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Acknowledgements
This report is the product of a working group convened by the International Life Sciences
Institute (ILSI) Risk Science Institute (RSI) under its cooperative agreement with the Office of
Health and Environmental Assessment (OHEA), U.S. EPA. Financial support for this effort was
contributed by OHEA and by the American Industrial Health Council (AIHC). The material
presented in this report represents the conclusions of the ILSI RSI working group but not
necessarily those of the U.S. EPA or the AIHC.
Thanks are extended to each member of the working group on physiological parameters listed
below for their contributions to the working group and for comments on various drafts of the
document. We gratefully acknowledge the contribution of Dr. Michael Delp who wrote the
section on regional blood flow. We also acknowledge the contribution of Dr. Stan Lindstedt to
the working group and in assembly and compilation of portions of the literature used for this
report, in particular, the interspecies allometric equations provided in Appendix C.
Special recognition is extended to Mr. Ron Brown who took the lead role in drafting this report.
Without his efforts, this paper would not have been possible. Special recognition is also
extended to Ms. Andrea Gasper of RSI for her tireless efforts to prepare the final draft of the
report.
RSI Working Group on Physiological Parameters
Dr. Linda Bimbaum
U.S. Environmental Protection Agency
Dr. Kenneth Bischoff
University of Delaware
Dr. Jerry Blancato
U.S. Environmental Protection Agency
Mr. Harvey Clewell
ICF Kaiser, Int.
Dr. Robert Dedrick
National Institutes of Health
Dr. Michael Delp
Allegheny-Singer Research Inst.
Dr. Lorenz Rhomberg
Harvard University
(formerly U.S. EPA)
Dr. Val Schaeffer
Consumer Product Safety Commission
ILSI RSI Project Staff
Mr. Ron Brown
U.S. Food and Drug Administration
(formerly with RSI)
Dr. Jeffery Foran
Dr. Stephen Olin
Dr. Denise Robinson
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The International Life Sciences Institute (ILSI) is a nonprofit, worldwide foundation
established in 1978 to advance the understanding of scientific issues relating to toxicology, risk
assessment, the environment, nutrition, and food safety. By bringing together scientists from
academia, government, industry, and the public sector, ILSI seeks a balanced approach to solving
problems of common concern for the well-being of the general public. ILSI is affiliated with the
World Health Organization as a nongovernmental organization and has specialized consultative status
with the Food and Agriculture Organization of the United Nations.
The ILSI Risk Science Institute (RSI), a public, nonprofit research institute within ILSI, was
established in 1985 to improve risk assessment by strengthening the scientific principles on which
assessments are based. RSI works toward this goal by facilitating cooperation among scientists in
government, academia, industry, and the public sector through a wide range of research activities.
workshops and conferences, publications, seminars, and training and educational programs. RSI
receives support for its programs from government agencies, industry, and foundations.
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TABLE OF CONTENTS
1.0 INTRODUCTION 1
2.0 BODY WEIGHT & ORGAN VOLUME 4
2.1 CRITERIA FOR DATA SELECTION AND REPRESENTATION OF THE DATA 4
2.2 BODY WEIGHT 6
2.2.1 Body Weights in Mice 8
2.2.2 Body Weights in Rat 9
2.2.3 Body Weight in Dogs 11
2.2.4 Body Weight in Humans II
2.3 ORGAN VOLUME 12
2.3.1 Adipose Tissue 16
2.3.2 Adrenals 23
2.3.3 Bone 23
2.3.4 Brain 25
2.3.5 Gastrointestinal Tract 26
2.3.6 Heart 29
2.3.7 Kidney . 29
2.3.8 Liver 29
2.3.9 Lungs 32
2.3.10 Muscle 32
2.3.11 Pancreas 32
2.3.12 Skin 32
2.3.13 Spleen and Thyroid 34
2.4 USE OF ORGAN WEIGHT VALUES IN PBPK MODELS 34
2.4.1 Mass-to-Volume Conversion 34
2.4.2 Selecting Organ Weight Values for Animals Within a Species 35
2.4.3 Tissue Mass Balance 37
2.4.4 Anatomical and Physiological Heterogenicity 38
3.0 CARDIAC OUTPUT AND REGIONAL BLOOD FLOW 40
3.1 CRITERIA FOR DATA SELECTION AND REPRESENTATION OF THE DATA . 40
3.2 CARDIAC OUTPUT 42
3.3 REGIONAL BLOOD FLOW 45
3.3.1 Adipose Tissue 4l)
3.3.2 Adrenals 50
3.3.3 Bone : 50
3.3.4 Brain 51
3.3.5 Gastrointestinal Tract 51
3.3.6 Heart 52
3.3.7 Kidney 52
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3.3.8 Liver 52
3.3.9 Lung 53
3.3.10 Muscle 53
3.3.11 Skin 54
3.4 FACTORS THAT INFLUENCE TISSUE PERFUSION 55
3.4.1 Disease 55
3.4.2 Anesthesia 56
3.4.3 Physical Activity 59
3.4.4 Food Intake 60
3.4.5 Posture 60
3.4.6 Age 61
3.4.7 Gender 62
3.5 USE OF CARDIA OUTPUT AND REGIONAL BLOOD FLOW
VALUES IN PBPK MODELS 63
3.5.1 Selecting Cardiac Output Values for Animals
Within a Species 63
3.5.2 Summation of Regional Blood Flows 65
4.0 BLOOD VOLUME 67
4.1 CRITERIA FOR DATA SELECTION AND REPRESENTATION OF THE DATA .... 68
4.2 BLOOD VOLUME DATA 69
4.3 FACTORS THAT INFLUENCE ORGAN-SPECIFIC BLOOD VOLUME 73
5.0 ALVEOLAR VENTILATION 74
5.1 CRITERIA FOR DATA SELECTION 74
5.2 ALVEOLAR VENTILATION DATA 75
5.2.1 Mice 75
5.2.2 Rats 76
5.2.3 Dogs 76
5.2.4 Humans 77
5.3 FACTORS THAT INFLUENCE ALVEOLAR VENTILATION 77
5.3.1 Effect of the Compound Being Modeled on Respiratory Dynamics 77
5.3.2 Effect of Physical Activity 79
6.0 DISCUSSION XI
7.0 REFERENCES
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1.0 INTRODUCTION
Physiologically based pharraacokinetic (PBPK) models are becoming increasingly used by
regulatory agencies to estimate the internal dose of toxic agents or their metabolites to target tissues.
Using this technique, risk assessments for toxic substances can be based on estimates of the amount of
the agent that reaches the target tissue, rather than the dose estimated from exposure to the ambient
environment.
In PBPK modeling, the pharmacokinetic behavior of a compound in the body -- that is. its
absorption, distribution, metabolism, and elimination - is represented by equations that attempt to
quantitatively describe actual physiological processes. The parameters of these equations are key
anatomical and physiological descriptors of the organism, such as organ volume, organ per fusion rates
and breathing rates. Values for these parameters can be determined experimentally, external to the
process of fitting the model to the data. The advantage of such an approach is that a given model
structure can be used to describe different species, sexes, strains and conditions through choice of an
appropriate set of parameter values. Although models are invariably simplifications of complex
processes, their performance, accuracy, and biological relevance are enhanced by accurate
specification of parameter values. Accurate characterization of parameter values is especially
important for those parameters that have the greatest effect on the predictive ability of the model.
The parameter values necessary for the development of PBPK models fall into four broad classes:
physiological and anatomical descriptors, partition coefficients of the compound in various media.
descriptors of metabolic transformation pathways, and when the assumption of diffusion-limited
uptake is made transport parameters. Of these, the last three are compound-specific and must he
determined anew in each case; however, the physiological and anatomical descriptors will be common
to models for many different compounds. Therefore, it is advantageous to accumulate a base of
knowledge about representative physiological parameter values in multiple species.
In the application of pharmacokinetic models in risk assessment, the differences in compound
disposition between humans and experimental animals are of particular interest. Therefore, there is ;i
need to establish appropriate physiological values for humans and for the more commonly used
laboratory species. To address this need, representative values and biologically plausible ranges of
these values are provided for a number of anatomical and physiological parameters in multiple
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species. These representative values are means (or other measures of central tendency) selected from
a review of the literature for healthy, resting, young adult individuals. As a result, these values can
serve as reasonable, empirically based defaults that can be used in a PBPK model when case-specific
data are unavailable. Clearly, it is preferable to determine physiological and anatomical values
directly on the individuals under study, or, at least, on individuals known to be drawn from the same
population and subjected to similar conditions.
Several compilations of organ volumes, blood flows, and alveolar ventilation rates are available to
provide representative values for these parameters in a PBPK model. The document prepared for the
U.S. EPA by Arms and Travis (1988) has long served as the primary source of physiological
parameter values for PBPK models. More recently, Davies and Morris (1993) have prepared a
compilation of representative physiological parameter values that can be used in PBPK models. Each
of these documents provide "reference values" for the physiological parameters; values that were
selected by these investigators after their review of the literature. Although these reference values for
specific parameters provide modelers with input values for PBPK models, they do not indicate the
biological and experimental variability associated with data. Southern and Gruber (1994) have
recently commented on the absence of information provided by Davies and Morris (1993) on the
variability associated with their reference values. They note:
In their article presenting "acceptable" values..., Davies and Morris
(1) give a single mean reference value for each parameter which they
derived from an extensive search of the literature. While these values
may be useful for broad interspecies scaling, they represent a ballpark
without revealing the dimensions of the playing field.
Representation of the variability associated with these parameters is becoming increasingly
important with the use of distributional approaches, such as Monte Carlo analysis, in PBPK models.
This paper was prepared to expand and improve upon the efforts of Arms and Travis (1988) and
Davies and Morris (1993) by providing modelers with information on the variability associated with
each parameter and on factors that may influence the values selected for each parameter. This
document also expands on the earlier efforts of Arms and Travis (1988) and Davies and Morris
(1993) by expanding the database from which representative parameter values were selected; ensurins:
that parameter values are selected only from studies that used resting, healthy, unanesthetized (for
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cardiac output values) adult individuals; providing documentation of the criteria used to select the
studies; and addressing gaps in the data for several physiological parameters. Also included in this
paper are discussions of the potential problems associated with the use of default parameter values in
PBPK models.
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2.0 BODY WEIGHT AND ORGAN VOLUME
The compartments of a PBPK model correspond to specific organs and tissues in the body or to
organs and tissues that are grouped according to characteristics such the relative proportion of the
cardiac output that they receive (e.g., richly perfused tissues). The goal of this section is to provide
investigators with representative mean values for the volume of the organs, tissues, and tissue groups
that are typically represented in PBPK models, and an indication of the range of mean values for
these parameters identified in different studies. Organ volume values are provided for the adrenals.
adipose tissue, bone, brain, gastrointestinal tract, heart, kidneys, liver, lung, muscle, pancreas, skin.
spleen, and thyroid in four species. When available, values are also provided for the weight of
different regions within these tissues (e.g., stomach, small intestine, and large intestine of the
gastrointestinal tract).
PBPK models are often developed to simulate the pharmacokinetic behavior of a compound in a
group of experimental animals with known body weights. However, models can also be developed
for animals of a specified reference weight, typically a 25 g mouse, a 250 g rat, or a 70 kg human.
These values were proposed by Arms and Travis (1988) as reference body weights in their document
and have since been widely used in PBPK models. Prior to a discussion of organ volume values, the
validity of the reference body weights proposed by Arms and Travis (1988) will be explored.
2.1 CRITERIA FOR DATA SELECTION AND REPRESENTATION OF THE DATA
Body and organ weight values are provided in this document for healthy, adult animals. In
general, organ weight data were not used from mice less than 20 g or 7 weeks of age and rats less
than 200 g or 9 weeks of age. Data were collected only for strains of mice and rats that are
commonly used in research; organ weight data for other strains of mice and rats can be found in the
extensive compilations of data prepared by Crispens (1973) and Frank (1976). Also, only those
animals fed a conventional laboratory chow diet were used in this study. No data were collected from
transgenic animals or animals selectively bred to express a certain trait (e.g., obesity), captured in tin-
wild, kept under adverse environmental conditions, or exposed to drugs or toxic agents.
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Data obtained on organ weights of B6C3F1 mice and F344/N rats used as controls in 13-week
studies conducted by the National Toxicology Program (NTP) are reported separately from data
extracted from the open literature. Separate listing of these data provides investigators who are using
these strains exclusively for pharmacokinetic or modeling purposes with access to a data set specific
for these strains.
Two very comprehensive sources of organ weight data were not used to provide values for this
report: The encyclopedic collection of organ weight data for the rat complied by Donaldson (1924)
and the paper by Crile and Quiring (1940) providing organ weight data on multiple species. A
concern exists that organ weight values from these sources may not be representative of the organ
weights in strains of animals currently used in research.
Laboratory animal breeders and contract laboratories are potentially useful sources of organ
weight data. Data reported by Frank (1976) from these sources were used in this analysis, but the
reader should be aware that these values were not reported in the peer-reviewed open literature.
With few exceptions, the values provided for the weight of human organs were taken from the
ICRP (1975) Report of the Task Group on Reference Man. Given die comprehensive nature of this
work, and its degree of acceptance in many fields, no attempt was made to refine or expand on these
values.
Although the intent of this document is to provide investigators with physiological parameter
values for the species that are most commonly used in pharmacokinetic studies (mouse, rat. dog.
human), physiological parameter values may be required for other species as well. To address this
need, physiological parameter values for gerbils, goats, guinea pigs, hamsters, horses, oxen, and
rabbits are provided in Appendix C. Interspecies allometric equations were also provided in
Appendix C to estimate physiological parameter values for other species. When the data were
available, equations were provided in the text to allow investigators to estimate age- and body weight-
related changes in organ weight within a species.
The physiological parameter values provided in the tables in the body of the document are means
of the mean values reported in individual studies. The standard derivation values are standard
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deviations of the means. This approach was necessary because values for individual animals were
rarely reported in the literature. Although representation of the data in this way may be useful as a
measure of central tendency measure, it does not fully represent the variability of the data for
individuals within a species. Instead, the standard deviations reported in this paper are measures of
the variation among the different studies. This variability may be due to sampling error,
interlaboratory variation, and notably for some parameters (e.g., adipose tissue weight), differences in
the techniques used to obtain the data. As a result, these standard deviations reflect uncertainty more
than biological variability. Investigators that require data on the full range over which the parameter
values within a species can vary are encouraged to access the original literature. Each of the studies
used to derive the mean organ weight values are indexed in Appendix A.
Mean values for organ weight represented as a fraction of the body weight were derived only
from those studies that provided explicit body weight data or when the data were presented as percent
body weight in the paper. Relative organ weight values were not derived when only a range of body
weights was provided in the paper. Also, default organ weight estimates used in PBPK models were
not used to derive the mean values reported in this paper. Only those studies that reported values
obtained experimentally were used as sources of data.
In most cases, the values provided in this paper reflect the weight of organs that are drained of
blood. Notable exceptions are the data on mouse organ weight obtained from the Durbin et al.
(1992), where an effort was made to retain the blood in the tissues. As discussed in some detail in
Section 2.3.1, die weight of the adipose tissue reflects the weight of dissectible tissue only.
Gastrointestinal tissue weights do not include the contents of the gut. The weight of the "bone" in
rodents is, in some cases, the wet weight of the entire skeleton. When data were provided in a study
only for one-half of a paired organ (e.g., kidney), the assumption was made that the weight of both
halves was equal to twice the weight of the organ from one side.
2.2 BODY WEIGHT
Whenever possible, the actual weight of the animals undergoing the pharmacokinetic study should
be used when developing a PBPK model to describe the pharmacokinetic behavior of a compound or
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drug. However, default or reference body weight values may be necessary for certain applications.
such as scaling pharmacokinetic data to another species of a "standard" for body weight.
The reference body weight values selected by Arms and Travis (1988) for mice and rats were
largely derived from the standard body weights recommended by the U.S. EPA (1980) for these
species. Reference body weights of 30 g and 350 g are recommended in the U.S. EPA (1980)
document for mice and rats, respectively, because they are intended to approximate the terminal
weight for these species. However, Arms and Travis (1988) recommended reference body weights of
25 g and 250 g to be used for mice and rats, respectively, because they felt that animals are typically
used in pharmacokinetic studies before they reach terminal body weight. In contrast, Arms and
Travis (1988) recommend 70 kg as the reference weight for humans, a value that approximates the
terminal body weight in human males.
Male B6C3F1 mice and F344/N rats that weigh 25 g or 250 g, respectively, are only about 9-10
weeks of age, a period in which these animals are undergoing a period of rapid growth. There are
several concerns with the selection of reference body weights that occur in animals in a rapid-growth
phase. First, animals remain at this weight for only a short period, therefore, the proposed reference
weights are not representative of the weight of the animal at the majority of it's lifespan. Second.
organ weights are represented in this document as a fraction of the body weight. As long as the
organ weight/body weight ratio remains the same across all body weight values, then the selection ot
any body weight as the reference weight may be valid. Although the organ weight/body weight ratio
remains constant for most organs across body weights, there are notable exceptions, particularly the
volume traction of fat. As discussed in Section 2.3.1, the dissectible fat weight is about 9% ot the
body weight in a 250 g male F344/N rat and about 16% of the body weight in a 450 g rat. Since a
male F344/N rat weighs about 450 g for most for its lifespan, then it would be inappropriate to derive
a representative value for volume fraction of fat in this species based on the reference body weight
proposed by Arms and Travis (1988). Finally, an inconsistency exists when body weight values tor
mice and rats in a rapid-growth phase are used to develop a PBPK model that will be scaled up to
adult, 70 kg humans.
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2.2.1 Body Weight in Mice
Altman and Dittmer (1972) and Frank (1976) have compiled body weight values for a number or
strains of mice. Terminal body weight values reported by these investigators range from 28 to 40 g
in male mice and about 28 to 37 g in female mice, depending on the strain.
Data on age-related changes in body weight are routinely compiled for control animals used in
carcinogenesis bioassays conducted or sponsored by the NTP or the National Cancer Institute (NCI).
These compilations serve as useful and comprehensive sources of data on age-related changes in body
weight for strains of mice and rats that are often used in PBPK modeling efforts.
Cameron et al. (1985) described age-related changes in body weight among B6C3F1 mice used as
controls in carcinogenesis bioassays conducted or sponsored by the NCI between 1968 and 1981.
Data collected on these animals indicate that male mice gain approximately one gram of body weight
per week from the time they are put on test (6 weeks of age) to about 20 weeks. The mice then gain
weight more gradually until a maximum is reached about Week 80. A gradual weight loss is
observed in male mice from Week 80 to Week 110. A somewhat different growth pattern was
observed for female mice. The initial growth phase is not as rapid and a weight loss late in life was
not observed. In fact, untreated female mice weighed 1.3 g more than their male counterparts at
Week 110.
Presumably, age-associated body weight data were used by Cameron et al. (1985) to derive the
mean values without regard to the year in which the bioassay was conducted. However. Rao et al.
(1990a) have observed that the maximum mean body weight of B6C3F1 mice used in NCI or NTP
bioassays decreased over a nine year period from 1973 to 1981. For example, the maximum mean
body weight of male mice used as controls in bioassays initiated in 1973 was 45.4 g. whereas the
maximum mean body weight of male mice used as controls in bioassays started in 1981 was 41 .l) g.
A similar but less dramatic trend was seen in the body weight of female mice.
To provide an indication of the weight of mice used in more contemporary studies, the body
weight data reported by the NTP for mice used in the two-year bioassay of mercuric chloride (NTP.
1993a) was used to establish die relationship between age and body weight in B6C3F1 mice at
different growth stages. From these data, it appears that male mice typically go through tour growth
8
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phases throughout their life. A rapid growth phase occurs from birth to about 19 weeks of age. This
is followed by a period of more gradual growth from 19 to about 67 weeks of age. Body weight
seems to plateau at around 40 g in male mice from 67 to 91 weeks of age, followed by a gradual
decline in body weight in animals from 91 to 109 weeks of age. A similar pattern is seen in female
mice, however, the final stage of age-related loss of body weight is less dramatic, with body weight
plateauing at around 35 g for the remainder of the lifespan. Table 2-1 provides regression equations
for estimating the body weight of male and female B6C3F1 mice of various ages. General use of
these relationships requires the assumption that the growth pattern displayed by the mice used in this
particular NTP bioassay study are representative of their strain and species.
Table 2-1. Age-Related Growth in B6C3F1 Mice
Age (Weeks) Male Female
7 - 19 0.68(age) + 18.98 r = 0.97
7 - 18 O.SO(age) + 15.61 r = 0.94
20 - 67 0.18(age) + 28.04 r = 0.98
19-63 0.25(age) + 19.51 r = 0.99
68-91 Plateau around 40 g
63-109 Plateau around 35 g
92 - 109 -0.24(age) + 61.78 r = -0.65
The relationships shown in Table 2-1 are consistent with the observation at male B6C3F1 mice
weighing 25 g are only about 9 weeks of age. Therefore, this reference value is not representative of
the body weight of an adult animal.
2.2.2 Body Weight in Rats
Terminal body weight in rats ranges from about 335 g to over 500 g in male rats and about 220 y
to over 300 g in female rats, depending on the strain (Altman and Dittmer, 1972; Frank. 1976).
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Unlike the time-related decreases in maximum mean body weight observed in B6C3F1 mice used
in NCI or NTP bioassays, Rao et al. (1990b) noted a marked increase in the mean body weight of
male and female F344/N rats used in NCI and NTP bioassays from 1971 to 1983 (Table 2-2).
