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DART I
ntroduction : The Problem
and an Approach
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Risk Assessment: Historical Perspectives
Seymour L. Friess
Beginning in the 1930s in the United States and Europe, the protection
of human health from chemicals in the workplace, the market place, and
the environment became a commonly recognized international goal. The
general approach toward that goal developed over time, but it was to be
characterized roughly by processes that involved the development of some
form of human dosage versus response relationships for undesirable health
effects, the assessment of risk for those effects under specified modes of
exposure to the chemical in question, and finally, the setting of permissible
exposure limits for the chemical in various exposure situations based on
some form of societal perception of acceptable risk.
To set this chain of procedures into action, it was first necessary to
generate some form of trustworthy picture of dosage versus response for
the most serious or most sensitive health effect that a chemical might
produce in a human target. Indeed, since the early l900s data had begun
to accumulate on such health effects in human populations occupationally
exposed to major industrial chemicals. In the 1930s and thereafter, data
on dosage versus response were also generated in ever-increasing volume
by dosing experiments in experimental animal systems under laboratory
conditions. These toxicological experiments with rodents or larger mam-
mals had the special merit of permitting exposure to much larger dosages
and concentrations of chemical than adventitious occupational exposures
of worker populations, and of providing precise measures of the total
exposure of the biological target rather than the general guesses found in
the early industrial epidemiological studies. The animal toxicology data,
3
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4 SEYMOUR L. FRIESS
usually from subchronic or chronic exposure experiments, were always
clearly indicated in the early studies as being pointed toward their ultimate
use of predicting the risk of the corresponding health effects in human
populations exposed to the chemical of concern. Toxicology was, and is,
intended as a predictive science, with test data from animal experiments
to be translated into assessments of risk for human and other populations.
Generally, only the toxicological experiments furnished quantitative dose-
response data for specific effects produced at specific target tissues or
organs.
The risk assessment process, therefore, beginning roughly in the 1930s,
took the form of an initial review of the epidemiological health effects
data available for a given chemical in worker and user populations and
of the dose versus response data generated in test animal systems. Some-
how, usually by deliberations of a committee of specialists in the health
sciences, the body of epidemiological and animal toxicological data for
the chemical was assessed for scope and reliability, and then interpreted
in terms of the most probable form for the dosage versus response rela-
tionship for each serious health effect in the human as a general target.
For a given health effect, then, the relationship could be displayed either
as a curve of dosage versus anticipated response or, in an attempt to
linearize the relationship, as a curve of log dosage versus percentage
response. The display could also take other forms, in parallel with modes
of display developed in pharmacology.
Whatever the display mode, however, the predicted human dose-re-
sponse curve was then used for two purposes. First, it could be used to
predict human response amplitudes under a specified exposure scenario.
Second, by accepting a 5 percent response amplitude as being essentially
a no-effect level within the limits of biological variability in populations,
the curve could be used to establish the human no-observable-effect level
(NOEL). This procedure was, and is, a primitive quantitative risk as-
sessment methodology.
A variant on this mode of generating human NOELs for specific health
effects produced by a given chemical has also enjoyed wide international
usage, beginning in the 1940s. Since the toxicological data base is usually
far more extensive and more quantitative than that available from occu-
pational epidemiological observations, the concept developed that human
risk assessment (in the form of human NOELs) for health effects from a
given chemical could be generated from the animal data base alone and
later validated as human data accumulated. In this mode, if data exist for
a spectrum of adverse health effects produced by a chemical in an as-
sortment of test animal systems, either reversible or irreversible effects,
the risk assessor selects the most serious health effect in the most sensitive
animal species tested and uses the data to estimate the animal NOEL for
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Risk Assessment: Historical Perspectives 5
that effect. In the choice among several health effects involving different
tissues and organs, that effect may be selected which is manifested at the
lowest dose range. Then, by application of a suitable safety factor (SF)
or translation factor to the animal NOEL, a human NOEL is projected.
This translation procedure evolved. At least two key review papers in
the 1950s serve as milestones in this evolution, that of Barnes and Denz
(1954) and that produced by Lehman and colleagues (1959) at the U.S.
Food and Drug Administration. In particular, the rationale for and size of
the safety factor to be employed in the animal-human NOEL translation
was developed largely at the hands of Lehman et al., although variants
are still being discussed in today's literature. For a well-defined toxic
action at a target tissue which appears to display a dose threshold and
which is at least moderately reversible, a widely applicable SF of 100
was postulated, with a first factor of 10 for the NOEL translation from
animal to human and a second factor of 10 to account for the variability
in sensitivities in human populations. For more serious, irreversible types
of effects, even including carcinogenesis in earlier considerations of risk
assessment for this chronic effect, additional safety factors (range, 2-10
and higher) were factored into the fundamental SF of 100. For example,
at times in the last two decades, total safety factors of 2,000 or 3,000
have been mentioned as being applicable to the apparent NOEL for tu-
morigenesis in a chronic animal bioassay of a chemical in converting to
an estimate of a NOEL for tumorigenesis in human populations.
