United States
Environmental Protection
Agency
Office of Research and
Development
Washington, DC 20460
September 1988
EPA/600/8-88/089
Research to Improve Health
Risk Assessments (RIHRA)
Program

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TABLE OF CONTENTS
EXECUTIVE SUMMARY	iii
INTRODUCTION	1
Risk Assessment Framework	1
Uncertainties in Risk Assessment	1
Research Strategy	1
Topic 1: Analyses of Uncertainly in Risk Assessment	3
Topic 2: Integrated Exposure Assessment	3
Topic 3: Physiologically Based Pharmacokinetic Models	3
Topic 4: Biologically Based Dose-Response Models	4
Project Selection	4
Program Implementation	4
TOPICS FOR RESEARCH	6
TOPIC I: Analyses of Uncertainty in Risk Assessment	7
Issue 1.1: Uncertainty Analyses	7
TOPIC 2: Integrated Exposure Assessment	7
Issue 2.1: Human Exposure Models	8
Issue 2.2: Human Activity Patterns	8
Issue 2.3: Data Base on Indirect Exposure Parameters	9
TOPIC 3: Physiologically Based Pharmacokinetic Models	9
Issue 3.1 Experimental Absorption and Biological Parameter Data	10
Issue 3.2 Route-to-Route Extrapolation	10
Issue 3.3 Theoretical Models	11
TOPIC 4: Biologically Based Dose-Response Models	12
Issue 4.1: Inter/Intraspecics Extrapolation	12
Issue 4.2: Exposure Scenarios	13
Issue 4.3: Mechanistic Variation	13
SUMMARY	14
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EXECUTIVE SUMMARY
The Environmental Protection Agency (EPA) increasingly
relics on quantitative assessment of health risks to make
decisions about protection of public health. The utility of the
risk-based approach for decision making is dependent upon the
availability of an adequate data base that is appropriate for the
questions being asked. Insufficient data can lead to large
uncertainties that, in turn, allow wide latitude for interpreta-
tion. Thus, where the underlying scientific uncertainties are
great, the data may support diametrically opposed interpreta-
tions, each with dramatically different ramifications for re-
lated regulatory decisions.
In 1988, Congress recommended that the EPA's Office of
Research and Development (ORD) establish a systematic and
integrated Research to Improve Health Risk Assessments
(RIHRA) program. Although it was acknowledged that much
of ORD's ongoing research focuses on this issue, the Agency
agreed that it would benefit from a more formal and structured
approach. Consequently, S3 million in FY88 and $10 million
in FY89 have been earmarked for development of a targeted,
coherent research program to reduce uncertainties in the risk
assessment process, including both health and ecological risks.
The primary objective of the health research plan is the
development of a systematic and integrated program that
would be effective in improving health risk assessments.
Moreover, the emphasis is placed on identifying and address-
ing the significant uncertainties inherent in the risk assessment
process. This research program is designed to provide critical
daui on the relationship between exposure (applied dose), dose
to target tissue (delivered dose), and associated health effects.
The program emphasizes laboratory and field research that
will improve our understanding of basic biological mecha-
nisms, especially as they relate to our ability to extrapolate
from one set of circumstances (e.g., animals exposed to long-
term, high concentrations) to another (e.g., humans exposed to
long-term, low concentrations).
Based on the established guidelines for program develop-
ment, four general topic areas were selected for investigation.
The relationship between the major components in health risk
assessment and the principal topics to be addressed by this
research program is shown schematically in Figure 1. Two
topics, "Analysisof Uncertainty" (i.e., assessmentofthemajor
contributors to uncertainty for a given risk assessment) and
"Integrated Exposure Assessment" (i.e., improvements in the
quality and consistency of data used to assess exposure), are
defined to be relatively narrow in scope. Two other topics,
"Physiologically Based Pharmacokinetic (PB-PK) Models"
and "Biologically Based Dose-Response (BB-DR) Models,"
are defined to be broad in scope and to include a variety of
health endpoints and exposure scenarios. The construction of
PB-PK models can be used to establish a quantitative relation-
ship between exposure and dose delivered to a target site in
animals and humans under a variety of conditions. The devel-
opment of BBDR models allows for delineation of a quantita-
tive relationship between the dose and associated health ef-
fects. In summary, by focusing the resources through a struc-
tured and integrated program, it will be possible to make
significant improvements in EPA's health risk assessments.
Major Components of Major Components
Health Risk Assessment of RIHRA
Environmental
Levels
Applied Dose
Delivered Dose
(Target)
Health Effects
Exposure
Assessment
Physiologically Based
Pharmacokinetic
Models
Biologically Based
Dose-Response
Models
^ Uncertainty Analyses
RISK ASSESSMENT
Figure 1. Relationship Between the Major Components of
Health Risk Assessment and the Major
Components of the RIHRA Program .
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INTRODUCTION
This document describes an integrated and systematic re-
search program that will be carried out by the Office of
Research and Development (ORD) to improve health risk as-
sessments. It is generally acknowledged that substantial gaps
exist in the scientific data bases that underlie the risk assess-
ment process. In many instances, quantitative risk assessment
is precluded because of the paucity of appropriate data. Even
in cases where quantitative risk assessment is feasible, critical
data gaps typically ex island require the application of numer-
ous assumptions, which represent "fall back" or "default"
positions. This new program will reduce important uncertain-
ties in health risk assessments ihrough targeted laboratory and
field research.
RISK ASSESSMENT FRAMEWORK
The elements of the risk assessment process, as well as the
interrelationships between research, risk assessment, and risk
management, are shown in Figure 2. Research provides the
scienti fic data bases that underl ie the three steps in risk assess-
ment; namely, hazard identification, dose-response assess-
ment, and exposure assessment. The uncertainties associated
with these sleps, resulting primarily from deficiencies in the
quality and quantity of appropriate data, lead to uncertainties
in quantitative health risk assessment.
UNCERTAINTIES IN RISK ASSESSMENT
Uncertainties in the risk assessment process are the result of
one or more conditions: 1) lack of appropriate and adequate
data or underutili/ation of existing data, or 2) a fundamental
lack of understanding of the basic underlying physical, chemi-
cal, and biological mechanisms. The most critical problematic
areas in risk assessment involve uncertainties about extrapo-
lating observed effects from one set of circumstances (e.g.,
cancer incidence in experimental animals subjected to high,
chronic exposures in controlled experiments) to an entirely
different set of circumstances (e.g., individual excess cancer
risks in humans experiencing intermittent, low-level expo-
sures). These uncertainties arc encountered while extrapolat-
ing from species to species, from one individual or subgroup to
another individual or subgroup within a particular species, and
from one set of exposure conditions to another. The uncertain-
ties arise not simply from insufficient data, but also from a lack
of fundamental understanding about the relevant underlying
physical (e.g., atmospheric dispersion characteristics, human
activity patterns),chemical (e.g.,chemical rcactionsand trans-
formations), and biological (e.g., metabolism, disease proc-
esses) mechanisms that affect the validity of the extrapolation
assumptions. Research to reduce these uncertainties must
focus on development of an understanding of the key processes
and how these processes interact to assess either exposure or
dose-response.