Table 2-2. Time-Related Changes in Body Weight in
Year
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
Untreated Male
NCI/NTP
Male
408
422
441
444
466
433
447
441
452
470
477
484
477
and Female F344/N Rats Used in
Bioassays (Rao et al. 1990b)
Body Weight (g)
Female
307
310
313
315
318
316
321
308
319
335
347
359
346
Cameron et al. (1985) reported that the body weight of male F344/N rats reached a maximum of
about 428 g at 76 weeks. However, according to Rao et al. (1990b), the mean maximum body
weight of male F344/N rats put on test in 1983 was 477 g. This value is consistent with the
maximum body weight of male F344/N rats used in the recent NTP (1993a) bioassay of mercuric
chloride. Body weight from male and female rats animals used as controls in this study were used to
derive the regression equations shown in Table 2-3.
10
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Age (Weeks)
7- 19
20-31
20-55
35-91
56-91
92- 109
Table 2-3. Age-Related Growth in
Male
16.20(age) + 86.80 r = 0.97
2.59(age) + 330.00 r = 0.99
Plateau around 475 g
-2.38(age) + 691.7 r = -0.94
F-344 Rats
Female
6.60(age) + 94.0 r =
Plateau around 225 g
2.07(age) + 152.93 r
Plateau around 330 g
0.94
= 0.99
Male F-344 rats weighing 250 g are only about 10 weeks of age and are in a rapid phase of
growth. The terminal weight of these animals, about 450-475 g, is maintained for most of the second
year of life. The terminal weight of male Sprague-Dawley rats can exceed 500 g (Gur and Waner.
1993).
2.2.3 Body Weight in Dogs
Body weight is dogs is highly strain-dependent and can range from around 1 kg to over 100 kg.
However, the Beagle is commonly used when dogs are required in pre-clinical toxicity and
pharmacokinetic studies. Andersen (1970) conducted a survey of caretakers in 18 commercial or
institutional Beagle colonies and found that male Beagles are typically used for experimental purposes
when they weigh about 23 Ibs (10.5 kg). Female Beagles are typically used when they weigh about
20 Ibs (9.9 kg). In the same volume, Andersen and Goldman (1970) provide data on age-related
changes in body weight in male and female Beagles. In female Beagles, body weight seems to
plateau at around 7-9 kg in the first and second years of life, and around 9-11 kg from years 2-7.
One group animals a little over three years of age weighed about 15.5 kg.
2.2.4 Body Weight in Humans
The ICRP (1975) has recommended a reference human body weight of 70 kg for males and 58 kg
for females. Although there is widespread acceptance of these values as reference body weights tor
male and female humans, they were derived primarily from only two studies (Stoudt et al.. 1960.
1965). Furthermore, subjects selected for these studies represent only one race and geographic area.
Therefore, these values should be used with some caution as reference body weights for humans.
11
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Designation of reference body weights does not provide information on the variability associated
with body weight values. Stoudt et al. (1960) reported that the mean body weight for males was 71.7
kg with a standard deviation of 10 kg. The mean body weights for females was 56.7 kg with a
standard deviation of 8.6 kg.
In summary, the reference body weights proposed by Arms and Travis (1988) for mice and rats
may be representative of the weight of the animals typically used in pharmacokinetic studies, but are
markedly lower than body weights attained by these animals for a majority of their lifespan. Use of
these reference weights in a PBPK model could result in an underestimate of the volume of the tat
compartment in adult mice and rats. Equations are provided for estimating age-related changes in
body weight in F344/N rats and B6C3F1 mice. Although reference values are not provided in this
document, it appears that representative body weights for adult male and female B6C3F1 mice are
about 35 and 40 g, respectively. Representative body weights for adult male and female F344/N rats
are about 330 and 450-475 g, respectively. Body weight values in Beagle dogs used for experimental
purposes range from about 9 to 16 kg. Regarding human body weight values, it is important to
recognize that the reference body weights for humans derived by the ICRP (1975) and adopted by
Arms and Travis (1988) are representative only for one race of humans in one geographical area.
2.3 ORGAN VOLUME
Values for the volume fraction of organs and tissues typically represented in PBPK models are
provided in Table 2-4 through Table 2-7 for mice, rats, dogs, and humans, respectively.
The mean values reported in Tables 2-4 through 2-6 were derived from experimentally derived
mean values reported in the literature. These data are provided in Appendix A. Data are also
provided in Appendix A for the weight of some organs not found in Tables 2-3 through 2-7 (e.g.
ovaries, testes, thymus).
12
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Organ
Adipose Tissue
Adrenals
Bone
Brain
GI Tract
Stomach
Small Intestine
Large Intestine
Heart
Kidneys
Liver
Lungs
Muscle
Pancreas
Skin
Spleen
Thyroid
Table 2-4. Relative
Mean ± SD
See text
0.048
10.73 ± 0.53
1.65 ± 0.26
0.60
2.53
1.09
0.50 ± 0.07
1.67 ± 0.17
5.49 ± 1.32
0.73 ± 0.08
38.40 ± 1.81
See text
16.53 ± 3.39
0.35 ± 0.16
ND
Organ Weight (% Body
in Mice
Range
See text
10.16- 11.20
1.35-2.03
0.40 - 0.60
1.35- 1.88
4.19-7.98
0.66 - 0.86
35.77 - 39.90
See text
12.86 - 20.80
0.16-0.70
ND
Weight)
Studies
1
3
4
1
1
1
4
7
7
5
4
5
5
n
Animals
5
30
419
5
5
3
46
84
84
35
40
45
60
Organ
Adipose Tissue
Adrenals
Bone
Brain
GI Tract
Stomach
Small Intestine
Large Intestine
Heart
Kidneys
Liver
Lungs
Muscle
Pancreas
Skin
Spleen
Thyroid
Table 2-5. Relative
Mean ± SD
See text
0.019 ± 0.007
See text
0.57 ± 0.14
0.46 ± 0.06
1.40 ± 0.39
0.84 ± 0.04
0.33 ± 0.04
0.73 ±0.11
3.66 ± 0.65
0.50 ± 0.09
40.43 ± 7.17
0.32 ± 0.07
19.03 ± 2.62
0.20 ± 0.05
0.005 ± 0.002
Organ Weight (% Body
in Rats
Range
See text
0.010-0.031
See text
0.38-0.83
0.40-0.60
0.99- 1.93
0.80 - 0.89
0.27 - 0.40
0.49-0.91
2.14-5.16
0.37 -0.61
35.36 - 45.50
0.24 - 0.39
15.80 - 23.60
0.13-0.34
0.002 - 0.009
Weight)
Studies
7
9
4
4
4
9
12
15
7
2
3
5
8
3
n
Animals
1017
548
46
46
46
632
1091
2230
173
30
34
138
582
215
13
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Table 2-6. Relative Organ Weight (% Body Weight) in Dogs
Adipose Tissue
Adrenals
Bone
Brain
GI Tract
Stomach
Small Intestine
Large Intestine
Heart
Kidney
Liver
Lungs
Muscle
Pancreas
Skin
Spleen
Thyroid
Mean ± SD
0.009 ± 0.004
8.10
0.78 ± 0.16
0.79 ±0.15
2.22 ± 0.68
0.67 ± 0.03
0.78 ± 0.06
0.55 ± 0.07
3.29 ± 0.24
0.82 ± 0.13
45.65 ± 5.54
0.23 ± 0.06
See text
0.27 ± 0.06
0.008 ± 0.0005
Range
0.004-0.014
0.43 - 0.86
0.65 - 0.94
1.61 -2.84
0.65 - 0.69
0.68 - 0.85
0.47 - 0.70
2.94 - 3.66
0.62- 1.07
35.20 - 53.50
0.19-0.30
See text
0.21 -0.39
0.0074-0.0081
Studies
4
1
4
4
4
2
6
6
6
9
2
3
6
2
n
Animals
64
8
230
37
37
37
206
206
206
339
24
14
182
10
Table 2-7. Relative Organ Weight (% Body Weight) for
Reference Man (ICRP, 1975)
Organ
Adipose Tissue"
Adrenals
Boneb
Brain
GI Tract'
Stomach
Small Intestine
Large Intestine
Heart
Kidney
Liver
Lungsd
Muscle
Pancreas
Skin
Spleen
Thyroid
Reference Weight
21.42
0.02
14.29
2.00
1.71
0.21
0.91
0.53
0.47
0.44
2.57
0.76
40.00
0.14
3.71
0.26
0.03
a Subcutaneous, separable yellow marrow, interstitial
b Bone and marrow
c Except esophagus
d Without blood
14
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Organ weight values have been reported by the NTP since 1991 for control and treated in animals
13-week and two-year studies. Typically, data are reported on the weight of the brain, heart, right
kidney, liver, lung, and thymus in animals undergoing 13-week studies and on the weight of the
brain, right kidney, and liver at a 15-month time interval in the two-year bioassay. Mean organ
weight values were derived for B6C3F1 mice and F-344 rats from the organ weight data reported in
ten randomly selected bioassays for control animals in 13-week exposure studies. These values are
summarized in Table 2-8.
Table 2-8. Relative Organ Weight (% of Body Weight)
Organ
Adrenal
Brain
Heart
Kidneys
Liver
Lungs
Thymus
Body Weight
of Control B6C3F1 Mice and F-344
13-Week NTP Studies*
B6C3F1 Mice
Male Female
0.02 0.04
1.49 1.98
0.53 0.53
1.75 1.52
4.62 4.73
0.70 0.83
0.12 0.22
30.57 23.91
Rats Used in
F-344 Rats
Male
0.01
0.56
0.30
0.67
3.49
0.45
0.09
341.90
Female
0.03
0.90
0.34
0.69
3.22
0.55
0.13
195.60
a Values are means of mean organ weight values reported in ten randomly selected 13-week NTP studies.
There appears to be relatively little difference in body weight-normalized values for organ weight
among different strains of rats used in NTP studies (Table 2-9).
15
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Table 2-9. Relative Organ Weight (% Body Weight) of
Three Strains of Rats Used as Controls in a
13-Week NTP Study
Brain
Heart
Kidneys
Liver
Lung
Thymus
Body Wt. (g)
Male
0.54
0.29
0.68
4.29
0.48
0.08
363
F-344/N
Female
0.93
0.33
0.76
3.53
0.62
0.13
194
Sprague-Dawley
Male
0.47
0.41
0.84
4.11
0.55
0.11
449
Female
0.73
0.40
0.76
4.12
0.71
0.14
271
Osborne-Meiulel
Male
0.50
0.37
0.74
3.92
0.45
0.08
421
Female
0.71
0.37
0.66
3.79
0.56
0.11
274
A more complete discussion of organ weight values is provided below.
2.3.1 Adipose Tissue
Prior to discussing values for this parameter, it is important to first define what constitutes the tat
compartment in a PBPK model. In their review of PBPK modeling principles, Krishnan and
Andersen (1994) have noted that "fat depots such as perirenal, epididymal, and omental fat as well as
the adipose component of many other tissues are grouped and represented as a single "fat"
compartment." However, values selected for this parameter in rodent PBPK models have largely
come from studies in which the fat was carefully dissected from the animal (e.g.. Banks et al.. 1990:
Caster et al., 1956; Decad et al., 1981; Delp et al., 1991; Gasiewicz et al., 1983). Consequently, the
fat compartment in most rodent PBPK models primarily represents dissectible fat in fat depots, and
depending on how the dissection was done, the fat that is present interstitially in muscle, but not the
adipose component of other tissues. There are two reasons why die weight of the adipose component
of other component tissues is not usually included in the fat compartment: 1) the adipose would
already be accounted for in the total weight of those organs, and 2) any storage role for these lipids
would be accounted for in the partition coefficient for these tissues. Therefore, for the purposes of
this document, the weight of the adipose tissue in mice, rats, dogs, and humans is intended to
represent the weight of dissectible fat, not the total fat content of those species.
Values for the fat content of humans is rarely derived through dissection. Rather, techniciues such
as in vivo neutron activation analysis, whole body counting for total body potassium, tritiated water
16
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dilution for total body water, bioelectric impedance, underwater weighing, and skinfold
anthropometry are commonly used to estimate total body fat. However, values reported in this
section were obtained from the limited studies of human cadaver dissection.
Mouse
Table 2-10 summarizes data on the dissectible fat content of nine strains of mice used in research.
Values for dissectible fat content range from 5.0% to 14.0% and are highly strain and age dependent.
For example, the mean fat content of DBA strain mice is 12.2%, compared to a mean fat content of
6.8% in C57BL strain mice (with body weights £ 33g).
Strain
C57BL/6J
C57BL/6J
C57BL/6N
C57BL/6N
C57BL/6N
C57BL/6N
DBA/2J
DBA/2J
B6D2
Sex
M
M
M
M
M
M
M
M
M
Table
BW
23.1
26.0
25.2
33.0
30.1
37.5
23.9
25.1
24.3
2-10. Fat Content
Tissue Weight
(% BW)
5.9
7.5
5.8
7.6
7.4
14.0
11.5
12.9
5.0
of Mice
Reference
Gasiewicz et'al. (1983)
Decadetal. (1981)
Birnbaum (1993)
Birnbaum (1993)
Birnbaum (1993)
Birnbaum (1993)
Gasiewicz et al. (1983)
Decad et al. (1981)
Gasiewicz et al. (1981)
In heavier mice, fat constitutes a greater percentage of body weight. Birnbaum (1993) has shown
that 18 month old C57BL/6N mice weighing 37.5 g have a fat content of 14%. whereas three-month-
old mice of die same strain weighing 30.1 g have only about half as much fat (7.4%). This does not
appear to simply be an age-related effect, since 28-month-old animals of the same strain, weighing 33
g, had a fat content of 7.6%.
West et al. (1992) have conducted an extensive investigation of the fat content of various strains of
mice. Values are provided in this paper for the weight of various adipose tissue depots (e.g..
epididymal, retroperitoneal, inguinal, mesenteric, and interscapular). Although these data may he
useful for investigators dial require data on the weight of individual fat depots, it is not clear that the
sum of the depot weights represents the weight of all of the dissectible fat in these mice. For
example, the sum of the tissue weights from these depots as reported by West et al. (1992) equals
17
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2.02% and 4.26% of the body weight in C57BL/6J and DBA/2J mice, respectively, compared to
values about three times greater for these strains reported by Decad et al. (1981) and Gasiewicz et al.
(1983). The weight of various adipose tissue depots in mice has also been reported by Atal et al.
(1994) and Rebuffe-Scrive et al. (1993).
Rats
Values reported by Caster et al. (1956), Lutz et al. (1977), and Delp et al. (1991) for fat content
of the rat have been widely used for this parameter in PBPK models. In these studies, fat content was
determined by careful dissection, removal, and weighing of all visible adipose tissue. The values for
fat content reported in these studies range from 5.5% to 7.0% for male Sprague-Dawley rats.
Bailey et al. (1980) have conducted a thorough study of body weight-related changes in the weight
of individual fat depots in male Sprague-Dawley rats and have derived intraspecies allometric
equations to describe these relationships (Table 2-11).
Table 2-11. Intraspecies Allometric Equations to Describe
the Relationship Between Body Weight and the Size of Various
Fats Depots in Male Sprague-Dawley Rats (Bailey et al., 1980)
Fat Depot
Axillary
Buttock
Epididymal
Inguinal
Mesenteric
Perirenal
Equation'
y = 0.83 BW •»
y = 0.16BW168
y = 0.012 BW216
y = 0.009 BW239
y = 0.97 BW1 •*
y = 0.00062 BW--70
r
0.945
0.961
0.981
0.951
0.937
0.976
a y = log tissue weight (mg), BW = log body weight (g)
Data on age- and body weight- associated changes in the weight of intrascapular brown adipose
tissue (IBAT) in male Sprague-Dawley rats was reported by Sbarbati et al. (1991). Based on these
data, the following relationship can be derived to estimate the weight of this fat depot as a function <>t
body weight:
IBAT Wt. (g) - 0.00094 (BW) + 0.12, r = 0.96,
18
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where BW equals body weight in grams.
Body weight-related changes in the combined weight of the fat depots in male Sprague-Dawley
rats, as reported by Bailey et al. (1980) are shown in Table 2-12.
Body Weight
152.2
254.5
337.6
443.1
497.1
Table 2-12. Body Weight-Related Changes
Weight in the Male Sprague-Dawley Rats
(g) Total Fat (g)
7.016
18.354
27.072
44.410
59.785
in the Total Fat Depot
(Bailey et al., 1980)
Depot Weight (% BW)
4.61
7.21
8.02
10.02
12.03
These values are fairly consistent with those obtained by Delp et al. (1991) for the weight of all
dissectible fat.
Assuming the sum of the fat depot weights in the Bailey et al. (1980) study closely approximates
the total weight of dissectible fat, the following relationship can be used to estimate the proportion or
the body weight in male Sprague-Dawley rats that represents dissectible fat.
Adipose tissue (% BW) = 0.0199 (BW) + 1.664, r = 0.99,
where BW equals body weight in grams.
Extensive use of the rat as a animal model in nutrition and endocrinology research has lead to the
publication of a large body of literature containing values for the fat content of various strains of rats
Typically, chemical extraction methods are used in these studies to determine the total amount of tat
in the body. Use of chemical extraction or other methods to determine total body fat content often
yields values that are as much as 2-3 times higher than those obtained though dissection. Therefore;.
modelers requiring these data should keep in mind how values for fat content were obtained before
using these values in a PBPK model. However, chemical extraction methods can also be used to
assess the accuracy of dissection methods to determine fat weight. For example, using direct
19
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dissection, Manning et aJ. (1991) found the body fat of male Sprague-Dawley rats to be 7.36% of the
total body weight. Chemical extraction of the carcass minus the visceral organs yielded a similar
value (6.9%) for this parameter.
To accurately describe age-related changes in the pharmacokinetic behavior of TCDD in F-344
rats, Birnbaum and colleagues (Banks et al., 1990; Anderson et al., 1993) obtained data on the fat
content of F-344 rats from age 3 to 120 weeks (Table 2-13). Based on these data, the following
relationship can be derived to estimate fat content from body weight in male F-344 rats:
Fat Content (% BW) = 0.035 (BW) + 0.205, r = 0.98,
where BW equals body weight in grams.
This equation has recently been used to estimate the fat content of male F-344 rats in the PBPK
models developed by Kedderis et al. (1993) and Evans et al. (1994).
Week
3
5
8
10
13
21
36
52
56
64
86
100
117
120
Table 2-13. Fat Content of
Anderson et al Banks et al.
(1993) (1990)
4.0 ± 0.7
4.3 ± 0.2
9.6 ± 0.3
10.6 ± 0.7
15.6 ± 0.7
16.0 + 2.1
18.2 ± 2.2
13.0 ± 3.3
Male Fischer 344 Rats
Study
Carter et al. Rikans et al.
(1991) (1993)
10.0
21 ± 1
13.8
29 ± 1
15.1
17 ± 1
20
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As shown in Table 2-13, age-related differences in the fat content of male F-344 rats have been
reported in at least two other studies. Although comparisons at the same time points are not possible.
the fat content values reported by Carter et al. (1991) for carcass without visceral organs are
comparable to those reported by Banks et al. (1990) and Anderson et al. (1993). Close
correspondence of the values obtained by dissection (Banks et al., 1990; Anderson et al., 1993) and .
chemical extraction of the carcass (Carter et al., 1991) suggest that careful dissection can yield
accurate values for the fat content of the animal minus the visceral organs, as also shown in the
Manning et al. (1991) study. Rikans et al. (1993) reported obtained values for fat content of male F-
344 using a dual-energy x-ray absorptiometry technique. These values are somewhat higher than
those reported by Banks et al., 1990; Anderson et al., 1993; or Carter et al., 1991, perhaps, in part.
because this technique quantifies all of the lipid in the body.
Dogs
Wilkinson and McEwan (1991) used an ultrasound technique to estimate the thickness of the
subcutaneous layer of fat in dogs at different body sites, and correlated subcutaneous fat thickness to
total body fat. Using this technique, they found fat constitutes about 38.2% of the body weight in
Beagles. However, this value seems to be too high for Beagles used for experimental purposes.
Humans
Studies of fat content in humans number in the hundreds, if not thousands. However, relatively
few studies have employed dissection to obtain these values. Clarys et al. (1984) summarized the
results of all of the studies they identified in the literature in which human fat content values were
obtained through dissection. Values for fat content in adult males 30 to 60 years of age (mean age =
42.4 years) range from 5.2% to 21.6% of the total body weight (mean fat content = 13.6 ± 5.3%, n
= 7). Only two values were provided in this summary for adult females; one of which was a 67 year
old woman that died from carcinoma. Therefore, these data were not used in this analysis.
In addition, Clarys et al. (1984) determined the fat content of 25 adult cadavers using dissection.
However, the mean age of males and females in this study was 72 and 80 years, respectively. Since
fat content increases in humans with increasing age (Deurenberg et al., 1991), the values obtained h\
Clarys et al. (1984) are not representative of young adult humans. The ICRP (1975) offered the
21
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following default values for weight of adipose tissue in a 70 kg reference man and a 58 kg reference
woman (Table 2-14).
Site
Subcutaneous
Separable
Yellow Marrow
Interstitial
TOTAL
Table 2-14. Adipose Tissue Distribution
as Reported by ICRP (1975)
in Humans
Relative Adipose Tissue Weight (%BW)
Male (70 kg)
10.7
7.1
2.1
1.4
21.3
Female (58 kg)
22.4
6.9
2.2
1.2
32.7
The total fat mass corresponds to 21.3% of the body weight in males and 32.7% of the body
weight in females.
