20 30-40-30 25-35-40 m e corresponding distribution of judgments by the expert committee might be as follows: Degree of Degree of Concern,% Confidence, ~ Low Med. High Low Med. High Stage 3 toxicity dossier 60 30 10 60 25 15 These distributions are consistent with an assumpton that 81% of the chemicals moving from Stage 2 to Stage 3 are noncarcinogens, 15% are weak carcinogens, and 4% are strong carcinogens. Note that the expert committee is not asked to make any judgment about the value of proposed tests. We propose that systematic and largely predetermined rules be used to determine the value of a mutagenicity assay or a lifetime bioassay in clarifying the concern about carcinogenicity for a specific chemical that has already been assessed by an expert committee. The recommendations for testing would then be reviewed by the board of scientific counselors, or a similar body, to ensure that they are reasonable, given the status of existing information and the detailed properties of the substance in question. Unfortunately, this whole approach to testing decisions is not as well suited to evaluating reconnaissance testing (e.g., 90-d feeding studies), in which an effect of concern may be specified only generally, if at all. The performance characteristics for such tests would have to be either created from the aggregate of several effects that tests could detect or defined for a generalized toxicity measure, which would be sought only because exposure is fairly high and fairly certain. 274

SELECTION RULES As in Stage 2, the Stage 3 rules (Appendix B) operate on the finding of high, medium, or low toxicity and high, medium, or low exposure; later, they should be revised to consider degree of confidence. The choices for Stage 4 are a short-term test, a long-term cancer bioassay, and no action. STAGE 4 Because the objective of priority-setting must be the minimization of misclassification of the potential public-health concern about chemicals, the system cannot be complete without an analysis of the predictive power of the tests to which it leads. We discuss here some problems related to the selection of toxicity tests and the relations between operating characteristics of tests and selection of chemicals for toxicity testing. At this stage of the priority-setting process, the goal is to select, for the chemicals to be evaluated, tests that provide the most useful toxicity information for the resources invested. Because testing resources are limited, selection of an optimal test or combination of tests involves a tradeoff between the total number of chemicals evaluated and the completeness with which any one chemical can be characterized. To illustrate how this tradeoff can be made, we constructed a mathematical model for the allocation of resources for one kind of toxicity, carcinogenicity (Appendix B). This choice was made both because methods for carcinogenicity testing are better than methods for most other toxicity testing and because carcinogenicity testing consumes a larger fraction of NTP resources than does testing for any other toxic effect. Tests of other effects, like tests to assess carcinogenicity, entail consideration of both cost and accuracy of testing. These tests range in cost from a few hundred dollars for some short-term tests with bacteria to more than a half-million dollars for a standard long-term bioassay in rats and mice (Table 17~. The cost of a given test may vary among laboratories, depending on the substance being tested, the conditions of testing, institutional overhead expenses, and other factors (Lave et al., 1982). Tests vary in predictive accuracy. None is considered accurate enough to predict with complete reliability the carcinogenicity of a substance for humans; that can be established only by epidemiologic evidence of carcinogenic effects in humans. Nevertheless, the demonstration that a substance is carcinogenic in appropriately conducted animal tests is generally considered an adequate basis for classifying it a presumptive human carcinogen (IRLG, 1979; U.S. Congress, 1981; IARC, 1982~. Interpretation of animal tests is uncertain, however, and requires expert judgment. Extrapolation from animal test results to quantitative estimation of human risks entails large uncertainties in 275

TABLE 17 Estimates of Costs of Some Carcinogenicity Testsa . Testsb TO e of Test - P Bacterial cell: Estimated Average Cost, No. $ Responses _ 1-4,6-13 Salmonella his-1,200 10 19 Escherichia cold WP2400 2 21 Bacillus subtilis rec-800 1 22-24 Escherichia cold rec-1,500 1 29 Degranulation 2,500 1 37 Yeast cell: Saccharomyces D7 · ~ cereals 1ae Mammalian cell: 1,400 1 40-42 Unscheduled DNA synthesis-- 5,200 3 human fibroblasts, HeLa ceils 43,45 Sister-chromatid exchange-- 3,000 1 CHO cells 44 Chromosomal aberrations-- 7,500 3 CHO cells, rat liver cells c Transformation--CHO cells 1,400 1 c Transformation--C3H-lOT 1/2 5,400 4 48 TK +/- L5178Y mouse 4,900 1 lymphoblasts 50,51 HGPRT-CHO cells, 6,500 4 V79 cells Whole Animal: 56-58 Sex-linked recessive lethal-- 10,000 1 Drosophila melanoqaster (injection) 59 Sister-chromatid exchange--mouse 3,000 1 60-62 Micronucleus--mouse 3,400 2 63 Sperm morphology--mouse 11,400 1 Whole-animal two-species rodent bioassay a Modified from Lave et al., 1982. b See Table 19 for list of tests. c Test was not conducted in International Collaborative Program (de Serres and Ashby, 1981) in either CHO or C3H cells, but in BHK-21 cells. d From Weinstein, 1983. 500,000d 1 276