It should be noted that the simplistic form of risk assessment considered
up to this point was always generated singly, chemical by chemical, and
was also viewed as a prediction that should be validated or rejected as
additional animal and human dose versus response data for a chemical
were developed. When multiple chemical exposures were considered, the
state of the art and knowledge only extended to the possibility of additivity
for closely related structural analogs that produced simmilar effects on a
given target tissue by similar interaction mechanisms. The possibilities of
synergism, potentiation, or antagonism in multichemical exposures were
discussed, but were rarely attacked in the form of a joint risk assessment.
An important point of departure from this relatively simplistic but prac-
tical methodology for risk assessment related to health effects from chem-
ical exposures took place in the 1960s-1970s, with the evolution of the
regulatory concept that there could be no such thing as a NOEL for
chemical carcinogenesis in humans and no such observable as a practical
threshold for the complex carcinogenic process in mammals. All exposures
were conceived of as contributing finite increments of excess lifetime
cancer risk from the chemical in question, regardless of whether repair
processes were operable at some level after the initial attack on DNA.
From this regulatory philosophy there evolved the process of modeling
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6 SEYMOUR L. FRIESS
these excess lifetime risks for carcinogenesis in the humans based on
postulated human exposure scenarios and the observed tumorigenic re-
sponses measured in chronic bioassay experiments with test animal sys-
tems (usually rodents). The modeling process has been labeled quantitative
risk assessment for chemical carcinogenesis, and because it has moved in
certain sectors of the public perception from being viewed as a predictive
technique into the status of a supposedly factual presentation of real human
risks, it deserves some explicit analysis, as follows.
1. The process starts with a chronic bioassay, usually in rodent systems,
in which dosing with the test chemical extends over more than 0.5 lifetime
of the species involved, with daily administered doses at the maximum
tolerated level and one or more submultiples of the maximum tolerated
dose (MTD).
2. The data, in the form of administered dosages versus tumorigenic
responses, are then fitted to one or more modeling equations (for example,
one-hit, multistage, Weibull) of a form in which the probability of excess
cancer development is some function of the average daily lifetime dose.
3. Generally, additional restrictions are placed on this modeling step
in the form of assumptions that the tumorigenesis process has no threshold
(zero probability only at zero dose), and that the modeling equation is
linear in the very low dose region, regardless of the curve's shape at the
very high administered doses (MTD, 0.5 MID, 0.33 MID) under which
the bioassay is performed.
4. The fitted equation of the modeler's choice is then used to extrapolate
from the high-dose region of animal administered dose versus response
down to theoretical response levels at a very low dose.
5. The assumption is then made (explicitly or implicitly) that the low-
dose sector of the animal-fitted curve can be used to predict human risks
for tumorigenesis by the test chemical at very low ambient exposure levels.
In this translation process, it is then customary to make a gross correction
for metabolic differences in handling of the chemical by the animal and
the human in the form of a correction ratio applied to dose based on either
relative body weights or body surface areas. The implicit assumption in
this correction process is that the mechanisms of handling, target organ
specificity, etc., in the two mammalian species are similar.
6. Finally, under a series of postulated human exposure scenarios, each
of which leads to a calculated average daily lifetime dose (administered),
the low-dose equation for the animal is used to predict a corresponding
series of excess lifetime cancer risks in humans.
Regulatory communities worldwide now use these modeled risks for
prioritizing their regulatory activities over a wide range of potentially
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Risk Assessment: Historical Perspectives 7
carcinogenic chemicals in the environment or in the workplace, and for
setting numerical triggers to be used in initiating rulemaking or restrictions
on specific chemicals. These regulatory activities are important and are
powerfully assisted by the quantitative risk assessment process. The pro-
cess itself is being extended by investigators to cover simultaneous ex-
posures to many potentially carcinogenic chemicals found at low levels
in the environment, such as the assortment of chemicals found in drinking
water supplies, by the use of risk combination techniques (e.g., Crouch
et al., 19831.
It should be realized, however, that there are scientific problems inherent
in the use of the modeling techniques based on animal bioassay data. To
cite just a few: (1) There are no general experimental/theoretical justifi-
cations for the modeling assumptions, the validity of high dose-low dose
extrapolations of the animal bioassay data, or animal to human translations;
(2) the methodology provides no insight as to what delivered dose of what
active material (original chemical or a metabolite) delivered to what target
tissue should actually be modeled in a truly meaningful risk assessment;
and (3) there is no assurance in any given risk assessment that modeling
of the administered dosage data has any direct relationship to delivered
dosage, for the test compound or an active metabolite. Indeed, recent
examples abound to show a lack of administered dose/delivered dose
congruence. All of these points have been well recognized and discussed
in the 1970-1986 time frame by scientists concerned with making quan-
titative risk assessment more meaningful and sound.