If estimates of fat content in humans are encountered in the literature, modelers should be aware
that these estimates can vary widely depending on the techniques used to obtain the estimates. For
example, estimates of fat content in males can vary from about 15-16%, as measured using
bioelectrical impedance, to a value about twice as high in the same subjects, when estimated based on
total body potassium (Wang et al., 1993). Therefore, variability in reported fat content values in
humans is due, in part, to the experimental technique used to obtain these values.
To improve the fit of PBPK model-derived simulations to experimental data, it may be necessary
to include more than one fat compartment in the model. Fiserova-Bergerova (1992) provides an
example of how two fat compartments were included in a PBPK model of anesthetic agents in
humans. Consistent with the reference values provided by the ICRP (1975), Fiserova-Bergeruva
(1992) assumed that 60% of the body fat of a reference man is subcutaneous fat and 35% of the tat is
found in internal fat depots. The remaining 5% is assumed to be interstitial fat and is not explicitly
represented in the model.
22
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2.3.2 Adrenals
The adrenals are rarely represented as a separate compartment in PBPK models. Nevertheless,
the weight of this organ is often determined in control and treated animals in toxicity studies. As a
result, data are readily available on die weight of this organ in experimental animals.
The adrenals constitute approximately 0.02% of the body weight in male B6C3F1 mice at the end
of 13-week studies conducted by the NTP and 0.04% of the body weight of female mice used in these
studies. These estimates are consistent with the data reported by Dowell et al. (1992) for female
C57BL mice. However, the data compiled by Frank (1976) on the weight of the adrenals in 20
strains of mice suggests that the mean weight of this organ in male mice is on the order of 0.01 % and
0.02% of the body weight for male and female mice, respectively.
Based on data from six studies and over 1,000 animals, the mean relative weight of the adrenals in
rats is approximately 0.02% of the body weight. The adrenals of male F344/N rats used as controls
in 13-week NTP studies constituted about 0.01 % of the body weight; the relative weight of the
adrenals in female rats was about 0.03% of the body weight.
The relative weight of the adrenals ranges from about 0.004% to 0.14% of the body weight in
dogs, with a mean weight of about 0.01%.
In humans, adrenal weight remains fairly constant throughout adult life, weighing about 13 g in
males and 12 g in females, or about 0.02% of the body weight (ICRP, 1975).
2.3.3 Bone
The traction of the body weight composed of bone in mice is fairly consistent in the three studies
identified that report these data. Baxter et al. (1994) found that bone comprises 10.16% of the body
weight in female Nu/Nu mice, Bourne et al. (1992), reported a value of 10.83% of the body weight
in female Balb/c mice, and Durbin et al. (1992) determined that the skeleton comprised 11.20% of
the body weight of female Swiss Webster mice.
Values for relative bone weight in rats reported in most studies range from 5-7% of the body
weight. Caster et al. (1956) determined that the fresh weight of the skeleton constituted 5.96% of the
23
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body weight in rats. Donaldson (1924) has compiled an extensive collection of data on body weight-
and age-related changes in bone weight in Albino rats. These data suggest the skeleton of a 250 g rat
constitutes about 6% of the body weight, whereas the skeleton of a 450 g rat constitutes about 5% of
the body weight. MacPherson and Tothill (1978) determined fat-free bone weight to be 4.77 ±
0.17% of the body weight of male rats. Prior to developing a PBPK model for bone-seeking
elements in the growing rat, O'Flaherty (1991a) characterized age-related changes in bone weight and
volume in rats. From her review of the literature, she selected a value of 7.3 g/100 g BW and 4.9
ml/100 g BW as the mass and volume, respectively, of the skeleton (minus cartilage) in a mature
small animal skeleton. In contrast to these values that range from about 5-7% of the body weight.
Delp et al. (1991) reported that the mass of bone in rats with a mean weight of 366 g was 53.9 g, or
about 14.7% of the body weight. The discrepancy between values for bone weight reported by most
investigators and those obtained by Delp et al. (1991) may be due, in part, to residual tissue present
on the bones in the Delp et al. (1991) study. For example, cartilage was included with many of the
bones dissected from the rat, especially the ribs. Also, small amounts of residual muscle and
connective tissue remained even after scraping. Since such a marked difference exists between values
for this parameter identified by different investigators, no mean value across studies was derived tor
Table 2-5.
Few studies have been published that report total bone weight in dogs. The mean relative bone
weight in mongrel dogs with a mean body weight of 21 kg is 8.1 % of the body weight (Quillen and
Reid, 1988).
The entire skeleton of a reference adult male human makes up 14.3% of the body weight (ICRP.
1975). This value is essentially identical to that reported by Clarys et al. (1984) for dissected
cadavers. Bone comprises 50% of the weight of the skeleton (or 7.1% of the body weight) in
humans; 80% of the bone mass is cortical bone and 20% is trabecular bone. The remainder of the
skeleton is composed of red marrow (hematopoietic tissue), yellow marrow (fatty tissue), cartilage.
and periarticular tissue. O'Flaherty (1991a) identified the proportion of the mature skeleton (minu>
cartilage) in a 350 g male rat that would be represented by cortical bone, trabecular bone, red inum>u
and yellow marrow. These estimates are shown in Table 2-15, with similar estimates tor the
composition of bone in mice and humans from Durbin et al. (1992) and ICRP (1975), respectively.
24
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Table 2-15. Composition of the Skeleton
Skeleton
Bone
Cortical
Trabecular
Red Marrow
Yellow Marrow
Cartilage
Periarticular Tissue
Mouse*
11.2
5.4
4.0
1.4
5.8d
Rat"
7.3
5.0
4.0
1.0
2.1
0.2
Human"
14.2
7.1
5.7
1.4
2.1
2.1
1.6
1.3
Durbin et al. (1992)
O'Flaherty (1991a)
ICRP (1975)
Bone soft tissue, mostly marrow, but also may include some connective tissue and adherent
muscle.
O'Flaherty et al. (1991a,b) has derived intraspecies allometric equations to predict skeletal weight,
marrow weight, and marrow-free bone weight in rats and humans as a function of age (Table 2-16).
Table 2-16. Body Weight-Dependent Changes in Bone Weight
in Rats and Humans (O'Flaherty, 1991a,b)
Rat3 Humanb
Skeletal Weight (g) = 0.0801 (BW)0983 58 (BW)1 :i
Marrow Weight (g) = 0.0469 (BW)0** 7.02 (BW)1 M
Marrow-free Bone Wgt. (g) = 0.0257 (BW)"° 29 (BW)':i
a BW = body weight in grams
b BW = body weight in kilograms, marrow-free bone weight in humans includes
marrow-free and cartilage-free bone weight
2.3.4 Brain
The brain constitutes about 1.7% of the body weight in mice, 0.6% in rats, 0.8% in dogs, aral
2.0% in humans. When expressed on a body weight-normalized basis, a difference in brain weight
also exists between male and female rodents (Table 2-8), principally because of the relatively larger
mass of male animals.
25
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The brain has been represented as a single compartment in a number of PBPK models of
compounds with neurotoxic or therapeutic effects in the central nervous system. However, parallel
increasing knowledge of the site-specificity of drug or neurotoxicant action in the brain, more
sophisticated PBPK models are being developed that represent different regions of the brain in the
models. Therefore, knowledge of the relative weight of the brain regions in different species is
important for PBPK models that represent these regions. Table 2-17 provides information on the
relative weight of the cerebrum, cerebellum, and brain stem in rats, dogs, and humans.
Region
Cerebrum
Cerebellum
Midbrain
Olfactory Lobe
Brain Stem
Medulla
Pons
Table 2-17. Relative
Rats
Rat"
51.6
14.3
15.2
2.8
16.1
11.5
4.6
Weight of Brain Regions in
and Humans
Percent of Total Brain Weight
Humanb
85-88
10-12
1.9-2.3
Delp et al. (1991)
ICRP (1975)
2.3.5 Gastrointestinal Tract
Explicit representation of the gastrointestinal tract in a PBPK model may be necessary when the
modeled compound is administered orally (Clewell and Jarnot, 1994), when enterohepatic
recirculation or biliary clearance occurs (e.g., Engasser et al., 1981; King et al, 1983). when the
gastrointestinal tract is a target tissue of toxicity, or when gut metabolism is represented in the model
(e.g., Frederick et al., 1992).
Without contents, the gastrointestinal tract (stomach, small intestine, and large intestine)
constitutes about 2-4% of the body weight in mice, rats, dogs, and humans. Somewhat higher values
have been reported in two mouse studies (Baxter et al. 1994; Bourne et al. 1992), but the weight nt
the gastrointestinal tract reported in these studies includes the contents. Values for the relative weight
26
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of the different subdivisions of the gastrointestinal tract in rats, dogs, and humans are provided in
Table 2-18.
27
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Table 2-18. Relative Weight (% Body Weight) of the Gastrointestinal Tract
Segments in Mice, Rats, Dogs, and Humans
Segment
Stomach
Forestomach
Glandular Stomach
Small Intestine
Duodenum
Jejunum and Ileum
Large Intestine
Cecum
Colon
Gl Tracl Total
Mouse
Stott et al.
(1983)
0.60
0.16
0.44
2.53
1.09
0.30
4.22
Rat
Caster et al. Delp et al. Peters & Stott et al.
(1956) (1991) Boyd (1983)
(1966)
0.50 0.40 0.52 0.40
0.13 0.13
0.39 0.27
1.93 1.39 0.99 1.27
0.15
1.24
0.89 0.80 0.86 0.82
0.35 . 0.32 0.33
0.44 0.54
3.32 2.59 2.37 2.49
Dog
Andersen Andersen Goodhead Quillen &
(1970) (1970) (1969) Reid
(1988)
0.94 0.91 0.65 0.69
2.77 2.84 1.61 1.65
0.25 0.19
1.36 1.46
0.69 0.65
0.23 0.47
4.40 4.40
Human
ICRP
(1975)
0.21
0.91
0.53
1.65
28
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23.6 Heart
As shown in Tables 2-4 through 2-7, the weight of the heart is fairly constant across species and
constitutes approximately 0.50% of the body weight in mice, 0.13% of the body weight in rats.
0.78% of the body weight in dogs, and 0.44% of the body weight in humans.
2.3.7 Kidney
The kidney constitutes about 1.67% of the body weight in mice, 0.73% in rats, 0.55% in dogs.
and 0.44% in humans. The volumetric composition of the human and dog kidney is on the order of
70% cortex, 25% medulla, and 5% collecting system (ICRP, 1975).
2.3.8 Liver
The relative weight of the liver is fairly constant across species. For example, to develop an
allometric scaling equation for this parameter, Boxenbaum (1980) used relative liver weight values
that ranged from 1.06% in cattle to 5.06% in the mouse. The mean relative liver weights for the
species addressed in this paper are: mouse, 5.5%; rat, 3.4%; dog, 3.3%; and humans 2.6%. A more
complete discussion of these parameter values is provided below.
Mice
The mean weight of the liver in mice derived from the data reported in 7 studies is about 5.5% of
the body weight. The mean values from these studies range from 4.2% to 8.0%. Values for
individual liver weights in some studies spanned approximately the same range.
The data reported by Reubner et al. (1984) suggest that strain-related differences do not exist in
relative liver weight in mice. The geometric means of liver weight/body weight ratios reported in
C57BL/6, C3H/He, and B6C3F1 strains of mice were 5.7%. 5.5%, and 5.6%. respectively.
Body weight-normalized values for liver weight in mice appear to decrease slightly as the animal
ages. Demarte and Enesco (1986) found that the liver constitutes about.5.7% of the body weight in
8-week-old male Swiss albino mice. This value fell to about 4.6-4.9% in mice aged 12 to 36 weeks.
and to about 4.2% in mice from 52 to 78 weeks old.
29
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The mean value reported in Table 2-4 for this parameter is identical to the reference value selected
by Arms and Travis (1988) for liver volume in mice. To develop interspecies scaling relationships
for liver weight, Boxenbaum (1980) used a value of 5.06% of the body weight as the relative liver
weight in mice. However, the reference value selected by Davies and Morris (1993) for this
parameter, 8.75%, is significantly higher than the mean values that have been reported in the
literature. In fact, this proposed reference value overestimates mean values for relative liver weight
in 20-week-old mice (Table 2-8) by about two-fold.
Rats
Relative liver weight in rats ranges from about 2.1% of the body weight, as reported by Kozma et
al. (1969) for male Long Evans rats, to 5.2% of the body weight, as reported by Frank (1976) tor
male Sprague-Dawley rats. The mean value for relative liver weight for the rat across 15 studies is
3.7%, a value similar to that reported by Delp et al. (1991) for male Sprague-Dawley rats and to the
mean value derived from rat liver weight data reported in ten randomly selected 13-week studies
conducted by the NTP (Table 2-8).
Based on the data reported by Coniglio et al. (1979), the following equation can be derived to
estimate the absolute weight of the liver of male F344 rats as a function of age:
Log Liver Weight (g) = Log Age (months) x 0.1482 + 0.9468; r = 0.999.
Dogs
The liver constitutes approximately 3.3% of the body weight in dogs. Mean values for this
parameter identified in the literature range from 2.9% to 3.7%. Davies and Morris (1993) selected a
reference value of 3.2% from their review of the literature, and Boxenbaum (1980) used a value nt
2.9% of the body weight for allometric scaling.
Humans
In humans, the median liver weight in males and females aged 20-29 is 1820 g and 1440.
respectively (ICRP, 1975), or about 2.6% of the body weight. A comparable liver volume was
reported by Swift et al. (1978) for persons in the same age group. In this study, individuals with
30
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healthy, non-palpable livers had a liver volume that was 1.8% of the body weight, as measured by
ultrasound.
Liver weight remains relatively unchanged throughout most of adulthood, but declines by about
25% in persons over the age of 65 years compared to 40-year-old individuals. A fairly poor
correlation is obtained when body weight is plotted against liver volume in females (r = 0.64). but
this correlation improves somewhat for males (r = 0.71).
Both Arms and Travis (1988) and Davies and Morris (1993) selected 2.5% as the reference value
for this parameter in humans. Boxenbaum (1980) used 2.42% as the relative liver weight in humans
for allometric scaling of this parameter.
As discussed above, advanced age is associated with a decline in liver volume. The reduced
capacity of the liver to clear substrates like antipyrine is due in part to age-related reduction in liver
volume, hepatic blood flow and, to some degree the intrinsic metabolic capacity of the liver
(Woodhouse and Wynne, 1992).
A number of compounds are known to produce hepatomegaly in humans and experimental animals
(Plaa, 1991). In some cases, liver volume can increase by two-fold in rodents exposed to hepatotoxic
compounds. For example, the relative liver weight in Swiss Webster mice exposed to 10.000 ppm or
oxazepam in a 14-week study conducted by the NTP (1993b) was 10% of the body weight, compared
to 5% of the body weight in control animals.
Depending on the pathological process leading to liver enlargement, increased liver volume may
be associated with an increase, a decrease, or no change in the hepatic clearance of xenobiotic
compounds (Sotaniemi et al., 1992). Induction of metabolic enzymes along with liver enlargement
will result in an increase of metabolic capacity in vitro and may produce increased hepatic clearance
in vivo. Fatty infiltration is a common cause of liver enlargement in humans. Patients with a fatty
liver will have.reduced hepatic capacity, when metabolic activity is normalized for liver weight, hut
the metabolic capacity of the whole liver will be unchanged. Fibrotic changes in the liver (e.g..
cirrhosis) result in increased liver volume, but decreased metabolic capacity. When liver volume is
increased because of the presence of tumors, the metabolic capacity of the unaffected tissues typical!)
31
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remains the same. Therefore, liver volume may increase in animals and humans as a result of
pathological processes. As result, it may be necessary to represent these changes in a PBPK model.
However, changes in liver volume do not always result in an increase in the metabolic capacity of the
liver and changes to the intrinsic metabolic capacity of the liver should be accounted for as well.
2.3.9 Lungs
The lungs constitute from 0.5-0.8% of the body weight in mice, rats, dogs, and humans. Since
the lung is such a vascular tissue, some percentage of the lung weight will consist of residual blood.
even in reasonably well drained tissues.
2.3.10 Muscle
Skeletal muscle constitutes, by far, the largest single tissue in the body on a weight or volume
basis. Muscle mass represents about 40% of the body weight in mice and rats and 45% of the body
weight in dogs. Skeletal muscle constitutes about 29% and 40% of the mass of adult female and mule
humans, respectively.
Investigators requiring data on the weight of specific muscles in the rat are encouraged to access
the extensive data set data published by Delp et al. (1991).
2.3.11 Pancreas
The weight of the pancreas constitutes about 0.32% of the body weight in humans, 0.69% of the
body weight in dogs, and 0.14% of the body weight in humans. Few data are available on the weight
of the pancreas in mice. Data tabulated by Crispens (1975) suggest that the pancreas makes up 0.5-
0.7% of the body weight in two strains of obese New Zealand mice, but the relevance of these data
for strains of mice used more commonly in pharmacokinetic studies is unknown.
2.3.12 Skin
Representation of the skin in PBPK models is important when the skin and skin-associated
structures (hair) serve as a route of absorption (e.g., McDougal, 1991) or elimination (e.g.. Farris et
aJ., 1993).
32
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Reported values for the weight of the skin of mice, rats, and dogs vary somewhat, largely because
of the differences in the tissues that are included with the skin. For example, the weight of the "pelt"
in mice reported by Durbin et al. (1992) includes the weight of the subcutaneous fat, ears, and
presumably hair. Although the skin weight reported by Friedman (1955) for mice also includes some
subcutaneous fat, the value for this parameter on a body weight-normalized basis are much lower than
those reported by Durbin et al. (1992) or Stott et al. (1983). The mean value for relative skin weight
in mice, obtained from data reported in five studies, is 16.5% of the body weight.
Values for the weight of the skin in rats range from 15.8% to 23.6% of the body weight, with a
mean across five studies of 19.0%. The PBPK model developed by Farris et al. (1993) to describe
the pharmacokinetic behavior of methyl mercury in rats is unique in its explicit representation of a
hair compartment. This compartment was necessary in this model to account for the loss of methyl
mercury via shed hair and oral uptake of the compound via ingestion of hair during grooming. In
their model, hair constitutes 1.5% and 2.0% of the body weight of male F344/N rats weighing 307
and 548 g, respectively.
Some discrepancy exists among values identified for the weight of the skin in dogs. Warner and
McFarland (1970) reported that the integument constitutes around 16% of the body weight in Beagles.
This value, which includes the weight of the nose, foot pads and nails, is similar to the values
reported for other species. However, Quillen and Reid (1988) found that the mean weight of the skin
in eight mongrel dogs with a mean body weight of 21.1 kg was 1.911 kg, or about 9.1 % of the body
weight. Although it is not surprising that this value is less than that reported by Warner and
McFarland (1970), since the latter does not include the weight of structures such as foot pads and
nails, it is not possible to identify a representative value for this parameter in dogs without additional
data.
The skin constitutes about 3.1% and 3.7% of the hody weight in reference woman and man.
respectively flCRP, 1975). The dermis makes up 95-96% of the total skin weight in humans and the
epidermis makes up the remainder.
In addition to total skin weight, values for the thickness of the skin or skin regions may be
required for PBPK models with a dermal input function. Data on the thickness of the stratum
33
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coraeum and other skin layers in the rat and human are provided by Bronaugh et al. (1983) and
Scheuplein and Blank (1971) respectively, and are discussed in the U.S. EPA (1992) document on
dermal exposure assessment. McDougal (1991) and Singh and Roberts (1993) have demonstrated
how these data can be used in a dermal PBPK model.
2.3.13 Spleen and Thyroid
Although they represent a small proportion of the total body weight, the spleen and thyroid can be
important target organs of toxicity. Mean values for the weight of these tissues in mice, rats. dogs.
and humans can be found in Tables 2-4 through 2-7.
2.4 USE OF ORGAN WEIGHT VALUES IN PBPK MODELS
Use of the organ weight data provided in Tables 2-4 through 2-7 in a PBPK model requires that
die weight estimates be converted to units of volume. In addition, the values need to be scaled to the
body weight of the animals under study, tissue mass balance should be accounted for in the model.
and the anatomical and physiological heterogeneity of die organs may need to be represented. These
issues are discussed in more detail below.
2.4.1 Mass-to-Volume Conversion
Widi few exceptions, the values provided in Section 2.3 represent die mass of-die organs.
However, PBPK model compartments are defined by their volume not mass. Since die density of
most visceral organs approximates 1.00 (most have densities that range from 1.02-1.06), a mass-to-
volume conversion is usually ignored. However, die density of some tissues, such as bone, is
significantly different enough from 1.00 to warrant consideration of a mass-to-volume conversion.
For example, die density of marrow-free bone is 1.92 g/cm3. Although the weight of this tissue in a
mature small mammal skeleton is 5.00 g/100 g BW. the volume is 2.60 cm3/100 g BW (O'FIaherty.
199la). The only odier tissues diat may require a mass-to-volume conversion to more accurately
reflect their volume in die model are adipose tissue and the stratum corneum of die skin, with
densities of 0.916 and 1.50 cm7/100 g BW, respectively.
Investigators that wish to make more precise mass-to-volume conversions can use the specific
gravity values reported in ICRP (1975) for human tissue (Table 2-19). Presumably, the density ut'
34
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mouse, rat, and dog organs is sufficiently similar to allow for the use of these values for other
species.
