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FUNDAMENTAL AND APPLIED TOXICOLOGY 37, 16--36 (1997) ARTICLE NO. FA972305 WORKSHOP OVERVIEW Implementation of EPA Revised Cancer Assessment Guidelines: Incorporation of Mechanistic and Pharmacokinetic Data N. P. Page,* D. V. singh,~" W. "Farland,? J. I. Goodman,~: R. B. Conolly,§ M. E. Andersen,II H. J. Clewell,I C. B. Frederick,** H. Yamasaki,tt and G. Lucier~ *ToxaChemica. International P.O. Box 10547. Gaithersburg. Ma~'land 20849: *US EPA. NCEA-DC. Washington. DC 20460: .~Michigan State Universit.'. East Lansing. Michigan 48824: §CilT. Research Triangle Park, North Carolina 27709: tlCF/Kaiser Engineers. Research Triangle Park. North Carolina 27709: llCF/Kaiser Engineers. Ruston. Louisiana 71270: **Robin & Haas Co.. Spring House. Penno.lvania 19477: **International Agency for Research on Cancer. Lyon. Cedex 08. France: +,~National Institute for Environmental Health Sciences. Research Triangle Park. North Carolina 27709 Received January 27. 1997 Implementation of EPA Revised Cancer Assessment Guidelines: Incorporation of Mechanistic and Pharmacokinetic Data. Page, N. P., Singh, D. V., Farland, W., Goodman, J. I., Conoily, R. B., Andersen, M.E., Cl~well, FL J., Frederick, C. B., Yamasaki, H., and Lucier, G. (1996). Fundam. Appl. Toxicol. 37, 16-36. A workshop entitled "Implementation of EPA Revised Cancer Assessment Guidelines: Incorporation of Mechanistic and Phar- macokinetic Data" was held in Anaheim, California, in 1996 at the 35th Annual Meeting of the Society of Toxicology (SOT). This workshop was jointly sponsored by the Carcinogenesis, Risk As- sessment, and Veterinary Specialty Sections of the SOT. The thrust of the workshop was to discuss the scientific basis for the revisions to the EPA Guidelines for cancer assessment and EPA's plans for their implementation. This is the first revision to the original EPA guidelines which have been in use by EPA since 1986. The princi- pal revisions are intended to provide a framework for an increased ability to incorporate biological data into the risk assessment pro- cess. Two cases were presented, for chloroform and trichioreethyl- ene,.that demonstrated the use of the revised guidelines for specific cancer risk assessments. Using these new guidelines, nonlinear margin of exposure analyses were proposed for these chemicals instead of the linearized multistage model previously used by the EPA as the default method. The workshop participants generally applauded the planned revisions to the EPA.guidelines. For the most part, they considered that the revised guidelines represented a positive step which should allow for and encourage the use of biological information in the conduct of cancer risk assessments. Several participants cautioned however that the major problem gith cancer risk assessments would continue to be the inadequacy of available data on which to conduct more scientific risk assess- ments. ¢ I~? Socie~ of Toxkology. INTRODUCTION (N. P. Page and D.V. Singh) The revised EPA Guidelines for cancer assessment were released for public comment in the Federal Register on April 23. 1996, and simultaneously made available via the Internet on the EPA Office of Research and Development home page. This public release provided for a 120-day comment period. After that, the EPA Science Advisory Board was requested to again review the guidelines along with the public com- ments. The final step will be for the EPA staff to redraft as needed and then publish the guidelines in final form. It is expected that the process to finalize the guidelines will be completed in mid- 1997. These revised guidelines are intended to replace the EPA' s guidelines on carcinogenic risk assessment that were formu- lated in 1986 (U.S. EPA, 1986) and have been in use since that time by EPA as well as other national and international agencies. In the process of evaluating various issues that have been of considerable concern and debate within the scientific community, the EPA has undertake.n a rather ex- haustive review and revision process. This has included the sponsorship of several workshops to address specific guide- line issues (U.S. EPA, 1989a,b, 1994). The Society of Toxi- cology (SOT), at the 1994 annual meeting in Dallas, held a workshop on the "'Evolution of the Methodology for Quanti- tative Cancer Risk Assessments." That workshop specifi- cally addressed dose-response and quantitation methodol- ogy which was being considered for revision. The SOT membe~hip provided to the EPA administrators and scien- tific staff very useful ideas at that time. In addition to input from the SOT, the Society for Risk Analysis also held a 02"2-05q0/t~7 $25 t~) Cop.~nght ~? It,~7 h.~ the St~:~et) of Toxicolt~g) All tagh[~ of reprt~uctlon in any form reserved. 16

REVISED EPA CANCER ASSESSMENT GUIDELINES 17 workshop pertaining to the EPA cancer assessment guide- . lines at its 1992 annual meeting (Anderson et al., 1993). While the EPA has reached a significant milestone in its guidelines revision process, they have announced that the • guidelines will continue to evolve as the scientific knowledge of carcinogenesis increases. Indeed. it is anticipated that ad- ditional changes will evolve as some aspects continue to remain contentious. The revision to the EPA guidelines has set forth principles and procedures that the Agency will use to guide its future carcinogenicity risk assessment ap- proaches in the future. Indeed, EPA has already begun imple- mentation of these revi~ed-guidelines with procedures in place to institute the final guidelines when the time arrives. The following summaries of workshop presentations in- clude an overview of the main scientific issues of the guide- lines revision and a paper describing the types of information needed to utilize mode of action or mechanisms in the carci- nogenesis assessment process. These were followed by pre- sentations of two case studies (for chloroform and trichloro- ethylene) in which the revised cancer guidelines were used to conduct cancer risk assessments. The speakers also com- pared the results obtained with the revised approaches with results obtained with the previous default model (linearized multistage). A panel consisting of scientists representing in- ternational agency (IARC), industry (Rohm & Haas), and non-EPA U.S. agencies (National Institute for Environmen- tal Health Sciences) discussed issues of concern in imple- menting the revised guidelines. Finally, comments from the open discussion with other workshop participants are sum- marized. INCREASING THE USE OF SCIENTIFIC INFORMATION IN RISK ASSESSMENT: REVISIONS OF THE EPA CANCER ASSESSMENT GUIDELINES (William Farland) The revised EPA guidelines for cancer assessment were released in the Federal Register on April 23, 1996. and made available on the Interact via the EPA Office of Research and Development home page. This was followed by a 120-day comment period and review by the EPA Science Advisory Board is anticipated. Several workshops will be held to fur- ther evaluate specific aspects of the proposed guidance, pri- marily through the use of case studies. R is expected that the process to finalize the guidelines will take about 18 months from their release date. These guidelines set forth principles and procedures that the Agency will use to" guide its carcinogenicity risk assess- ment approaches in the future. EPA scientists will use new approaches which have been evolving over the last few years. This guidance also provides an opportunity to inform decision makers and the public about how EPA conducts its work. We know from past experience that there has been a wide usage of these guidelines by other Federal and State FIG. 1. Overview of revised EPA cancer assessment guidelines. Agencies. The final Agency guidelines are likely to benefit from revisions based on comments from those agencies as well as the public and industry. The proposal reflects the fact that new information has evolved on the earcinogenieity processes and the develop- ment of tools that can be incorporated in the conduct of risk assessments. The new guidelines attempt to take these developments into account. The guidelines should be flexible so that they can change as new information and develop- merits evolve. New information should be incorporated into the guidelines more easily than in the past. People have asked whether or not once we release these guidelines we will start the revision process again, as has happened in the past. We think that we have built flexibility into the guide- lines and that they are written in such a way that we can take into account emerging science. However. in the future we will publish a series of technical documents that will address significant issues which may bring about a revision of the overall guidelines. , How have the guidelines been revised and how will they increase our use of scientific information in risk assessment? First, we recognized the need for the risk assessment process to provide information useful for risk management decision making. As can be seen in Fig. 1, risk characterization is the product of the process of risk assessment keying into decision making, along with discussions of non-risk analyses and various control options that are available. Risk character- ization is obviously not the whole story for decision making in risk management, but it is an important part. But what is often not discussed is the process for identifying research needs through the risk assessment process, seeing that those needs are addressed in the laboratory, and assuring that the scientific data and research finds its way back into the risk assessment process. The iterative nature of the process is the important part in our ability to advance the state of the

18 PAGE ET AL. science of risk assessment and the update of our perspectives on what is known and not known about various agents. Major Revisions The revision direction of these cancer guidelines can be summarized in four major points. First, these guidelines em- phasize the importance of full characterization. Second, they expand the role of mechanistic information. This is a goal that is written in the guidelines explicitly, and we think that there is a real opportunity to take advantage of this type of data. The implication of the use of these data will fundamen- tally change the way we evaluate carcinogenesis, but we must also understand the uncertainties that come with the use of mechanistic information. Third, they suggest how to use all the information that is available todesign dose- response approaches. Finally, these new guidelines take the approach of a two-step, dose-response assessment. Full characterization examines hazard assessment, dose- response assessment and exposure assessment. It involves a knowledge as to what we know and what we don't know, what the assumptions and the uncertainties are, and how confident we are about the ability to extrapolate from animals to humans and from high dose to low dose in each step of the process. This full characterization allows one to get away from the linear process of going from hazard to dose re- sponse to exposure to characterization and to begin to realize that exposure has a bearing on how one considers hazard and hazard has the ability to influence dose-response assess- ments. These types of interrelational issues come out in this enhanced characterization approach. Expanding the role of mechanistic information in the haz- ard characterization step involves the use of mechanistic information to inform hazard assessment, particularly as re- lated to the relevance of animal data to humans. This is captured in the guidance to assure that this is part of all hazard characterization activities and pursue the question of how we look at conditions of expression of this hazard as part of the hazard characterization. What we do know about are route-specific effects or levels of exposure-specific ef- fects with regard to potential for hazard, not just risk, but hazard. These are somewhat controversial points that are specifically highlighted in the notice of the guidelines. In terms of dose-response characterization, we want to try to bring mechanistic information into dose-response assess- ment. We will use a decision logic for approaching dose response with mechanistic information contributing strongly to the output of that decision logic. As we move toward hazard characterization of the car- cinogenic endpoint, we are seeing evolution of scientific thought. We are seeing an evolution that has moved us from hazard identification, as black and white decisions, through traditional toxicologic testing, to hazard characterization through evaluation of mechanisms, modes of action, and biologically based models of cancer assessment. This is a fundamental change: it is a change that has been readily accepted by most of the scientific community to really focus on this idea of moving beyond just traditional approaches to toxicologic testing. An additional issue that one begins to address with hazard characterization is weight of evidence versus strength of the evidence. Again, the idea is to consider all studies that are available, both positive and negative studies, understanding the power of those studies to be positive or negative. We must understand what the studies tell us about the responses in animals or in humans. Using all of the evidence in hazard characterization goes way beyond the idea of just animal or human tumor responses. We are really examining key data for clues to inform our assessment. This information with regard to dose level, metabolism, and mechanism improve our insights on hazard and risk does in a very important way. In addition, this is a big departure from the way we used the 1986 guidelines. In 1986, we classified chemicals on the basis of animal or human tumor response but said we would then modify them if we found other types of information that would make us "'change our mind." Now our concept is to bring all of the information together with an integrated approach for discussing hazard. In terms of relevance of animal response, certainly some of the species- specific responses that have to do with the r,-2/a-globulin mechanism in male rat kidneys and issues related to over- coming homeostasis in thyroid carcinogenesis, and other such insights are particularly important to focus on. We can use some examples to illustrate this approach. We have limited experience thus far in dealing with mechanistic information risk assessment for several agents. This experi- ence has led to the discussion contained in these cancer guidelines and represents an evolution of the approach that we had been using. Dioxin is an ongoing activity that looks at receptor-mediated toxicity and we are clearly tryirfg to bring the huge literature on dioxin to bear on this question of both hazard and risk. D-Limonene is an example of a natural compound that produces cancer in animals by a male rat kidney response; however, these make rat kidney re- sponses are the only response seen in a 2-year bioassay. We think that we understand the mechanism of that response, and we feel that it is probably not relevant to human cancer response. That's not to say that all male rat kidney responses axe irrelevant, but, for those where we believe we understand the underlying mechanism of action, we ought to take that into account. Thyroid tumodgens and the question of T3-T4-thyroxin ratios and the overcoming of homeostasis clearly is an issue that needs to be dealt with. The Agency has developed a report that is going to be available soon. As yet another example, science has come a long way in understanding the carcinogenic mechanisms for methylene chloride. Certainly