Basically, risk characterization can be thought of as the
combined result of dose-response assessment and exposure
assessment (See Figure 2). Thus significant uncertainties in
either factor can cause uncertainty in the final risk estimate. In
the dose-response area, EPA's Carcinogen Assessment Group
(CAG) has estimated that uncertainty in only five "fall-back"
or "default" assumptions can lead to three or four orders of
magnitude difference in the risk estimate for a carcinogen.
Similarly, CAG analyses have demonstrated that incorpora-
tion of knowledge about the underlying mechanisms of toxic-
ity and dose-rate information can result in estimates of carc ino-
genic risk that vary by up to six orders of magnitude. For
systemic toxicity, uncertainties of several orders of magnitude
arc possible. Moreover, a high degree of uncertainty may be
introduced by failure to test chemicals adequately over a
sufficient range of health endpoints. For example, if a risk
assessment is based on an inappropriate or insensitive end-
point, the final estimate may be a significant underestimation
of the actual health hazard.
Uncertainties may also be large for the assessment of human
exposure. EPA's Office of Air Quality Planning and Standards
(OAQPS) has delineated some of the uncertainties in the as-
sessment of exposure to carcinogens in the air and the OH ice
of Solid Waste (OS W) has reviewed the magnitude of uncer-
tainties inherent in selected fate and transport models for both
ground and surface water. These analyses indicate that there
arc many potential sources of uncertainty in exposure assess-
ment that can lead to differences of several orders of magnitude
in the final risk estimate.
RESEARCH STRATEGY
Substantial uncertainties necessitate the application of ap-
propriate assumptions throughout the risk assessment process.
Significant unknowns exist in all aspects of risk assessment,
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Research
Risk Assessment
Risk Management

Agency decisions
and actions
Exposure Assessment
(What exposures are
currently experienced
or anticipated under
different conditions?)
Dose-Response
Assessment (What is
the relationship
between dose and
.incidence in humans?)
Evaluation of public
health, economic,
social, political
consequences of
regulatory options
Development of
regulatory options
Risk Characterization
(What is the estimated
incidence of the
adverse effect in a
given population?)
Hazard identification
(Docs the agent
cause the adverse
effect?)
Laboratory and field
observations of
adverse health
effects and exposures
to particular agents
Field measurements,
estimated exposures,
characterization of
populations
Information on
extrapolation methods
for high to low dose
and animal to human
Figure 2. Elements of Risk Assessment and Risk Management (From: National Academy of Sciences INASI, 1983.)
including emission estimates, pollutant fate and transport
models, ambient measurements, human exposure estimates,
and dose-response assessment. Because the scope and magni-
tude of these problems are extensive and the resources arc
limited, it is important that the available resources be focused
on the most significant problems.
Based on the goal of developing an integrated and systematic
research program that significantly improves health risk as-
sessments, three important decisions were made about the
focus of the plan. First, our collective judgment and under-
standing of the risk assessment process was used to narrow the
scope of the program. Accordingly, the RIHRA program will
focus on elucidating the relationship between exposure (ap-
plied dose), internal dose to the target tissue (delivered dose),
and associated health effects (Sec Figures 1 and 3.). Second,
emphasis will be given to non-cancer health endpoints, such as
neurological, pulmonary, and reproductive effects. This em-
phasis is appropriate because EPA is increasingly called on to
estimate these kinds of risks for environmental exposures to a
variety of contaminants. In general, the risk assessment issues
are less wel 1 defined and articulated for non-cancer, as opposed
to cancer, health effects. Third, much of the research needed to
reduce the uncertainties of risk assessment is iterative in
nature; that is, the research progresses in multiple stages, with
significant outputs at each stage. This dictates that both short-
term and medi um to long-range research planning and stabi I ity
are required for this program.
As shown in Figure 3, four major topics were selected for
inclusion in the program: analysis of uncertainty in risk assess-
ment; integrated exposure assessment; physiologically based
pharmacokinetic models; and biologically based dose-response
models. It is important to recognize that the RIHRA program
represents a comprehensive overview of the research needs to
reduce uncertainties in specific components ol the risk assess-
ment process. It provides an intellectual framework to design
and implement a coherent research program that will address
identified issues within the broad topic areas, Even with this
narrow focus, resolution of these issues is likely to require a
concerted effort over time. An overview of each topic is
presented below.
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Risk Characterization
Exposure Assessment
Health Effects Assessment
Environmental'
Levels
"Applied Dose	
(point of contact)
Delivered Dose
(target dose)
Hazard I. D.
(qualitative)
Dose-effect
(quantitative)
Integrated Exposure
Assessments
Physiologically Based
Pharmacokinetic Models
Biologically Based
Dose-Response Models
Analyses of Uncertainty in Risk Assessment
Figure 3. Schematic Representation of the Relationship Between the Four Topics Included in RIJIRA and the Major
Components of Risk Characterization.
Topic 1 — Analyses of Uncertainty in Risk
Assessment
tions used in health risk assessments through development of
a standardized approach.
The degree of uncertainly in the qualitative and quantitative
aspects of risk assessment is often poorly understood. Re-
search issues related to this topic address the clarification of
assumptions and the definition of the uncertainty associated
with each of these. Analyses will be conducted to determine
which uncertainties are most critical in selected risk assess-
ments anil to understand the impact of these uncertainties on
the ultimate risk assessment.
Topic 2 — Integrated Exposure Assessment
Exposure assessment (i.e., contact between chemical and
humans) is based on either ambient or biological measure-
ments. Ambient measurements can be further subdivided into
direct (e.g., individual monitors) and indirect (i.e., combining
human activity data with pollutant measurements in important
microenvironments) approaches. Research related to predic-
tive exposure techniques will focus on improvement of expo-
sure models through collection of appropriate activity pattern
dam, microenvironmental pollutant concentration data, and
human dose measurements. Another research area will be
devoted to improving the quality and quantity of direct expo-
sure assessments, which will be used to generate more realistic
exposure estimates. An additional research area will address
the uncertainty generated by inconsistent exposure assump-
Topic3—Physiologically Based Pharmacokinetic
(PB-PK) Models
Although the trend is to base quantitative risk assessments
on dose delivered to the site of toxic action (delivered dose),
measurements of applied dose (or exposure concentration) are
frequently used as surrogates for the delivered dose, which is
usually unknown. Better data on dose delivered to target tissue
will help to reduce uncertainties associated with extrapolation
from one route of exposure to another, from chronic to acute
exposure, from high to low exposure, and from one species to
another. While biological factors must also be considered
when assessing risk, it is important first to account for the
effects of the duration, magnitude, and frequency of the expo-
sure on the dose to the target tissue (i.e., pharmacokinetics).