Table 2-19. Organ Density in Humans (ICRP, 1975)
Tissue Specific Gravity
Adipose Tissue 0.916
Adrenals 1.016-1.033
Bone
Cortical 1.99
Trabecular 1.92
Red Marrow 1.028
Yellow Marrow 0.783
Brain 1.030-1.041
Gastrointestinal Tract
Stomach 1.048-1.052
Small Intestine 1.041 - 1.047
Large Intestine 1.042
Heart 1.030
Kidneys 1.050
Liver
Lungs 1.045-1.056
Muscle 1.041
Pancreas 1.040-1.050
Skin
Stratum Corneum 1.50
Epidermis 1.10-1.19
Dermis 1.116
Hypodermis 0.971
Spleen 1.054
Thyroid 1.036- 1.066
2.4.2 Selecting Organ Weight Values for Animals Within a Species
Unlike previous compilations of organ weight data (e.g., Arms and Travis, 1988; Davies and
Morris, 1993), the mean organ weight values presented in this document were not adjusted to provide:
representative values for mice, rats, dogs, and humans of a "standard" body weight. Since the mean
organ weight values provided in Table 2-4 through 2-7 were derived from adult animals whose body
weight fell within the range of values that would be considered normal, then use of relative organ
weight values expressed as % body weight should be valid for estimating the organ weights tor
animals with the same body weight range within a species, if organ weight increases at the same rate
as body weight. In cases were organ weight may increase at a disproportionately greater rate than
35
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body weight (e.g., adipose tissue), intraspecies allometric equations are provided when the data were
available. However, it has been somewhat common practice in PBPK modeling to use interspecies
allometric equations to estimate organ weights for animals of different weight within a species. Since
the relative organ weight values provided in Table 2-4 through 2-7 are species-specific, one might
expect that they would predict organ weight for animals within a species with greater accuracy than
interspecies allometric equations developed using data from multiple species. This assumption was
tested using the rat organ weight data obtained in the studies conducted by Delp et al. (1991) and
Farris et al. (1993). The results of this exercise are shown in Table 2-20; the interspecies allometric
equations that were used to estimate organ weight are provided in Appendix C.
Table 2-20. Ability of Intraspecies and Interspecies
Scaling Relationships to Predict Organ Weight Values
Male
Sprague-Dawley Rats
in
Organ Weight (g)
Brain
Delp et al.
Farris et al
Farris et al
GI Tract
Delp et al.
Farris et al
Farris et al
Skin
Delp et al.
Farris et al
Farris et al
Liver
Delp et al.
Farris et al
Farris et al
(1991)c
. (1993)d
. (1993)°
(1991)
. (1993)
. (1993)
(1991)
. (1993)
. (1993)
(1991)
. (1993)
. (1993)
Measured"
2.20
1.83
2.02
9.50
9.49
13.53
69.80
48.54
87.29
12.42
13.42
17.17
Predicted
Table 2-5
2.12
1.78
2.92
10.87
9.12
14.93
69.65
58.46
95.67
12.48
10.47
17.14
using:
Interspecies
Equations'"
4.47-7.17
3.92 - 6.28
5.63-9.13
28.77
24.40
38.77
53.93
45.72
72.73
13.93 - 15.76
11.96- 13.58
18.36-20.64
Mean
b Provided in Appendix C
c 366 g BW
d 307.21 gBW
• 502.75 g BW
36
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Although the interspecies allometric equations were derived using data from animals that range in
size from the shrew to the elephant, they were generally able to estimate the mean organ weight
values obtained in the Delp et al. (1991) study within an order of two or so. However, in every case.
the relationships shown in Table 2-5 were able to more closely estimate the organ weights values
obtained in the Delp et al. (1991) study. This result is not surprising since these relationships are
specific to the rat and the Delp et al. (1991) data were among those used to used to derive the
relationships provided in Table 2-5.
Similar results were obtained when this assumption was tested with the organ weight data obtained
by Farris et al (1993), with two notable exceptions. The interspecies allometric equations were able
to more closely predict the mean weight of the skin and liver in rats weighing around 300 g in the
Farris et al (1993) study. The results of this exercise suggest that it is valid to use the relationships
provided in Table 2-5 to provide organ weight estimates for rats of different weights. However, in
some cases, interspecies allometric relationships can provide a reasonable estimate of organ weight, at
least in male Sprague-Dawley rats.
2.4.3 Tissue Mass Balance
A mass balance must be maintained for the volume of the compartments in the model. In other
words, the sum of the volumes of the individual compartments must equal the total volume of the
animal. Table 2-21 demonstrates that a tissue mass balance can be maintained using the values
provided in Tables 2-4 through 2-7.
37
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Tissue
Adipose
Bone
Brain
GI Tract
Heart
Kidneys
Liver
Lungs
Muscle
Skin
GI tract contents
Blood
Rest of body
TOTAL
Mice
~7
10.7
1.7
4.2
0.5
1.7
5.5
0.7
38.4
16.5
5.7
4.9
2.5
100.0
Table 2-21. Tissue Mass
Rats
-7
7.3
0.6
2.7
0.3
0.7
3.4
0.5
40.4
19.0
~5
7.4
5.7
100.0
Balance
Dogs
-15
8.1
0.8
3.7
0.8
0.5
3.3
0.8
45.7
9.1
4.3
8.2
0
100.5
Humans
21.4
14.3
2.0
1.7
0.5
0.4
2.6
0.8
40.0
3.7
1.4
7.9
3.3
100.0
Since these values are means derived from multiple studies, it is not surprising that the totals for each
species do not exactly equal 100%, even when liberties are taken with the weight of tissues in the rest
of the body. Nevertheless, this exercise does indicate that the values provided in Tables 2-4 through
2-7 provide a reasonable starting point for the selection of representative organ weight (volume)
values for use in PBPK models.
Investigators who include terms to account for age-related changes in organ growth in their
models are reminded to keep tissue mass balance considerations in mind, especially for compartments
(e.g., adipose tissue) that increase in size at a rate greater than that of other tissues.
2.4.4 Anatomical and Physiological Heterogeneity
Use of the data in Tables 2-4 through 2-7 to derive a value for the volume of a particular organ
implies that this organ is anatomically and physiologically homogeneous. This assumption is
sufficient for most PBPK applications; however, it may be important to represent the heterogeneity of
organ in the model. An attempt has been made in Section 2.3 to identify values for the weight or
anatomically or physiologically distinct regions of organs and tissues. For example, data have been
provided for the weight of different regions of the adipose (brown vs. white; subcutaneous vs.
internal), bone (cortical vs. trabecular; marrow vs. marrow-free), brain (cerebrum, cerebellum, hram
38
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stem), and gastrointestinal tract (forestomach, glandular stomach, duodenum, jejunum, ileum, cecuiu.
colon). This level of detail is not necessary for every PBPK model, but may be required depending
-on the process being modeled. For example, Frederick et al. (1992) included a detailed description of
the gastrointestinal tract in their PBPK model of orally administered ethyl acrylate to account for
uptake and metabolism of the compound in different regions of the gut. Data on the weight of the
gastrointestinal tract necessary to develop this model are found in Table 2-18. Because of the rapid
rate at which ethyl acrylate is metabolized in the liver, these investigators also chose to represent the
metabolic heterogeneity of the liver in this model.
The respiratory tract is represented in many PBPK models as a simple lung compartment.
However, models have recently been developed to account for regional distribution, metabolism.
uptake of compounds in the respiratory tract. The data provided in this paper are insufficient to
provide values required for the detailed representation of the respiratory tract found in these models.
However, investigators requiring these data may find the review prepared by Medinsky et al. (1993)
of recent efforts in this field to be useful.
39
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3.0 CARDIAC OUTPUT AND REGIONAL BLOOD FLOW
In classical pharmacokinetic models, movement of a compound across a membrane is represented
either using mass terms and kinetic rate constants or concentration terms and transfer constants.
However, in flow-limited PBPK models, the transfer constant is equivalent to the blood flow to the
tissue (O'Flaherty, 1987). Consequently, values are needed in flow-limited PBPK models for cardiac
output and the regional distribution of cardiac output to the organs. Values for these parameters are
provided in this section for mice, rats, dogs, and humans.
3.1 CRITERIA FOR DATA SELECTION AND REPRESENTATION OF THE DATA
Because cardiac output regional blood flow distribution is dramatically influenced by a number of
factors, such as the degree of consciousness or level of physical exertion, inclusion criteria were
established to try to ensure that the blood flow data provided in this paper are representative of flow
patterns in "normal" subjects. The exclusion of studies, such as those of anesthetized animals.
represents a departure from the approach used in previous compilations of blood flow data (e.g..
ICRP, 1975; Arms and Travis, 1988; Williams and Leggett, 1989; Davies and Morris. 1993).
Regional blood flow data in experimental animals were obtained only from studies that used the
radiolabelled microsphere technique. This technique was originally reported by Rudolph and
Heymann (1967) and has become the method of choice for measuring the distribution of blood flow
among and within organs in animals (Hoffman et al., 1977). This is not to imply, however, that
there are not limitations to this technique. On the contrary, great care must be used to ensure
accurate results. For example, aggregation of the microspheres, inadequate mixing of the
microspheres with the blood, "streaming" of microspheres past small arteries, tissue samples
containing less than 400 microspheres, and flow impairment following infusion of too many spheres
can lead to inaccuracies in flow determination (Austin et al., 1989; Hoffman et al.. 1977; Zwissler et
al., 1991). Technical strategies have been developed to overcome each of these difficulties, and
methods to verity accuracy are routinely used by investigators (Austin et al., 1989; Hot' et al.. 1980:
Laughlin et al.. 1982; Zwissler et al.. 1991). The overwhelming advantage of microspheres is that
they can be used to simultaneously measure cardiac output and blood flow distribution among and
40
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within organs throughout the entire body. In addition, use of the microsphere technique does not
induce surgical trauma to organs and vascular beds of interest, as frequently occurs with flow probes.
Previous estimates of regional blood flow distribution in the mouse have largely been based on the
studies conducted by Wetterlin et al. (1977), Stott et al. (1983), and Quintana et al. (1979).
However, these studies were not included in this analysis because the mice were anesthetized, and
because of technical problems experienced by these investigators. As pointed out by Barbee et al.
(1992) and Wang et al. (1993), these problems included inadequate mixing of microspheres. the
development of catheter-induced outflow obstructions, and potential cardiac dysfunction from direct
injection of microspheres through the ventricular wall.
To our knowledge, there are the only two studies, by Barbee et al. (1992) and Wang et al. (1993).
reporting regional blood flow distribution in conscious mice. Blood flow in the study of Wang et al.
(1993) was measured while the mice were restrained. Physical restraint also has the potential to
greatly alter blood flow distribution. However, flow data from this study were included in Table 3-2
because of the close agreement between flows reported in this study and those reported by Barbee et
al. (1992).
Regional blood flow values for the rat in many PBPK models are based on the results of Malik et
al. (1976), Sasaki and Wagner (1971), and Tsuchiya et al. (1978), as summarized by Arms and
Travis (1988). These studies were included in this analysis, along with the studies of Carmichael et
al. (1988), Delp et al. (1991), and Nishiyama et. al. (1976). Eight additional studies were used to
provide a more comprehensive blood flow database, in units of ml/min/100 g tissue, for rats.
Studies of canine blood flow have tended to focus on a particular organ or organ system.
Therefore, most studies report flow to only a few tissues. A notable exception is the study published
by Quillen and Reid (1988). In addition to reporting regional blood flow distribution, these authors
report cardiac output and blood flow as a percent of cardiac output for conscious dogs at rest.
Williams and Leggett (1989) have recently published a comprehensive review of regional blood
flow values in humans. These authors have compiled human data from studies using various
techniques to measure tissue perrusion. Where blood flow values were not available for humans in
41
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the literature, representative flow values from animals studies are given (Williams and Leggett. 1989).
A few of the human studies referenced by Williams and Leggett (1989) used techniques to measure
blood flow that are now recognized to yield erroneous results, such as Xenon clearance. However,
the reference values suggested by Williams and Leggett (1989) for regional blood flow in humans are
consistent with those recommended by other investigators (Rowell, 1993). Therefore, human tissue
perfusion rates listed in Table 3-5 are based primarily on those previously published by Williams and
Leggett (1989).
Representation of blood flow in units normalized for tissue weight, as shown in Tables 3-1 to 3-5.
can result in significant errors if default reference weights are used instead of tissue-specific weight
values reported in the same paper as the flow values. As a result, weight-normalized flow values
were used only when the data were reported as such in the original paper, or when tissue weights
were reported in the paper, or could be deduced from other data in the same paper. Similarly, data
in units of % cardiac output (% CO) were used only when the data were presented that way, or when
data on CO was reported in die same paper.
3.2 CARDIAC OUTPUT
Mean cardiac output values for unanesthetized mice, rats, dogs, and humans are shown in Table
3-1.
Table 3-1. Cardiac Output (ml/min)
Species
Mouse
Rat
Dog
Human
Mean ±
13.98 ±
110.4 ±
2,936'
5,200*
Mice,
Cardiac
SD
2.85
15.60
in Unanesthetized
Rats, Dogs and Humans
Output
Range
12-16
84-134
1.300-3.000"
4.600-4.600d
Studies
2
5
la
n
Animals
16
92
8'"
1 Quillen and Reid (1988)
b Detweiler et al. (1970)
c Astrand (1983)
d Arms and Travis (1988)
42
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Only two studies (Barbee et al, 1992; Wang et al, 1993) were identified in the literature that
reported cardiac output measurements in unanesthetized mice. Values ranged from about 12 ml/min
in the Wang et al. (1993) study to 16 ml/min in the Barbee et al. (1992) study. Each of these studies
employed the microsphere method to measure cardiac output in male C3H mice.
The mean value for cardiac output in unanesthetized mice listed in Table 3-1 is slightly lower than
the reference value selected by Arms and Travis (17 ml/min), but quite a bit higher than the value
selected by Davies and Morris (1993) as a default value for this parameter. The reference value
selected by Arms and Travis (1988) was derived as follows. First, the heart rate in unanesthetized
mice reported by Blizard and Welty (1971) was multiplied by the average stroke volume reported by
Wetterlin and Pettersson (1979) in anesthetized mice to derive a cardiac output estimate. Then,
assuming cardiac output is related to the 0.75 power of body weight, they developed the following
allometric equation to estimate cardiac output in a standard 25 g mouse:
Cardiac output (L/min) = 0.275 (BW)°",
where BW equals body weight in kilograms. Although this approach yields a value similar to those
derived experimentally, it seems preferable to use a data-based approach free of assumptions about
cross-species scaling patterns to derive estimates for this parameter.
The mean cardiac output value for unanesthetized rats, 110.4 ml/min, was derived from the results
reported in five studies: Coleman (1974), Delp et al. (1991), Hachamovitch et al. (1989), Jansky and
Hart (1968) and Tsuchiya et al. (1977). Although the results reported by Carmichael et al. (1988)
were used to derive regional blood flow estimates, the absolute cardiac output value reported in this
study was about half of that reported by other investigators. Therefore, these data were not used to,
derive the mean absolute cardiac output value for rats. In addition, data on the cardiac output of
spontaneously hypertensive rats in the Tsuchiya et al. (1977) study were not used in this analysis.
The default value for cardiac output in rats was developed by Arms and Travis (1988) in much the
same way as the mouse value was derived, except only data from unanesthetized rats was used and a
geometric mean of the ratios of cardiac output/body weight0 75 values from these studies was used to
derive the value for the intercept. The resulting equation:
43
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Cardiac Output (L/min) = 0.235 BW (kg)073
yields a value of 83 ml/min for a 250 g rat and 118 ml/min for a 400 g rat. This range encompasses
the mean cardiac output value for rats (weighted mean BW = 396 g) reported in Table 3-1.
Detweiler et al. (1970) report that cardiac output values in unanesthetized Beagles weighing 8-12
kg range from 1,300 to 3000 ml/min; dogs under anesthesia have cardiac output values ranging from
900 to 2,700 ml/min. Since mean values were not reported by Detweiler et al. (1970), these data
were not used to develop Table 3-1. However, these values are consistent with those identified in the
literature for anesthetized and unanesthetized dogs. For example, using the microsphere technique.
Quillen and Reid (1988) determined the mean cardiac output of unanesthetized male and female
mongrel dogs (mean weight 21 kg) to be 2,936 ml/min. Goodhead et al. (1969) and In-Nami et al.
(1974) report cardiac output values of 2,421 and 2,140 ml/min, respectively, in anesthetized dogs.
Cardiac output has been well characterized in humans, consequently, it is impractical to provide a
comprehensive listing of all of the values that have been reported in the literature. As summarized by
Arms and Travis (1988), mean cardiac output values identified in the literature for unanesthetized
humans range from about 4.6 to 6.5 L/min. The work conducted by Astrand (1983) is highly
respected, and, as a result, cardiac output parameter values in human PBPK models (e.g.. Dankovic
and Bailer (1994) have been derived from this work. Astrand (1983) reports a cardiac output value nt
5.2 L/min in resting individuals. During light work (33.67 W of exercise), cardiac output increases
to 8.36 L/min. Slightly more strenuous exercise (50 W) requires a cardiac output of 9.9 L/min.
Very strenuous exercise is associated with cardiac output values of up to 30 L/min in humans.
Cardiac output remains constant at about 6.5 L/min in males aged 20-35 years, then begins a
gradual decline. Based on the data obtained by Brandfondbrenner et al. (1955), the following
equation can be derived to estimate cardiac output as a function of age in males:
Cardiac Output (L/min) = -6.846 log age (yrs) + 16.775; r = -0.98.
In Section 3.3, the distribution of the cardiac output to various organs and tissues is discussed.
44
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3.3 REGIONAL BLOOD FLOW
Table 3-2 provides mean blood flow values for major organ systems in the mouse, rat. dog and
human. The statistical variability and uncertainty associated with these estimates is described more
fully for each species in Tables 3-3 to 3-6.
45
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Tissue
Adipose
Adrenal
Bone
Brain
Heart
Kidney
Liver (Total)
Hepatic Artery
Portal Vein
Lung
Muscle
Skin
Thyroid
Table
Mouse
3.3
6.6
9.1
16.1
2.0
14.1
0.5
15.9
5.8
3-2. Regional Blood
Mean % Cardiac
Rat
7.0
0.3
12.2
2.0
5.1
14.1
18.3
2.1
15.3
2.1
27.8
5.8
Flow Distribution
Output
Dog
0.2
2.0
4.6
17.3
29.7
4.6
25.1
8.8
21.7
6.0
Humana
5.2
4.2
11.4
4.0
17.5
22.7
18.1
19.1
5.8
1.6
Provisional measure of central tendency from Williams and Leggett (1989).
Table 3-3. Regional Blood Flow Distribution in Mice
Blood Flow Rate
Tissue
Adipose
Adrenal
Bone
Brain
Heart
Kidney
Liver (Total)"
Hepatic Artery*
Portal Vein*
Lung*
Muscle
Skin
ml/min/lOOg
Mean Range
(SD)
85 ± 1 84-85
781 ± 18 768-793
35
24 + 6 20-28
18 ± 12 9-26
Blood Flow Distribution
% Cardiac Output
n'
2
2
1
2
2
Mean (SD)
3.3 ± 0.3
6.6 ± 0.9
9.1
16.2
2.0
14.1
0.5
15.9 ± 5.2
5.8 ± 3.5
Range n'
3.1-3.5 2
5.9-7.2 2
7.0-11.1 2
2
1
13.9 - 14.2 2
1
12.2 - 19.6 2
3.3 - 8.3 2
Number of studies
Hepatic artery and portal vein
Principally through the hepatic artery
Sum of flows through the splanchnic organs
Bronchial flow
46
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Table 3-4. Regional Blood Flow Distribution in Rats
Blood Flow Rate
ml/min/lOOg
Tissue
Adipose
Adrenal
Bone
Brain
Heart
Kidney
Liver (Total)1"
Hepatic Artery*
Portal Vein"1
Lung*
Muscle
Skin
Mean (SEM)
33 ± 5
429 ± 90
24 ± 3
110 ± 13
530 ± 46
632 ± 44
23 ± 44
108 ± 17
127 + 46
29 ±4
13 ± 4
Range
18-48
246-772
20-28
45-134
405-717
422-826
9-48
67-162
38-147
15-47
6-22
n"
6
6
3
7
8
11
10
5
6
8
5
Blood Flow Distribution
% Cardiac Output
Mean (SEM)
7.0
0.3 ± 0.1
12.2
2.0 ± 0.3
4.9 ± 0.1
14.1 ± 1.9
18.3 ± 1.2
2.1 ± 1.0
15.3 ± 1.2
2.1 ± 0.4
27.8
5.8
Range
0.2-0.3
1.5-2.6
4.5-5.1
9.5-19.0
13.1-22.1
0.8-5.8
11.1-17.8
1.1-3.0
na
1
2
1
4
5
5
6
6
6
5
1
1
' Number of studies
b Hepatic artery and portal vein
Principally through the hepatic artery
Sum of flows through the splanchnic organs
Bronchial flow
Tissue
Adipose
Adrenal
Bone
Brain
Heart
Kidney
Liver (Total)b
Hepatic Artery5
Portal Veind
Lung"
Muscle
Skin
Table 3-5. Regional Blood
Blood Flow Rate
ml/min/lOOg
Mean (SEM) Range
14 +. 1 13-14
311 ± 143 171-543
13 ± 1 12-13
65 ± 4 59-76
79 ± 6 57-105
406 ± 37 307-509
21+3 12-30
52 + 4 42-58
79 + 43 36-122
11+2 6-18
9 ± 1 8-13
Flow Distribution in Dogs
na
2
3
2
5
7
5
5
4
2
6
5
Blood Flow Distribution
% Cardiac Output
Mean (SEM) Range IT'
0.2 1
2.0 1
4.6 . 1
17.3 1
29.7 1
4.6 1
25.1 1
8.8 1
21.7 1
6.0 1
Number of studies
Hepatic artery and portal vein
Principally through the hepatic artery
Sum of flows through the splanchnic organs
Bronchial flow
47
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Table 3-6. Regional Blood
in Humans (from
Tissue
Adipose
Adrenal0
Bone
Brain
Heart
Kidney
Liver (Total)
Hepatic Artery
Portal Vein'
Lung*
Muscle
Skin
Thyroid
Reference
Male
5.0
0.3
5.0
12.0
4.0
19.0
25.0
19.0
2.5
17.0
5.0
1.5
Flow Distribution (% Cardiac Output)
Williams and Leggett, 1989)
Value"
Female
8.5
0.3
5.0
12.0
5.0
17.0
27.0
21.0
2.5
12.0
5.0
1.5
PCMTb
5.2
4.2
11.4
4.0
17.5
22.7
18.1
19.1
5.8
1.6
Range'
3.7-11.8
2.5-4.7
8.6-20.4
3.0-8.0
12.2-22.9
11.0-34.2
12.4-28.0
5.7-42.2
3.3-8.6
1.9-2.2
n"
11
5
39
19
85
56
26
54
10
2
Value determined by the authors to be most representative for this parameter. May be based on
animal or human data.