REVISED EPA CANCER ASSESSMENT GUIDELINES 19 the metabolism and pharmacokinetics of methylene chloride are big points of discussion now. This information suggests that we probably should take another look at methylene chlo- ride and try to bring more of that information to bear on the risk assessment. The same thing goes for formaldehyde. Again. many of you have followed the story of the use of DNA-protein crosslinks as a dosimeter for formaldehyde and have looked at the issue of the new cell separation techniques in evaluating the risks tbr formaldehyde. These are all important issues to take into account as we improve our cancer risk assessments. In addition to these discussions that have gone on over the last few years, the guidelines have a discussion of several cases where we examine the available data on hypothetical cases. The compounds in these cases are not necessarily identified, but most of you know the data well enough to recognize that we used real cases or just slightly altered them to illicit our point. There are seven of those cases discussed in the guidelines to try to illustrate how these guidelines will be applied to a set of information to charac- terize hazard. In addition to that, there are five cases where the hazard characterization paragraphs or discussion that would be evoked by this type of database are actually illus- trated in example form in the back of the guidelines. These are meant to stimulate thought, for people to comment on, and to see how well they track with the guidance we are giving and how useful they are in terms of making some decisions. Now, as we move into dose response, the important ques- tion to ask is how do you use all the information to conduct dose-response assessment, not only the tumor data, but pharmacokinetics and metabolism data to begin to look care- fully at both dose and response issues and to deal with data on effects of the carcinogenic process or processes in select- ing an approach to dose response and to characterizing. The approach that we are going to use is a two-step dose- response assessment. The first step is to evaluate and model the data in the range of observation, to focus on the informa- tion that is available to us from the animal or human studies or perhaps both, and to do the modeling at that point only, within the range of observation. Then we will explicitly move into a discussion in the second step of how one evalu- ates dose response below that range, into the range of human exposure, basically what we call extrapolation. So, being explicit as we move from the observed range into the range of extrapolation is one of the features of these new guide- lines, one that we think is going to be very important. In this first step, evaluation of the range of observation, we use tumor data and other effects data to first choose a biologi- cally based model. If biological models are not available or feasible, is it possible to conduct curve-fitting using standard statistical approaches and models that will fit the data to the best of its ability? To explore the lower range, we use served data as our point of departure and identify some benchmarks for comparison with noncancer health effects assessment. There are some controversial issues associated with benchmark dose assessment and selection of points of depar- ture. But the point is to be able to bring the cancer and the noncancer guidance together so that one can look at both of these issues across individual chemicals. In the case of carcinogens, we want to identify the lowest reliable part of the dose-response curve as a point of departure for extrapo- lation. The second step attempts to make use of approaches that are indicated by the mechanism of action. We choose a biologically based model to extrapolate if at all possible and, hopefully, link it to the range of observation in a way that makes biological sense. If not, we find ourselves back to a default situation where ~ne needs to look at how one deals with dose response in the range of extrapolation in the ab- sence of data that helps to inform us of the likely shape to the point of confidence. Certainly, one would look to choose a linear approach if there are data that suggest that linear is the appropriate way to go or a nonlinear approach if that is the approach that the data suggest. Perhaps here one will look to the "'margin of exposure" approach, where one asks the question "how far is the ob- served range in a particular human situation from the ob- served range from animals or humans?" We look at this "'margin of exposure" as a way to get an idea of how far we exposed humans are from where we actually observe effects in animals. We characterize results and use alterna- tive approaches when it is appropriate. In some cases we conduct both a model approach and a margin of exposure assessment if that seems like the most appropriate thing to do. There is some guidance in the guidelines to suggest how one would do that. As we begin to use mode-of-action data to inform dose- response assessment, we hope to be able to construct a bio- logically based or case-specific model as we have been trying to do for dioxin, as we are evaluating right now for trichloro- ethylene and for other cases that you have heard about and will hear more about today. We will use dose response for other effects in lieu of tumor effects if they are judged to be a better measure of potential risk. For those of you who know the formaldehyde story or know some of the stories where you do have a good opportunity to look at induced cell proliferation, we can put more of an emphasis on cell proliferation as a modulator of carcinogenic activity to help to understand the shape of the dose-response curve. And, finally, to use this to conduct the assessment of risk in the range of extrapolation, to ask whether or not those 'would carry down below the range of observation. So, the decision logic that we are using is to suggest that one would use a linear approach to dose response for DNA-reactive i+ •

20 PAGE ETAL. or other evidence that supports a linearity of response. If chemicals are not DNA-reactive, but if there are insufficient data to characterize a nonlinear mode of action, then the default will be made to a linear approach. This is a public health protective approach, and that linear extrapolation that we will use is not going to be the typical linearized multistage default model as used in the past. But, in fact. it is going to be what we term "truth in advertising." which is to say that we will characterize the point of depar- ture at the lower end of the dose-response curve and extrap- olate simply down to zero. Basically, one can lay a ruler on the page and determine the slope of the dose-response curve if one assumes a linear response from that point of departure. If does not model the response, it does not suggest more precision than it ought to. and it gives us a conservative, what we think will be an upper bound, estimate of risk in those low-dose regions. Clearly, depending on how close you are to the range of observation, you may have more or less confidence in that estimate of risk and that should be part of the uncertainty discussion. In terms of nonlinear responses, if chemicals are not DNA- reactive or otherwise linear and sufficient data are there to characterize a nonlinear mode of action, we would certainly want to see that as a nonlinear dose-response curve. In some cases, we are going to suggest that perhaps both should be done. depending on whether there is differing activity at different sites. We heard just earlier that there may be three or four different modes of action called into play for chemi- cals like trichloroethylene. If there is complex activity need- ing both approaches to describe, certainly we would want to have both of those included in the assessment. In the case of the nonlinear dose-response curve, we think it is going to be quite unlikely that in the near future we are going to see biologically based dose-response curves for nonlinear carcinogenesis below the range of observation. And in that case, we,would argue that the default should be a "margin of exposure" approach. It should not be linear and it should not be a half-baked attempt to try to describe dose response in the face of great uncertainty. Instead, look at this from the standpoint of how close human exposures of concern are to the range of observation to gain some insights on risk. So, risk characterization is the bottom line. We are try. ing to integrate and summarize the hazard characterization, dose responses, and exposure assessment characterizations that have gone on to develop a public health risk estimate where that is possible. We will also develop a framework to define the significance of the risk in every assessment that we do and to present the assumptions and certainties and scientific judgments that went into that to provide alternative ap- proaches and their implications. We think that biologically based dose-response models and biologically based risk as- sessments are possible and that they will improve hazard characterizations by the use of biomarkers of response with some mechanistic linkage to endpoints of concern and that that's going to be a real advance in the way we do business. This will strengthen some of the inferences regarding the shape of the dose-response curves outside the range of ob- servation and this is a goal. This will also help to identify targets of opportunity for further study of potentially sensi- tive human populations and allow us to do a better job of collecting epidemiology data in the future. Now, this approach is not without some risk itself. Biolog- ically based risk assessment presents increased complexity, which complicates simple approaches to risk management, some of which you heard about in the discussions of trichio- roethylene. It complicates already difficult risk communica- tion about difficult scientific issues, but we think it is abso- lutely critical for scientific integrity in the risk assessment process and we hope to be able to further that aim with these new guidelines. USE OF MODE OF ACTION INFORMATION IN CANCER RISK ASSESSMENT (J. I. Goodman) The carcinogen bioassay is a qualitative test (Goodman, 1990). However, our purpose is not to simply identify chemi- cals that can be labeled as carcinogens. On the contrary, the overall goal is to provide a reasonable estimate of the possi- ble hazard that a chemical might pose to people under realis- tic conditions of exposure. The key issues center around dose selection, dose-response relationships, and species-to- species extrapolation (Counts and Goodman, 1995a: Bucher et aL. 1996; Counts et aL. 1996). Therefore, the bioassay should be approached more like a research project than sim- ply a test and a rational approach to risk assessment requires the use of biological information (Goodman, 1994). Dose influences mechanism and. over a wide range of doses, mechanism may be expected to change with dose. Thus, a carcinogenic effect observed at a high dose is not necessarily expected to occur at lower doses (Counts and Goodman, 1995a), especially when dealing with nongeno- toxic :chemicals (McClain. 1994). For example, a report on the rdationship between use of the MTD and study sensitiv- ity for detecting rodent carcmogemc~ty concluded "... [an] important limitation of our analysis is that the range of doses used in NCI/NTP long-term rodent studies is generally rather narrow, typically extending from ¼ MTD to MTD or from ½ MTD to MTD. Thus, it could be argued that carcinogenic effects that are present at even the "lowest' of these doses are due to the same cell killing and compensatory mitogen- esis effects that occur at the MTD" (Haseman and Lockhart, 1994). Increased cell proliferation may facilitate carcinogen- esis due to the fact that mitogenesis can facilitate mutagene- sis (Ames and Gold, 1990). However, this is a complex process and it is not surprising that a one-to-one relationship between cell proliferation and carcinogenesis is not apparent (Melnick. 1992). ~o