Therefore, the need has been recognized for moving quantitative risk
assessment to a more realistic dimension, particularly by the use of data
from metabolic and comparative pharmacokinetic studies of a given chem-
ical which, when combined with chronic bioassay data from animal ex-
periments, can lead to knowledge about the active chemical species that
reaches specific target tissues at measurable delivered concentrations (as
a function of time) in the species of prime interest, humans.
The purpose of the workshop on which this volume is based was to
review progress in this development of the risk assessment process and
to probe the current strengths and weaknesses in this area.
REFERENCES
Barnes, J. M., and F. A. Denz. 1954. Experimental methods used in determining chronic
toxicity. Pharmacol. Rev. 6:191-242.
Crouch E. A. C., R. Wilson, and L. Zeise. 1983. The risks of drinking water. Water
Resources Res. 19: 1359- 1375.
Lehman, A. J., F. A. Vorhes, et al. 1959. Appraisal of the Safety of Chemicals in Foods,
Drugs and Cosmetics. The Association of Food and Drug Officials of the United States.
107 pp.
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Tissue Dosimetry in Risk Assessment, or What's
the Problem Here Anyway?
Meivin E. Andersen
I NTRODUCTION
The overall risk assessment process integrates hazard assessment data
on chemical toxicity with exposure assessment information (Figure 11.
Hazard assessment is the process by which the toxicity of a chemical is
determined either by a series of bioassay experiments with intact test
animals or by observing increased morbidity/mortality in exposed humans.
Often there is no human epidemiology on particular chemicals, and risk
managers have to rely solely on results of animal toxicity experiments for
the hazard assessment. These animal experiments allow us to generate
dose-response information on how much chemical is required to produce
a specified degree of toxicity in test animals. The major challenges in the
hazard assessment process are to generalize toxicity results in the test
animal to (1) predict what will happen in test animals given much lower
amounts of chemical; (2) predict what will happen in an entirely different
species of animal, namely, humans; and (3) predict what will happen in
a different species receiving a chemical by a route of administration dif-
ferent from that used in the animal studies. These are all problems of
extrapolating beyond the conditions used in the actual toxicity studies to
predict outcome under very different exposure conditions in a variety of
species. What concepts tie these problems together and give us some
confidence in the ultimate success of efforts to develop methods to conduct
these extrapolations?
8
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Tissue Dosimetry in Risk Assessment 9
.
l TOXICOLOGY _ ~ ~ hAPOLATIONS Ill
1 .
L
HARD
ASSESS - ENT
CONTAMINANT l
CONCENTRATION
AND LOCATION
l
1
1
1
1
RISK
ASSESSMENT I
-
RISK
MANAGEMENT
ENGINEERING DESIGN
OR
RElIIEDIAL ACTION
EXPOSURE l
DURATION
AND TECH - ISLES l
EXPOSURE
ASSESS - ENT
ENGINEERING / COST:
I 1~DE4FF ANALYSIS ,
FIGURE 1 Elements of chemical risk assessment. The overall risk assessment process consists
of both a hazard assessment and an exposure assessment. These provide information on which
to make a risk analysis and give the risk manager detailed information on which to make decisions
regarding acceptable environmental concentrations of a toxic chemical, cost-effective engineering
design enters for reducing effluent or emission concentrations, and the feasibility of replacing
one chemical by another in a particular industrial application. Pharmacokinetic modeling is useful
in hazard assessment where it can aid in estimating realistic measures of target tissue dose in
exposed animals and be used to support extrapolations to estimate tissue dose in humans.
Basically, there seem to be two fundamental assumptions which toxi-
cologists are forced to make in attempting quantitative extrapolations based
on animal toxicity experiments. The first is that experimental animals are
true surrogates for exposed humans. That is, chemicals would cause effects
in the same tissues in humans as those tissues in which they cause effects
in the exposed test animals, and the mechanisms of these effects would
be qualitatively similar in the two different species. This assumption ac-
cepts that there is a qualitative similarity in effects in different species.
There are instances where this assumption is suspect. For instance, vinyl
chloride causes zymbal gland cancer in rats (Maltoni and Lefemine, 1974),
but humans do not have this structure. However, vinyl chloride is ob-
viously carcinogenic in a variety of animal species. In any case, the
universal validity of this assumption of qualitiative similarity in toxicity
is really not within the purview of the papers in this volume. It does seem
to be valid in the great majority of instances. Instead, this volume focuses
our attention on the other basic assumption that we are forced to make to
conduct our risk assessment calculations.