Provisional measure of central tendency, the median of five measures of central tendency.
For human studies only.
Number of human studies.
Based on animal studies.
Sum of blood flows to stomach, esophagus, small intestine, large intestine, spleen and pancreas.
Bronchial flow.
Some of the values presented in Tables 3-2 to 3-6. notably the blood flow distribution to the liver
in rodents, differ from values that have been widely used in PBPK models. These differences are
due, in part, to the prior use of blood flow values derived from studies using anesthetized animals in
the models. The mean values for each parameter, and ranges for each parameter, are discussed more
fully below, with an emphasis on how these values compare to those used previously in PBPK
models. The factors that have the greatest effect on regional blood flow, such as the use of
anesthesia, are explored more fully in Section 3.3.
48
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3.3.1 Adipose Tissue
Despite its importance as a pharmacokinetic compartment, there are relatively few studies
available to base estimates of blood flow to the adipose tissue on. The limited number of studies that
are available suggest that the values selected by Arms and Travis (1988) for rats and humans are
reasonable. No data were identified on regional blood flow to adipose tissue in mice.
Adipose is a physiologically heterogeneous tissue consisting of "white fat" in the hypodermis and
around the abdominal organs, and "brown fat" existing in the interscapular hypodermis and in the
perirenal and axillary regions. This tissue is physiologically heterogeneous both in terms of function
(white fat is assumed to take up excess energy whereas brown fat plays a role in consuming excess
energy) and blood flow.
Brown fat receives considerably more blood flow in rats than white fat when normalized for tissue
weight. For example, Kajita et al. (1994) found that white fat in rats received a blood flow of 5
ml/min/100 g, whereas brown fat received about 36 ml/min/100 g. Similar results were observed by
Jansky and Hart (1968) However, because white fat represents a greater proportion of body weight
than brown fat, it receives a greater percentage of the cardiac output. In contrast, no significant
difference was reported by Bulow and Madsen (1978) between blood flow to abdominal and perirenal
fat in humans (1.4 ml/min/100 g for abdominal fat vs. 2.3 ml/min/100 g for perirenal fat).
Expressed in units of ml/min/100 g, humans and rats receive about the same blood flow to the
white adipose tissue. Values range from about 1.4 to 8.3 ml/min/100 g of tissue. These values are
consistent with those reported previously by Mapleson (1963) and Cowles et al. (1971) for humans.
Based on the value reported in Table 3-6, and the default adipose weight of 12,500 g in males and
17,500 g in females, about 3 to 11 % of the cardiac output is distributed to the adipose tissue in
humans. Based on the blood flow values reported by Delp et al. (1991) for adipose tissue in the
epididymal, inguinal and abdominal regions and the total weight of dissectible fat. about 7% of the
cardiac output is distributed to adipose tissues in the rat.
As discussed in Section 2.0. Fiserova-Bergerova (1992) included two adipose tissue compartment-
in a PBPK model of anesthetic agents in humans. Blood flow to the inner adipose tissue compartment
was set at 0.66 L/min. a value equivalent to about 11 % of the cardiac output. A value of 0.19 L nun
49
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was used for blood flow to the subcutaneous adipose tissue. This value was not experimentally
determined, but was derived from the difference between the cardiac output and the sum of the
perfusion rates to the other tissues.
3.3.2 Adrenals
Normalized for tissue mass, the adrenal cortex is among the most richly perfused tissues in the
body. For example, Delp et al. (1991) found that the mean blood flow to the adrenal cortex of
unanesthetized rats was about 863 ml/min/100 g tissue (blood flow to the medulla was 43 ml/min/100
g tissue). To provide a blood flow estimate that is representative of the entire tissue, a weight-
averaged estimate of 429 mJ/min/100 g tissue was derived for rats and reported in Table 3-4.
However, this value does not reflect the marked hemodynamic heterogeneity of this organ.
Although the adrenal tissues are well perfused, they account for only a small percentage of the
total cardiac output (< 1% in rats) because of the small size of this organ. Therefore, unless the
adrenal is determined to be a target tissue, omission of this tissue in a well perfused compartment will
not introduce significant error into estimates of regional blood flow distribution.
No data were found in the literature regarding blood flow distribution to the adrenals in
unanesthetized mice or humans. The reference value of 200 ml/min/100 g provided by Williams and
Leggett (1988) for this parameter in humans was derived from animal data.
3.3.3 Bone
Accurate estimates of blood flow to the bone are essential for PBPK models of bone-seekiny
elements. As mentioned above, bone perfusion has been estimated to be approximately 3% of cardiac
output in anesthetized rats (O'Flaherty, 199la,b) and approximately 12% in conscious rats (Delp et
al., 1991). To our knowledge, there are no studies reporting skeletal blood flow in conscious mice.
or bone perfusion rate in conscious dogs as a portion of cardiac output.
PBPK models of compounds that are toxic to the hematopoietic system require a separate
compartment to describe the pharmacokinetic behavior of the compound or its metabolites in the hnne
marrow. Various estimates of bone marrow blood flow have been used in PBPK models.
Experimentally derived values for this parameter correspond well to blood flow estimates used in
50
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recent PBPK models that contain a bone or bone marrow compartment. For example, in their recent
PBPK model of chloropentafluorobenzene, Clewell and Jarnot (1994) assumed that 11% of the cardiac
output was distributed to the bone marrow in mice, rats, monkeys and humans. This value
corresponds well to the values reported by Kahn et al. (1994).
As with muscle, blood flow to bone demonstrates a marked heterogeneity (e.g., Delp et al..
1991). This heterogeneity should be kept in mind when selecting a representative value for this
parameter.
3.3.4 Brain
A marked species difference exists in regional blood flow to the brain. In mice, rats, and dogs.
about 2-3% of the cardiac output is distributed to the brain. In contrast, the human brain receives
about 11-12% of the cardiac output.
Interest in developing pharmacological agents to improve cerebral circulation after occlusion or
stenosis of cerebral vessels has resulted in the recent publication of a number of studies in which
blood flow to the human brain has been measured. The results of these studies confirm earlier
estimates of regional blood flow to the brain.
Data on blood flow to different regions of the brain may be necessary for complex PBPK models
that incorporate this level of detail. Investigators requiring such data are referred to Delp et al.
(1991) for such values in the rat.
3.3.5 Gastrointestinal Tract
All of the blood reaching the liver via the portal vein is derived from the splanchnic circulation.
including blood flow from the stomach, small intestine, large intestine, pancreas and spleen. In the
unanesthetized rat, the gastrointestinal tract receives about 14% of the cardiac output (Delp et al..
1991). Values for the blood flow to different regions of the gut in the rat have been reported by Delp
et al. (1991).
51
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3.3.6 Heart
Blood flow rates to the myocardium are remarkably constant across species: Mice, rats. dogs.
and humans each receive about 4-7% of the cardiac output to the heart.
Delp et al. (1991) has shown that interregional differences exist in blood flow to the heart in rats.
with the ventricles receiving about twice the flow rate as the atria. Similar heterogeneity of flow in
the myocardium has also been observed in miniature swine (Laughlin et al., 1988).
3.3.7 Kidney
Renal blood flow rates are fairly constant across species, both when expressed per unit mass (406-
632 ml/min/100 g) or as the relative portion of cardiac output (13.5-17.5%). This apparent
consistency exists across species in spite of the relatively wide range of values for kidney blood flow
within each species.
3.3.8 Liver
Studies on unanesthetized animals suggest that blood flow to the liver constitutes approximately
16% of the cardiac output in mice, 18% of the cardiac output in rats, 30% of the cardiac output in
dogs, and 23% of the cardiac output in humans. The mean value for humans derived from these
studies is comparable to the reference value suggested by Arms and Travis (1988); however, the
mean value for blood flow to the liver of mice and rats is considerably lower. In fact, the reference
value suggested by Arms and Travis (1988) for blood flow to the liver in rodents (25%) does not
even fall within the range of mean values identified for this parameter in mice and rats.
As discussed briefly above, the difference between the mean values for liver blood flow in rodents
presented in Tables 3-2 to 3-6 and the reference values selected by Arms and Travis (1988) tor this
parameter is due to their reliance on studies of anesthetized animals, but also, in part, to their
imprecision in selecting a representative value from the existing data. For example, the reference
value selected by Arms and Travis (1988) for blood flow to liver in rats is based primarily on the
results of the studies conducted by Tsuchiya et al. (1978) and Malik et al. (1976). These
investigators reported values for total liver blood flow of about 17% and 20%, respectively.
Nevertheless, Arms and Travis (1988) selected a reference default value of 25% for this parameter, a
value that has been used extensively in PBPK models. Since the metabolism of highly cleared
52
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compounds in the liver is blood-flow limited, values for hepatic blood flow should be accurately
characterized.
As discussed more fully in Section 3.4, blood flow rate through some organs such as the liver is
highly variable over short time intervals and can be markedly influenced by factors such as
anesthesia, posture, food intake, and exercise. Longer-term changes in hepatic blood flow rate can be
brought about by the presence of disease (e.g., cirrhosis or tumors) and as a function of the aging
process. These changes may need to be accounted for in a PBPK model.
3.3.9 Lung
In PBPK models with a lung compartment, it is assumed that all of the cardiac output goes
through the lung. However, the values presented in Tables 3-2 through 3-6 for the lung compartment
represent blood flow to the bronchial region.
3.3.10 Muscle
Muscle blood flows (ml/min/100 g) to the mouse and rat are approximately two-fold greater than
that in the dog and 5- to 6-fold greater than that in man. However, the relative portion of cardiac-
output going to skeletal muscle is surprisingly similar across species.
Mean resting muscle blood flows in Tables 3-2 to 3-6 do not reflect the heterogeneity of blood
flow to this tissue. For example, resting blood flow in the rat can range from 8 ml/min/100 g in the
abdominal muscles to 121 ml/min/100 g in the vasrus intermedius muscle of the thigh, more than an
order of magnitude difference (Delp et al., 1991). This heterogeneity of flow distribution primarily
reflects differences in the activities of the various muscles when the animal is at rest. The muscles
receiving the highest flows, such as vastus intermedius, soleus and triceps brachii muscles, are
antigravity muscles which are active in maintaining posture. When the animals are anesthetized
(Laughlin et al., 1982) or no longer weight-bearing (McDonald et al., 1992), blood flow to these
antigravity muscles decreases to less than 10 ml/min/100 g. Conversely, when the animals begin to
move about in their enclosure, flows to various muscles increase significantly. This heterogeneity of
flow to muscle makes it important for investigators measuring muscle perfusion to thoroughly sample
this tissue and for modelers to use values that are representative of the entire mass of skeletal muscle.
53
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As one might expect, physical activity is the single greatest determinant of muscle blood flow.
From a modelling perspective, this is important because any compound that influences the activity of
an organism will alter the blood flow to muscle. In addition, if occupational exposure to a certain
compound were being modelled and the occupation involved physical exertion, then muscle and other
tissue perfusion parameters would be different from those at rest. Such changes were incorporated
into the PBPK model of methylene chloride developed by Dankovic and Bailer (1994) that simulated
the pharmacokinetic behavior of this compound in humans at work and at rest.
3.3.11 Skin
PBPK models of dermal absorption require a separate compartment for the skin. However.
caution should be exercised in selecting a default value for blood flow to the skin, because of the
marked variability of dermal blood flow rate at different anatomical sites. For example, Monteiro-
Riviere and colleagues (1990) found that cutaneous blood flow rates in the mouse varied from 1.41
ml/min/100 g when measured in skin on the ear to 36.85 ml/min/100 g when measured in skin on the
ventral abdomen.
Dermal blood flow data were also obtained by Monteiro-Riviere et al. (1990) at four other sites in
eight other species, including the species that are the focus of this paper. As a result, the work
conducted by Monteiro-Riviere and colleagues (1990) may serve as a valuable source of dermal blond
flow data for modelers requiring such data. However, these values were obtained using anesthetized
animals, and therefore, are presented separately in Table 3-7 below.
Table 3-7. Region-Specific Blood Flow Measurements (ml/min/100 g)
in Mice, Rats and Dogs (Monteiro-Riviere et al., 1990)
Site
Buttocks
Ear
Humeroscapular area
Thoracolumbar area
Ventral abdomen
Mouse
3.88 + 0.92
1.41 ± 0.48
10.10 ± 3.51
20.56 ± 4.69
36.85 ± 8.14
Rat
4.20 ± 1.05
9.13 ± 4.97
6.22 ± 1.47
9.56 ± 2.17
11.35 ± 5.53
Dog
2.21 ± 0.67
5.21 ± 1.53
5.52 ± 1.31
1.94 ± 0.27
8.78 ± 1.40
There also appears to be some diurnal variation in blood flow to the skin in humans. Houben et
al. (1994) reported that forearm blood flow, which is principally a measure of blood flow to the skin.
54
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increased in humans from 2.8 ml/min/100 ml in the morning to 4.3 ml/min/100 ml in the afternoon.
Delp et al. (1991) have reported a similar pattern in blood flow to hindlimb skin of the rat.
Upon dermal application, lipophilic compounds can penetrate through the epidermis and dermis.
and migrate into deep tissues underlying the skin before being taken up into the systemic circulation.
Representation of this process in a PBPK model requires that blood flow values be obtained for both
dermal and underlying subcutaneous tissues. The values were recently obtained by Singh and Roberts
(1993) in the anesthetized rat and incorporated into their model. Using a microsphere technique, they
found that blood flow to the skin measured 5.18 ml/min/100 g tissue, a value somewhat less than the
mean value provided in Table 3-4, but within the range of values reported by Monteiro-Riviere et al.
(1990) for anesthetized rats.
3.4 FACTORS THAT INFLUENCE TISSUE PERFUSION
Although there are some factors that can alter organ volume values within an individual (Section
2.3), these changes are, in general, less dramatic than the changes that can occur in regional blood
flow in an individual. Also, regional blood flow values can change dramatically in a relatively short
period of time. As a result, it is important for modelers to be aware of the factors that have the
greatest influence on the values that may be selected for blood flow parameters in the model. In this
section, the potential effect of disease, anesthesia, physical activity, food intake, posture, age. and
gender on regional blood flow is discussed.
3.4.1 Disease
The parameter values provided in this paper are intended to be representative of values tor healthy
subjects. However, most PBPK models have been developed describe the pharmacokinetic behavior
of environmental compounds with known or potential toxicity or carcinogenic activity, or tor
therapeutic agents used in treatment of disease. Some of the disease states that may be either causal
or treated by the compound may involve changes in overall or regional hemodynamics. Therefore, it
may be necessary to represent changes in blood flow rate in the model that parallel blood flow rate
changes occurring due to pathological processes in the exposed individuals.
55
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Certain disease states are known to alter regional blood flow rates. Among the most important
pathological alterations to keep in mind for the development of PBPK models are hepatic diseases that
affect blood flow through the liver. Notable among these is cirrhosis, a disease that can produce a
marked decrease in hepatic blood flow with a resulting decease in the hepatic elimination highly
cleared compounds (Bauer et al., 1994).
Hepatotoxic compounds can produce alterations in liver blood flow as one of their effects on the
liver. For example, carbon tetrachloride, a compound whose pharmacokinetic behavior has been
described in at least five PBPK models, exerts a vasoconstrictor effect on hepatic vessels, thereby
altering blood flow patterns in the liver. Other compounds, such as beryllium and
dimethylnitrosamine, produce hepatocellular necrosis which can subsequently effect liver blood flow
rates (Plaa, 1991).
Much of the recent interest in PBPK modeling stems from the application of this technique to
assess human health risk posed by exposure to compounds that have been demonstrated to have
carcinogenic activity in experimental animal species. Implicit in this approach is the assumption that
the presence of tumors in experimental animals has no effect on physiological parameter values used
in the models. However, Carter et al. (1994) and others have identified hemodynamic changes that
occur in the liver of patients with intrahepatic tumors. Blood flow alterations are also observed in
experimental animals with some types of tumors (Hemingway et al., 1993). Therefore, if PBPK-
based simulations of the pharmacokinetic behavior of rodent carcinogens are carried out for long time
courses, it may be necessary to account for tumor-associated changes in blood flow in tumor bearing
tissues.
3.4.2 Anesthesia
Anesthesia has a profound effect on tissue perfusion, particularly that of cardiac and skeletal
muscle, splanchnic, and hepatic tissues. As a result, default values for these parameters in PBPK
models of compounds that are not expected to exert an anesthetic effect should be based only on
studies which used unanesthetized animals. Conversely, PBPK models of clinical anesdietic agents or
environmental pollutants that exert an anesthetic effect should account for the potential effect or the
anesthetic agent on tissue blood flow.
56
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Administration of anesthetic agents can result in increases or decreases in tissue blood flow. For
example, in mice, anesthesia (Avertin: 2.5% 2,2,2-tribromoethyl and tertiary amyl alcohol) increased
blood flow to the liver via the portal vein by 33% and decreased skeletal muscle perfusion by 42%.
when expressed as % cardiac output (Barbee et al., 1992). In rats, inhalation anesthesia has been
shown to reduce skeletal muscle blood flow by 79% (Laughlin et al.,1982) and hepatic flow by
approximately 50% (Stanek et al., 1988), when flow is expressed in ml/min/unit mass. However, rat
liver perfusion has also been shown to increase with phenobarbital anesthesia (Sasaki and Wagner.
1971).
Perfijsion of other tissues essential for PBPK models may also be influenced by anesthetics. For
example, in the models of lead disposition in the rat and human, O'Flaherty (1991a,b) set bone blood
flow equal to 3% of the cardiac output. This estimate, based on data reported by Tothill and
McCormick (1976) and Schoutens et al. (1979) for blood flow to different regions of the mature rat
skeleton, is significantly different from that reported by Delp et al. (1991), who indicated that 12.2%
of the cardiac output is distributed to the skeleton in the rat. Although each of these studies measured
blood flow using the microsphere technique, Tothill and McCormick (1976) and Schoutens et al.
(1979) used anesthetized animals, whereas Delp et al. (1991) used conscious rats. Whether the
difference in bone perfusion reported in these studies is due to the use of anesthetics is unknown, but
reports of bone blood flow (ml/min/100 g) in other studies using conscious rats (Table 3-3) are
consistent with the notion that skeletal perfusion is higher in the absence of anesthetics.
Unlike many other tissues, anesthesia appears to have little effect on blood flow to the brain. For
example, Barbee et al. (1992) found no difference in relative blood flow to the brain of conscious
mice and mice anesthetized with Avertin. Similarly, phenobarbital had little effect on cerebral blood
flow in rats (Goldman and Sapirstein, 1973). However, narcotizing doses of thiopental have been
shown to increase, decrease, or have no effect on cerebral blood flow in cats (rets, see Goldman and
Sapirstein, 1973).
In addition to anesthetic agents, a number of drugs produce changes in tissue blood flow rates.
including beta-adrenergic blockers such as propranolol (Laughlin and Armstrong, 1987; Shepherd et
al., 1985; Zoller et al., 1993) and calcium channel blockers such as nifedipine (Reiss et al.. 1991).
The influence of pharmacological agents is not limited to cardiac and skeletal muscle, splanchnic.
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hepatic or bone tissue. For example, certain drugs (e.g., benidipine HCI) have also been shown to
increase blood flow to adipose tissue, principally to brown fat (Jansky and Hart, 1968; Kajita et al..
1994).
Other compounds for which PBPK models have been constructed may have direct or indirect
vasoactive effects, resulting in alterations in tissue perfusion. One such compound is
trichloroethylene (TCE). In the study conducted by Cowan et al. (1991), patients exposed to TCE
experienced a mean 32% reduction in hepatic blood flow; some individuals in the study experienced
close to a 70% reduction in hepatic blood flow after exposure to TCE. This report is interesting
because it points out the potential problems associated with the use of default values for flow
parameters in a PBPK model. However, the importance of representing altered hepatic blood flow in
specific PBPK models for TCE obviously depends on whether this effect occurs at environmentally or
occupationally relevant exposure levels of TCE, whether die altered blood flow effects the
pharmacokinetic behavior of the compound, and whether other drugs given with TCE in the Cowan et
al. (1991) study could have contributed to this effect.