REVISED EPA CANCER ASSESSMENT GUIDELINES 21 A consideration of dose selection for the bioassay entails two primary questions: Ca) What is an appropriate range of doses, including the maximum tolerated dose (MTD), to use for chronic exposure'? (b) After the assay has been com- pleted, what are the appropriate doses to employ in order to estimate the possible effect(s) the agent in question may produce in people? The two key principles that underlie dose selection are (a) it is not correct to make an assumption a priori that these doses are the same: and (b) any high dose. no matter how high, that permits the test animals to survive long enough to develop cancer is not necessarily an appro- priam dose to employ for the purpose of a risk assessment (Goodman, 1995; Counts and Goodman, 1995a). Nongenotoxic compounds appear to produce cancer either in a species- and/or dose-specific fashion (Cohen, 1995). We have made progress in discerning a basis for this observation by focusing on the'~.ariety of roles that alterations in DNA methylation may play in carcinogenesis (Counts and Good- man, 1995b) and placing an emphasis on the role that hypo- methylation may play as an epigenetic, nongenotoxic mecha- nism involved in tumor promotion (Counts and Goodman, 1994; Counts and Goodman, 1995c). Tumorigenesis in mouse liver is employed as our model system (Vorce and Goodman, 1991; Ray et al., 1994; Counts et al., 1996). The results of our research indicate that the B6C3FI mouse is deficient with regard to is ability to maintain normal DNA methylation and this appears to, in part, underlie its uniquely high susceptibility towards development of liver tumors (Counts and Goodman, 1995c,d: Counts et al.. 1996). We believe that hypomethylation is relevant to tumorigenesis in both rodents and humans (Counts and Goodman, 1995c), and that humans may be less susceptible than rodents due, in part, to a better ability to maintain nascent patterns of DNA methylation (reviewed in Counts and Goodman, 1995c: Counts et al., 1996). It appears to be inappropriate to make human risk assess- ment decisions based upon a mouse liver tumor response. However, in those situations where the results of a bioassay indicate that the mouse liver is one of several sites where an increased tumor incidence occurs the mouse fiver tumor response, as well as the other target sites for tumorigenesis, should be evaluated with regard to the mode of action of the chemical in question. Safety assessment for those chemicals (especially nongenotoxic chemicals) acting through a thresh- old-exhibiting mode of action should be based on a safety factor, or multiplicity of exposure, approach (Counts et aL, 1996). In this regard, it should be noted that the high propen- sity of the B6C3F1 mouse to develop liver tumors indicates that there is a "built-in" safety factor when this end point is viewed in comparison to the human, even at equal doses of the chemical in question. The maintenance of nascent DNA methylation status should be regarded as a fundamental homeostatic mecha- nism. Accordingly, it is appropriate to invoke the secondary mechanism concept (Scheuplein. 1995) in this context. Al- tered DNA methylation can be viewed as a secondary mech- anism involved in carcinogenesis and assessment of this pa- rameter may provide insight leading to a more rational inter- pretation of animal studies for human risk assessment (Counts and Goodman, 1995c). Therefore, an examination of DNA methylation status should be considered for inclu- sion as an ancillary component (e.g., in addition to assess- ments of cell proliferation in vivo and in vitro tests for the potential to cause genotoxicity) of both subchronic studies. and the carcinogen bioassay (Counts and Goodman, 1994; Counts and Goodman, 1995c.d: Counts et aL, 1996). This can aid in discerning the mechanism of action (e.g., a possi- ble nongenotoxic, threshold exhibiting mechanism) of the chemical being evaluated. In addition, this information could facilitate a rational approach to dose setting and the selection of appropriate doses for risk assessment; e.g., if toxicity occurs only at doses above those which cause altered DNA methylation in the target organ(s), these data could aid in providing the basis for placing a proper emphasis on lower doses (Counts and Goodman. 1995c: Counts et aL, 1996). However, it would not be appropriate to consider measure- ment of alterations in DNA methylation as a short-term test for carcinogens (Counts and Goodman, 1994). In summary, emphasis should be placed upon research that may discern probable thresholds for the carcinogenic effect of carcinogenic agents, especially nongenotoxie chemicals (Counts and Goodman. 1994: Counts and Good- man. 1995a,c,d). This has to involve hypothesis-driven re- search and be based upon insight regarding the mode of action of the chemical of interest (McClain. !994). The practical significance here is that the proposed strategy can provide the basis for a safety factor, or multiplicity of expo- sure, approach to risk assessment for those chemicals for which a likely threshold can be demonstrated (Williams and Whysner, 1995). This is a rational approach to risk assessment. The Environmental Protection Agency's (EPA) new Pro- posed Guidelines for Carcinogen Risk Assessment (EPA, 1996) represent a major positive step in the correct direction. These proposed Guidelines permit, indeed encourage, the use of biological information to make rational risk assess- ment decisions. Specific classification groups A through E have been discarded in favor of placing emphasis on a narra- tive description of the carcinogenic potential of a chemical under particular conditions of exposure. The linear multi- stage model has been discarded in favor of permitting the use of linear and nonlinear dose-response models as justified by the experimental data available. Terms like mode of action, threshold, secondary mechanism, and genotoxic (and by in- ference nongenotoxic) are employed. Additionally. the pro- posed Guidelines recognize explicitly that a carcinogen may

22 PAGE ET AL. (Upper bound on risk) overwhich actual dsk X: Pradic~ed dsk at may exceed predicted ~ upper end of range risk even though dsk of uncertainty due assessment is to consewative dsk conservalive, assessment. (Lower bound on risk) FIG. 2. Range of uncertainty about predicted risk (x). True risk lies somewhere between the upper and lower bounds, which are not known with certainty. Since conservative assumptions are typically used. the pre- dicted risk is likely to be near the upper limit of the range of uncertainty. However, even with the use of conservative assumptions, the actual risk may exceed the predicted risk. may be overly stringent in some cases and insufficiently stringent in others are direct reflections of the uncertainty associated with risk assessment. If there were no uncertainty, i.e., if risk assessment were known to accurately estimate actual risk, such concerns would be moot. The need to im- prove risk assessment to minimize the possibilities of over- and underregulation can therefore be restated as a need to reduce uncertainty in risk assessment. In this report, I briefly describe a biologically based expo- sure response (BBER) model for the hepatotoxicity and he- patocarcinogenicity of chloroform and compare the uncer- tainty of dose-response assessment performed with this model with an assessment based on default approaches as described in the 1986 U.S. Environmental Protection Agency (U.S. EPA) Guidelines for Carcinogen Risk Assessment (U.S. EPA, 1986). The Proposed Guidelines for Carcinogen Risk Assessment (U.S. EPA, 1996) specifically encourage the use of biologically based models for cancer risk assess- ment. Thus the new chloroform model described herein also illustrates some aspects of how dose-response assessment motivated by the new Guidelines is likely to differ from older approaches. act through a nonmutagenic mode of action, including per- turbation of DNA methylation patterns which my contribute to carcinogenesis by alteri.ng gene expression. I applaud the EPA for proposing these new Proposed Guidelines for Car- cinogen Risk Assessment and I look forward to opportunities to work with the Agency in order to implement them. CASE STUDIES IN CANCER RISK ASSESSMENT: CHLOROFORM (Rory B. Conoily) Risk assessment influences regulations intended to protect the public health. These regulations incur economic and so- cial costs associated with remediation, product substitution, and other aspects of compliance. Because risk assessment is intentionally conservative in the face of scientific uncer- tainty, some of these costs are prolqgb~ly unnecessary, i.e., the conservatism of risk assessment leads to regulations more stringent than needed to protect the public health. Uncer- tain~y in risk assessment also means, at least in theory, that risk assessment intended to be conservative may not, in fact, be protective of the public health (Fig. 2). These two fac- torsmthe likelihood that unnecessary costs are incurred and the possibility that in some cases the public health is not protected--motivate research to improve the scientific basis of risk assessment. While both exposure assessment and dose-response assessment can be pursued using policy- based default options, reduction of uncertainty for these ac- tivities depends on improved scientific understanding of the relevant biology, chemistry, and exposure conditions. The concerns that regulations based on risk assessment Exposure-Dose Response What is commonly called dose-response modeling en- compasses both the pharmacokinetic and pharmacodynamic components of the overall linkage between exposure and response. The BBER model for chloroform consists of linked submodels for pharmacokinetics (PK submodel) and phar- macodynamics (PD submodel) and can readily provide quan- titative descriptions of the relationships between (1) expo- sure to chloroform in air, water, or any other medium and tissue dose (PK submodel) and (2) tissue dose and response (PD si~bmodel). This approach to partitioning the exposure- response relationship leads to an expansion of the standard definition of dose-response (NRC, 1983: U.S. EPA, I996) with exposure-dose-response in which "dose" refers to the dose to the target tissue. This expanded definition is used throughout this report and is in general useful when describ- ing BBER models. Description of the BBER Model for Chloroform The basic structure of the chloroform model has been previous.ly described (Conolly and Butterworth, 1995) and -is only briefly reviewed here. The PK submodel corresponds to the physiologically based pharmacokinetic model for chloroform described by Corley et al. (1990). This submodel allows for definition of an hepatic dose surrogate that is the interface to the PD submodel. The PD submodel links tissue dose with a tissue response, in this case the killing of hepato- cytes by chloroform. The PD submodel also describes regen- erative hepatocyte replication in response to chloroform-in- duced cytolethality.