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TO MELVIN E. ANDERSEN
This second tenet is that there is a quantitative equivalence in the tissue
chemical exposure required to produce an equivalent intensity of biological
effect in various species. This is the concept of tissue dose equivalence.
More simply stated, all species are regarded to have equal sensitivity to
the toxic chemical. Again, there are notable exceptions, such as the ex-
treme interspecies differences in toxicity of 2,3,7,8-tetrachlorodibenzo-p-
dioxin (Kociba and Schwetz, 19821. For more simple toxicities, related
to reactive chemical moieties, this assumption seems entirely appropriate.
In addition, the species and strain differences in dioxin toxicity might
diminish substantially if the dose were expressed in relation to the con-
centration and affinity of the dioxin receptorts) in these various animal
species (Poland and Knutson, 19821. The catch, of course, is that tissue
dose is not a simple concept and will be different for different chemicals.
In fact, the real problem in hazard assessment is defining and measuring
tissue dose under a variety of exposure conditions in several species.
A DOSE OF WHAT?
This hazard assessment process sounds deceptively simple. Determine
the toxic tissue dose in the test species and calculate the exposure con-
ditions under which this dose is likely to be achieved in humans. All we
need to do is to define tissue dose. As a working definition, we can say
that an appropriate measure of tissue dose is some measure of the intensity
of chemical exposure which is directly linked to the biological processes
leading to toxicity or tumor formation. With this definition, it is clear that
some presumption of the mechanism of interaction between the chemical
and the tissue is required before we can define tissue dose for any particular
chemical.
What then are the primary processes by which chemicals interact with
tissue constituents to cause biological changes in the tissue? The first
process is by direct chemical reaction in which the toxic chemical reacts
with and consumes cellular constituents (Figure 21. With this type of
interaction the expected degree of damage, as loss of cellular constituents
or accumulation of bound reactive intermediate, should be related to the
time integral of tissue exposure to the reactive chemical. This time integral
of tissue exposure is also called the area under the tissue concentration
curve for the reactive chemical. The equations for reactivity in Figure 2
are true only for acute-exposure situations. In chronic administration, the
equation should be expanded to include terms for the synthesis and normal
catabolism of the macromolecules.
The second common process by which chemicals interact with tissue
is by noncovalent binding to cellular receptor molecules. This is the mech-
anism by which dioxin is presumed to interact to initiate toxic changes in
cells. This binding with concomitant changes in receptor occupancy causes
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Tissue Dosimetry in Risk Assessment ~ ~
HOW DOES TISSUE DOSE
ELICIT TOXIC RESPONSE?
·CHEMICAL REACTIVY:
k1
T + MM- , T - MM (DEPLETION)
rem rt
t d(MM) = _ | kl(T)dt
MMc MM J o
ln[(MM)t / (MM)o]=-kl (AUTC)
· RECEPTOR BINDING:
K1
T + R ~ ~ TR (Occupancy)
TR (T)
TR + R (T) + K
FIGURE 2 Tissue dose metrics and their relation to toxicity. Toxic chemicals interact with
tissues by two general processes. In one case, chemical reactivity, the toxic chemical, T. reacts
with cellular macromolecules, MM, to cause covalent binding of the toxic chemical and a depletion
in the concentration of MM. Simultaneously, there are increases in the bound toxic chemical,
T-MM, which for genotoxic carcinogens can be regarded as similar to a DNA adduct. Solution
of the rate equation for loss of MM with time shows that the natural logarithm of the remaining
MM is proportional to the second-order rate constant for the reaction of T with MM and the area
under the tissue time course concentration of T (AUTC). In the second case, receptor binding,
T binds to a receptor molecule, R. with a dissociation constant, Kit. Toxicity develops due to
occupancy of the receptor with some attendant biological consequence. Occupancy is the ratio
of bound receptor (TR) and total receptor (TR + R). As shown, this is equivalent to Tl(T +
Kit), i.e., occupancy is determined by the free concentration of T and the binding constant.
some response on the part of the organism which is ultimately expressed
as toxicity. The therapeutic action of most drugs is also related to specific
receptor binding (Goldstein et al., 19741. With this type of interaction,
the response of the cell is dependent on the occupancy of the receptor and
occupancy is determined by the binding constant for the chemical and the
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|4 MELVIN E. ANDERSEN
have provided a very good review of the status of PB-PK modeling of
chemical disposition. These PB-PK models describe the body in terms of
realistic tissue compartments with specified volumes, blood flows, par-
tition coefficients, and tissue binding characteristics (Gargas et al., 1986;
Ramsey and Andersen, 19841. Biochemical constants for metabolic path-
ways and for tissue binding can be included in the mass-balance equations
for organs in which these interactions are important. For most of these
metabolic pathways the important constants are the maximum velocity of
the reaction (Vmax; in milligrams per kilogram) and the binding affinity of
the particular substrate for the metabolizing enzyme (in milligrams per
liter). Complex metabolic pathways involving parallel or sequential re-
actions of the parent chemical or involving interactions between chemical
metabolism and cofactor depletion can also be readily incorporated into
these models, as necessary (H. J. Clewell III and M. E. Andersen, this
volume).