connection with mechanisms of carcinogenesis and species differences in carcinogen metabolism (IRLG, 1979; Calkins et al., 1980; IARC, 1982~. The difficulties in interpreting tests for carcinogenicity have led the International Agency for Research on Cancer (1982) to publish guidelines for interpretation. Long-term bioassays in rats and mice are so expensive (Table 17) and time-consuming (requiring up to 5 yr for completion) that such tests are not feasible for more than a small percentage of the many thousands of chemicals to be tested. Faster and less expensive assays are needed. To this end, more than 100 short-term tests have been introduced (Hollstein _ al., 1979~. Emus far, however, such tests have been used only for screening purposes, and not for definitive predictions of carcinogenicity, pending further standardization and validation of their accuracy. The need for standardization of such tests is indicated by the variability in results of the most widely used short-term screening test--the Salmonella typhimurium/microsome plate mutagenicity assay. Table 18 shows the degree of agreement found by the International Collaborative Program, which had 12 laboratories apply the test to a series of 19 carcinogens and noncarcinogens (de Serres and Ashby, 1981~. The discrepancies are attributable at least in part to the use of differing procedures. Despite the variations, the Salmonella mutation assay yielded preponderantly positive results with chemicals known to be carcinogenic in rodents. Nevertheless, the observed correlation between mutagenicity and carcinogenicity has varied from one class of chemicals to another. For some carcinogens (e.g., asbestos and halogenated hydrocarbons, such as DDT) and for most tumor-promoting agents (such as phorbol esters and some naturally occurring hormones), the test has given negative results (Rinkus and Legator, 1979; Ames and McCann, 1981; Purchase, 1982~. For chemicals of all classes tested to date, its overall accuracy is 60-80% (see Table 19) (Ames, 1979; Purchase, 1982; Upton et al., in press). Other short-term tests have received less systematic evaluation than has the Salmonella test; only limited data are available on their comparative results (see Table 19~. One naturally successful combination of the two tests is the Salmonella test with the in vitro cell-transformation assay. Combinations of various short-term tests, in batteries or in tiers, have been observed to yield greater accuracy than any one of the tests alone (Bridges, 1976; Weisburger and Williams, 1981; Lave et al., 1982~. Six combinations of tests have been calculated to have predictive accuracies of 81.6-89.7% (Table 20) for a limited number of animal carcinogens and noncarcinogens (Table 21~. None of the combinations appears capable of avoiding a substantial percentage of false-positives and false-negatives. However, where a false-positive is observed, it may be suspected that the carcinogenicity of the chemical under consideration escaped detection because of deficiencies in the animal test used as a criterion. 277

TABLE 18 Correlation among Results of Salmonella/microsome Tests Performed by 12 Investigatorsa Investi- 1 2 3 4 6 7 8 9 10 11 12 13 1 1.00 0.81 0.53 0.47 0.47 0.34 1.00 0.62 0.81 0.47 0.34 0.22 1.00 0.65 0.62 0.62 0.53 0.81 0.81 1.00 0.65 0.53 0.15 1.00 0.65 0.65 0.34 0.53 0.53 0.65 0.42 0.34 0.19 4 1.00 0.33 0.53 0.47 0.47 0.62 0.65 0.26 0.15 6 1.00 0.53 0.47 0.47 0.62 0.35 0.26 0.03 7 1.00 0.34 0.34 0.53 0.46 0.30 0.05 8 1.00 0.62 0.81 0.47 0.34 0.22 9 1.00 0.81 0.47 0.34 0.07 10 11 12 13 a From Lave et al., 1982. 1.00 0.65 0.53 0.15 1.00 0.46 0.02 1.00 0.21 1.00 Entries are squared correlation coefficients computed from test results on 19 chemicals reported to International Collaborative Program by 12 investigators. 1.00 indicates complete agreement and O indicates no agreement between investigators. 278