REVISED EPA CANCER ASSESSMENT GUIDELINES 23 The exposure-response curve for chloroform-induced cy- tolethality and regenerative replication is taken to be a suit- able surrogate for the exposure resl~mSe curve for chloro- form induced hepat¢~.'ellular carcinoma for the reasons dis-. cussed in detail by Larson et aL (1994c) and Butterworth et aL (1995). Briefly. I1) there is a large body of evidence showing that chloroform is not a directly genotoxic carcino- gen in mammals; (2) chloroform is a potent cytotoxicant to human and rodent liver and kidney; and (3) in all cases studied to date. carcinogenic effects of chloroform are pre- ceded by cytolethality and regenerative replication. Thus the available data. which are substantial, suggest that the mode of carcinogenic action of chlorotbrm is cytolethality. Under this mode of action, the mutations that lead to chloroform- induced hepatocellular carcinoma are assumed to arise as consequences of chronic cytolethality and induced cellular regeneration, not as direct effects of chloroform or of its metabolites on hepatocyte DNA. The exposure response curve for cancer under this mode of action is expected to be sublinear (U.S. EPA, 1996). In fact. the chloroform expo- sure-cancer response curve probably has a true exposure threshold since it seems unlikely that a single molecule of chloroform is capable of killing a hepatocyte, thereby initiat- ing the chain of events that ultimately leads to formation of procarcinogenic mutations. Definition of the target tissue dose surrogate is a key feature-of any BBER model. The dose surrogate is the transi- tion point between the PK and PD submodels and can be thought of as the pharmacokinetic driving force for subse- quent PD events. Before the advent of PBPK modeling, this driving force was typically an exposure metric such as the concentration of chemical in inhaled air or in drinking water. PBPK modeling allows for definition of a tissue dose that incorporates nonlinearities in the relationship between.expo- sure and dose to tissue and which is consistent with the roles in toxicity of bioactivation and metabolite kinetics. Chloroform is metabolized to phosgene and hydrochloric acid (Pohl. 1979). Phosgene has a short half-life in aqueous systems. In the liver, phosgene can be conjugated with gluta- thione or form macromolecular adducts, but any phosgene that does not enter one of these two pathways is rapidly hydrolyzed. Chloroform-derived hydrochloric acid should similarly be short-lived since it is removed by intracellular buffering. It follows that the pharmacokinetic driving force for hepatocyte killing by chloroform is more closely, related to the rate of chloroform metabolism, i.e., to the rate of production of phosgene and hydrochloric acid than to, for example, the area under the curve for metabolite production. The latter definition would b,e appropriate for stable metabo- lites. Ideally. the dose surrogate is defined without reference to the biochemical mechanism of the tissue response, i.e.. the pharmacodynamic component of the exposure-response re- 0.3O 0.~$ tO.~O ~ 0.'15 ~0.10 0.05 0.00 I 81 - o.oo ~.oo a.oo 3.oo 4.oo s.oo e.oo Liver dose surrogate (~rnol metabol/zed/g Iiver/60 m/n) FIG. 3. Empirical function describing the relationship between target tissue dose surrogate, as defined in the pharmacokinetic (PK) submodel. and ceil killing inferred from the pharmacodynamic (PD) submodel using 3.5-day labeling index data. During a simulated chloroform exposure, the value of the dose surrogate is calculated at each time point, t. and the function spe~ifics the corresponding amount of cytolethality. See text for further details. lationship. Limitations in the available data. however, make it difficult to completely maintain this. distinction in devel- oping the BBER for chloroform. The dose surrogate .used for the current model probably represents not only a pharma- cokinetic driving force but also some of the kinetic aspects of the pharmacodynamic response. Because of this. the quan- titative definition of the dose surrogate is provided within the following description of the PD submodel. The PD submodel consists of difference equations that track time-dependent changes in the number of hepatocytes in the liver as a function of basal rates of cell division arid death, chloroform-iladuced cytolethality, and regenerative replications. Note that tracking of both basal and regenera- tive replications allows the labeling index to be simulated. The model is constructed so that for each cell killed due to chloroform there is a corresponding regenerative replication. This one-for-one correspondence allows the number of cells killed at any level of chloroform exposure to be calculated from labeling index data (Larson et aL, 1995a, b) and corre- lated with the dose surrogate (Fig. 3). The dose surrogate is the only adjustable parameter in this approach to defining the tissue dose-cytolethality-regenerative replication rela- tionship. The amount of chloroform metabolized over the interval (t, t - 60 min), where t is the current time, was found to provide a good simulation of the labeling index data. As noted above, this definition of tissue dose is proba- bly not a purely pharmacokinetic tissue dose surrogate but also embodies to some extent the kinetics of the tissue re- sponse that leads to cytolethality and regenerative replica-

tion. Given that the half-lives of chloroform-derived phos- gene and hydrochloric acid inside hepatoc~tes are expected to be brief, a purely pharmacokinetic dose surrogate would be expected to be defined for an interval considerably shorter than 60 rain. Integration of the rate of metabolism over 60 rain probably reflects kinetic aspects of the tissue response ending with cell death and regenerative replication. This response has not, to date, been characterized at the biochemi- cal level. Refinement of the dose surrogate definition re- quires data on tissue half-lives of chloroform-derived phos- gene and hydrochloric acid that are currently unavailable. lnterspecies Scaling Conolly and Butterworth (1995) described interspecies scaling of the chloroform model where different scaling strategies were used for the PK and PD submodels. The PK submodel was scaled from rodents to humans using a combination of allometric relationships and human data as described by Corley et al. (1990). Since PD scaling is not as well understood as PK scaling and since no data were available to guide scaling of the PD submodel, it was not changed when used to describe the human response to a liver dose of chloroform. The human version of the chloro- form BBER model thus uses a PK submodel scaled from that used for rodents but the same PD submodel used for the rodent models. This hybrid scaling strategy takes advan- tage of the different levels of sophistication in our under- standing of PK and PD for chloroform. Such a strategy is likely to be useful for other chemicals since PK is, in general, better understood than PD. Preliminar3." Simulation of the Human Hepatoxicity of Chloroform Wallace (I 950) described a case of hepatitis and nephrosis in a 50-year-old man who consumed about 12 ounces/day of a.cough syrup containing chloroform and 3% alcohol. After a prolonged period of cough syrup consumption at this rate, the individual experienced signs of both hepatic and renal toxicity. He had been consuming about 33.4 mg chloro- form/kg/day. The PK submodel was configured for this indi- vidual according to Corley et al. (1990). including the speci- fication of his body weight at 78 kg, as reported by Wallace (1950). It is worth noting that Corley et aL (1990) had used human liver microsomes to estimate the capacity of human hepatocytes to metabolize chloroform (V~, of 15.7 mg chlo- roform/kg body wt/hr, multiplied by BW°'7 to adjust for body weight differences either between or within species). With this configuration, a simulation of 7 days of cough syrup consumption showed no effect on labeling index, i.e., label- ing index stayed at its basal value (Fig. 4). However. increas- ing Vm~, by a factor of two to 31.4 mg/kg/hr resulted in an increase in simulated labeling index for the same exposure scenario. Under these conditions, the model predicted chlo- 1.0 0.9 1.0 FIG. 4. Simulation of hepati~ concentration of chloroform (solid line) and hepatic 3.5-day labeling index (dashed line) in a 78-kg man consuming a bolus dose of 33.4 mg chioroform/kg/day for 7 days. Labeling index is increased (upper dashed line) when the capacity to metabolize chloroform (V,,~) is set to 31.4 mg chioroform/kg BW/day. With V,~, at 15.7. the value obtained by Corley et al. (1990). no increase in labeling index over the basal level was seen (horizontal dashed line). roform hepatotoxicity. The change in V~,., by a factor of two that was required to simulate liver damage is not unreason- able given (1) the coexposure to alcohol in the cough syrup and (2) the possibility that prolonged exposure in this case may have caused some induction of the capacity to metabo- lize chloroform. This result, while preliminary, suggests that the model development process to date is valid. More work, however, is needed before the model can be used with confidence for quantitative prediction of the hu- man hepatotoxicity of chloroform. Particularly important is the specification of drinking behavior. For the simulation shown (Fig. 4), cough syrup consumption was modeled as a single bolus dose to the gastrointestinal tract, once a day, with a first-order absorption rate constant of 1.0 (1/hr). Pre- diction of hepatotoxicity is sensitive to changes in this de- scription. For example, splitting the single daily bolus dose into 12 equal doses taken 1 hr apart over a 12-hr period (probably a more realistic description of drinking behavior) decreases the value of the dose surrogate obtained at the dose rate of 33.4 mg/kg/day and eliminates the predicted hepatotoxic response. Wallace (1950) provides no informa- tion on the details of the drinking behavior associated with chloroform toxicity. Without this detail, description of the drinking behavior as a single bolus dose per day m. aximizes the value of the dose surrogate calculated by the PK submo- del and thereby provides a worst-case estimate of the contri- bution of chloroform absorption kinetics from the gastroin- testinal tract to the likelihood of toxicity. One of the advantages of mechanism-based modeling is its ability to identify specific sources of uncertainty such as the description of drinking behavior. In default approaches to chloroform risk assessment (see below), this factor could not be explicitly considered, and its associated uncertainty would be hidden. It is easy to infer that uncertainty hidden

REVISED EPA CANCER ASSESSMENT GUIDELINES TABLE 1 Comparative Uncertainty of Default and Mechanism-Based Dose-Response Modeling for Ch/oroform 25 Default model Mechanism-b~ed model Component 11980 Guidelines)~ (1996 Proposed Guidelines)~ Equivalent dose calculation C "< T with duration adjustment Target tissue dose from PBPK model based on physiology and mechanistic considerations. (1~ uncertainty) (~, uncertainty) BWu' PBPK scale-up based on data. allometric relationships, and physiology. (~ uncertainty) (~ uncertainty) n/a Single bolus vs sips Irate dependence) if uncenain~ O, uncen.aimy) LMS Cell replication response surrogate (1" uncertninty) (~ uncertainty) Drinking ~havior Cancer model a U.S. EPA (1986). b U.S. EPA (1996). in this way does not exist, leading to the mistaken impression that default models are less uncertain than mechanism-based models. Relative Uncertain~. of Default and Mechanism-Based Models for Chloroform The cu~.ent noncancer risk assessment for chloroform by the U.S. EPA is in the form of an oral reference dose(RfD) calculated from a study by Heywood et al. (1979). In this study, fatty cysts developed in beagle dogs given chloroform in a toothpaste base in gelatin capsules 6 days/week for 7.5 years. The lowest-observed-adverse-effect level (LOAEL) for the study was 12.9 mg/kg/day, and the RfD was set at 0.01 mg/kg/day (U.S. EPA, 1995). Uncertainty factors of 10 were applied to the LOAEL to account for interspecies conversion, protection of sensitive human subpopulations, and concern that the effect seen was a LOAEL and not a no-observed-adverse-effect level. The RfD was calculated without use of either pharmacokinetic or nontumor pharma- codynamic data specific to chloroform. In contrast, the mech- anism-based, exposure-response model described here makes maximum use of available data to construct the PK and PD submodels (Table 1). As a result, predictions of the exposure-regenerative cell replication relationship obtained with the mechanism-based model are less uncertain than the RfD calculation. A further advantage is the explicit identifi- cation of sources of model uncertainty obtained with the mechanism-based approach (Table 1). This contrasts with the hidden or implicit nature of much of the uncertainty in the current default models. The standing U.S. EPA cancer risk assessment for chloro- form (U.S. EPA, 1995) uses the LMS model with tumor data from NCI (1976) and Jorgensen et aL (1985). As with the noncancer risk assessment described above, the cancer risk assessment uses no pharmacokinetic or nontumor pharmaco- dynamic data. The lack of direct, mammalian genotoxicity of chloroform (Rosenthal, 1987; Larson et aL, 1994c) and the correlation between chloroform-induced cytolethality and regenerative proliferation and carcinogenicity (Eschenbren- her and Miller, 1945; Larson er aL. 1994a.b: Larson er aL, 1995a.b) are consistent with the hypothesis that cytolethality and regenerative proliferation are necessary precursors to chloroform-induced cancer. These factors suggest that predic- tions of cancer risk obtained with a mechanism-based model for chloroform cytolethality are less uncertain than risk as- sessments based on the LMS model (Table 1). Application of the mechanism-based model for chloro- form in formal risk assessment should include use of Monte Carlo analysis to approximate variability in the human popu- lation. Confidence in the model could also be increased by more extensive use of human data for its parameterization. Studies designed to support these improvements are under- way at the Chemical Industry Institute of Toxicology. When these studies are complete, the model will be used for predic- tion of human risk of hepatotoxicity and bepatocarcinogeni- city from chloroform exposure. Under the 1996 Proposed Guidelines for Carcinogen Risk Assessment (U.S. EPA, 1996) a margin of exposure analysis would be used, re- flecting the nonlinear mode of action'of chloroform as both a cytotoxicant and a carcinogen. CONSIDERING PHARMACOKINETIC AND MODE2OF- ACTION INFORMATION IN CANCER RISK ASSESSMENTS FOR ENVIRONMENTAL CONTAMINANTS: EXAMPLE WITH TRICHLOROETHYLENE (Melvin E. Andersen and Harvey J. Clewell) The principal challenge facing cancer risk assessors today is to realistically consider the implications of the chemical's