One area for research will be the accumulation of more
experimental data relative to the effective dose responsible for
biological effects, including the influence of varying exposure
parameters (e.g., duration) on delivered dose. A second re-
search area will address identification of assumptions and
conditions for extrapolation from one route of exposure to
another. Efforts in this area will focus on reviewing and
summarizing information related to routc-to-routc extrapola-
tions, highlighting critical assumptions and limitations, pro-
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viding guidance for risk assessments, and recommending
future directions for research. A third research area will con-
centrate on development of theoretical models and computa-
tional methods for making intra- and interspecies dosimetric
comparisons. These pharmacokinetic models will depend not
only upon physiological parameters of the systems being
modeled, but also upon molecular structures and reactivities of
chemicals under consideration. Validation of the models will
allow scaling of exposure, dose, and effect observed in one
situation to a completely different situation (e.g., scaling from
animals exposed in a laboratory to humans exposed in an
ambient environment).
Topic 4 — Biologically Based Dose-Response
(BB-DR) Models
Although a key element in the risk assessment process is
estimating the incidence of a specific health effect, human
exposure data at relevant levels are not available in most cases.
Risk is then generally assessed by high level exposure data
from species other than humans and applying an appropriate
strategy to extrapolate. A biological mechanism orientation
will be used to focus on thcconditions under which testspccies
and test systems can be used to predict toxicity in humans.
However, since much remains to be understood about the
biological aspects of the test species, latitude must be left to
incorporate new data into the models. New data will be
incorporated into models which will provide insight into the
variations that occur in different species and under different
exposure situations. The conditions for which data from test
species and test systems can be used to predict human toxicity
will also be explored. Factors contributing to a health effect of
concern will be identified, and directions for research will be
dependent upon the current state of mechanistic knowledge for
that particular effect.
Research areas address intra- and interspecies extrapolation
(e.g., mechanisms of action, species sensitivity), extrapolation
of health risk across different exposure scenarios (e.g., vari-
ations in route of administration, dose, or dose rale), and incor-
poration of recent mechanistic concepts into BBDR models
(e.g., potential for different biological mechanisms to elicit,
initiate, or contribute to health effects). Areas of investigation
will include pulmonary, reproductive/developmental, neuro-
logical, immunological, and carcinogenic effects.
PROJECT SELECTION
The four topic areas described above constitute the frame-
work for a structured health research program. The desired
objective of reducing uncertainties in risk assessment cannot
be achieved unless the projects developed to address these
topics arc supportive of the programmatic goals. To this end
four major decision criteria were used to determine the appro-
priateness of individual projects for inclusion in the program.
1.	Projects should focus on major significant uncertain-
tics and knowledge gaps in Agency risk assessments.
Important areas for research include assumptions and
extrapolations that arc used frequently and in which we
have little confidence.
2.	Projects should have a reasonable probability of
success. The proposed work should be technically fea-
sible in terms of existing expertise, resources, and
knowledge. The overall program of research should
produce a mixture of both short- and long-term products
of use to the Agency in risk assessments.
3.	Results of the research should directly support the
needs of the Agency's risk assessors. Scientists in EPA
and elsewhere should be able to apply the results of the
research in risk assessments.
4.	The results of projects should ultimately have wide
application. Results should be widely useful and not be
focused on specific situations of limited use. Ideally, the
short-term products of this research would be of imme-
diate utility to the Agency, while providing logical
building blocks for the long-term improvement of risk
assessment methodologies.
Furthermore, the projects must be consistent with the EPA
mission and must be the kind of work that EPA (and ORD) are
expected to perform; that is, the projects are expected to
provide results appropriate to EPA's legislative mandates and
regulatory authorities, and to be useful to Program Offices.
Since a large amount of the base program addresses other key
elements of risk assessment, the ultimate success of the
RIHRA program has a direct and, in some cases, a dependent
linkage to the ongoing base research program. Finally, al-
though projects selected will have high relevance and a reason-
able probability of success, they will not yield instantaneous
results. Much of the research needed to reduce the uncertain-
ties in risk assessment is iterative in nature; that is, the research
progresses in multiple stages, with significant outputs at each
stage. This dictates that both short-term and medium- to long-
range research planning and stability are required for the
success of this program.
PROGRAM IMPLEMENTATION
Formal responsibility for the RIHRA program will rest with
the EPA Interdisciplinary Research Committee, and more
specifically, with the RIHRA Subcommittee. As shown in
Figure 4, the subcommittee will be composed of the Office
Directors (and other key designees) from the participating
ORD Offices. It will be the responsibility of this committee to
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design, implement and manage the RIHRA program. The
Subommittec will coordinate the intramural (e.g., Program
Offices, Science Advisory Board, Risk Assessment Council)
and extramural (e.g., outside peer-review groups) reviews of
the RIHRA program, as well as be responsible for ensuring that
the reviews are used to strengthen and improve the research
program. The S ubcom m ittee w il 1 al so establ i sh working groups
for each of the major topics that are defined in this document.
r
These working groups will be composed of one permanent
member from each participating office and a varying number
of other ORD scientists. The working groups will integrate
input from their respective offices to develop a focused re-
search plan (down to the project level) for each topic. These
research plans will be reviewed and approved by the Subcom-
mittee.
Interdisciplinary
Research Committee
Program Offices
Risk Assessment
Council
Science Advisory Board ¦
RIHRA Subcommittee
( Participating ORD Office Directors)
Extramural
Peer Review
Working Groups
(1 Permanent Member/Office/Topic)
I	1	1	1	1
Topic I	Topic II	Topic III	Topic IV
Uncertainty	Exposure	Physiologically Based Biologically Based
Analysis	Assessment	Pharmacokinetics	Dose Models
Figure 4. Proposed Implementation Scheme for the Research to Improve Health Risk Assessments (RIHRA) Program.
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TOPICS FOR RESEARCH
Thus far, most risk assessments have assumed a priori that
an equivalency of response exists between animals and hu-
mans. As one proceeds from the molecular level or biochemi-
cal event toward injury at the tissue or organ level, that
assumption m ay become less tenable because of variables such
as species differences in repair processes and levels of antioxi-
dant enzymes. If it is sufficiently high, the dose can produce
damage at any level from the target molecule to the intact
organ, resulting in various disease states. On the other hand,
host defense and/or compensatory systems could intervene
and might prevent or repair the damage if it is not sufficiently
severe. Disease outcome is also heavily dependent upon deliv-
ered dose and dose-time relationships. Under some scenarios,
defense systems may play a role in the etiology of diseases. The
interplay between dose, defense, and outcome is a dynamic
one. The lack of information on these interrelated events
results in significant uncertainty in current risk assessments
and, as a result, the use of a variety of default assumptions.
Due to the paucity of data in many areas, assumptions must
be made at various stages of the risk assessment process.
Careful consideration of these assumptions for various health
effects and exposure scenarios can be useful in the identifica-
tion of research needs to improve future risk assessments by
replacing assumptions with scientifically defensible data. If
the research docs not refute the assumptions but the new data
are not yet sufficient to stand alone, this may lead instead to a
more defensible default assumption. In either case, such re-
search will increase our confidence in applying the assump-
tions used in Agency risk assessments.