The entire process of problem definition, tissue dose assignment, and
pharmacokinetic model development can be captured in a simplistic flow
diagram (Figure 4~. In this representation the process of model formulation
comes after evaluation of the nature of the problem and consideration of
the impact of mechanism on the choice of tissue dose metric. It is followed
by exercising the model, evaluating its success at predicting known kinetic
and toxicity behavior, designing necessary experiments to collect crucial
data for verifying or improving model performance, and refining the model
when needed. A successful model can then be used as an integral part of
the hazard assessment process. The take-home lesson here is that phar-
macokinetic modeling is not some kneejerk process where the investigator
collects blood time course curves and draws limited inferences about the
behavior of the chemical in the body by an abstract mathematical curve-
fitting procedure. Instead, the pharmacokinetic modeling intended for risk
assessment use Ivan integrating process which should be done early on
before major data collection efforts. It should provide a comprehensive
description or chemical disposition in target organs and be designed to
predict human kinetic behavior when the biochemical metabolic constants
and the tissue-binding characteristics of the chemical have been determined
. .
n human tissues.
The remainder of this chapter discusses tissue dose for various mech-
anisms of carcinogenesis, identifies essential elements required in PK
models for tracking these particular forms of tissue dose, and emphasizes
that pharmacokinetic model development will often suggest a need to
collect critical metabolic or kinetic data that might not be available from
the literature. In fact, it would be completely wrong to believe that PK
models should be developed on existing toxicity data bases. The existing
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Tissue Dosimetry in Risk Assessment 15
PROBLEM
IDENTIFICATION
-
| L~ERAT - E
L EVALUATION
MECHANISIIIS BIOCHEMICAL
OF TOXICITY CONSTANTS
1 '
.
PHYSIOLOGICAL |
CONSTANTS ~
MODEL
FORMULATION
_
SIMULATION
REP INK COMPARE TO
MODEL ~ ~ ~ ~~R
VALIDATED
IdIODEL
.
DESIGN/ CONDUCT E X TRAPOLATION
CRITICAL EXPERII`IIENTS TO HUI`IIANS
FIGURE 4 Simplified flow chart of the development of a pharmacokinetic model intended for
use in risk assessment. Problem identification: the finding of a particular toxicity, in a particular
organ(s), in a particular species. This effect is the benchmark on which the risk assessment will
be conducted. Literature evaluation: the integration of available information about the mechanism
of toxicity, the pathways of chemical metabolism, the nature of the toxic chemical species, the
tissue-binding characteristics, and the physiological parameters of the target species. From these
data a model is developed to estimate the appropriate measure of tissue exposure for a wide
variety of exposure conditions. The essential elements to be included in such a model are outlined
in the text. Before a PK model can be used in human risk assessment it has to be validated
against kinetic, metabolic, and toxicity information and in many cases refined based on com-
parison with experimental results. The model development process can frequently be used to
design critical experiments to collect data needed for final validation.
literature can be helpful for model definition, for drawing conclusions
about the nature of appropriate measures of tissue dose, and for providing
limited PK information, but it is also replete with experiments which are
virtually useless for hazard assessment. If a new approach, such as PB-
PK modeling, is proposed as an adjunct to existing hazard assessment
techniques, it will have data requirements of its own and require some
independent experimentation not previously conducted on a routine basis
for each chemical for which a risk assessment was planned. In general,
this does not mean that there has to be major new data acquisition needs
for each PK model that might be developed for risk assessment use. For
many cases, this will be only limited, critical experiments that are required
to provide important constants for use in the PK model (Figure 4) or to
fill data gaps identified in the literature survey.
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16 MELVIN E. ANDERSEN
GENOTOXIC CARCINOGENS
In terms of the chemical carcinogens themselves, there are two broad
mechanisms by which chemicals cause cancer: by some direct chemical
interaction with the DNA structures of the cell or by indirect effects on
the cellular environment which increase tumor yield without direct chem-
ical alteration of DNA. The former are called genotoxic carcinogens and
the latter, epigenetic carcinogens (Weisburger and Williams, 1980~. As
might be expected, the distinction between these two categories of car-
cinogens is not always clear-cut. Many substances appear to possess prop-
erties characteristic of both categories of carcinogens. However, this division
can be profitably examined in terms of the importance of a proper definition
of tissue dose for both types of chemical carcinogens.