26 PAGE ET AL. mode of action as a carcinogen in developing risk assessment approaches. It is becoming increasingly difficult to justify the use of the same standard risk assessment approach for both chemicals that act through a purely radiomimetic, geno- toxic mechanism (such as vinyl chloride (VC) or diethylnitro- samine) and for those that act by increasing cell proliferation secondary to cytotoxicity (chloroform) or receptor interaction (peroxisome proliferators). Mode-of-action-dependent risk assessment approaches are the only alternative for main- taining the credibility of cancer potency estimates in the face of increasing sophistication in the understanding of the mech- anisms of carcinogenicity. The new draft revisions to the U.S. Environmental Protection Agency (U.S. EPA) guidelines for cancer risk (U.S. EPA. 1996) would appear to provide the flexibility necessary to move forward in this area. In the last few years there have been significant advances in our understanding of chemical carcinogenesis in general and the mechanism of carcinogenicity of trichloroethylene (TCE) in particular. This talk outlined the steps required to conduct a state-of-the-science risk assessment for TCE, using informa- tion mode-of-action and pharmacokinetics of TCE and its important metabolites. Reevaluation of the cancer risk assess- ment process for TCE is of more than academic interest: costs for remediation of TCE contaminated sites are in the range of hundreds of millions of dollars per year. USEPA cancer risk estimates for TCE (U.S. EPA, 1985; 1987),.calculated on the basis of metabolized dose with the linearized multistage (LMS) model, have continued to be used for environmental decision-making since 1985. How- ever, it is discouraging to note that these tissue,dose based potencies for TCE are very similar to those for VC (Clewell et aL, 1995). despite the strong epidemioiogical evidence suggesting that VC is a more potent human carcinogen than TCE. Clearly, pharmacokinetics alone does distinguish the relative potencies of these two compounds. Integrated Cancer Risk Assessment for TCE Several steps are involved in performing a risk assessment for TCE that considers both mode-of-action and pharmacoki- netics. Information must first be gathered on metabolism of TCE to identify key metabolitesmchloral (CHL), trichloro- acetic acid (TCA), dichloroacetic acid (DCA), and dichloro- vinylcysteine (DCVC)--associated with TCE-induced tu- mors. Mode-of-action data specific to each tumor type links the biological or biochemical effects in the target tissue with the target tissue exposure to the appropriate metabolite. Thus the mode-of-action associated with the production of a par- ticular tumor provides the qualitative basis for expectations regarding (I) the dose-response for tumor incidence (i.e., linear or nonlinear). (2) the metabolite associated with tu- morigenicity, and (3) the cross-species scaling for the target tissue dose of the metabolite. Together, mode-of-action and metabolism data can be integrated into a PBPK model to provide predictions of the appropriate concentration profiles for TCE and its metabolites in each of the target tissues in the test animals and in people. These quantitative dose .predictions from the PBPK model together with the low- dose extrapolation methodologies suggested by the mode-of- action provide the basis for making human risk projections. Evidence for Carcinogenicity Several studies have shown that TCE causes liver and lung tumors in mice (Davidson et aL, 1991). Statistically increased tumor outcomes observed in only a single study include malignant lymphoma (HAN:NMRI mice), renal tu- bular cell adenoma and carcinoma (male rats), and benign testicular (Leydig cell) tumors (Sprague-Dawley rats); of these, the rat kidney tumors have raised the greatest concern since they were not observed in control animals. Metabolites and Their Modes of Action TCE metabolism consists of oxidation to CHL by cyto- chrome P450 enzymes, followed by either oxidation of CHL to TCA by an aldehyde oxidase or reduction to TCOH by alcohol dehydrogenase with subsequent glucuronidation. Oxidation of TCOH to TCA has also proposed (Mueller et aL, 1975). DCA, a minor urinary metabolite of TCE (on the order of 1%) in rats and mice, has not been detected as a metabolite of TCE in the human. Liver TCA and DCA appear to play a major role in the liver tumors caused by TCE exposure in mice (Bull et aL, 1993). Both compounds produce focal hyperproliferative lesions, adenomas, and carcinomas on chronic administration. In the typical sequence of events, there is early evidence of a slight, but generalized liver hyperplasia, consistent with action as a weak mitogen. The cell proliferation rates soon return,to normal in spite of continued exposure, indicating the pres- ence of a mito-inhibitory, adaptive responses. After about 30 weeks, hyperplastic nodules appear and eventually pro- gress to neoplastic lesions. This sequence of events is consis- tent with a "suppression escape" mechanism for promo- tional carcinogenicity (Andersen et aL. 1995). This escape from mitosuppression and a role for the mitoinhibitory growth factoroTGF-~lmhas been suggested as a likely mode-of-action with liver tumors associated with peroxi- somal proliferators. TCA and DCA induce peroxisome pro- liferation at sufficiently high doses. Lung In vivo toxicity studies (Odum et al.. 1992) were conducted in female mice and rats by inhalation. A specific lesion, char- acterized by vacuolization of lung Clara cells, was only seen in mice. Mice exposed to 100 ppm CHL had a similar lesion.

REVISED EPA CANCER ASSESSMENT GUIDELINES 27 Only mild effects were observed with inhaled TCOH, and none were observed with 500 m~m~kg TCA given intraperitone- ally. Thus CHL appears to be responsible for the lung toxicity. Mouse lung cells have low glucuronidation capacity and low ADH. the enzyme which converts CHL to TCOH. Thus. the acute toxicity in the mouse lung appears related to accumula- tion of CHL in Clara cells. The impScations of these results for the lung tumorigenicity of TCE are twofold. First, CHL is known to be genotoxic in a number of studies (Odum et aL. 1992). And. second, the recurrent toxicity observed with intermittent exposure is likely to produce compensatory cell proliferation, exacerbating any genotoxic effect. Kidney Direct conjugation of TCE with glutathione occurs in the liver followed: by further metabolism in the kidney to a cys- teine conjugate~ which can then be cleaved to a reactive intermediate in the kidney tubular cells (Birner et aL, 1993). The cysteine conjugate formed from TCE. DCVC, is nephro- toxic and mutagenic in the Ames test. Detoxification and clearance of DCVC takes p!ace by urinary excretion of the N-acetyl derivative; the fact that N-acetyl-DCVC has been identified in the urine of humans exposed to TCE at work (Bimer et aL, 1993) indicates that exposure of the kidney to DCVC does occur in the human. Cell proliferation also appears to play a role in kidney. In the only bioassay that reported a significant increase in kidney tumors from TCE, cytotoxicity was observed in the kidney at both the low and high doses, while tumors were observed only at the high dose. DCVC, then, appears to have the potential for both direct genotoxic activity and cytotoxicity. Selection of a Risk Assessment Approach All three tumor types discussed above have a complex modes-of-action with contributions from nongenotoxic path- ways related to cytotoxicity and receptor-mediated mitogenic stimulation as well as from genotoxic species: DCVC, CHL, and perhaps reactive oxygen species related to peroxisomal induction in the liver. The new U.S. EPA guidelines for ear- cinogen risk assessment permit several methods for analysis of data in the observable range and for low-dose extrapola- tions. The extrapolation can be based on a linear or nonlinear mode-of-action or on a margin-of-exposure calculation. A linear extrapolation is more appropriate for potent genotoxic carcinogen. In the extreme, a nonlinear relationship gives a threshold, i.e., a dose below which there is no risk. The margin of exposure (MOE) approach is similar in practice to the threshold approach, but the assumptions un- derlying its use are not as constraining. In practice a margin of exposure requires estimation of a dose associated with a response and comparison of that dose with ambient levels. The quotient (effect level/ambient level) provides a margin of exposure or margin of safety. Equivalently, a decision can be reached a priori stating what MOE would be tolerable for a given chemical and mode-of-action. It is this latter definition that is followed here. Rather than estimating a human exposure threshold below which no risk is expected, the MOE approach estimates the human exposure producing a dose-metric value which is a specified factor ("margin") below the value of the dose metric at which a minimal tumor response (e.g.. 10%rathe EDto) was observed in animals. The MOE approach admits the possibility that in spite of the presence of a highly nonlin- ear dose response in the experimental regime there may still be residual risk, and even low-dose linear behavior, below the apparent threshold for the nonlinear process. However, it relies on the basic nonlinearity of the process underlying the carcinogenic mode of action to assure that the margin of risk between the human and animal exposures is much greater than the MOE. That is, an MOE of 100 might be expected to provide a risk reduction of greater than 1000, since it is expected that risk falls off at a much faster rate Tdchloroethylene Model CI ~QP ICX CV ~ Alveol.rAk" I CA QC Alveolar Blood QC CVI"B Tracheo-Bronchiel Tissue PTB CTB VTB ~- QTB ~VMTB, KMTB CVF ] Fat Tissue PF CF VF QF CVR I Rapidly Perfused Tissue PR CR VR QR CVS I Slowly perfused Tissue~ PS CS VS QS ~.~ Gut L~SD I Stom'ctl ~_..po0$E KTD , Lumen ~ Lumen PG CG VG QG CVG ~, CVL Liver Tissue PL CL VL QL VM, KM FIG. 5. Tdchtoroethylene model.