In recent years, progress has been made in developing
mechanistic models as a means of investigating and improving
extrapolations. In such models, the key physiological and
biological elements and processes, as well as their interactions,
are described. Well constructed models trace the consequences
of variation in any key element as it differs among species or
dose levels. Such models can reduce the uncertainties in
extrapolation in the following ways: 1) The structure of a
model embodies a particular theory about what underlying
processes are important in the extrapolation and how different
elements interact. The model provides a context within which
to evaluate the impact of hypotheses about pharmacokinetics
or mechanisms of toxic action. 2) Species differences in the
underlying biological processes can be determined experimen-
tally, and the impact of these differences on the extrapolation
process can then be modeled. This provides a means of devel-
oping rational, scientific bases for interspecies extrapolation
factors. 3) Differences in the operation of biological processes
at different dose levels can be experimentally determined and
incorporated into the models. For example, this can allow dif-
ferences in DNA repair, different levels of cytotoxicity, and
various non-linear biological effects to be incorporated into
low-dose extrapolation. 4) As new data and theories about
special mechanisms of toxic action arc developed, mechanistic
models provide a means for their quantitative incorporation
into extrapolation. For example, the impact of very different
levels of chemical stimulation of peroxisome proliferation in
different species could be accounted for by modeling the con-
sequences to the chain of biological processes, i.e., carcino-
genesis.
In summary, the advantage of the mechanistic approach is
that it allows the overall process of extrapolation to be broken
up into its biological elements. Experimental data can be
developed on independent elements, and the consequences to
the overall extrapolation determined. As knowledge of the
underlying processes improves, the biological realism of the
model improves, and an experimentally testable basis is devel-
oped for extrapolations that must currently be done on the basis
of assumptions. The models themselves are generic and are
applicable to a variety of chemicals, but they can be adjusted
to incorporate chemical-specific effects (such as metabolic
differences across species or particular mechanisms of toxic-
ity) by the use of experimental data on the effects of a chemical
on key biological processes that are elements of the model.
The following sections highlight the specific research topics
that are proposed for emphasis in this program. An overview
is included to describe why these topics are important, what
research they would contain, and where they contribute to the
risk assessment process. Although the RIHRA program is pre-
sented in a somewhat categorical hierarchy (i.e., topic/issue/
activity), it is realized that various research activities may
provide important data across these categories (e.g., assessing
the effects of varying exposure conditions on delivered dose
and health outcome). This will be especially true of projects
that are less target-organ specific.
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TOPIC 1: ANALYSES OF UNCERTAINTY IN
RISK ASSESSMENT
In characterizing the health risks of environmental pollut-
ants for Agency decision makers, the degree of uncertainty in
the qualitative and quantitative aspects of risk is often poorly
understood. A framework is needed to delineate clearly the
various assumptions and alternatives and the degree of uncer-
tainty associated with each. The following research issue
related to this topic will be pursued.
Issue 1.1: Uncertainty Analyses
Evaluation of major uncertainties in the risk assessment
process as a whole is needed. A rigorous evaluation of where
uncertainty is most critical in risk assessments that are used for
decisions would improve planning and implementation of
research. Granted that much uncertainty exists, this activity
will address whether these uncertainties are of such magnitude
as to make potential differences in decisions. If so, the types of
uncertainties (extrapolation, source assessment, etc.) will be
described and, if possible, quantified. This activity also will
include investigation of what the end users of risk assessments
(i.e., decision makers) would like to see in the way of uncer-
tainty assessment, including both quantitative and qualitative
aspects.
Activities within this issue will be a continuation of the
current Estimating Assumptions in Risk (EAR) Project initi-
ated by the Risk Assessment Council and an extension of the
Risk Assessment Forum projects on uncertainties in exposure
assessment that will be initiated in FY88. These activities will
include further efforts to identify major assumptions and to
assess the magnitude of each. New efforts will be initiated to
develop the data base supporting the qualitative and quantita-
tive work described above, with case studies being developed
to illustrate the numbers and impacts of the uncertainties in
specific risk assessments.
Projects under this issue might include several which ex-
plore possible approaches to the problem of uncertainty analy-
sis building upon such formal disciplines as decision analysis
theory or evaluating the use of Monte Carlo simulation for
assessing environmental sources of risk as compared to other
sources (food, lifestyle, etc.). A number of such approaches
have been recognized as potentially useful, but further work
will be needed to select those better suited for this task.
TOPIC 2: INTEGRATED EXPOSURE
ASSESSMENT
Over the past several years, exposure assessors at EPA and
elsewhere have approached the problem of assessing the
exposure (contact between chemical and organism) or dose
(amountenteringthe organism aftercontact) in three ways,one
direct and two indirect The direct measurement approach
involves real time measurements of contact intensity through
the use of personal monitors such as radiation badges or active
devices that pump and trap volatile chemicals, through analy-
sis of the amounts and contamination levels of food and water
ingested, and through methods to measure dermal exposure.
The indirect methods can either be predictive, using models for
fwllutant behavior or human (ecological) behavior or, under
limited conditions, they can be reconstructive, using body
burden and knowledge of pharmacokinetics to back-calculate
what the exposure must have been to result in the observed
levels. All of these methods have strengths and weaknesses,
and all have associated uncertainties for their intended uses.
Reducing uncertainty in the reconstructive approach is dis-
cussed separately under Topic 3.
Predictive exposure assessment techniques have been par-
ticularly appealing to a regulatory agency such as EPA, since
they allow the evaluation of the impacts that regulatory options
have on risk. Predictive techniques need not only estimate (or
measure) concentrations of pollutants but may also relate those
media pollution levels to what is being contacted by the target
populations. Clearly, living organisms are mobile in the envi-
ronment and the assumption of constant levels of exposure
over time for an individual or population is at best an approxi-
mation, at worst a major misrepresentation of the actual situ-
ation. In the case of human exposure, knowledge of human
activities, activity patterns, and ways to incorporate this infor-
mation into the assessment has long been a weak link and thus
the origin of much uncertainty in exposure assessment. The
first two issues discussed below (2.1 and 2.2) deal directly with
reducing that uncertainty.
A second major area of uncertainty is how the data for
exposure assessment are taken in the field. For measurements
to be used in predictive assessments and also for measurements
for directly determining exposure, the methods used to collect
the data are particularly important if the data are to be used
appropriately in an assessment to reach conclusions with
minimal uncertainty. Of particular recent interest in this area,
for example, is the question of how a series of short-term
duration exposure peaks would differ in a risk context from
equivalent lifetime long-term exposures at fairly constant but
lower levels, and how this information can best be measured in
the field and incorporated into the exposure assessment. Issue
2.3 addresses this topic, which is related to the work proposed
under Issue4.3 (which addresses how information from differ-
ent exposure conditions would be used in a dose-response
relationship). Taken together, Issues 2.3 and 4.3 will reduce
uncertainty in risk assessments by making the assessments
more closely describe what happens in the actual environment.