Genotoxic chemical carcinogens themselves can be further subdivided
on the basis of whether parent chemical or a metabolite is the moiety that
reacts with DNA. The possibilities include cases where parent chemicals,
such as ethylene oxide or dimethylsulfate, are genotoxic; cases where
stable metabolites, such as ethylene oxide formed from ethylene or bu-
tadiene epoxides formed from butadiene, are genotoxic; and cases where
reactive, nonisolatable metabolites, such as the epoxide formed from vinyl
chloride or the chloromethylgluthathione formed from methylene chloride,
are presumed to be responsible for genotoxicity (Figure 51. These three
possibilities for the nature of the DNA-reactive chemical need to be con-
sidered independently.
PARENT CH EM ICAL
For the simplest case there is a chemical reaction between DNA and
parent chemical leading to chemical alteration of the DNA which can
cause mutation during cell replication. As discussed for cases of chemical
reactivity, the tissue burden of altered DNA is expected to be associated
with integrated tissue exposure to the DNA-reactive chemical. The mod-
eling problem is to identify the chemical-specific tissue solubilities or
tissue-binding characteristics and the distribution and activity of chemical-
specific detoxifying enzymes in various tissues. The goal of the PK model
is to identify and understand the metabolic and physiological processes
that limit the action of the parent chemical in the cells.
Interspecies scaling is the determination of how target tissue exposure
is affected by animal size for a particular administered dose. An attempt
was made in volume 6 of Drinking Water and Health (National Research
Council, 1986) to predict the interspecies scaling of tissue dose, depending
on the nature of the toxic moiety for example, parent or metabolite, etc.
This analysis assumed that both metabolic and physiological clearances
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|8 MELVIN E. ANDERSEN
ical risk assessments conducted by the Environmental Protection Agency
(EPA). The use of this factor is usually justified by reference to studies
on the interspecies differences in acute toxicity of a variety of chemicals
used medically in cancer chemotherapy (Freireich et al., 19661.
STABLE METABOLITES
Ethylene oxide can also be produced in vivo by the oxidation of ethylene
by microsomal metabolism. In developing a pharamacokinetic model for
ethylene oxide as a DNA-reactive, stable metabolite, other PK modeling
considerations become important. These include the rate of formation of
the epoxide in various tissues, the stoichiometric yield of the epoxide from
ethylene in vivo, and the distribution of the stable metabolite to target
tissues. With butadiene, there are two epoxide metabolites that have gen-
otoxic potential, and some provision for their differential DNA reactivities
might have to be included in model development. A very elegant analysis
of the relative risks of ethylene and ethylene oxide has been conducted
by Bolt and Filser (in press). They developed pharmacokinetic models
for both of these chemicals and attempted to predict ethylene exposure
conditions that would yield carcinogenic tissue doses of the epoxide. They
did not use a physiological model, and their results are limited to inter-
pretation of the bioassay results in experimental animals. Nonetheless,
their study is an excellent example of the use of sound pharmacokinetic
principles in the analysis, interpretation, and design of toxicity experi-
ments.
In instances in which the genotoxic chemical is a stable, freely circu-
lating metabolite, the analysis of the effect of body size on tissue dose
includes consideration of the metabolic formation of a DNA-reactive me-
tabolite and its consumption by various clearance pathways. For the pur-
poses of risk assessment, when there is no available information on the
human population, it seems appropriate to assume that both the metabolic
production and the clearance pathways are related to the same fractional
power of body weight (National Research Council, 19861. Thus, equiv-
alent doses on a body weight basis are expected to produce approximately
equal tissue exposures expressed as area under the tissue curve of the
genotoxic, stable metabolite. This suggests that larger animals should be
at the same risk from equivalent doses of these chemicals as smaller
animals. For this class of chemicals, the standard surface area correction
used by EPA would overestimate the expected risk in humans based on
extrapolation of toxicity results in small laboratory animals. The Food and
Drug Administration approach which uses body weight for interspecies
dose conversion is the more appropriate correction factor for this class of
chemical carcinogens.