The vasoactive influence of every compound is unique, as demonstrated by the fact that alterations
in tissue blood flow induced by similar compounds, such as inhalation anesthetics, are not
homogeneous. It should be noted that pharmacological agents can also affect cardiac output.
Therefore, in a PBPK model, it is important to know how to represent these changes; i.e., either as
an alteration in cardiac output with a constant proportion of the cardiac output going to the various
tissues, or as a selective change in tissue blood flow. The lack of a consistent pattern between tissue
blood flow responses and exposure to pharmacological agents suggests that values for this parameter
should ideally be obtained through experimental determination of blood flow distribution patterns
during exposure to the agent whose pharmacokinetic behavior is being modeled. The importance of
accurately characterizing blood flow distribution is underscored by the sensitivity of a number of
PBPK models for this parameter, such as in models of compounds that exhibit flow-limited hepatic
clearance. The sometimes dramatic effect that anesthetic agents can have on blood flow distribution
also underscores the importance of basing default or reference values for this parameter on blood flou
studies of unanesthetized animals.
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3.4.3 Physical Activity
Physical activity, whether through circadian variations in activity or exercise, results in profound
changes in cardiac output and the distribution of cardiac output. In rats, for example, cardiac output
changes by approximately 30% through the diurnal cycle (Smith et al., 1987). This change in cardiac
output primarily reflects diurnal changes in behavior; cardiac output is highest when the rats are
engaged in foraging, grooming and exploratory activities, and lowest when the animals are inactive
and sleeping (Delp et al., 1991; Smith et al., 1987). The increase in cardiac output resulting from
feeding and locomotory activities is primarily directed to skeletal muscle, splanchnic tissue and fat
pads (Delp et al., 1991). Humans exhibit similar circadian changes in tissue perfusion. For example.
Lemmer and Nold (1991) have shown that hepatic blood flow in humans varies about 25% over the
course of the day. Circadian variation in hepatic blood flow may be responsible for time-dependent
variations observed in the pharmacokinetics of several drugs. Therefore, accurate prediction of blood
or tissue levels of highly cleared compounds with a short elimination half-life may require
incorporation of circadian variability of tissue blood flow estimates into the PBPK model.
Exercise represents one of the greatest stresses that can be placed on the cardiovascular system.
resulting in dramatic, intensity-dependent increases in cardiac output and alterations in blood flow
distribution (Rowell, 1993). Tables 3-2 to 3-5 depict tissue blood flows in mice, rats and dogs at
rest. When animals are conditioned to exercise, the mere anticipation of an upcoming bout of
exercise results in increases in heart rate, blood pressure, and possible elevations in muscle blood
flow (Armstrong et al., 1989; Bolme and Novotny, 1969). At the commencement of low-intensity
walking, skeletal muscle blood flow increases 83% and 173% in rats (Laughlin and Armstrong, 1982)
and miniature pigs (Armstrong et al., 1987), respectively. This increase in flow to the skeletal
muscle is a result of both an increase in cardiac output and a redistribution of flow away from other
tissues, including the kidneys, splanchnic tissue, spleen and fat. In the rat, slow treadmill walking
results in an 52, 85 and 91% decrease in blood flow to the kidneys, spleen and fat, respectively
(Laughlin and Armstrong, 1982). As exercise intensity increases, the cardiac and skeletal muscles
receive greater absolute flows and a greater portion of cardiac output. For example, blood flow to
the red portion of gastrocnemius muscle in the rat increases from 54 ml/min/100 g at rest to 317
ml/min/100 g during high-intensity treadmill running (Laughlin and Armstrong, 1982). Similarly.
flow to the deep gluteal muscle in the miniature swine increases from 22 ml/min/100 g at rest to 202
ml/min/100 g during high-intensity treadmill running (Armstrong et al., 1987). Cardiac muscle blood
59
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flow increases from 107 ml/min/100 g at rest to 648 ml/min/100 g during exercise in miniature pigs
(Armstrong et al., 1987). In addition to the increases in muscle blood flow, there are corresponding
decreases in blood flow to many other tissues. Blood flow to the kidneys, splanchnic tissue, spleen
and fat is between 80-95% lower during intense exercise than at rest (Armstrong et al., 1987;
Laughlin and Armstrong, 1982). In general, exercise at even very low intensities results in increases
in blood flow to cardiac and skeletal muscle, lungs and adrenal glands, remains unchanged to the
brain, and decreases to most other tissues (Armstrong et al., 1987; Laughlin and Armstrong, 1982).
These patterns of blood flow distribution during exercise are also evident in dogs (Musch et al.. 1987)
and humans (Rowell, 1993).
3.4.4 Food Intake
Food ingestion can influence blood flow to tissues involved in digestion and nutrient absorption,
due to elevations in basal metabolic rate. As indicated above, when rats are actively engaged in
foraging and eating, blood flow is elevated to skeletal muscle and visceral tissues (Delp et al., 1991).
However, this phenomenon is not limited to rats, but is true for mice, dogs and humans as well. For
example, Okazaki et al. (1986) found that human portal vein blood flow increased from 644 mJ/min
to 1470 ml/min following food consumption, a 130% increase. Post-prandial increases in portal
blood flow have obvious implications for the hepatic elimination of highly cleared compounds in the
liver and also contribute to the biological variability of this parameter within a species. They may
also need to be taken into account when the pharmacokinetic behavior of compounds administered in
the feed or by gavage is modeled. Animals in the studies from which blood flow values in Tables 3-2
to 3-6 were compiled were presumable post-absorptive, although in most studies there was no
apparent attempt to control this variable.
3.4.5 Posture
Posture can also have a significant effect on tissue blood flow rates. The blood flows presented in
Tables 3-2 to 3-6 are for mice, rats, dogs, and humans in a "resting" state. However, there is
considerable variation in what a "resting state" is. Rest could be while the animals are lying down,
quietly standing, or moving about in their enclosures. The variations in "rest" may be best illustrated
by differences in resting activities during the diurnal cycle, and the consequent differences in tissue
perfusion (Delp et al., 1991). In compiling these data, there was no attempt made to standardize the
resting state of the animals, since the majority of the studies did not define the behavioral
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characteristics of the "resting" animals. When several flow measurements were made at various times
during the diurnal cycle, the blood flow values were averaged.
Postural differences in blood flow are also evident in humans. For example, Brown et al. (1989)
reported that the mean blood flow rate in the portal vein in humans was reduced by 26% from the
supine to the standing position (864 vs. 662 ml/min). However, these changes parallel those in
cardiac output that occur when going from a supine to a standing position. Therefore, absolute liver
blood flow decreases when going from the supine to standing position, but relative hepatic flow,
expressed as a percent of cardiac output, does not change.
Human skeletal muscle blood flow may also be strongly influenced by posture. For example,
when individuals are recumbent, few muscle are needed to actively maintain posture. However.
during sitting or standing, skeletal muscles must become more active to provide postural support.
This difference in posture may explain, in part, the range of values reported for human muscle blood
flow. In the majority of studies in which muscle blood flow has been measured, the subjects were in
a reclining position, resulting in flows of approximately 4 ml/min/100 g (e.g., Harding et al., 1989;
Snell et al., 1987). However, in studies measuring muscle blood flow while subjects are seated,
flows range from 9-16 ml/min/100 g (Richter et al., 1988; Rolett et al., 1990; Savard et al., 1987).
3.4.6 Age
The mean parameter values provided in Tables 3-2 to 3-6 are intended to be representative for
young adult members of the species. However, it may be necessary to incorporate age-related
changes into a PBPK model for compounds with a long half-life or when the pharmacokinetic
behavior of a compound at specific life stages (e.g., neonatal, elderly) is modeled. Furthermore.
incorporation of age-related changes into a PBPK model may be important when the model is used to
estimate the lifetime average daily dose (LADD) of a compound or it's metabolites for risk
assessment purposes.
Age-related changes in tissue perfusion have been demonstrated in several tissues. For example.
age-related reductions in hepatic blood flow have been well characterized in humans (Woodhouse and
Wynne, 1992; Wynne et al., 1990), and to a lesser extent in rats (Yates and Hiley, 1978). In
general, it appears that liver blood flow decreases approximately 1% per year in humans after age 40
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to 50 years. These changes can have a dramatic effect on the pharmacokinetic behavior of highly
cleared drugs in elderly populations. Fewer studies have been conducted of age-related changes in
hepatic blood flow in experimental animals. Yates and Hiley (1978) reported that the distribution of
the cardiac output in the hepatosplanchnic region fell from 21.1 % in young rats (3-4 months old) to
11.4 % in "middle-aged" rats (11-12 months old). However, blood flow measurements in this study
were conducted in rats anesthetized with ketamine. The potential therefore exists that the difference
in hepatic blood flow between the young and middle-aged rats could represent a differential effect of
the anesthetic agent and not simply an age-related difference in flow. In addition to hepatic tissue,
blood flow to other rat visceral tissues, such as the kidneys and small intestines (Hoffman et al.,
1982) and spleen (McDonald et al., 1989; Tuma et al., 1985) have been reported to be lower in
senescent rats.
Changes in body composition, which occur with advancing age, could aJso have a major impact
on the relative distribution of cardiac output. For example, with increasing age during adulthood,
there is an increase in relative body fat (Myhre and Kessler, 1966; Wessel et al., 1963) and a
concomitant decrease in muscle mass (Borkan et al., 1983; Tzankoff and Norris, 1977) in humans.
These age-related changes in body composition will likely influence the relative portion of cardiac
output going to these tissue.
Since the results of PBPK models are used in risk assessment to interpret the results of chronic
bioassays in experimental animal species, it seems appropriate to more accurately characterize age-
related changes in anatomical and physiological hemodynamic parameters in mice and rats, and to
incorporate these changes into PBPK models when appropriate.
3.4.7 Gender
Mean blood flow values in Tables 3-2 to 3-6 are derived almost exclusively from male animals;
the one exception is a canine study (Quillen and Reid, 1988) which used bodi male and female dogs.
In general, there is a paucity of data comparing male and female tissue blood flows. It is likely that
blood flow rates to reproductive tissues will differ, either when flow is expressed per unit mass or as
a percent of cardiac output. There is also evidence that blood flow to other tissues may vary between
males and females. For example, it has been reported that perfusion of human brain (Perl mutter et
al., 1987) and myocardial (Rowe et al., 1959; Weinberg et al., 1964) tissue differs between males
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and females. In addition, gender-related variations in body composition could result in differences in
the relative distribution of cardiac output among the various organs. For example, the gastrointestinal
tract and adipose tissue of females may represent a larger portion of total body mass than in males
(ICRP, 1975). This being the case, then it is not unreasonable to assume that these tissues may
receive a greater portion of cardiac output than in males.
3.5 USE OF CARDIAC OUTPUT AND REGIONAL BLOOD FLOW VALUES
IN PBPK MODELS
In this section, methods for estimating cardiac output values for individuals of different body
weight within a species are examined and the need for maintaining equivalence between the sum of
regional blood flows and cardiac output in PBPK models is emphasized.
3.5.1 Selecting Cardiac Output Values for Animals Within a Species
In their landmark paper, Andersen et al. (1987) used the following allometric scaling relationship
to derive cardiac output values in their methylene chloride PBPK model for rats, hamsters, and
humans:
,0.74
Cardiac output (L/hr) = 15 (BW)'
where BW equals body weight in kilograms. Subsequent PBPK models (e.g., Evans et al. 1994:
Fisher et al. 1989; Kedderis et al. 1993) have either used this equation or a slight variation of this
relationship to estimate cardiac output for rats.
Based on the cardiac output data reported by Delp et al. (1991), Dallas et al. (1994) developed the
following relationship to generate cardiac output values for rats in their PBPK model of
tetrachloroethylene:
Cardiac Output (ml/min) = 1.54 (ml/min/g) BW (g)075.
General use of this equation requires the assumption that cardiac output remains relatively constant
over the range of body weights typically encountered for young adult rats used in pharmacokinetic
studies. The data reported by Hachamovitch et al. (1989) suggests that cardiac output changes very
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little in male F344 rats over much of their lifetime. For example, cardiac output in these rats
increases from 84 ml/min in 290 g, 4-month-old rats, to 98 ml/min in 363 g, 12-month-old animals,
and remains at about that level in 20-month-old rats weighing 400 g. Assuming a similar pattern
exists for male Sprague-Dawley rats, the equation used by Dallas et al. (1994) to derive cardiac
output values for rats is probably valid for use in estimating the cardiac output of adult, male Sprague
Dawley rats of other body weights.
Comparison of estimated and predicted values of cardiac output in rats, as shown in Table 3-8,
suggests that the widely used equations developed by Andersen et al. (1987) and Arms and Travis
(1988) are appropriate for estimating cardiac output in unanesthetized rats. As expected, the
relationship derived by Dallas et al. (1994) closely predicts the mean cardiac output reported by Delp
et al. (1991) and only slightly overpredicts the mean cardiac output for rats derived from five studies.
Table 3-8 Predictive
Equations Used to
the
Reference
Ability of Various Allometric Scaling
Estimate Cardiac Output Values for
Rat in PBPK Models
Cardiac Output (ml/min)a
Estimated Measured
Andersen et al. (1987)
Arms and Travis (1988)
Dallas et al. (1994)
Mean from Table 3-1
Delpetal. (1991)
117.6
110.6
128.9
110.4
131.0
1 Estimated for a 366 g rat, the mean body weight of rats used in the Delp et al. (1991) study.
In contrast, the equations developed by Andersen et al. (1987) markedly overpredict the mean
cardiac output value in unanesthetized mice derived from the results reported in the literature. The
equation proposed by Andersen et al. (1987):
Cardiac output (L/hr) = 28 BW074,
where BW equals body weight in kilograms, yields a value of 29.3 ml/min, for a 25 g mouse.
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In comparison, the mean cardiac output derived from results reported by Barbee et al. (1992) and
Wong et al. (1993) for unanesthetized mice with a mean body weight of 23-30 g is around 14 ml/min
(Table 3-1). However, the equation derived by Arms and Travis (1988):
Cardiac output (L/hr) = 16.5 BW075,
where BW equals body weight in kilograms, yields a value (17.3 ml/min) very similar to that found
in the literature.
The following equation, derived by Dallas et al. (1994) to predict cardiac output in the dog was
developed using the data obtained from Detweiler et al. (1970):
,0.75
Cardiac output (ml/min) = 1.05 (ml/min/g) BW (g)'
However, use of this equation to predict cardiac output in a 10 kg dog (the presumed weight of
dogs in their model) yields a value of 1,050 ml/min, a value that falls outside of the range of values
reported by Detweiler et al. (1970) (cited as Andersen, 1970 in their paper) for cardiac output in
unanesthetized dogs. Use of this equation to predict the cardiac output of dogs weighing 21 kg yields
a value of 1,831 ml/min, a value that is around 60% lower than that determined experimentally in 21
kg dogs by Quillen and Reid (1988). Therefore, this equation should be used with some caution.
3.5.2 Summation of Regional Blood Flows
In parametrizing a PBPK model, it is crucial that the sum of the regional blood flows exactly
equal to 100% of the cardiac output. Failure to do so results in a flow imbalance in the model which
typically leads to severe inaccuracy and model failure.
However, in Tables 3-2 through 3-6, the sum of mean tissue flows is less than 100% of cardiac
output for mice (57.3%), rats (93.5%), dogs (90.3%), and humans (91.5%). There are several
reasons why summed tissue flow rates from these tables do not equal cardiac output. First.
representative flows from normal unanesthetized animals could not be found in the literature for
certain tissues, such as blood flow to adipose and bone tissues in mice and dogs. The gaps in the
available blood flow data make it impossible to account for all of the cardiac output in these animals.
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Second, it was rare for any study to report cardiac output and blood flow to most tissues. (One
exception is the study by Delp et al. (1991); these investigators used a direct measure of cardiac
output and the sum of individual tissue blood flows to assess cardiac output in the rat. There was
close agreement in the cardiac output values derived using these two methods.) In the absence of
studies reporting total tissue perfusion rates, we compiled data from investigations in which blood
flow to several individual tissues was measured. While this approach establishes a representative
mean or measure of central tendency for tissue blood flows, it does not mathematically yield
individual perfusion rates which, when summed, equal 100% of the cardiac output. This is due to the
inter-study variability of tissue perfusion rates. Finally, and most importantly, Tables 3-2 through 3-6
are not exhaustive in that they do not include all tissues in the body (e.g., the reproductive tissues,
eyes, and urinary bladder). Thus, summed tissue flows from these tables would not be expected to
equal 100%.
Although the regional blood flow values provided in Tables 3-3 to 3-6 for rats, dogs, and humans
do not yield 100% when summed, they should provide modelers with useful guidance in deciding how
cardiac output should be apportioned among compartments, and may be good sources of data for
blood flow to specific organs represented in the model. However, since data are unavailable for
regional blood flow to many tissues in the mouse, the values provided in Table 3-2 cannot be used by
themselves to develop cardiac output distribution estimates for a mouse PBPK model.
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4.0 BLOOD VOLUME
Inherent in many recent PBPK models is the assumption that uptake of a compound into storage
tissues is perfusion limited, that is, diffusion across the tissue membranes occurs rapidly relative to
blood flow. As a result, one can assume that the concentration of the compound is in equilibrium
between the tissue and the blood in the tissue. Therefore, there is no need to represent the tissue and
blood components of a storage compartment separately when the assumption of perfusion-limited
uptake is made. In contrast, when diffusion occurs less rapidly than blood flow, then uptake is said
to be diffusion-limited. Diffusion-limited uptake may occur for compounds that are highly bound to
plasma proteins or other blood components or when the compounds have a high molecular weight or
are charged. When diffusion-limited uptake occurs in a storage compartment, it is necessary to write
a separate mass balance equations to describe the behavior of the compound in the tissue and in the
blood in the tissue. Therefore, data on the volume of blood in the compartment are required when it
is necessary to represent diffusion-limited uptake in a compartment.
Data on the residual volume of blood in each organ are also required when it is necessary to
correct tissue:blood partition coefficient values used in the model for the volume of residual blood in
the organ. Tissue:blood partition coefficient values are determined either by dosing the animal.
removing and homogenizing the tissues of interest, and determining the concentration of the
compound in the blood and homogenized tissues or, for volatile compounds by determining the
partitioning behavior of the compound between homogenized tissues and blood in vitro using the vial
equilibration method. In either approach, homogenized tissues are used. However, residual blood in
the homogenized tissue has the potential to introduce error into the determination of the partition
coefficient. The extent of error is dependent on the amount of blood that remains in the tissue and
the extent to which the compound binds to blood components. Khor and Mayersohn (199la,b) have
demonstrated how tissue:blood partition coefficient values can be corrected for the amount of residual
blood in the tissue. Implementation of this approach requires data on die volume of residual blood in
each organ.
The compartments of a PBPK model are connected via a representation of die circulatory system.
Although arterial and venous blood compartments are explicitly included in many PBPK models,
odiers use an algebraic simplification of the mass balance differential equation for the blood
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compartment under the assumption of steady state. Representation of the mass balance equations in
this way creates a "bloodless" PBPK model because the volume of the blood in the animal is not
explicitly accounted for. However, when it is necessary to obtain estimates of the amount of
chemical in the blood with the model, or when the compound being modeled either binds extensively
to blood elements or is metabolized in the blood, then it is necessary to include a parameter in the
model to represent blood volume in the major arteries and veins.
4.1 CRITERIA FOR DATA SELECTION AND REPRESENTATION OF THE DATA
Measurement of residual blood volume in experimental animals usually involves injection of
radiolabelled erythrocytes or plasma proteins into the animals and measurement of the radiolabel in
excised tissues. All of the blood volume values presented in Table 4-1 below for experimental
animals were obtained using this approach. The use of blood volume values from excised tissue in a
PBPK model requires the assumption that blood volume in an excised tissue is the same as the blood
volume in the living state. However, the method used to sacrifice the animal may effect organ blood
volume (e.g., immersion in liquid nitrogen may cause rapid hypothermia-induced shifts in blood
volume). Another factor that may cause differences in organ blood volume between the living and
excised state is the dissection techniques used by the investigators. Accidental or deliberate draining
of blood from the organ during dissection and removal of the organ from the body would result in an
underestimate of the amount of "equilibrium" blood in the tissue in the intact animal. In general, the
studies used to provide the data represented in Table 4-1 involved excision and homogenization of
tissues without attempts to drain blood from the organ. In some cases (e.g., Kaliss and Pressman,
1950), attempts were made to preserve the blood volume of the tissues by ligation of vessels prior to
excision of the organ.
Although blood volume measurements in animals have been made largely using the same
technique, a number of different techniques have been used to measure organ-specific blood volume
in humans. Leggett and Williams (1991) have discussed the merits and limitations of these techniques
in their review of the literature. In general, any study in humans that was deemed appropriate tor
inclusion in the Leggett and Williams (1991) paper was also considered for this analysis. In organs
for which blood volume data were lacking in humans, Leggett and Williams (1991) derived reference
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values based on the results of animal studies. However, the results of animal studies were not used as
a surrogate for human data in our work.
4.2 BLOOD VOLUME DATA
Mean values and ranges are provided for the residual blood volume in various tissues of the
mouse, rat, dog and human are provided in Table 4-1.