A third major area of concern in reducing uncertainty in
exposureassessments is the inconsistency in assumptions used
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by various assessors for similar exposure situations. This often
leads to two assessments of the same situation done by differ-
ent assessors (for example, an Agency assessment of a Super-
fund site and an assessment sponsored by a potentially respon-
sible party) which use somewhat different methodology and
parameter values, and thereby reach estimates of exposure or
risk that are substantially different. Issues 2.1 to 2.3 will also
address the way EPA approaches exposure assessment, both
by developing data that can be used consistently across many
assessments, and by standardizing the approach to estimating
population exposures related to certain commonly evaluated
situations such as incinerators, waste sites, or indoor air.
In summary, the proposed program in exposure assessment
focuses on three major areas of uncertainty: acquiring better
information on human activity patterns as they relate to expo-
sure estimates, improving methods to obtain exposure assess-
ment data, and standardizing the ways the Agency uses these
data. The following paragraphs discuss the issues in more
detail.
Issue 2.1: Human Exposure Models
More work is needed to develop and validate human expo-
sure models which can generate realistic predictions of
exposure to chemicals using human activity patterns and
source information. Human exposure models seek to combine
the concentrations of pollutants people experience in various
microenvironments (microenvironmental exposures) with the
time spent in those microenvironments (human activity pat-
terns), and to integrate this information with the resulting doses
experienced from those microenvironments. Such models
should address all the microenvironments in which people visit
or reside (homes, stores, schools, subways, buses, automo-
biles, workplace) and must include multiple routes of expo-
sure (air, food, drinking water). In particular, they should take
into account indoor and in-transit microenvironments. The re-
search problems to be addressed in human exposure model
development lie not only in development of improved expo-
sure models based on existing data (2.1.1), but also in validat-
ing these models (2.1.2).
2.1.1: Development of Human Exposure Models.
Research on this topic will proceed by first constructing
human exposure models for a family of important pollutants
that EPA regulates (e.g., respirable particles, volatile organic
compounds, semivolatile organics, formaldehyde) using the
best m icroen vironmental data and the best activity pattern data
available. For those pollutants for which microenvironmental
field data are missing, special microenvironmental field inves-
tigations will be conducted to construct the needed submodels.
The human activity pattern data and resulting microenviron-
mental concentration data will combine human activities, time
budgets (See Issue 2.2), and microenvironmental concentra-
tions using a generalized exposure equation. Suitable pharma-
cokinetic models will be incorporated into the resulting expo-
sure models to estimate body burden and dose from these
chemicals.
2.1.2: Model Validation.
Once the models are developed, they will be validated by
testing them with field data collected in total human exposure
field studies for a variety of situations. Uncertainty ranges
around the predictions will be characterized. After the uncer-
tainty of the model is characterized (validation phase), guid-
ance for the risk assessor in the use of human exposure models
will be incorporated into guideline documents. The guidelines
will include discussion of the appropriateness of various expo-
sure situations and the expected accuracy/uncertainty of the
models.
Issue 2.2: Human Activity Patterns
More data are needed on human activity patterns to improve
exposure analyses in risk assessments. Human activity pat-
terns, sometimes called "time budgets," are records of what
people do, where, when, and for how long. Recent findings
from field studies of human exposure, such as the Total
Exposure Assessment Methodology (TEAM) studies, have
shown that an individual's activities are critical in explaining
the exposures of the population to environmental pollutants.
Current predictive exposure assessment methods often use
assumptions that essentially treat an entire population as a
homogeneous unit rather than a collection of individuals. This
is done for the most part because the aggregate data on
population activity patterns are unknown. Development of
these data will allow the Agency to advance to a much more
realistic way of predicting exposures using probabilities. For
example, instead of using a worst-case scenario, activity pat-
tern information will allow exposures to be presented as a
frequency distribution, allowing statements to be made about
the average case, the 90th percentile exposure, etc. Thus
current exposure assessment methods will be replaced by a
new generation of techniques.
The initial phase will entail a critical review of all previous
activity pattern-time budget studies and the subsequent devel-
opment of an improved activity pattern questionnaire. This
questionnaire will focus on those activities which result in
exposure to pollutants. Part of this task will include develop-
ment of an automated data-logging activity diary. (The devel-
opment of a microprocessor-driven activity diary would be a
major innovation in these studies and should result in much
improved data.)
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Issue 2.3: Data Base on Indirect Exposure
Parameters
More work is needed to improve our data base on parameters
used to make indirect exposure estimates and to clarify how
to use them. More information is needed on the ranges and
distributions of parameters used in indirect exposure assess-
ments, such as ingestion rates, exposure durations, contact
rates, and short-term vs. long-term exposures. The Regions
have repeatedly requested guidance on such topics to improve
consistency in risk assessment. Guidance is also needed on
how to apply these factors to create different scenarios such as
typical and reasonable worst case.
Two topics that will receive special attention under this issue
relate to 1) predicting the incidental soil ingestion of children
based on site-specific parameters such as ground cover and
weather; and 2) determining the contribution of short-term
peaks to total exposure. Significant controversy exists about
the amount of soil ingested by children, and this is a very
significant exposure route in many assessments. Field work
will be done to develop the data base needed to establish the
relationship among these variables.
Also, it has become clear that for many pollutants, short-
term peaks are extraordinarily important contributors to expo-
sure. Besides their importance as contributors to exposure,
short-term peaks are important in the dose-response portion of
the risk assessment (see Issue 4.3). Methods will be pursued for
measuring short-term peaks and then incorporating this infor-
mation in establishing the dose-response relationships. These
data would then be used to supply risk assessors with basic
parameters and ways to incorporate these parameters into
exposure assessments.
TOPIC 3: PHYSIOLOGICALLY BASED
PHARMACOKINETIC (PB-PK) MODELS
The trend over the last few years has been to base quantita-
tive risk assessments on the "delivered dose"—the dose of
proximate toxicants, whether parent compound or metabolite,
at the tissue site of toxic action—rather than on the applied
dose or ambient concentration. The determination of this
delivered dose is an extension of exposure assessment, in that
the direct exposure of the actual target tissue is examined free
of the various physiological fate and transport processes by
which the body filters, attenuates, degrades, and modifies
compounds absorbed from its environment. Uncertainly will
be reduced by knowing more about the effects of different
conditions of exposure on the amount and pattern of delivered
dose. For example, examination of delivered dose will be very
useful in comparing the toxic results of exposures by different
routes of administration. In this way, extraneous factors such
as different degrees or rates of absorption can be accounted for,
resulting in more meaningful comparisons. The ability to
estimate tissue-level doses also is necessary for progress in
mechanistic biological modeling of toxicity, which will re-
quire extensions of exposure assessment to the internal sites
where these mechanisms occur.