28 PAGE ET AL. Trlchloroethylene Target T~ssue Submodels FIG. 6. Trichloroethylene target tissue submodels. Application of the Pharmacokinetic Mrdel in the Integrated Assessment The dose measures from the PBPK model are used to determine the target-tissue-related ED l0 for tumor response. For instance, the kidney tumor incidence is related to the tissue exposure to ~he reactive metabolite produced from DCVC. The EDI0 (mg DCVC metabolized/kg kidney/day) is then adjusted by the MOE to give the human tissue dose associated with the acceptable risk level (Table 2. column 1). The human PBPK model is then exercised to calculate the exposure concentration (ppm in air or/~g/liter in drinking water) that would lead to the acceptable tissue dose (Table 2. column 2). A similar approach was used to obtain the 10-° risk level using the LMS model. The results of the dose metric calculations with the PBPK model are summarized in Table 2. In this table, the most plausible estimates of acceptable exposure levels are shown for each target tissue and human exposure scenario of con- cern. The numbers in parentheses represent alternative, worst-case risk estimates. The purpose for including these alternative estimates is to demonstrate the broad uncertainty in the current risk estimates. In every case the discrepancy between the best estimate and worst-case estimate could be greatly reduced by experiments which are well within the state of the science. In this way, the results of the risk assess- ment defines the most important research required to im- prove confidence in the risk assessment itself! In the case of lung tumors, the numbers in parentheses represent the calculations which assume that the cross-spe- cies scaling for the clearance of CHL in the lung parallels that of P450 (which falls off dramatically) rather than follow- ing allometric expectations. In the case of kidney tumors, than exposure. With TCE, the proposed guidelines would seem to SUl~port a MOE assessment for this compound. These calculations require construction of a suitable PBPK model, the structure of which is dictated by the presumed modes- of-action of TCE and its metabolites in target tissues. Description of PBPK Model The PBPK model fused or TCE (Figs. 5 and 6) was an expansion of a previously published model of TCE and TCA (Allen and Fisher, 1993) and included other key metabolites: DCA, TCOH (the principal source of DCA), DCVC in the kidney, and CHL in the lung. The model included both inha- lation and oral routes of exposure and the three target tissues, the lung. kidney, and liver. The dose metrics provided are the instantaneous concentration and area under the curve for CHL in the lung, the total production of the thioacetylating intermediate from DCVC in the kidney: and the AUC for both DCA and AUC for TCA in liver (Clewell et al.. 19951. TABLE 2 Comparison of Virtually Safe Lifetime Exposure Level's (ppb in Air or mg/L in Water) for TCE Based on PBPK Model Results and Either the Margin of Exposure (MOE) Approach or the Linearized Multistage (LMS) Approach I0-~ Risk MOE° = 1000 EDI0/MOE MOE level level~ Inhalation (ppb): Lung 0.009 6000 (9)' 41 (0.06) Kidney 9.02 15000 (36) 300 (0.64) Liver 3.59 88 (12.5) 0.35 (0.05) Drinking water (mg/L) Lung 0.0{)9 600.000 (900) 40~X) (6.0) Kidney 9.02 225.000 (540) 4'500 (9.6) Liver 3.59 390 (56) 5.6 (0.8) "Margin of exposure belo,~ EDI0 (dose corresponding to an extra risk of 10%). ~ Lifetime extra cancer risk based on the linearized multistage model. + Alternate (worst-case) calculationmsee text.

REVISED EPA CANCER ASSESSMENT GUIDELINES 29 the numbers in parentheses rePresent the calculations which assume an extremely low GST pathway production in the rat compared to the human (based on one animal study) rather, than assuming a production more in keeping with allometric expectations (based on another animal study). Both of these uncertainties can readily be addressed by in vitro studies similar to those which have been performed with methylene chloride (Reitz et al., 1989). For the liver tumors, the numbers in parentheses represent the calculations which assume that the human susceptibility to mitogenic carcinogens is similar to that of the mouse, as opposed to the most plausible estimates, which assume that the human susceptibility is more similar to the rat. (In tact. both species are likely to exaggerate the risks of TCA- and DCA-associ- ated liver tumors in humans.) Table 2 also shows the use of the PBPK dose measures and the LMS model to obtain quantitative estimates of the risk associated with a given human exposure scenario, based on the bioassay dose-response data. Typically, USEPA has considered an increased lifetime risk of cancer on the order of l0-~ to be acceptable for the public (U.S. EPA, 1983, 1985. 1987). Depending on the target tissue, the TCE expo- sure levels associated with an increased lifetime risk of l0-6 range from 0.35 to 300 ppb in air or 5.6 to 4500 mg/liter in water. For comparison, the most recently published risk estimates from U.S. EPA would equate to lifetime 10-6 risk exposure levels of 0. l l-ppb and 3.1 rag/liter. For the MOE calculation, a minimum MOE of 100 would seem to be justified on the basis of l0 for human variability (particularly for variability in the activities of the key metab- olizing enzymes) and l0 for uncertainty in the animal to human extrapolation. For exposures of the general public, it might sometimes be appropriate to add an additional margin of l0 because of the potentially large number of individuals exposed. For the purpose of this illustration a MOE of 1000 was used in obtaining the public exposure levels in Table 2. q'he new U.S. EPA guidelines for carcinogen risk assessment propose a factor of 100 with the LEDt0, the lower confidence bound on the EDto (US EPA, 1994). Depending on the target tissue, the TCE exposure levels which provide an MOE of 1000 range from 88 to 15000 ppb in air or 390 to 600,000 mg/L in water. The MOE approach with TCE results in acceptable levels which are higher than those obtained by the LMS approach by roughly two orders of magnitude. Together. the mode-of-action and PB-PK dose measures per- mit development of qualitative methods for extrapolatioti and quantitative evaluation of the exposures leading to a particular dosing intensity in target tissues. MOE type-approacbes are more appropriate than linear low-dose extrapolation approaches for a carcinogen such as TCE for which (a) there is weak potential for interactions with DNA, (b) there is evidence of enhanced cell prolifera- tion due to receptor interaction or cytotoxicity associated with every target tissue at tumorigenic dose levels, and there is little-evidence of cross-species correspondence or the production of rare tumor types. The cancer risk from a chemical like TCE, for which the mode of action appears to involve the nonlinearities associated with enhanced cell proliferation, is likely to fall off much faster than dose. pro- ducing an incremental reduction in risk far exceeding the reduction in exposure. The specifics of the general applica- tion of nonlinear approaches augmented bY quantitative PBPK models remain to be codified in the new guidelines. However, the general approach applied with TCE should provide a useful guide for future developments in this area. COMMENTS ON DRAFT REVISIONS TO THE EPA'S GUIDELINES FOR CARCINOGEN RISK ASSESSMENT (Hiroshi Yamasaki) A major revision to the EPA's Guidelines for Carcinogen Risk Assessment is the incorporation of more mechanistic information into the process of risk assessment. Similar deci- sions have been made for IARC Monographs on "Evaluation of Carcinogenic Risks to Humans" and are being considered by the U.S. National Toxicology Program for adoption as part of the process for establishing carcinogen listing in its "'Biennial Report of Carcinogens.'" This is probably an inev- itable and healthy path, considering the unprecedented prog- ress made during the past few years in our understanding of cellular and molecular mechanisms of carcinogenesis. It is often considered that the incorporation of mechanistic information is a new step in the process of cancer.hazard identification and risk assessment. However, it is only in fact a form of evolution from earlier practice. In the past, we used data from mutation assays as well as those derived from cytogenetic studies for identifying carcinogens. These endpoints were based upon our mechanistic understanding of carcinogenesis at that time, according to which carcino- genesis involved gene and chromosomal mutations. We have thus been using mechanistic information for a long time. What is now evolving is the realization that carcinogenesis involves not only mutagenie events but also nonmutagenic mechanisms, and that the primary actions of some carcino- gens .indeed depend upon nonmutagenic processes. At the same time, molecular biological approaches have also started to provide extensive data which are important for risk assess- ment. for example, those concerning genetic susceptibility of individuals. The more we know about mechanisms of carcinogenesis and mechanisms of action of agents, the more reliable will be our judgment in carcinogen risk assessment. Thus, I believe the proposed revisions to the EPA Guidelines are a valuable step forward. In view of the continuous eyolution of science, and espe-