TABLE 19 Predictive Accuracy of Various Short-Term Tests for Carcinogenicitya Test Accuracy of Test Resultsb Code Number Type of Test N Accuracy Bacterial Mutation Assays 1 S. typhimurium/plate 37 0.70 2 S. typhimurium/plate 37 0.68 3 S. tYphimurium/plate 36 0.59 4 S. typhimurium/plate 38 0.71 5 S. typhimurium/fluctuation 31 0.71 6 S. typhimurium/plate 38 0.63 7 S. typhimurium/plate 33 0.64 8 S. typhimurium/plate 38 0.68 9 S. typhimurium/plate 37 0.57 10 S. typhimurium/plate 37 0.65 11 S. typhimurium/plate 37 0.73 12 S. typhimurium/plate 38 0.68 13 S. typhimurium/plate 38 0.71 14 S. typhimurium/plate 28 0.57 norharman 15 S. typhimurium/ 33 0.55 f luctuation 16 S. tYphimurium/ 38 0. 66 azaguanine res 17 S. typhimurium/E. cold 36 0.67 W2/f luctuation hepatocytes 18 S. typhimurium/E. cold 36 0.78 WP2/plate 19 E. cold WP/2/plate 34 0.65 20 E. cold 343 18 0.72 Bacterial Repair, Phage Tnduction, Degranulation, and Nuclear Enlargement Assays 21 B. subtilis, M45 rec- 38 0.79 22 Ee coli, RecA/PolA 34 0.59 23 Ee coli, RecA- 37 Oe62 24 E e coli, RecA-/PolA 36 0.58 25 E. coli, Pol 36 0.58 26 X-induction (gal+) 20 0. 65 27 X-induction (lysis) 36 0.56 279

TABLE 19 (continued) Test Accuracy of Test Resultsb Code Number Type of Test _ Accuracy 28 Degranulation of RER 33 0.39 29 Degranulation of RER 30 0.67 ribonuclease post treatment 30 Nuclear enlargement, 22 0.32 He La cells 31 Nuclear enlargement, 22 0.64 human fibroblasts Yeast Assays 32 S. cerevisiae XV185-14C 30 0.70 l 33 S. pombe PI 29 0.66 34 S. cerevisiae PG 148 35 0.43 PG-154 PG-155 PG-166 35 S. cerevisiae D4 31 0.42 _ , 36 _. cerevisiae D6 37 0.65 37 S. cerevisiae D7 35 0.66 38 S. cerevisiae JD1 32 0.72 39 S. cerevisiae red 32 0.72 In Vitro Mammalian Test Systems 40 Unscheduled DNA synthesis, 18 0.39 human fibroblasts 41 Unscheduled DNA synthesis, 21 0.62 human fibroblasts 42 Unscheduled DNA synthesis, 38 0.68 human fibroblasts 43 Sister chromatic exchange, 19 0.53 CHO cells 44 Sister chromatic exchange, 18 0.67 CHO cells 45 Sister chromatic exchange, 33 O.S2 CHO cells 46 Cytogenetic analysis, 21 0.57 micronucleus test 47 Cytogenet~c analysis, 18 0.72 micronucleus test 48 Forward-mutation assay, 19 0.53 mouse lymphoma cells L518Y 280

TABLE 19 (continued) Test Code Number Accuracy of Test Resultsb Type of Test N - AccuracY 49 Gene-mutation assay, CHO 9 0.44 cells, HGPRT gene 50 Gene-mutation assay, CHO 3 0.67 cells, HGPRT gene 51 Gene-mutation assay, 5 0.60 V79 hamster cells 53 Cell transformation 34 0.59 54 Cell transformation, 38 0.82 BKH-21 cells In Vivo Assays 56 Sex-linked recessive lethal 9 0.44 Droposphila 57 Sex-linked recessive lethal 15 0.53 58 Sex-linked recessive lethal 9 0.44 59 Sister chromatic exchange, 16 0.63 mouse 60 Micronucleus assay, mouse 29 0.66 61 Micronucleus assay, mouse 17 0.47 62 Micronucleus assay, mouse 33 0.45 63 Sperm morphology, mouse 15 0.47 aFrom Lave _ al., 1982. bFigures tabulated indicate accuracy (number of chemicals correctly identified divided by number of chemicals tested) for tests 1 through 63. Data subset includes all 42 chemicals listed in Table 21 except presumptive noncarcinogens 2, 16, 20, 22, and 27, which had high frequencies of positive results in international study (de Serres and Ashby, 19817. Diphenylnitrosamine (22) was found to be carcinogenic. 281

TABLE 20 Predictive Accuracy of Several Short-Term Tier Testing Regimensa Tier Number Tests Included in Tierb No. of Chemicals on Which Results Predic tive are Based Accuracy, - typhimurium/plate (4) Differential killing, B. subtilis M45 Rec~ (21) Cell transformation, BHK-21 cells (54) S. typhimurium/plate (4) Cell transformation, BHK-21 cells (54) Forward mutation, S. Bombs (33) S . typhimur ium/plate (4) - Forward mutation, S. pombe (33) Cell transformation, BHK-21 cells (54) Unscheduled DNA synthesis, HeLa cells (42) 4 typhimurium/plate (4) Unscheduled DNA synthesis, HeLa cells (42) Cell transformation, BHK-21 cells (54) S. typhimurium/plate (4) Cell transformation, BHK-21 cells (54) Rabin's test (degranulation) rat liver cells (29) _. tyPhimurium/plate (4) Unscheduled DNA synthesis, HeLa cells {42) Cell transformation, BHK-21 cells (54) 38 29 29 38 30 38 84.2 86.2 89.7 81.6 83.3 81.6 . a From Lave et al., 1982. ~ _ _ Numbers in parentheses are code numbers of tests (Table 19~. 282