In risk assessment as currently practiced, measurements of
applied dose or exposure concentration are used as surrogates
of the unknown delivered dose. The equivalencies among
different conditions of exposure are set by assumptions, many
of which have little empirical support and, therefore, represent
sources of uncertainty. Among the most critical uncertainties
associated with extrapolation from experimental to actual
conditions are assumptions about: (1) route-to-route extrapo-
lation-comparability of exposure by different routes of ad-
ministration (by accounting for differences in absorption,
bioavailability, and first-pass metabolism); (2) chronic-to-
acute extrapolation-comparability of different regimes of
exposure, such as the effect of repeated versus single dosing on
dose delivery, and the equality of episodic, peak, and chronic
exposures totalling the same cumulative dose (by comparing
the resultant delivered doses); (3) high-to-low-dose extrapola-
tion-proportionality between external exposure level and the
resulting delivered dose for high exposure studies, compared
to lower levels typical of environmental exposure (by account-
ing for sources of non-proportionality such as saturation of
metabolism, utilization of different pathways of biotransfor-
mation, and non-linear binding); and (4) species-to-species
extrapolation -scaling or translation of dose to determine expo-
sures yielding equivalent doses in different species, especially
when extrapolating toxic effects in experimental animals to
those expected in humans (by examining species differences in
the degree of delivery of given applied doses).
One way to reduce these uncertainties is to obtain data on
doses at a more biologically meaningful level, i.e. delivered
dose at the target tissue. Of course, the examination of deliv-
ered dose does not answer all questions about extrapolation in
risk assessment, since the equivalency of effects across species
is determined not only by relative dose delivery but also by any
species differences in reactivity or susceptibility to a given
delivered dose. Similarly, the extrapolation of effects to low
doses or from acute to chronic exposures depends not only on
the delivered dose differences in these circumstances, but also
on the relative toxicological effects of different degrees and
durations of tissue exposure to the proximate toxicant.
The ability to determine patterns of internal exposure at
particular tissue sites focuses attention on the mechanisms of
action. For example, it may not be clear at which target site the
delivered dose should be described. Depending on the mecha-
nism of action, the toxic response may be a function of quantity
of metabolite formed, number of adducts or other covalent re-
action products formed with crucial cellular macromolccules,
extent of reversible binding to specific receptors, average
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toxicant concentration, peak toxicant concentration, or dura-
tion spent above a crucial concentration. There may becounter-
vailing repair processes of limited or perhaps saturable effi-
cacy. These other factors can and probably do vary among
species, strains, sexes, previous histories of exposure, and
physiological condition of the subjects. In summary, although
examination of delivered doses can remove a great deal of
uncertainty from the various extrapolation processes in quan-
titative risk assessment, it is not a panacea. The other biological
factors cannot be addressed, however, without first accounting
for and eliminating the confounding and obscuring effects of
dose delivery and pharmacokinetics. Thus, progress in phar-
macokinetics is central to performing biologically rational risk
assessments.
Issue 3.1: Experimental Absorption and
Biological Parameter Data
More experimental and physiological data relative to the
effective dose responsible for biological effects are needed
for risk assessments. Often both the amount and the biologi-
cally active form of the toxicants are unknown. This results in
the use of uncertainty factors to a greater extent than would be
necessary if appropriate experimental data on the absorption,
metabolism, transport, and elimination of the parent com-
pound and its metabolites were available. Such experimental
data can be coupled with studies on toxic mechanisms of action
to reduce uncertainties inherent in the use of external exposure
or administered dose.
3.1.1: Experimental Absorption Studies.
Efforts to develop theoretical models (see below) to study
the uptake and distribution of chemicals need to be comple-
mented with experimental studies in which the uptake, distri-
bution, and time course for elimination of the parent chemical
and various metabolites are determined in the major body
organs for various species. Moreover, the experimental do-
simetry studies will support the guidance and design of bio-
logical experimentation in a number of organ systems, such as
reproductive, nervous, and pulmonary. An integrated approach
is needed to encompass oral, dermal, and inhalation exposures
for adult, neonatal, and fetal animals with a linkage to human
studies where possible.
3.1.2: Physiological and Anatomical Parameters
Across Species.
The great advantage of physiologically based pharmacoki-
netic modeling is that the model structure is common across
species—only the scale is changed. The model for one species
(and the attendant insights about delivered dose) can be applied
to another if the various physiological and anatomical parame-
ters governing the kinetics of the compound in the first species
are replaced by those of the other. Physiological parameters
describe capacities and volumes (organ weights, blood vol-
ume, partition coefficients, lung capacity, etc.) and rates (blood
flows, metabolic rates, ventilatory rates, elimination rates,
etc.). Anatomical parameters describe the structure of an
organ, such as the size and number of airways in the lung, and
the number of glomeruli and the structure of the nephrons in the
kidney. Once most of these values are determined, they can
serve as input data in the construction of models for many
compounds. Caution must be exercised when making generali-
zations if there is any evidence that the chemical being mod-
eled can itself influence the various physiological and ana-
tomical parameters which help to define the model. Metabolic
parameters can be very chemical-specific, but even these can
benefit by characterization of major biochemical pathways for
metabolism of xenobiotic compounds.
3.1.3: Influence of Varying Exposure Parameters
(Route, Duration, Rate) on Delivered Dose.
In Section 3.1.1, experimental dosimetry studies were de-
scribed that would be associated with health effects studies.
High-to-low dose extrapolation is an area with major uncer-
tainties due to a lack of pharmacokinetic and pharmacody-
namic data. Also, one of the extrapolations that must be made
in quantitative risk assessment is from the experimental dose
regimen used in an animal toxicological study (repeated dos-
ing or chronic exposure, usually for extended periods) to the
expected human exposure patterns (which may be single
exposure or chronic, episodic or continuous). The doses are
usually compared on a total cumulative dose basis, e.g., the
total mg/kg orppm/h of exposure. However, both dose rate and
dose level can affect the pharmacokinetics of a compound and
hence the amount that is delivered to the target site. For ex-
ample, high dose levels may include pathways that at lower
dose levels do not contribute to metabolic conversions which
are linked to the toxicity of the compound.
As work progresses under activities 3.1.1 and 3.1.2, inves-
tigations will begin to examine the influence of route, duration,
and rate of exposure on delivered dose to understand better the
uncertainties inherent in extrapolating toxicological data ob-
tained using one exposure scenario and species to that of
another exposure scenario and species. Data obtained from
such projects will enable guidance to be developed for improv-
ing risk assessment methodologies.
Issue 3.2: Route-to-Route Extrapolation
Research is needed to identify the assumptions and conditions
for route-to-route extrapolation to be scientifically defen-
sible in risk assessment. There are many chemicals for which
risk assessments are needed for a given route of exposure but
for which the necessary pharmacokinetic and toxicological
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data are not available. Instead, information may be available on
toxicological effects associated with a different route of expo-
sure. Route-to-route extrapolation can use such data for the
exposure route of interest. Development of PB-PK models
needed to perform route-to-route extrapolation would allow
the maximum use of data from experiments other than by the
route of concern. For example, the derivation of some inhala-
tion reference doses (RfDs) would be facilitated if the condi-
tions under which oral toxicity data could be used were better
understood. Having a better definition of the problems in hand,
a research program can then be proposed that supports such
extrapolations.