30 PAGE ETAL. cially the experimental growth in data accumulation in the life sciences, we need to be flexible in how we use mechanis- tic data on carcinogen risk assessment. It was initially con- sidereal that the Ames test was a quite versatile one for predicting carcinogens. Subsequently, tumor promotion mechanisms' and thus tumor-promoting agents attracted much attention. At that time, it was impossible to imagine the progress that has now been made in the identification of molecules involved in cell cycle regulation and apoptosis as well as their involvement in carcinogenesis. Some of the relevant genes have already been knocked out in rodents, and such genetically engineered mice are being used not only in studying mechanisms of cell growth control but also for studying mechanisms of action of carcinogens. Even more recently, we have begun to recognize the importance of telomerase activity in carcinogenesis. Many more exciting developments will come in the near future and guidelines should be flexible enough to be able to incorporate them rapidly and appropriately. Since flexibility is important in establishing procedures for using mechanistic information, much more responsibility should be carried by those who actually evaluate such infor- mation and decide its relevance to carcinogenicity. Our judg- ments are always based upon available data, and we therefore tend to neglect other possibilities. For example "'mutation" data have ge.nerally been taken more seriously than "nonmu- tagenic" endpoints, since there is firmer evidence for the involvement of genetic changes in carcinogenesis, This ap- proach itself is understandable, but sometimes seems to lead to the assumption that "since we know genotoxic mecha- nisms better than nongenotoxic ones, genotoxic mechanisms are more important.'" Such an erroneous presumption must be avoided, since what we do not know now may become important as our mechanistic knowledge improves. There have been and still are attempts to categorize agents based on mechanistic information, in the hope that risk assessment will thus be simplified. Such categories include "genotoxic/ nongenotoxic." "tumor initiating/promoiing," and "peroxi- some proliferation inducing" agents. It is my personal view that such categorization is not only useless, but sometimes impedes the conduct of meaningful risk assessment. The reason is that any such characteristic used for categorization is just one of many activities exerted by a given agent and. thus, any categorization excludes other possible mechanisms which might turn out to be more important for the carcinoge- nicity of a given agent. We should bear in mind that we do not yet fully understand the mechanisms of action of any known human carcinogen. If the agent inhibits gap-junc- tional intercellular communication, for example, it is proba- bly better to use this information directly than to categorize the agent as a nongenotoxic carcinogen, It is my view that "'studying'" rather than "'testing'" agents would give more useful information on carcinogen risk as- sessment. From this point of view, I am pleased to see that mechanistic information is attracting increasing attention. THE CRITICAL ROLE OF PEER REVIEW IN SCIENTIFICALLY-BASED CANCER RISK ASSESSMENT (Clay B. Frederick) lnff'oduction A variety of risk assessment guidance documents have recently advocated a more active role for peer review in scientific decision-making during the risk assessment pro- cess (e.g. Environmental ,Protection Agency (EPA) 1992. 1996; National Research Council, 1994: and California Envi- ronmental Protection Agency (CaFEPA), 19967. These rec- ommendations are largely based upon the traditional role that peer review has played in scientific decision-making over the last century. Although the effective use of peer review is generally acknowledged as being the most useful tool for establishing consensus and ensuring the quality of scientific decisions, peer review is also acknowledged to have certain potential pitfalls that can either bias or otherwise decrease the quality of the resulting recommendations. This review will be framed as answers to a series of ques- tions in order to address some of these potential sources of error and to assist in the development of high quality" risk assessments. The questions formed the basis of part of a panel discussion at the 1996 Annual Meeting of the Society of Toxicology on the EPA's proposed new cancer risk as- sessment guidelines (EPA. 1996). The perspective for this discussion is that of a bench scientist who has participated in numerous peer reviews and has discussed aspects of the process with many of his colleagues. The immediacy of the issue derives from the EPA's proposal of new cancer risk assessment guidelines that rely heavily on effective peer review for key scientific decisions in the risk assessment process. Does Risk Assessment Need Peer Review? Absolutely, yes! The institutionalization of peer review in the evaluation of scientific grant proposals, manuscript reviews, and for professional tenure decisions reflects its societal value. Traditionally. important scientific decisions that involve a substantive allocation of societal resources have been subjects for peer review. The sophistication of the review is typically scaled appropriately to the issue under consideration (e.g., two or three mail-ifi reviews to an editor for a manuscript, face-to-face meeting of a 3-10 member committee for grant reviews, etc.). The societal need for consensus scientific opinions on issues essentially mandates some form of peer revie~~. Unresolved issues tend to relate to the adequacy of the implementation rather than the intrin- sic need for the process. The only alternatives to peer review are generic policy decisions or the decisions of single indi- o o~ "~0 o

REVISED EPA CANCER ASSESSMENT GUIDELINES viduais--neither of which are generally associated with quality that good peer review provides. What Constituencies Care about Peer Review of Risk Assessments ? Essentially all constituencies that care about the quality of risk assessments have an interest in peer review. For dsk assessments that generally have an impact on society, these include elements of the general public, regulatory, agencies. politicians, academics, industrial scientists, industrial man- agers, public interest groups, lawyers, and the press. Each group has a different culture, perspective, and set of prod- ties. Although scientific peer review is generally confined to scientists with the appropriate technical background, the voice of many of the other constituencies can. and should. be heard as part of the decision-making associated with risk management. What Difficulties Are Encountered in Implementing Peer Review of Risk Assessments? The key to optimum effectiveness in peer review is ob- taining the involvement of the best quality and most objec- tive scientists in the area of concern. In practice, this may be very difficult, since the best peer reviewers are often overly committed to a plethora of other important projects (including other peer reviews). Generally, flexibility in the logistics of the review (date, location, number of reviewers. etc.) greatly facilitates the assembly of an appropriate peer review panel. However. the major barrier to implementing effective peer review often lies with the institution responsible for the risk assessment. Reticence in implementing and fully supporting an effective peer review policy often relates to a perceived loss of institutional or managerial control, impatience and uncertainty during the review period (which may be per- ceived as an unnecessary delay in the implementation of the risk assessment), and the cost of conducting peer reviews in the face of inadequate institutional resources. These reserva- tions relate as much to institutional culture as anything else, and they apply equally to government regulatory agencies as well as private institutions. Notably, institutions that have traditionally incorporated peer review in their critically deci- sion-making processes (e.g., grant review and tenure deci- sions by the National Institutes of Health and the use of advisory committees on new drug applications by the Food and Drug Administration) view peer review as an integral part of their institutional processes and not an unnecessary impediment to their function. What Is in Peer Review for the Peer Reviewer? Generally. the institutional implementation of peer review is considered by an outside advisory body or from the per- 31 spective of senior management. The availability and willing- ness of a pool of suitable peer reviewers is often taken fbr granted. But why would a "typical overloaded stressed-out scientist" with an appropriate level of professional expertise want to be involved in regulatory peer review': Laudable reasons tend to relate to a feeling of professional and civic responsibility, a desire to see intbrrnation gathered during laboratory research translated into societal benefits, and the enjoyment of working with other scientists to critically eval- uate and make recommendations on important societal is- sues. Malevolent reasons tend to relate to a desire to impose personal opinions or philosophy on the regulatory process without objectively evaluating the relevant information. Typically, peer review provides little or no compensation (although travel expenses are generally reimbursed), there- fore direct financial considerations are not a deternlining factor. What about Internal Peer Review? The use of scientists from within an institution to review other scientists' work from the same institution is often cited as an expedient means of conducting peer review. Indeed, internal peer review can be fast and relatively inexpensive relative to using a peer review panel composed of scientists from outside of the institution. However. internal peer review tends to reintbrce the policies, procedures, and assumptions of the institution rather than challenge them when they may be in error. In addition, internal peer review may provide less opportunity than external peer review for new knowl- edge and new technology to be used during the review pro- cess. What Is the Most Effective Model for the Peer Review Process? Effective peer review models maximize the effectiveness of all the resources in the process by minimizing resource inefficiencies, costs, and wasted time. Typically. this would involve the preparation of a relatively mature document for the peer review by appropriately trained staff that have been provided with adequate resources. For a risk assessment, an important part of this process is the gathering of all relevant dam by thoroughly reviewing the scientific literature, institu- tional files, and by publicly soliciting outside input. Follow- ing some level of internal review, the document and support- ing information should be submitted to an appropriately con- stituted peer review panel. To ensure accountability, a single individual should carry the responsibility of expediently con- vening an appropriate peer review panel and ultimately man- aging an appropriate written response to the panel's recom- mendations. Ideally, the panel would meet face-to-face to discuss the body of information used for the dsk assessment and to consider other information that may not have been used for the risk assessment. Face-to-face meetings allow

PAGE El" AL "chalk-talk'" discussions of technical issues that cannot be replicated by conference calls or by "mail-in" reviews. Un- fortunately, face-to-face meetings are the most expensive and most difficult to arrange logistically. A second option is to convene a conference call of the peer reviewers after circulating written copies of each reviewers comments to each of the other reviewers. Although conference calls allow some discussion of areas of disagreement between reviewers, they are ineffective for dealing with technically complex or contentious issues. The least desirable option is the mail-in review teither E-mail or letter) which allows no discussion of the issues among the reviewers, and leaves the resolution of differences among reviewers to the institution commis- sioning the peer review. How ShouM a Peer Review Panel Be Constituted? Inevitably. the issues of appropriate technical expertise, balance of expertise, and objectivity must be faced when either constituting a peer review panel or evaluating the recommendations of a panel. Balance of perspective and appropriate technical expertise are probably the most im- portant factors to consider in constituting a peer review panel. Individual biases and misconceptions tend to be di- luted in groups of four or more, and the normal processes of group dynamics in decision-making will tend to favor well-grounded consensus recommendations. Issues that can- not be resolved as consensus recommendations are likely to be issues that have not been resolved by the general scientific community: consequently, the lack of consensus of a peer review panel on an issue can be a valuable result of the process. How Should an Institution Use the Results of a Peer Review? In all cases, it is important to stress that the results of a peer review are advisory only. The ultimate responsibility for the risk assessment resides with the institution that pre- pared the risk assessment and commissioned the peer review. To acknowledge consideration of the recommendations of the peer review panel, the suggestions presented by the panel should be addressed with a written document. Scientifically based disagreement with a panel's recommendation is a le- gitimate response to a peer review. Ultimately, the risk re- suits of the peer review (and the institutional response) should be conveyed to the risk manager as pan of package of information evaluated in the subsequent risk management process. Conclusions The use of external peer review for risk assessments has not been a routine pan of the regulator).' process in many regulatory agencies. The current emphasis on the use of the "best quality" science as a basis for risk assessment implies the routine use of peer review as a basis for establishing scientific consensus. Although the goal of improving the scientific quality of risk assessments is admirable, it is not easy to implement high quality peer reviews in a cost effi- cient and expedient process. Since there are no perfect re- viewers (perfection defined by infinite wisdom and knowl- edge with no personal biases), constitution of an adequate number of well-balanced perspectives that are allowed to reach a group consensus may be the best that we can provide. The EPA's new cancer risk assessment guidelines depend heavily on the guidance from external peer review to deal with critical decisions in the process (adequacy of the justi- fication for a mode of action, justification for a biologically based risk assessment, etc.), and the success of these guide- lines may depend on the effective implementation of peer review processes. Hopefully, the EPA (and other institutions charged with implementing external peer review) will re- ceive adequate funding and resources to conduct these re- views efficiently. In summary, each of the critical decision points in a risk assessment must be determined by either a case-specific sci- entifi, c decision or by a general policy decision (default value). A wide variety of recent regulatory guidance docu- ments have advocated a much more active role for peer review in the risk assessment process. In particular, the Envi- ronmental Protection Agency's 1996 proposed cancer risk assessment guidelines invoke peer review for many key sci- entific decisions. As a consequence, the success of the guide- lines may ultimately hinge on the effective implementation of peer review procedures. Although peer review has tradi- tionally been the tool used by scientists to establish consen- sus and maintain quality in scientific decision-making, its effective implementation is dependent on acknowledging and avoiding potential pitfalls that can serve as impediments or introduce error or bias into the process. NATIONAL TOXICOLOGY PROGRAM (NTP) PERSPECTIVE ON THE ENVIRONMENTAL PROTECTION AGENCY (EPA'S) CANCER RISK ASSESSMENT GUIDELINES (George W. Lucier) The NTP strongly supports EPA's efforts to use all rele- vant scientific data in risk assessments. Advances in our knowledge of the mechanisms involved in chemical carcino- genesis are creating opportunities to strengthen the science base for risk assessments, and EPA's development of revised risk assessment guidelines is a laudable attempt to take ad- vantage of those opportunities. My comments will ( 1 ) sum- marize the uses of mechanism-based toxicology in cancer risk assessment, (2) list some of the pitfalls and oversimpli- fications in using this approach, and (3) summarize some spin-off benefits of EPA's new guidelines. Programs in