The values presented in Table 4-1 are volume fractions for that organ or tissue, in other words,
the volume of residual blood in the organ relative to the volume of the organ. These values are not
representations of the fraction of the total blood volume that resides in that tissue.
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Table 4-1 Volume Fraction of Blood in Organs and Tissues
Adrenal
Adipose
Bone
Brain
Heart
Kidney
Liver
Lung
Muscle
Skin
Spleen
Thyroid
Mouse
Mean Range n
(SD)
0.03 1
0.11 1
0.03 1
0.24 0.12-0.34 3
0.31 0.23-0.36 3
0.50 0.40-0.62 3
0.04 0.03-0.05 2
0.03 1
0.17 0.17-0.19 3
Rat
Mean Range n
(SD)
0.24 1
0.04
0.03 0.02-0.04 3
0.26 1
0.16 0.11-0.27 3
0.21 0.12-0.27 3
0.36 0.26-0.52 3
0.04 0.01-0.09 3
0.02 1
0.22 0.17-0.28 3
0.18 1
Dog
Mean Range n
(SD)
0.01 1
0.07 1
0.08 1
0.15 1
0.30 1
0.01
0.51 1
Human
Mean (SD) Range n
0.02+ 0.01 0.02-0.03 3
0.04 1
0.04+ 0.01 0.03-0.10 15
0.36+ 0.01 0.22-0.50 4
0.11 1
0.01 1
0.08 1
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As shown in Table 4-1, bone, heart, kidneys, liver, lung and spleen are among the more vascular
tissues, whereas adipose, brain, muscle, and skin have a relatively small proportion of their volume
taken up by blood.
In general, there is relatively good agreement across species in the volume fraction of blood in
less vascular tissues. For example, it appears that from 1-5% of the volume of muscle tissue in mice,
rats, and humans is occupied by blood. A larger variability exists within and across species in the
volume of blood of the more vascular tissues. Although this variation may reflect true species or
strain differences in the blood volume of these organs, it is more likely due to differences in
technique or interlaboratory variability.
Important differences exist in values for blood volume of the liver and kidney in rats. For
example, Triplet! et al. (1985) found that about 24% of the volume of the rat kidney was occupied by
blood, whereas Khor and Mayersohn (1991b) estimated that the volume fraction of blood in the
kidney to be about 11%. A similar trend was seen in values reported for volume fraction of blood in
the rat liver: Triplett et al. (1985) reported a value of about 25% and Khor and Mayersohn (1991b)
found this value to be about 12%. Difference in the values reported in each of these studies may be
due to the different strains used (Triplett et al., 1985 used Sprague-Dawley rats and Khor and
Mayersohn, 199Ib used Fischer rats), differences in experimental techniques, or may simply reflect
the biological variability of this parameter. A wide variation in values for liver and kidney blood
volume in the rat is also reported in the earlier literature. For example, the rat liver blood volume
values reported by Caster et al. (1956), Everett et al. (1956), and Lewis et al. (1952) are 10%. 27%,
and 18%, respectively. The values for blood volume of the rat kidney reported by these investigators
are 9%, 13%, and 28%, respectively.
Blood volume in most organs in humans has been fairly well characterized. For example, at least
15 studies of cerebral blood volume in humans have been published. If studies based on the
indicator-dilution methods are disregarded, data indicate that the volume fraction of blood in the brain
is 0.03-0.05. In contrast, there are no good estimates of the volume fraction of blood in the human
liver. The reference value proposed by Leggett and Williams (1991) for blood volume in the human
liver is based an estimate taken from the review published by Greenway and Stark (1971), and their
estimate is based on data from dogs.
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The early PBPK models developed by Bischoff and colleagues (e.g., Bischoff and Brown, 1966)
included detailed representations of the capillary blood volume, interstitial volume, and intercellular
volume for each compartment in the model. Based on data available at that time, Dr. Bischoff
assumed that capillary blood occupied about 6% of the liver volume, 9% of the lung volume, and
13% of the kidney volume of a hypothetical "minimammal". These estimates are consistent with the
low end of values that have been reported in the literature; however, they are intended to represent
capillary blood volume, and not the blood in the larger vessels present in the tissue. Greenway and
Stark (1971) have suggested that 44% of the blood in the liver resides in the large vessels (e.g.,
hepatic artery, portal vein) and the remainder resides in the small vessels. Therefore, the assumption
that 6% of the hepatic volume is occupied by blood seems like a reasonable one. Similar, but slightly
lower values were used in the PBPK model for 2,3,7,8-tetrabromodibenzo-p-dioxin (TBDD)
developed by Kedderis et al. (1993). For example, these investigators assumed that blood occupied
only 5% of the liver, slowly perfused tissues, and fat, whereas only 1 % of the volume of the richly
perfused and skin compartments was occupied by blood. These values are consistent with those
presented in Table 4-1 for slowly perfused tissues, but, may underestimate the amount of blood in
more vascular tissues.
Since excision and homogenization of tissues will include the blood from large as well as small
vessels, the values used in Table 4-1 may be appropriate when correcting tissue:blood partition
coefficients for the presence of residual blood. However, selection of values for organ-specific
capillary blood volume in a model should take into account that the values presented in Table 4-1
presumably represent blood in large and small vessels of the organ.
PBPK models with explicit compartments for the arterial and venous vessels require data on the
blood volume that resides in those vessels. Standard textbooks of physiology apportion blood volume
in the body as follows: Veins, 64% (39% in large veins and 25% in small veins); arteries, 15%
(8% in large arteries, 5% in small arteries, and 2% in arterioles); and 5% in capillaries. The ICRP
(1975) document recommends die following distribution of blood volume be used for reference man
and woman: Arterial system, 19%; venous system, 61%; pulmonary circulation, 10%; heart cavities.
10%. Lumping the blood in the heart and pulmonary circulation with the arterial blood yields values
similar to those used in PBPK models developed by Igari et al. (1983) for arterial and venous blood
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volume. The values proposed by Leggett and Williams (1991) and Mapleson (1963) suggest a 25:75
division of blood volume between the arterial and venous circulations.
4.3 FACTORS THAT INFLUENCE ORGAN-SPECIFIC BLOOD VOLUME
The two factors that have the greatest influence on blood volume in different compartments are
posture and exercise. Going from a sitting to a standing position results in a shift of about 15% of
the total blood volume from the upper body (intrathoracic and splanchnic regions) to the lower body
(legs and pelvic area). From a modeling perspective, the factor that has the most effect on blood
volume distribution is exercise. Summarizing data from several sources, Leggett and Williams (1991)
note that blood volume can drop by 15% in the liver and 35% in the splanchnic region in exercising
humans. In contrast, the blood volume in the lungs may increase by 30%.
Limited data are available on age-related changes in blood volume. Leenders et al. (1990) have
found that cerebral blood volume decreased about 0.5% per year in humans aged 22-82 years. These
changes may be important to consider for specific research in cerebrovascular hemodynamics, but
probably have little impact on values that would be used in PBPK models.
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5.0 ALVEOLAR VENTILATION
PBPK models of compounds that are either taken up or eliminated by the respiratory tract require
a lung compartment with parameters to represent these processes in the model. Values for these
parameters are often taken from compendia such as the Arms and Travis (1988) document and other
sources. Given the widespread use of the this document as a source of respiratory parameter values
in PBPK models, it is important to examine the accuracy of these values. Perhaps more important is
the need to examine the validity of using default values for these parameters in PBPK models of
compounds that have the potential to effect the respiratory dynamics of animals and humans. These
issues are discussed below.
The pulmonary uptake of a volatile compound can be determined from data on the pulmonary
blood flow rate, the blood:air partition coefficient, the concentration of the compound in the inhaled
air, and the alveolar ventilation rate. The alveolar ventilation rate (QJ can be defined as:
QA = fx(VT-DS)
where f is the respiratory frequency, VT is the tidal volume, and DS is the physiological dead space.
Alternately, QA can be derived as:
QA = VE-(fxDS)
where VE is minute volume, which is equal to f x VT.
5.1 CRITERIA FOR DATA SELECTION
Values selected for this analysis were derived from studies using unanesthetized, healthy, resting.
adult animals breathing room air. Since tracheotomy has been shown to effect tidal volume and
respiratory frequency in animals, data from animals that had undergone this procedure was not used.
Alveolar ventilation rates, per se, are rarely reported in the literature for experimental animals.
However, values for this parameter they can be derived using the equations shown above. To derive
reference alveolar ventilation values, Arms and Travis (1988) assumed that 33% of the tidal volume
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represented physiological dead space. Therefore, alveolar ventilation is assumed to be equal to
0.67VE in resting individuals.
5.2 ALVEOLAR VENTILATION DATA
Alveolar ventilation is among the best characterized of the physiological parameters required for
PBPK modeling. As a result, mean values can be derived for this parameter in mice, rats, dogs,
humans.
Table 5-1 Alveolar Ventilation at Rest
Species
Mouse
Rat
Dog
Human
ml/min/lOOg BW
Mean (SD)
116.5 ±0.0 83.0
52.9 ± 0.0 31.5
23.1
5.0 3.5
Range
- 145.1
to 137.6
-7.7.
n*
5
23
1
~
a Number of studies
5.2.1 Mice
Compared to other species, relatively few studies have been conducted to determine respiratory
parameters in unanesthetized mice. The relative lack of studies may be due to technical difficulties
associated with die small size of these animals.
Mean values for alveolar ventilation in unanesthetized mice range from 83.0 to 145.1 inl/min/100
g. The mean alveolar ventilation rate for mice provided in Table 5-1, assuming QA = 0.67VE, is
116.5 ml/min/100 g BW. This value is slightly higher than the reference value of 100 ml/min/100 g
selected by Arms and Travis (1988) for this parameter, largely due to inclusion of data from the more
recent study by Vijayaraghavan et al. (1993).
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5.2.2 Rats
The values for respiratory parameters in unanesthetized rats were derived from 23 studies. The
mean alveolar ventilation values (assuming QA = 0.677^ in rats range from 31.5 to 137.62
ml/min/100 g BW, with a mean across all studies of 52.88 ml/min/100 g. This value differs
somewhat from the reference value suggested by Arms and Travis (1988) for this parameter of 46.8
ml/min/100 g BW or 117 ml/min for a standard 250 g rat. Among the reasons for this difference are
the following.
Values for weight-normalized minute volumes in unanesthetized rats are provided by Arms and
Travis (1988) in their Table 4-23. According to the table header, minute volumes are represented in
units of L/min/kg; however, the first value in the table is represented in units of ml/min/kg. Correct
representation of the value from Blume and Zollner (1943) as 1.467 instead of 0.001 L/min/kg would
raise their mean estimate somewhat. Also, there are two other errors in their Table 4-23 that would
result in a lower estimate of mean minute volume. Values from the Bartlett and Tenney (1970) and
Olson and Derapsey (1978) were incorrectly listed as 0.142 and 0.326 L/min/kg, respectively, in the
table. The correct values are 0.381 and 0.528 L/min/kg for these studies. These higher mean values
will also result in a higher estimate of the mean across all studies. Four of the mean VE values used
by Arms and Travis (1988) in their analysis come from the study of Leong et al. (1964); one of
which was obtained from animals weighing 52.3 g. As discussed in more detail below, VE is
proportionally greater in smaller animals when the values are normalized for body weight. As a
result, one might argue that VE values from a 50 g rat may not may not be representative of those
from a "standard" 250 g rat. Therefore, this value was not used to derive the mean value provided in
Table 5-1. Finally, the overall mean estimate for alveolar ventilation provided in Table 5-1 for rats
was derived from the means of 23 studies. Arms and Travis (1988) considered 13 studies in their
derivation of the reference value for this parameter.
5.2.3 Dogs
Surprising few studies of alveolar ventilation rates measured in unanesthetized dogs were
identified in the literature. In the one study that was identified, Park et al. (1970) reported a mean a
mean minute volume of 34.5 ml/min/100 g BW in 20 Beagles of both sexes. Assuming a dead space
of 33%, the alveolar ventilation in the animals is expected to be 23.1 ml/min/100 g BW.
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5.2.4 Humans
Data on respiratory dynamics in humans has been collected for many years. Much of this data
has been summarized in compendia such as that compiled by Altman and Dittmer (1971). Using the
results of individual studies, these authors have estimated the minute volume expected for a reference
man (20 years old, weighing 70 kg, with a surface area of 1.8 m2) and woman (20 years old,
weighing 55 kg, with a surface area of 1.52 m2) from the data provided in each study. Estimated
minute volumes range from 4.38 to 8.44 L/min (5 studies) for a reference woman and 5.28 to 11.43
L/min (6 studies) for a reference man. The mean estimated minute volumes for reference woman and
man are 5.3 and 7.5 L/min., respectively. The values selected by the ICRP (1975) for the minute
volumes for reference woman and man are 6.0 and 7.5 L/min, respectively. The results of studies
published since the Altman and Dittmer (1971) and ICRP (1975) documents (e.g., Brobeck, 1979;
Frostell et al., 1983) are consistent with the reference values proposed for minute ventilation in
humans.
Similar to minute volume, numerous studies have been conducted to estimate dead space volume
in humans. Altman and Dittmer (1971) have summarized the results of 16 of these studies and
estimated dead space volume for a reference man and woman. The estimated values range from
17.6% to 39.4% of the tidal volume, with a mean estimate of 33%. This is identical to the value
selected by Arms and Travis (1988) and supports the use of 0.67VE to estimate QA in humans.
5.3 FACTORS THAT INFLUENCE ALVEOLAR VENTILATION
Before the alveolar ventilation rates presented in Table 5-1 are used as default values in a PBPK
model, the issues discussed below should be considered.
5.3.1 Effect of the Compound Being Modeled on Respiratory Dynamics
Implicit in the use of default alveolar ventilation values in a PBPK model of unanesthetized
animals breathing uncontaminated air is the assumption that exposure to the compound being modeled
has no effect on respiratory dynamics. However, inhaled compounds can have very characteristic
effects on breathing patterns. For example, exposure to respiratory irritants typically results in a
reduction in breathing rate. Compounds that act as bronchoconstrictors reduce VE by reducing the
tidal volume. Pulmonary irritants alter expiratory breathing patterns (Vijayaraghavan et al.. 1993).
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Anesthetic agents also effect respiratory dynamics. Vinegar et al. (1979) showed that both tidal
volume and respiratory rate were reduced in mice after intravenous administration of pentobarbital.
Based on the relationships described in the equations shown above, a corresponding reduction in VE
and QA is expected in animals anesthetized with pentobarbital.
Inhalation anesthetics are known to reduce tidal volume and increase respiratory rate (Lockhart et
al., 1991). The resulting effect is a depression of minute ventilation, because the increase in
respiratory rate cannot compensate for the decrease in tidal volume.
Despite the potential effect of inhaled compounds on respiratory dynamics, many PBPK models of
volatile compounds use default values for QA with little consideration of the potential error this may
introduce into model-derived simulations. Johanson and Filser (1992) have demonstrated that use of
the default values for QA proposed by Arms and Travis (1988) for mice and rats results in a
overestimate of the clearance uptake measured using the closed-chamber gas uptake method. They
found that experimentally determined clearance uptake values were about 60% of the values
determined when the default reference values were used. Successful estimation of the experimentally
derived clearance uptake values generally required the use of QA from about 30 to 80 ml/min for rats
and about 5 to 14 ml/min for mice. Johanson and Filser (1992) offer three reasons for the necessity
to use QA values that are about 60% lower than those proposed by Arms and Travis (1988) to
successfully estimate experimentally derived clearance uptake values for animals in gas uptake studies.
They point out that volatile compounds may act as respiratory irritants, which, as mentioned above,
can reduce respiratory rate. Alternately, a wash in-wash out effect could be occurring where the
volatile compound is absorbed onto the respiratory airways during inhalation, then desorbed during
exhalation. The result would be a reduced pulmonary uptake of the compound. Although alveolar
ventilation may not be effected by the compound per se, a lower value for QA would enable clearance
uptake from the chamber to be modeled more accurately. A third possibility, but one that Johanson
and Filser (1992) feel is remote, is the potential for volatile compounds to exert an anesthetic effect
on the animals in the closed chamber which thereby effects respiratory dynamics.
Regardless of the reason (direct effect on respiration or correction for a wash in-washout effect).
use of QA values that are 60% lower than those proposed by Arms and Travis (1988) may to be
necessary to accurately estimate clearance uptake of a number of volatile compounds in closed
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chamber gas uptake studies. These lower QA values have been used successfully by Johanson and
Filser (1993) and Csanady et al. (1994) in PBPK models of butadiene and styrene, respectively. It is
interesting to note that the alveolar ventilation rates derived by Medinsky et al. (1994) from a best fit
of the data in a PBPK model for butadiene are 17.1 and 70.8 ml/min for a 25 g mouse and a 250 g
rat, respectively. These values are about 68% and 61% lower than the reference values for this
parameter suggested by Arms and Travis (1988). Nevertheless, many investigators have had success
fitting closed-chamber data using alveolar ventialtion values similar to those proposed by Arms and
Travis (1988). For example, based on their experience Clewell (1994) and colleagues found that the
"best" values for alveolar ventilation were around 115 ml/min/100 g for the mouse and 35 to 50
ml/min/100 g for the rat.
Since PBPK models of inhaled compounds with high blood solubility are sensitive to values of QA,
and since these same compounds have the potential to alter respiratory dynamics, it is prudent to
measure values for this parameter during exposure of animals or humans to this compound, or at least
to be aware to the effect that volatile compounds can have on respiration, and to adjust the parameter
values accordingly. Use of default values for QA in PBPK models of some inhaled compounds may
result in overestimates of inhaled dose.
5.3.2 Effect of Physical Activity
Alveolar ventilation is one of the parameters in a PBPK model that responds most dramatically to
exercise and physical work. The values provided in Table 5-2 are derived from the VE data reported
in the ICRP (1975) document for male and female humans at rest and performing light, moderate,
and strenuous work.
Resting
Light Activity
Heavy Work
Maximal Work
Table 5-2 Alveolar Ventilation (L/min) During
Exercise in Humans"
Male
5
20
35
90
Female
5
14
20
70
Based on VE values reported in ICRP (1975) and assumptions that dead space = 0.33 Vr at rest
and 0.20 VT during physical activity.
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Extensive studies of the effect of exercise on respiratory dynamics have also been conducted by
Balke (1969) and reported in Altman and Dittmer (1971). For sedentary and reasonably active
individuals, the minute volume during moderate exercise (heart rate = 120) ranges from about 23 to
30 L/min. During strenuous exercise (heart rate = 150), minute volumes tend to range from about
35 to 65 L/min and maximal exercise (heart rate = 180+) results in minute volumes that range from
50-100 L/min. Values for minute volume at rest and during exercise are markedly increased in
highly trained individuals.
Physiological dead space decreases during physical work and exercise. As summarized in Altman
and Dittmer (1971), dead space volume in humans ranges from about 10 to 30% during exercise. It'
we assume that a dead space volume of 20% is representative of values that may be obtained in
exercising humans, the expected values for QA in humans doing light to moderate work would be on
the order of 18 to 24 L/min; strenuous work, 28 to 52 L/min, and maximal work, 40 to 80 L/min.
The values for light to moderate work are consistent with those used by Dankovic and Bailer (1994)
in their recent revaluation of the Andersen et al. (1987) methylene chloride PBPK model under light
work conditions.
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6.0 DISCUSSION
Sensitivity analyses have been conducted of a number of PBPK models to identify the parameters
that have the greatest effect on model output (Bois et al., 1990, 1991; Clewell et al., 1994; Evans et
al., 1994; Gearhart et al., 1993; Hattis et al., 1993; Hetrick et al., 1991; Woodruff et al., 1992).
Although PBPK model simulations of the pharmacokinetic behavior of volatile organic compounds
tend to be most sensitive to the values selected for metabolic parameters, they can also be markedly
influenced by the values selected for physiological parameters such as the volume of and blood flow
to the fat compartment, alveolar ventilation rate, and blood flow to the liver. For example, Evans et
al. (1994) demonstrated that PBPK model-derived estimates of metabolic rate constant values for
carbon tetrachloride in rats were most sensitive to values selected for blood:air partition coefficient,
followed by fat partition and fat volume > slowly perfused partition, ventilation rate, cardiac output,
fat blood flow percentage > liver blood flow percentage and slowly perfused blood flow percentage.
Therefore, accurate characterization of values for physiological parameters such as fat volume and
ventilation rate are important for the accurate determination of metabolic rate constants with the
model. Accurate characterization of the physiological parameter values in such a model is especially
important when the model is used to derive metabolic rate constants for compounds for which the
production of active metabolites "drives" the risk assessment.
The most accurate means of identifying physiological parameter values used in PBPK models is
direct measurement of the values in animals of the same age, strain, and species as the animals in
which the pharmacokinetic behavior of the compound is being studied. Ideally, these values should
also be obtained under the same conditions as those used In the pharmacokinetic study. However, not
all modelers have access to experimental facilities, nor is it necessary to experimentally determine
physiological parameter values for each new model when the parameters are unaffected by the
compound being modeled. It is important, however, for modelers to have access to data from which
valid and representative default values can be derived for the physiological parameters used In PBPK
models and to have an understanding of the conditions under which it is appropriate to use default
values for the parameters.
The goals of this document have been to provided modelers with representative values for
physiological parameters, to provide an indication of the variability associated with the parameter
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values, and to discuss the factors that have the greatest impact on the physiological parameters.
Unlike previous compilations, this document does not suggest reference values for these parameters.