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Tissue Dosimetry in Risk Assessment 19
REACTIVE, NONISOLATABLE METABOLITES
In a recent paper we attempted to develop a strategy for conducting a
pharmacokinetically based risk assessment for methylene chloride (An-
dersen et al., 19871. On the basis of a variety of kinetic and chemical
arguments, we suggested that the carcinogenicity of methylene chloride
was related to the metabolites produced by conjugation of parent chemical
with glutathione. If this proposed mechanism of toxicity is correct, the
appropriate measure of tissue dose should be the time integral of the tissue
concentration of the glutathione conjugate. This material is too reactive
to measure directly, and a surrogate measure of tissue concentration of
this chemical must be utilized in place of its concentration. The surrogate
dose metric that was developed based on kinetic principles was a ratio of
the integral of the amount of chemical metabolized by this pathway in the
target tissue divided by target tissue volume. This same approach could
be used with other chemicals, like vinyl chloride, where the presumed
genotoxic metabolite is also too short-lived to measure directly.
When reactive metabolites are associated with carcinogenicity, the sim-
plified pharmacokinetic analysis of the effect of animal size on integrated
tissue exposure suggests that larger species will be at proportionately less
risk than smaller species (National Research Council, 19861. The reason
for this dependence is that metabolic production (the numerator) is pro-
portional to a fractional power of body weight, while tissue volume (the
denominator) is directly proportional to body weight. The ratio of the two
then decreases with increasing body weight. This approach to interspecies
scaling for vinyl chloride was previously suggested by Gehring et al.
(1978) based on somewhat different arguments.
The above examples point out that it is very difficult to depend on a
single approach to interspecies scaling. When scaling strategies are de-
veloped based on generalized pharmacokinetic principles, there are several
very different types of interspecies scaling behaviors depending on the
nature of the DNA-reactive chemical whether it is parent chemical,
stable metabolite, or a highly reactive, nonisolatable metabolite. These
differences should in some way be reflected in the process of hazard
assessment when the mechanism of carcinogenicity of a chemical is fairly
well-established. Universal reliance on the surface area correction, or any
one particular adjustment factor, should be avoided; however, in the ab-
sence of information on the mechansim of toxicity, the surface area cor-
rection would at least err on the conservative side.
INTERCALATING AGENTS
Another group of direct-acting, DNA-interactive chemicals are the in-
tercalating agents, represented by acridine-type dyes and related chemicals
OCR for page 20
20 MELVIN E. ANDERSEN
(Rogers and Back, 19821. With these materials there is noncovalent bond-
ing between the dye and DNA, and the interactions are probably best
described by the mass action law with critical receptor site occupancy by
the intercalated dye. For this type of tissue interaction we would need to
know the dissociation constants and binding capacity for the agent-DNA
binding processes, and the time course of intercalator concentration in the
target tissues. Tissue dose in this case is probably best represented as a
time-weighted average receptor occupancy by the intercalating ligand.
Thus, even for genotoxic chemicals there are possibilities that interactions
can occur either by chemical reactivity or by mass action effects of par-
ticular chemical ligands. These two mechanisms lead to two very different
expressions for tissue dose.
These estimates of tissue exposure with chemically reactive or inter-
calating agents can be used as the dose inputs to drive increased mutational
frequency in biologically based cancer models such as that proposed by
Moolgavkaar and Knudson (19811. Combining pharmacokinetic and phar-
macodynamic modeling of the cancer process (Figure 6) promises to greatly
improve our ability to conduct interspecies scaling and support risk as-
sessment extrapolations. It is important to remember, however, that tissue
dose will often be nonlinear with respect to administered dose, and it is
clearly wrong to use administered dose uncritically in developing realistic
cancer models. To a very great extent, it is only the availability of accurate
pharmacokinetic descriptions of tissue exposure which permits validation
of biologically motivated models of chemical carcinogenesis. In fact, it
is essential to have an adequate understanding of the pharmacokinetic
characteristics of target tissue exposure before pharmacodynamic models
are developed for any kind of toxic response.
The mechanisms of carcinogenicity of directly acting genotoxic chem-
icals are still under active investigation in terms of fundamental questions
about the nature of DNA adducts formed, rates of repair of damaged
DNA, the presence of critical mutational sites on DNA, etc. Eventually,
as more information is developed, it may even be possible to use the
formation of particular adducts as the measure of tissue dose instead of
the use of integrated tissue exposure. This would give metrics for tissue
doses of carcinogens which were closer to the biological process of tumor
. .
induction.
EPIGENETIC CARCINOGENS
Despite the many outstanding questions with regard to the mode of
action of genotoxic carcinogens and to the relative importance of particular
DNA adducts, it is clear that a great deal more is known about the mech-
anisms of tumor initiation with these chemicals than about the detailed
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Tissue Dosimetry in Risk Assessment 21
D1
' ~'-
~D2
_~
1B1 (3
1 B2
me,
.O
FIGURE 6 A schematic of a two-stage cancer model: Normal cells (1) have a basal birth rate
(B1) and death rate (D1). There is also a background mutational rate (Pl). The probability of
undergoing a mutational event is the product of the birth rate and the mutational frequency (i.e.,
P1 x B1). The stage 2 cell (2) has undergone a single mutation but is not a tumor-forming cell.