TABLE 21 Chemicals Analyzed by Short-Term Tests (International Collaborative Study~a Chemical Carcinogenicity Class if icationb 2 3 4 5 6 7 8 9 B-Propiolactone 10 Y-Butyrolactone 11 9,10-Dimethylanthracene 12 Anthracene 13 Chloroform 14 1, 1,1-Trichloroethane 15 2-Acetylaminofluorene 16 4-Acetylaminofluorene 17 Dimethylcarbamoyl chloride 18 Dimethylformamide 19 2-Naphthylamine 20 1-Naphthylamine 21 N-Nitrosomorpholine 22 Diphenyloitrosamine 23 Dinitrosopentamethylene tetramine 24 Urethane 25 Isooroovl N-(3-chloronhenYl)carbamate 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 4-Nitroquinoline-N-oxide 3-Methyl-4-nitroquinoline-N-oxide Benzidine 3,3',5,5'-Tetramethylbenzidine 4-Dimethylaminoazobenzenetbutter yellow) 4-Dimethylaminoazobenzene-4-sulfonic acid, Na salt Benzo~alpyrene Pyrene _ , _ ,, ~ , ~, _, Methylazoxymethanol acetate Azoxybenzene DL-Ethionine Methionine Hydrazine sulfate Hexamethylphosphoramide (HMPA) Ethylenethiourea Diethylstilbestrol Safrole Cyclophosphamide Epichlorhydrin 3-Aminotriazole 4,4'-Methylenebis(2-chloroaniline) (MOCA) o-Toluidine hydrochloride Auramine (technical grade) Sugar (sucrose) Ascorbic acid - + + - - + + + + + + + + + + + + + - a From de Serres and Ashby, 1981. b Based on effects in human populations or experimental animals. 283

Other approaches being emphasized in current research efforts include those for identifying nongenotoxic carcinogens, including cocarcinogens and tumor-promoting agents (Sivak, 1982; Upton, in press), and the exploitation of in viva short-term bioassays (Ashby, in press). It may be envisioned that the test systems of the future will include various assays in addition to those represented in Table 19. It may also be expected that the particular combinations of tests used and the sequences in which they are used will depend on the nature of the chemicals being tested and their patterns of use. Whether a tier regimen culminates in a long-term bioassay in rats and mice will depend on the results of the antecedent short-term tests and their apparent predictive accuracy. The principles involved in setting priorities for carcinogenicity testing apply also to the setting of priorities for testing chemicals suspected of other forms of toxicity. It must be recognized that the process of predicting the toxic potential of a chemical is extremely complex. There are no firm rules, or even guidelines, for obtaining reliable answers. Attention is generally focused on devising animal models or tests for human health effects with attributable chemical causes. Thus, in the best circumstances, it may be possible to predict the biologic activity of a given chemical, identify a useful end point with an established animal model or test, and draw some tentative conclusion regarding the chemical's likely toxicity in humans. Results of toxicity tests on animals have been recorded in RTECS, a machine-readable file of approximately 15,000 chemicals, although the universe of chemicals defined by the Committee on Sampling Strategies contains over 70,000 chemicals. Even information on well-characterized chemicals is often limited to data on molecular structure and physical characteristics. A chemical may have several effects on human health that are individually dose-dependent. To set testing priorities among different types of toxic effects, two tasks must be accomplished: a catalog of human health effects must be established, and the various effects must be ranked according to relative severity. The relative importance of different types of health effects depends on their consequences to the affected persons and to society. Ranking of effects according to severity is implicit in most priority-setting schemes. It involves not only technical judgments of toxicity, but also individual perceptions of harm. An approach to determining the relative severity of toxic effects is described in Chapter 2. When a chemical is suspected of causing more than one toxic effect, which is often the case, the combined impacts of all its potential effects must be taken into account in setting priority for its testing. Because of the multiplicity, diversity, and complexity of the health effects of different chemicals, no attempt is made here to develop a detailed or comprehensive system for this purpose. 284

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Prepared at the request of the National Toxicology Program, this landmark report reveals that many chemicals used in pesticides, cosmetics, drugs, food, and commerce have not been sufficiently tested to allow a complete determination of their potential hazards. Given the vast number of chemical substances to which humans are exposed, the authors use a model to show how research priorities for toxicity testing can be set.

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