Prior to expanding current efforts on route-to-route extrapo-
lation, the Agency will commission the NAS or some like body
to assemble a panel of experts to: 1) discuss the critical
assumptions and limitations related to route-to-route extrapo-
lation, 2) provide specific guidance for risk assessments, and
3) recommend research areas which would facilitate route-to-
route extrapolation in the future. This represents an extension
of past activities of organizations like the NAS to emphasize
the potential use of pharmacokinetics in risk assessments.
S ince various EPA Program Offices are engaged in extrapolat-
ing oral toxicity data to inhalation, the panel will be requested
to focus on this issue. Also, dermal versus oral absorption
extrapolations would be a priority. ORD will seek Agency-
wide participation to identify questions for the panel to ad-
dress. Research recommendations arising from this exercise
will be incorporated into ongoing ORD research programs.
Issue 3.3: Theoretical Models
Theoretical models need to be developed for a unifying
structure upon which intra• and interspecies dosimetric
comparisons can be made in risk assessments. Development
of theoretical PB-PK models for chemicals will enable better
estimates of dose-equivalence across species for various rates
and durations of exposure. The development and modeling of
pharmacokinetic information from various species will allow
for the implicit determination of pharmacodynamic differ-
ences among species. Improved mathematical formulations
for the disposition of compounds following oral, dermal, or
inhalation exposure are needed that incorporate age- and
species-specific input parameters, such as partition coeffi-
cients and blood flow, and incorporate the properties of the
molecules being considered. Validated PB-PK models will
permit us to scale exposure, dose, and effect observed in one
circumstance (animals in a controlled environment in a labo-
ratory) to completely different circumstances (human beings
in an uncontrolled ambient environment). Successful work in
these areas offers the potential to reduce the magnitude of the
uncertainty factors (e.g., 10-fold interspecies extrapolation)
used in various risk assessments.
3.3.1: Theoretical PB-PK Models.
Theoretical PB-PK models provide a foundation for making
intra- and interspecies dosimetric comparisons in risk assess-
ments. Although specific chemicals may be restricted environ-
mentally to only some exposure routes, a general need exists to
develop models for all routes of exposure (oral, dermal, and
inhalation). A major impetus for the application of pharma-
cokinetics to risk assessment is the suspicion that experimental
rodents may have quite different degrees of delivery of an
applied dose to the site of action than humans may because
physiological and metabolic processes in small mammals
occur at much greater relative rates than in humans. While
pharmacokinetic differences are not the only source of differ-
ences in the potency of a chemical in various species, extrapo-
lation procedures should accountfor differential dose delivery.
3.3.2: Structure A ctivity Relationships in Mechanistic
Models.
The actions of xenobiotic agents in a biological system are
a direct consequence of their molecular properties and are
produced by a variety of specific molecular interactions and
non-specific processes. They may interact with receptors, en-
zymes, and macromolecules involved in transport by fully or
partially mimicking the relevant properties of endogenous
substances or by evoking the detoxification potential of the
biological system. The scientific basis for the evaluation of the
risk to human health of specific chemicals will be enhanced by
computational pharmacokinetic models that depend not only
on the physiological parameters of the systems being modeled
but also on molecular structure and reactivities. These models
will provide important insight into the transformation, distri-
bution, and deposition of the chemicals under consideration as
these properties relate to the biological activity of the chemi-
cals. Additionally, as the potential risk of many chemicals first
must be assessed when all the relevant data are not available,
a computational approach that allows the estimation of the
molecular properties in the model has a significant advantage.
3.3.3 Models Linking Exposure to Dose to Biological
Outcome.
Once estimates of delivered dose have been made, a great
deal of uncertainty still exists about how they should be
incorporated into the current quantitative risk assessment
methodology. The delivered dose information will aid in the
extrapolations, but other factors outside of pharmacokinetics
also influence the extrapolations. Species may have different
degrees of response to a given delivered dose, not only because
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of possible idiosyncratic differences in defenses, but also
because the physiological processes interfered with in the
course of the toxic reaction are themselves subject to scale
differences in different-sized mammals. When focusing on
"biologically effective dose," one must also incorporate
knowledge of the biological reaction to that dose to make
proper use of the pharmacokinetic data. Projects under this
issue will examine the interactive role of pharmacokinetic
factors and pharmacodynamic factors. For example, efforts
might focus on species differences in repair and tissue-dose
kinetics as they relate to the overall extrapolation process. The
activities in this section are linked to those in Section 4.2.3
(Interaction of exposure parameters on outcome).
TOPIC 4: BIOLOGICALLY BASED DOSE-
RESPONSE MODELS
The quantitative component of the risk assessment process
entails estimating the incidence of a particular health effect at
human exposure levels. Ideally, human data would be avail-
able at the relevant exposure levels. However, the data avail-
able usually reflect higher exposures, more often based upon
experiments in lest species than obtained from human studies.
As such, the risk assessor is required to select and apply an
appropriate strategy (e.g., RfDs or mathematical models) to
perform a high-to-low dose extrapolation. The major uncer-
tainty in quantitative risk assessment evolves from this selec-
tion process and the often untested assumptions that may guide
selection. The final risk estimate may vary by orders of
magnitude depending on the approach (model) applied.
The development and application of BB-DR models can
greatly reduce the uncertainties in quantitative dose-response
assessment. In the BB-DR approach, key physiological ele-
ments and processes, as well as their interactions, are de-
scribed. Utilization of such information facilitates the selec-
tion of a biologically plausible strategy upon which to base
extrapolations necessary for risk assessm ents. Moreover, such
models may be able to account for the variation in any key
element as it differs within and among species or varying
exposure conditions. The integration of biologic/mechanistic
data into the modeling process can also allow the risk assessor
to support or modify "default" assumptions that are often
applied in the risk assessment.
Utilizing a biologic/mechanistic orientation, research under
this initiative will be directed at determining the conditions
under which data obtained in test species and test systems can
be used to predict toxicity in humans. Such efforts will reduce
the uncertainties associated with existing methodologies as
well as lead to the development of new BB-DR models for
human health risk assessment. Ancillary components of these
activities will be the development of protocols to (1) validate
these models and, (2) facilitate their actual risk assessment
application.
The development of BB-DR strategies will entail both the
utilization of existing data and the generation of new data; the
extent to which those options are exercised will, in part, be a
function of the state of mechanistic knowledge for a given
health effect. The selected issues represent those for which
major uncertainties exist. The proposed research will reduce
these uncertainties by confirming or replacing assumptions
with scientifically defensible data. The specific issues to be
addressed are as follows: (1) intra- and interspecies extrapola-
tion; (2) extrapolation of health risk across different exposure
scenarios; and (3) delineation and incorporation of recent
mechanistic concepts into the development of BB-DR. Re-
search to help clarify these issues will emphasize especially
pulmonary, reproductive/development, and neurological health
effects with a smaller effort devoted to immunological and
cancer effects.
Whereas the primary focus of this research is to better
understand the role of various biological processes on chemi-
cally induced injury, the models should be flexible enough to
incorporate new information as it is obtained.