It has its own birth and death rate (B2 and D2) and some probability of undergoing a second
mutational event (P2) to become a cancer cell capable of progressing to a tumor. Genotoxic
carcinogens are expected to increase P1 and P2. The increase in P1 and P2 will be related to
the integrated area under the tissue concentration curve of the DNA-reactive chemical. These
tissue exposure estimates can be derived from physiologically realistic PK models. There are
two major classes of epigenetic carcinogens discussed in this paper: those which cause cell
toxicity with continuous cell division during chronic exposure, and those which act as promoters
by increasing synthesis of new enzymes (or altered levels of existing enzymes). These mechanisms
are more fully developed in the text. The former class of chemicals will primarily affect D1 and
D2 with subsequent changes in B 1 and B2. The latter group is believed to affect the balance of
B2 and D2 to give the cells with single mutations a growth advantage. PK models will have to
be developed to link tissue exposure, cell toxicity, enzyme induction, and changes in cell growth
kinetics. These coupled PK and pharmacodynamic models of the cancer process should greatly
improve cancer risk assessment for most chemical carcinogens.
mechanisms by which epigenetic carcinogens cause tumor development.
In general, there seem to be two very different groups of epigenetic
carcinogens. The first group consists of those chemicals that cause overt
cytotoxicity and cancer appears secondary to chronic tissue damage. Chlo-
roform and carbon tetrachloride are examples from this group (Reitz
et al., 19829. The second group consists of the tumor promoters which
interact with the cell in such a way to induce expression of new, char-
acteristic sets of enzyme activities. The altered cellular environment caused
by these promoters then leads to enhanced tumor yield under appropriate
exposure conditions. Examples here include phenobarbital and dioxin.
Tissue dosimetry for these epigenetic carcinogens will be more complex
. . . .
t nan it Is for genotoxlc carcinogens.
For epigenetic mechanisms, it will be necessary to include some kind
of pha~n~acodynamic modeling along with the pharmacokinetic descrip-
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22 MELVIN E. ANDERSEN
lion. For cytotoxicity (Figure 6) it will be necessary to model the linkage
between tissue reactivity of reactive chemical with depletion of critical
cellular macromolecules, cell death, and attendant hyperplasia. This new
birth rate function can then be used in a biologically motivated cancer
model (see R. B. Conolly, R. H. Reitz, and M. E. Andersen, this vol-
ume). With promoters the proper tissue dose metric will be related to
receptor occupancy and a resulting induction of new protein synthesis.
The pharmacokinetic modeling strategy ultimately devised for these pro-
moters will require physiologically accurate models for the processes in-
volved in enzyme induction. In the two-stage cancer model, the action of
these promoters is considered to be on the birth and death rates of the
stage 2 cell, providing cells with a single mutation with a selective growth
advantage. While dosimetry with these epigenetic carcinogens is more
demanding than with genetic carcinogens, there still appears to be two
dose metrics that emerge integrated exposure to reactive chemical for
cytotoxicants and time-weighted average receptor occupancy for chemicals
such as dioxin and phenobarbital. These seem to be the primary expres-
sions required for understanding our problem here: that is, just what is
tissue dose? On the other hand, what can be said of pharmacokinetics in
these cases. The modeling strategy is still the same- produce an integrated
description of chemical disposition and tissue exposure which is readily
amenable to interspecies extrapolation and in which all biochemical, phys-
ical chemical, biological, and physiological processes are as clearly de-
fined as possible.
SUMMARY
Mechanistic information on the processes involved in cancer causation
by a particular chemical is essential for defining the appropriate measure
of target tissue dose. Tissue dose will usually either be a function of
integrated tissue exposure or a function of the extent of receptor binding
in a tissue. This latter metric of tissue dose is dependent on mass action
principles and not simply on integrated tissue exposure. Measures of dose
related simply to administered dose or total amount metabolized should
be viewed with great caution unless there are compelling reasons for
believing there is a direct correlation of these very coarse measures of
dose with actual tissue exposure. Once the proper measure of dose is
defined, a pharmacokinetic model should be developed to predict this dose
metric for various exposure scenarios in a variety of species. The biological
realism of physiologically based models confers on them certain advan-
tages for use in the risk assessment arena. Finally, much better cancer
risk assessments will be possible when validated pharmacokinetic models
for tissue dose are used in conjunction with more biologically, realistic
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Tissue Dosimetry in Risk Assessment 23
pharmacodynamic descriptions of the biological processes involved in
chemical carcinogenesis.
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Representative terms from entire chapter:
tissue exposure