REVISED EPA CANCER ASSESSMENT G[,IIDEI.INES 33 mechanism-based toxicology should draw on the tools of molecular biology, which can characterize interactions of chemicals with critical target genes, to provide viable ap- proaches for the development of more accurate and inexpen- sive methods to perform not only the first step in risk assess- ment. i.e.. hazard identification, but also contribute to de- termining quantitative dose-response relationships and establish biomarkers for estimation of human exposure. These approaches can also help to understand species, strain. and individual differences in susceptibility and for species extrapolation (Lacier, 1995). Quantitative Dose-Response Relationships Assessment of dose-response relationships is often the most difficult and controversial issue in risk assessment. Data in experimental animals is usually obtained with rela- tively high doses because of limited resources and need to minimize the numbers of animals used. This requires use of methods to extrapolate health effects to exposure levels much lower than those for which experimental data are avail- able. Depending on the methods used, risk estimates may vary several orders of magnitude. Although ~gulatory deci- sions on potentially hazardous agents should not be delayed. biologically based models need to be applied when available and appropriate. These methods should be based on quantita- tion of critical molecular lesions over a wide dose range. Such models have been developed for dioxin, benzene, form- aldehyde, and other chemicals. Dose selection in bioassays and mechanistic studies must maximize the capacity to im- prove dose-response estimates. Effective use of biologically based models on a wide scale will require an intense effort to refine and develop methods for translating complex bio- logical data into mathematical terms suitable for risk assess- ments. Such approaches need to be reviewed and accepted by both the scientific and regulatory communities. Animal Models for Human Risk Another controversial issue has centered on the relevance of using animal models to estimate human risks. While in most cases animal experimental data are appropriate, it is recognized that there are situations where animal data may overestimate risk and others where it may underestimate risk. The relevance of a model can best be determined when mechanistic data are available which permit rational compar- isons between observed effects in experimental animals and expected effects in humans. More research on comparative mechanisms of toxicity is needed. This research should focus on both rodent and nonmammalian test systems and be di- rected at the development of more rapid and less expensive test systems. Human Exposure Assessment There is often inadequate information on human exposure to toxic chemicals in the general environment, although con- siderable data may be available lbr occupational exposures to these same chemicals. Increasing knowledge of the mech- anisms responsible tbr environmentally induced disease. • coupled with development of sensitive and specific tests to monitor the presence of a chemical in the body or an early biological effect of that chemical, are offering opportunities to monitor low-level human exposures. Validated exposure markers should be applied as part of the effort to determine the human burden of chemicals and the possible health con- sequences, in addition, the development of new tests need to be encouraged, and approaches need to be developed for validation of promising new tests. Biological Variation There is a wide variation in how parameters respond to pharmaceuticals, lifestyle factors, and environmental agents. The biological bases for these variations in response are now being discovered. Of particular importance are inherited genes that may predispose an individual to an adverse health outcome when exposed to certain classes of chemicals. It is now becoming possible, in some cases, to test individuals or populations for "at-risk genes," which, along with infor- mation being developed on sensitive subpopulations based on gender and age, should enable the true range of variation in response that might be expected to be determined. When this information is available, it should be used in risk assess- ments rather than default methodologies. Continued research to enhance the knowledge of gene/environment interactions is needed. There are some oversimplifications that should be avoided when using mechanism-based toxicology in can- cer risk assessment. First, categorization of carcinogens as genotoxic or nongenotoxic is not useful for dose-response evaluation. Evaluation of the entire NTP database (Portier et al., 1994) revealed that dose-response relationships (lin- ear or sublinear) for cancer incidence could not reliably be linked to positive or negative responses in genotoxicity assays. In fact, nongenotoxic carcinogens were more likely to exhibit linear behavior than genotoxic carcinogens~. The second oversimplification to be avoided is that toxic- ity causes cancer. Although chemically mediated cellular toxicity may predispose to cancer risk, there are several cases where toxicity alone and/or increases in cell proliferation cannot be linked to cancer risk. A third" oversimplification is that lifetime exposure of rodents to most chemicals at MTD doses causes an increase in cancer risk. While 50% of the chemicals evaluated by the NTP in rodent bioassays for cancer give positive results, only 20% of these chemicals tested because of significant human exposure are positive. On the other hand, 70% of those chemicals tested because of suspicion of carcinogenicity (i.e., positive result in an in vitro genetic toxicity test) cause cancer in rodents. There are several direct benefits that will emerge from implementation of the revised cancer risk assessment guide-

PAGE ET AL. lines. Use of the ED01 instead of the EDI0 as the benchmark dose will reduce some of the uncertainty in estimating human risks where dose-response data are available for critical mechanistic endpoints, as well as tumor incidences, the ED01 can be reliably estimated. A second point is that, in cases where use of a "margin of exposure" approach is appropriate, there will be increased emphasis on obtaining data on human body burdens for chemicals of public health interest. Data on body burdens are clearly preferable to using exposure or daily intake data alone since metabolic/clearance rates might be ve~' different between rodents and people. For example, the biological half-life for dioxin is 25 days in rats and 7-10 years in people. The revised EPA guidelines are consistent with other national and international activities. The use of all relevant data by the International Agency for Cancer Research in their evaluations of cancer hazard are discussed by Dr. Yamasaki in this paper. Similarly, the guidelines are consistent with the revised criteria for listing chemicals in the Biennial Report on Carcinogens: A Work in Progress (Environ. Health Perspect. 103(9), 806-807, September. 1995). These criteria now permit upgrading or downgrading re- sults of animal experiments; for example, an agent may be considered reasonably anticipated to be a human carcinogen if there is less than sufficient evidence of carcinogenicity in humans or laboratory animals; however, the agent, sub- stance, or mixture belongs to a well-studied, structurally related class of substances whose members are listed in a previous Annual or Biennial Report on Carcinogens as either a known-to-be human carcinogen, or reasonably anticipated to be a human carcinogen, or there is convincing relevant information that the agent acts through mechanisms indicat- ing it would likely cause cancer in humans. Likewise. conclusions regarding carcinogenicity in hu- mans or experimental animals are based on scientific judg- ment, with consideration given to all relevant information. Relevant information includes, but is not limited to, dose response, route of exposure, chemical structure, metabolism, pharmacokinetics, sensitive subpopulations, genetic effects, or other data relating tO hiechanism of action of factors that may be unique to a given substance. For example, there may be substances for which there is evidence of carcinogenicity in laboratory animals but there are compelling data indicat- ing that the agent acts through mechanisms which do not operate in humans and would, therefore, reasonably be antic- ipated not to cause cancer in humans. Finally. EPA's revised guidelines will stimulate research on mechanisms of carcinogenicity and the application of that information to improved dose-response evaluation, im- proved exposure assessment, improved selection of experi- mental models for human risk assessment, and better ways for identifying sensitive subpopulations. This research activ- ity will provide a more solid foundation for risk assessments and hopefully will help restore public confidence in regula- tory decisions. GENERAL DISCUSSION The open discussion generally focused on four main is- sues: risk communication, need for Peer Review Panels. need for continued evolution of knowledge and cancer assess- ment. and the complexities of biologically based models. Risk Communication The ability to effectively communicate changes in cancer risk estimates for specific chemicals resulting from the use of the revised guidelines was viewed as a major problem. It appears that biologically based risk assessments and margin of exposure analyses, as recommended in the revised EPA guidelines, will likely result in much lower risk estimates than those generated by the use of the default linearized multistage model. Regulatory scientists predicted that com- munication of the scientific basis and rationale for vastly different risk estimates to risk managers and/or decisions- makers and to the general public will be a major obstacle for them. Some, in fact, felt that decision-makers will be reluctant to accept changes, whereas the public (and often risk managers) generally will not understand or appreciate the scientific basis behind the changes. Peer Review Panels Considerable support was expressed for the use of Peer Review Panels (also referred to as Risk Assessment Advi- sory Committees) was generally considered as very valuable, especially if they are involved early on in the risk assessment process. It was expressed that. in addition to competent can- cer assessment scientists on such peer review panels, other scientific and public members should be included. This was considered desirable in order to obtain consensus in the sci- entific and public communities with the risk assessments performed or accepted by regulatory agencies. Some differ- ences in opinion existed as to whether peer review should be the responsibility of risk assessors or risk managers. Con- tern was also expressed that involvement of the general public in the risk assessment process would be rather frus- trating. Continued Evolution of Knowledge of Carcinogenesis and Risk Assessment It was recognized that the specific chemical risk assess- ments performed even now with the revised guidelines will require review and modification sometime in the future as knowledge of carcinogenesis and improved risk assessment methods become available. Such updates might routinely be scheduled (such as required every 5 years under the Clean

REVISED EPA CANCER ASSESSMENT GUIDELINES 35 Air Act) or specified at specific times as dictated by the courts. In other cases, revisions may not be routinely planned for but rather might be conducted at a time when the scien- tific or regulatory community declares that reevaluation is needed. This of course will be based on new knowledge of the chemical's properties and mechanisms of carcinogenic action. From the viewpoint of current knowledge versus past knowledge on which earlier risk estimate were based, many regulated chemicals may require reanalysis. For example. should all the 200 carcinogens in the Consensus Data Bank be reanalyzed? It was expressed that the regulatory agencies simply don't have the resources to undertake such a labor- intensive task. Obviously, some priodtizing system is needed. Regulatory scientists proposed that outside support from the regulated community should be involved in the reassessment of the regulated carcinogens. The resources required for reassessment of all currently regulated sub- stances would be enormous in terms of costs and staff time. Complexities of Biologically Based Models Several participants indicated that they already have been working and experime.ming with biologically based risk as- sessments. Their experience is that such models are quite complicated and fraught with uncertainties. This apparently is especially the case if one tales to examine certain hypothe- ses and the variability of risk when one considers susceptibil- ity among people and different exposures. Nevertheless. there was general consensus that use of biologically based risk assessments represents an important advance and should be vigorously pursued even if they are complex, data-rich undertakings. REFERENCES Allen. B. D.. and Fisher, J. W. (1993). Pharmacokinetic modeling of trichlo- roethylene and trichloroacetic acid in humans. Risk Anal. 13o 71-86.5. Ames, B. N.. and Gold, L. S. (1990). 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