Issue 4.1: Inter/Intraspecies Extrapolation
Considerable uncertainty exists as to the factors responsible
for differences in response within and across species. Re-
search is needed to elucidate the critical physiologic and
mechanistic factors that contribute to the health effects of
concern in the risk assessment process. Such research will
improve the basis on which to adjust for intra- and interspecies
variability in dose-response extrapolations.
4.1.1: Homologous Models.
To determine the extent to which effects observed in one
species can be extrapolated to another, research will be per-
formed to ascertain whether effects in animals are analogous
(i.e., superficially similar) or homologous (i.e., resulting from
a common mechanism of action) to those in humans. Research
emphasis will be placed on evaluating species similarities and
differences in both mechanism and expression of a given
outcome. As such, these efforts will not only attempt to
confirm the existence of homologous mechanisms for induc-
ing specific toxicities (i.e., disease), but also the degree of
homology in the expression of such disease (i.e., comparable
outcome).
4.1.2: Interspecies Sensitivities.
Using pharmacokinetic models (Topic 3), we will be able to
determine the effective dose at a given target site. However,
given equivalent target doses, we are still left with questions
regarding interspecies differences in sensitivity that need to be
addressed independently. Research will focus on the degree
to which dose-effect functions for a given health effect (e.g.,
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reproductive failure) differ across species, as well as the degree
to which the relative sensitivity of different health effects (e.g.,
reproductive versus neural) vary across species at a given dose.
A component of this activity will determine the appropriate
dose metric for expressing and comparing a given dose across
species (mass/unit volume, mass/unit area, etc.).
4.1.3: Intraspecies Sensitivity.
This research will characterize the factors that may contrib-
ute to differing sensitivities in response to chemical exposure
among individuals of the same species. Variables to be evalu-
ated include age of the individual (developing, adult, or aging
organism), previous or current health status, and genetic
makeup. Such data will allow for a better estimate of the
differential probability and extent of a given health risk for
particular subpopulations. An importantaspectof efforts under
this activity will be determining how these factors interact with
pharmacokinetics to produce intraspecies differences in sensi-
tivity.
Issue 4.2: Exposure Scenarios
Major uncertainties exist in our knowledge of how variations
in dose-rate, intensity, and duration of exposure to environ-
mental pollutants affect toxicological outcomes in humans.
Research efforts in this risk assessment issue are needed to
determine the effects of varying route, dose, dose-rate, dura-
tion, and cumulative dose on health outcomes. Attention also
needs to be directed towards defining the continuum of effects
and their toxicological significance as a function of exposure.
The intent of these efforts is to develop biologically based
dose-response models wherein the data and assumptions that
are utilized realistically reflect human exposure scenarios.
Because of the nature of this research, some activities are
expected to be crosscutting with Topic 3 (i.e., characterizing
the behavior of the delivered dose under different exposure
conditions). Clearly, exposure scenarios are important deter-
minants of outcome for a number of health endpoints. Re-
search in this area is therefore critically important to risk
assessment and risk management.
4.2.1: Mechanisms across dose.
Important in any extrapolation effort is knowledge of whether
the mechanism of toxicity varies as a function of dose. Testing
protocols that evaluate many toxicological endpoints use some
approximation of the "maximum tolerated dose" as their high
dose with lower doses being mathematically reduced multiples
of that level. In evaluating dose-response relationships, it is
often assumed that the mechanism of toxicity does not vary as
a function of exposure scenario, and that novel or secondary
mechanisms do not influence outcome at these very high
exposure rates. Yet the experimental subjects may be exposed
to conditions that might well exceed their capacity to biotrans-
form and excrete the active moiety, might saturate or cause
disruption of natural protective/repair mechanisms, and/or
might trigger nonspecific stress responses. Because of the
similarity of protocol designs, results from studies on the
validity of effects caused by very high dose exposures cut
across multiple areas of toxicological significance.
4.2.2: Sensitivity of endpoints as a function of dose.
In describing the full range of effects in a dose-response
study, endpoints change in severity from biochemical itera-
tions, to physiological changes, to pathological conditions, to
the ultimate effectof mortality. For the risk assessment process
it is important to understand the progression of biological
effects in terms of adaptive responses, compensatory responses,
and overtly adverse or pathophysiological responses. Re-
search efforts should therefore be directed at defining the full
extent of responses throughout the experimental dose range,
the interrelationships, and biological significance.
4.2.3: Interaction of exposure parameters on
outcome.
At one extreme, chemicals may exert their effects when a
critical body burden is exceeded, irrespective of the level and
duration of exposure. At the other extreme, the toxicity of a
chemical may depend on the dose rate or duration of exposure.
In these latter cases, the toxic effects of a short-term exposure
to high concentrations may be very different from one pro-
duced by long-term, low-level exposure. In some disciplines of
toxicology, this issue translates into whether it is the peak
concentration or the cumulative exposure that is the trigger for
inducing toxicity. It is important, therefore, to perform re-
search aimed at improving our understanding of the interplay
among rate, intensity, and duration of exposure as it affects the
toxicological outcomes.
Issue 4.3: Mechanistic Variation
It has become increasingly apparent that a variety of biologi-
cal events may contribute to the occurrence of a given health
effect. The intent in this area is to develop dose-response
models that take into consideration the potential for different
biological mechanisms to elicit, initiate, or contribute to the
health effects of concern. To date, the primary efforts in this
area have been in delineating the role of non-genetic events in
the development of dose-response models for cancer. It is en-
visioned that this effort will continue, while comparable con-
siderations will be given to the variety of mechanistic path-
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ways that may contribute to mutagenic events or other target
organ toxicities.
This research program will assess risks of nongenotoxic
carcinogens including the development of models incorporat-
ing biological data on promoters. An initial step would be to
review presently used models for carcinogens to determine
whether alternative models can be developed. Such a review
will attempt to define explicitly the assumptions used in the
current models and test thesensititivity of the model to changes
in these assumptions. Research focused on promoters will take
advantage of some of the known biological activities associ-
ated with these chemicals. A promising model that would
benefit from this research is the Moolgavkar and coworkers
multi-stage model that requires specific experimentally de-
rived constants not currently available. The determination of
these constants could help to define and test the Moolgavkar
model for its application to risk extrapolation.
SUMMARY
This document presents the objective, rationale, and ap-
proach for a research program to improve health risk assess-
ments. The program is designed to improve our understanding
ol the relationship between exposure (applied dose), dose to
target tissue (delivered dose), and related health effects, pri-
marily by providing data on basic biological mechanisms. Four
major topic areas were chosen for emphasis: analysis of
uncertainly in risk assessment, integrated exposure assess-
ment,physiologically based pharmacokinetic models, and bio-
logically based dose response models. Imporiant research
areas within each topic were identified and evaluation criteria
lor selecting individual projects to address the research needs
were established. It is unrealistic, however, to expect that the
relatively limited resources devoted to this program will re-
solve all of the uncertainties inherent in health risk assessment.
Nevertheless, by focusing the resources through a structured
and integrated program it will be possible to make significant
improvements in EPA's health risk assessments.
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