Rather, mean parameter values are provided, along with the standard deviation of the mean and the
range of mean values identified from what were felt to be valid studies. Such an approach is intended
to provide modelers with sufficient data to make decisions about what constitutes reasonable and
representative parameter values for their model. The representation of the variability associated with
the values should be useful when the need exists to adjust parameter values to obtain a better tit of
model-derived simulations to experimental data. Also, explicit representation of biologically plausible
ranges for the parameter values may be useful for modelers that employ the Monte Carlo approach in
their models.
An additional goal of this paper has been to serve as a pointer to the original literature, so
modelers can carefully review the conditions under which the data were derived before selecting a
representative value for the parameters in their models. The appendices to this document provide
careful annotation of the references associated with each data point that was used to derive the mean
parameter values.
In some cases, reference physiological parameter values proposed in other documents have been
derived from the results of relatively few studies. The approach taken in this document has been to
conduct an extensive search of the literature and, whenever possible, to derive the mean value tor the
parameter from as many valid studies as possible. The criteria used to identify what constitutes a
"valid" study are discussed in each section. Briefly, values were only selected from studies in which
healthy, resting, unanesthetized, young adult animals were used. Care was also taken to avoid the
use values from studies in which intervention by the researchers (e.g., placement of a tracheostomy)
could have an effect on die measurement of the parameter value.
Representative values for some of the physiological parameters used in PBPK models have been
difficult to obtain from the existing compilations of such data. For example, a reference value for the
volume of fat in die mouse does not appear in the compilation developed by Davies and Morris
(1993), despite the important of this species in pharmacokinetic modeling. Modelers have also had
difficulty accessing physiological parameter values for individual organs in some species and in
determining parameter values for anatomically or physiologically heterogenous tissues when the tissue
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is represented in different compartments in the model (e.g., subcutaneous and internal fat).
Hopefully, modelers with a need for such data will find this document useful. Although an attempt
was made to provide data for the organs and tissues of interest to most modelers, an exhaustive
compilation of the volume of and blood flow to all organs and tissues was felt to be beyond the scope
of this document. Furthermore, no attempt was made to include values for all of the organs or tissues
that many be necessary for models developed to describe the pharmacokinetic behavior of compounds
under special circumstances, such as pregnancy. Those interested in developing PBPK models that
include a fetal compartment are encouraged to refer to the papers by Fisher et al. (1989, 1990),
Leucke et al. (1994), and O'Flaherty et al. (1992) for the necessary parameter values.
A number of long-standing assumptions regarding default values for die physiological parameters
are explored in this paper. Specifically, we have examined the validity of the following assumptions:
that an appropriate reference body weight for mice and rats is 25 g and 250 g, respectively; that
values for die volume of the fat compartment of a PBPK model can be derived from the weight of
dissectible fat; that it is appropriate to derive values for blood flow parameters from studies in which
anesthetized animals were used; that the relative blood flow to the liver is constant across species; and
that the compound being modeled has no effect on physiological processes diat are represented in the
model.
Regarding the selection of values for body weight in a reference mouse or rat, the values proposed
by Arms and Travis (1988) are representative of relatively young animals (9-10 weeks old) that are in
a rapid phase of growth. In contrast, the value selected for die weight of a reference human is
representative of adult weight. Use of these reference body weights in a PBPK model to scale animal
data to humans may introduce error because die species are in different stages of development. In
addition, use of die reference body weight for mice and rats proposed by Arms and Travis (1988)
may introduce error into estimates of the volume of die fat compartment in mice and rats of
"nonstandard" weight. Therefore, consideration should be given to values for this parameter that are
eidier more representative of the body weight of the animal over the majority of its lifespan or that
occur during a period of less rapid growth.
Values selected for the volume of die fat compartment are among the most important in PBPK
models of lipophilic compounds. Since most PBPK model simulations are carried out for a relatively
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short time period, it is not necessary to account for age-related changes in the volume of this
compartment. However, when the pharmacokinetic behavior of the compound is simulated over an
extended time course, as is required for compounds with a long residence half-life, then it may be
important to account for age-related changes in body composition.
When model simulations are carried out for extended time periods, it may also be necessary to
account for compound-induced changes in compartment volume. For example, exposure to some
compounds can increase or decrease liver volume over time. However, changes in liver volume do
not necessarily result in a change in hepatic clearance. Compound-induced changes in intrinsic
metabolic capacity should be accounted for as well before incorporating changes in liver volume into
the model.
Anesthesia has the potential to markedly effect regional hemodynamics. As a result, the blood
flow values presented in Table 3-2 were derived only from studies that used unanesthetized animals.
The mean values derived for blood flow to the liver of mice and rats are somewhat lower than the
reference values selected by Arms and Travis (1988) for this parameters. This difference is perhaps
due to the reliance by Arms and Travis (1988) on data from anesthetized animals or on their
imprecision in selecting a reference value from the available data. The default value selected by
Arms and Travis (1988) for this parameter (25% of the cardiac output) has been widely used in PBPK
models and may have resulted in an overestimate of metabolic clearance of highly cleared compounds
in the liver.
Data on blood volume of specific organs and pharmacokinetic compartments is important when
diffusion-limited uptake is assumed, when it is necessary to correct tissue:blood partition coefficients
for residual blood volume, or when it is necessary to explicitly represent arterial and venous blood
compartments. However, these values are not provided in the Arms and Travis (1988) or Davies and
Morris (1993) documents. The mean values and ranges provided in Table 4-1 are probably most
useful when correcting tissue:blood partition coefficient for residual blood. However, these values
represent the blood present in both large and small vessels in the organs. Since the blood in
equilibrium with the tissue in an organ is capillary blood, direct use of the values in Table 4-1 in a
PBPK model will result in an overestimate of the volume of capillary blood in the tissue.
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A large variability is evident in the values for some blood volume parameters. It is not clear
whether the wide range of values represents biological variability or differences due to differences in
experimental technique. Modelers should keep this variability in mind when selecting values for these
parameters.
Organ blood volume can change as a result of changes in posture and physical activity. Perhaps
the most important effect to note from a modeling perspective is the shift of blood from the lower
body and liver to the lungs following an increase in physical activity.
Representation of diffusion-limited uptake in a PBPK model not only requires data on the residual
blood volume, but also values for a diffusion parameter. The diffusion parameter might be described
as a quasi-physiological parameter, equivalent to the product of the cell area/volume ratio, an
anatomical term, and capillary permeability, a parameter with compound-specific values. Since it is
not strictly a physiological or anatomical parameter, and because values for this parameter are often
obtained by fitting the model to a certain data set, this term is not addressed in any detail in this
document. However, investigators with a need to represent membrane-limited diffusion in their
models may find it useful to refer to the discussions offered by Dedrick and Bischoff (1968) and
Dedrick et al. (1982) on the derivation of this term. Also, use of a diffusion term to account for
membrane-limited uptake is demonstrated in the PBPK models developed by Lutz et al. (1977) and
Baxter et al. (1994). Use of this approach may be necessary to represent the uptake of hydrophilic
compounds in some organs (e.g., brain and testes) with fairly effective capillary barriers to many
substances and the uptake of large molecules such as antibodies.
Use of default values for alveolar ventilation is based on the assumption that the compound being
modeled has no effect on respiratory dynamics. However, Johanson and Filser (1992) have shown
that the clearance uptake of compounds in a closed chamber may be over predicted when the
reference value for alveolar ventilation proposed by Arms and Travis (1988) is used to derive the
clearance values. Based on empirical observations, Johanson, Filser and colleagues have used an
alveolar clearance value that is 60% of the default value proposed by Arms and Travis (1988) for
mice and rats in their subsequent PBPK models. Although alveolar ventilation may not actually be
reduced by 60% in animals exposed to volatile compounds in a closed chamber, use of this reduced
value is required to accurately predict the disappearance of some compound from the headspace. The
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mean value for alveolar ventilation provided in Table 5-1 for rats is even higher than the Arms and
Travis (1988) reference value for this parameter. Therefore, although the mean value provided in
Table 5-1 may be representative of the alveolar ventilation rate in unanesthetized rats breathing
uncontaminated air, it may not be appropriate for direct incorporation into a PBPK model of a volatile
compound.
In summary, this document provides modelers with mean values for the physiological parameters
that are used most often in PBPK models, with an indication of the variability associated with these
parameter values, and with an indication of the factors that have the greatest impact on the values.
Rather than providing "reference" values, sufficient information is provided to allow modelers to
select representative values for these parameters. In addition, the validity of a number of long-
standing assumptions regarding physiological parameter values has been explored and a discussion is
provided on when caution should be exercised in using default values for these parameters in a PBPK
model.
The data used to prepare the summary tables on organ weight and blood flow data are provided in
Appendix A and B, respectively. Physiological parameter values for species other than mouse, rat,
dog, and human, as well as interspecies allometric equations are provided in Appendix C.
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Armstrong, R.B., and M.H. Laughlin (1984). Exercise blood flow patterns within and among rat
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Armstrong, R.B., M.D. Delp, E.F. Goljan and M.H. Laughlin (1987). Distribution of blood flow in
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Armstrong, R.B., D.A. Hayes and M.D. Delp (1989). Blood flow distribution in rat muscle during
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Astrand, I. (1983). Effect of physical exercise on uptake, distribution, and elimination of vapors in man
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Atal, S., M.J. Zaraowski, S.W. Cushman, and J. Sampugna (1994). Comparison of body weight and
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103
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APPENDIX A
Organ Weight Values for Mice,
Rats, and Dogs
-------
Relative Weight (% Body Weight) of the Adrenals
in Mice, Rats, and Dogs
Species
Mouse
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Strain
C57BL
SD
NS
Wistar
WKY
Wistar
Wistar
LE
LE
LE
LE
LE
LE
SD
SD
SD
SD
SD
SD
SD
SD
SD
SD
Sex
F
M
NS
M
M
M
F
M
F
M
F
M
F
M
F
M
F
M
M
M
M
M
M
Age
(Weeks)
NS
NS
NS
21
21
13
13
9
9
35
35
52
52
9
9
13
13
NS
17-19
17-19
17-19
17-19
17-19
Mean BVV
(g)
22
366.00
355.00
458.00
347.00
329.00
194.00
261.65
210.06
524.70
297.25
555.18
324.31
245.45
223.97
366.03
342.24
529.01
442
496
422
454
534
n
5
8
6
10
10
10
10
17
17
17
16
11
13
98
344
142
33
83
19
19
20
19
19
Mean Organ
Weight (%BW)
0.048
0.025
0.012
0.012
0.014
0.013
0.023
0.017
0.027
0.011
0.026
0.010
0.020
0.019
0.031
0.016
0.025
0.014
0.012
0.011
0.013
0.012
0.01 1
Reference
Dowell et al. (1992)
Delp et al. (1991)
Jansky and Hart (1968)
Nishiyama et al. (1976)
Nishiyama et al. (1976)
Feron et al. (1973)
Feron et al. (1973)
Kozma et al. (1969)
Kozma et al. (1969)
Kozma et al. (1969)
Kozma et al. (1969)
Kozma et al. (1969)
Kozma et al. (1969)
Frank (1976)
Frank (1976)
Frank (1976)
Frank (1976)
Frank (1976)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
-------
Relative Weight (% Body Weight) of the Adrenals
in Mice, Rats, and Dogs
Species
Rat
Rat
Rat
Rat
Rat
Dog
Dog
Dog
Dog
Dog
Strain
SD
SD
SD
SD
SD
NS
Beagle
Mongrel
Beagle
Beagle
Sex
F
F
F
F
F
F
M
M/F
M
F
Age
(Weeks)
17-19
17-19
17-19
17-19
17-19
NS
62
NS
NS
NS
Mean BW
(g)
261
304
233
244
302
11,000
12,900
21,000
9,872
8,862
n
19
19
20
18
20
2
4
8
25
25
Mean Organ
Weight (%BW)
0.025
0.023
0.029
0.028
0.025
0.004
0.006
0.014
0.010
0.012
Reference
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Brody and Spencer (1972)
Mesa et al. (1994)
Quillen and Reid (1988)
Frank (1976)
Frank (1976)
-------
Relative Weight (% Body Weight) of the Brain
in Mice, Rats, and Dogs
Species
Mouse
Mouse
Mouse
Mouse
Mouse
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Strain
SW
ARM
B6C3F1
Mult.
Mult.
Holtzman
SD
Wistar
WKY
F-344
SD
SD
Wistar
Wistar
LE
LE
LE
LE
LE
LE
SD
SD
Sex
F
M
M
M
F
M
M
M
M
M
M
M
M
F
M
F
M
F
M
F
M
F
Age
(Weeks)
12
7
NS
17
17
16
NS
21
21
NS
13
27
13
13
9
9
35
35
52
52
9
9
MeanBW
(g)
35.00
22.20
20-23
32.62
28.15
338.00
366.00
458.00
347.00
250-280
307.21
548.43
329.00
194.00
261.65
210.06
524.70
297.25
555.18
324.31
245.45
223.97
n
19
9
5
206
180
22
8
10
10
6
48
48
10
10
17
17
17
16
II
13
3
34
Mean Organ
Weight (%BW)
1.51
1.74
2.03
1.35
1.63
0.55
0.60
0.44
0.59
0.65
0.60
0.38
0.54
0.83
0.65
0.81
0.38
0.65
0.38
0.57
0.72
0.70
Reference
Durbin et al. (1992)
Kaliss and Pressman (1950)
Stottet al. (1983)
Storer (1967)
Storer (1967)
Caster et al. (1956)
Delpetal. (1991)
Nishiyama et al. (1976)
Nishiyama et al. (1976)
Stottet al. (1983)
Farris et al. (1993)
Farris et al. (1993)
Feron et al. (1973)
Feron et al. (1973)
Kozma et al. (1969)
Kozma et al. (1969)
Kozma et al. (1969)
Kozma et al. (1969)
Kozma et al. (1969)
Kozma et al. (1969)
Frank (1976)
Frank (1976)
-------
Relative Weight (% Body Weight) of the Brain
in Mice, Rats, and Dogs
Species
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Dog
Dog
Dog
Dog
Dog
Dog
Strain
SD
SD
SD
SD
SD
SD
SD
SD
SD
SD
SD
SD
SD
Beagle
Mongrel
Beagle
Beagle
Beagle
Beagle
Sex
M
F
M
M
M
M
M
M
F
F
F
F
F
M/F
M/F
M
F
M
F
Age
(Weeks)
13
13
NS
17-19
17-19
17-19
17-19
17-19
17-19
17-19
17-19
17-19
17-19
NS
NS
NS
NS
NS
NS
Mean BVV
(g)
366.03
342.24
529.01
442
496
422
454
534
261
304
233
244
302
NS -
21,000
10,300
8,600
9,872
8,862
n
23
11
18
20
20
20
20
20
19
19
20
18
20
53
8
60
59
25
25
Mean Organ
Weight (%BW)
0.50
0.61
0.42
0.45
0.41
0.47
0.44
0.39
0.68
0.63
0.79
0.75
0.63
0.5 - 1.0
0.43
0.79
0.85
0.84
0.86
Reference
Frank (1976)
Frank (1976)
Frank (1976)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Andersen and Goldman (1974)
Quillen and Reid (1988)
Nielson (1974)
Nielson (1974)
Frank (1976)
Frank (1976)
-------
Relative Weight (% Body Weight) of the Heart
in Mice, Rats, and Dogs
Species
Mouse
Mouse
Mouse
Mouse
Mouse
Mouse
Mouse
Mouse
Mouse
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rai
Rai
Strain
B6C3F1
Swiss
Swiss
Swiss
Swiss
Swiss
Swiss
Nu/Nu
Balb/c
Holtzman
SD
NS
Wistar
WKY
F-344
Wistar
Wistar
LE
LE
LE
LE
LE
LE
Sex
M
M
M
M
M
M
M
F
F
M
M
NS
M
M
M
M
F
M
F
M
F
M
F
Age
(Weeks)
NS
8
112
1724
36
52
78
NS
NS
16
NS
NS
21
21
NS
13
13
9
9
35
35
52
52
Mean BW
(g)
20-23
33.97
35.40
41.76
43.83
49.93
47.93
22.15
22.90
338.00
366.00
355.00
458.00
347.00
250-280
329.00
194.00
261.65
210.06
524.70
297.25
555.18
324.31
n
5
5
5
5
5
5
5
6
3-5
22
8
6
10
10
6
10
10
17
17
17
16
1 1
13
Mean Organ
Weight (%BW)
0.55
0.50
0.54
0.46
0.41
0.40
0.48
0.60
0.52
0.29
0.33
0.29
0.32
0.32
0.30
0.32
0.37
0.34
0.36
0.27
0.37
0.27
0.32
Reference
Stott et al. (1983)
DeMarte and Enesco (1986)
DeMarte and Enesco (1986)
DeMarte and Enesco (1986)
DeMarte and Enesco (1986)
DeMarte and Enesco (1986)
DeMarte and Enesco (1986)
Baxter et al. (1994)
Bourne et al. (1992)
Caster et al. (1956)
Delp et al. (1991)
Jansky and Hart (1968)
Nishiyama et al. (1976)
Nishiyama et al. (1976)
Stott et al. (1983)
Feron et al. (1973)
Feron et al. (1973)
Kozma et al. (1969)
Kozma et al. (1969)
Kozma et al. (1969)
Kozma et al. (1969)
Kozma et al. (1969)
Kozma et al. (1969)
-------
Relative Weight (% Body Weight) of the Heart
in Mice, Rats, and Dogs
Species
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Dog
Dog
Dog
Dog
Dog
Dog
Dog
Dog
Strain
SD
SD
SD
SD
SD
SD
SD
SD
SD
SD
SD
SD
SD
SD
SD
NS
Beagle
Mongrel
Beagle
Beagle
Beagle
Beagle
Beagle
Sex
M
F
M
F
M
M
M
M
M
M
F
F
F
F
F
F
M
M/F
NS
NS
M
•F
M
Age
(Weeks)
9
9
13
13
NS
17-19
17-19
17-19
17-19
17-19
17-19
17-19
17-19
17-19
17-19
NS
62
NS
13
25
NS
NS
NS
Mean BW
(g)
245.45
223.97
366.03
342.24
529.01
442
496
422
454
534
261
304
233
244
302
11,000
12,900
21,000
4,620
8,130
10,300
8,600
9.872
n
26
110
67
21
39
20
20
20
20
20
19
19
20
18
20
2
4
8
8
15
60
59
25
Mean Organ
Weight (%BW)
0.40
0.38
0.35
0.44
0.33
0.30
0.29
0.31
0.31
0.28
0.33
0.32
0.36
0.37
0.31
0.68
0.83
0.73
0.70
0.76
0.83
0.82
0.80
Reference
Frank (1976)
Frank (1976)
Frank (1976)
Frank (1976)
Frank (1976)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Brody and Spencer (1972)
Mesaet al. (1994)
Quillen and Reid (1988)
Deavers et al. (1972)
Deavers et al. (1972)
Nielson (1974)
Nielson (1974)
Frank (1976)
-------
Relative Weight (% Body Weight) of the Heart
in Mice, Rats, and Dogs
Species
Dog
Strain
Beagle
Sex
F
Age
(Weeks)
NS
Mean BW
(g)
8,862
n
25
Mean Organ
Weight (%BW)
0.85
Reference
Frank (1976)
-------
Relative Weight (% Body Weight) of the Kidney
in Mice, Rats, and Dogs
Species
Mouse
Mouse
Mouse
Mouse
Mouse
Mouse
Mouse
Mouse
Mouse
Mouse
Mouse
Mouse
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Strain
Swiss
Swiss
Swiss
Swiss
Swiss
Swiss
SW
CF-1
AKM
B6C3F1
Nu/Nu
Balb/c
Holtzman
SD
NS
Wistar
WKY
F-344
WKY
WKY
SD
SD
Wistar
Sex
M
M
M
M
M
M
F
M
M
M
F
F
M
M
NS
M
M
M
M
F
M
M
M
Age
(Weeks)
8
12
24
36
52
78
12
NS
7
NS
NS
NS
16
NS
NS
21
21
NS
15
19
13
27
13
Mean BW
(g)
33.97
35.40
41.76
43.83
49.93
47.93
35.00
21.00
22.20
20-23
22.15
22.90
338.00
366.00
355.00
458.00
347.00
250-280
260
200
307.21
548.43
329.00
n
5
5
5
5
5
5
19
10
9
5
6
3-5
22
8
6
10
10
6
6
6
48
48
10
Mean Organ
Weight (%BW)
1.88
1.64
1.84
1.60
1.40
1.61
1.70
1.86
1.70
1.64
1.35
1.78
0.76
0.76
0.87
0.67
0.70
0.78
0.49
0.53
0.63
0.51
0.69
Reference
DeMarte and Enesco (1986)
DeMarte and Enesco (1986)
DeMarte and Enesco (1986)
DeMarte and Enesco (1986)
DeMarte and Enesco (1986)
DeMarte and Enesco (1986)
Durbin et al. (1992)
Friedman (1955)
Kaliss and Pressman (1950)
Stottet al. (1983)
Baxter et al. (1994)
Bourne et al. (1992)
Caster et al. (1956)
Delp et al. (1991)
Jansky and Hart (1968)
Nishiyama et al. (1976)
Nishiyama et al. (1976)
Stott et al. (1983)
Oudaret al. (1991)
Oudar et al. (1991)
Farris et al. (1993)
Farris et al. (1993)
Feron et al. (1973)
-------
Relative Weight (% Body Weight) of the Kidney
in Mice, Rats, and Dogs
Species
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Strain
Wistar
BHE
BHE
LE
LE
LE
LE .
LE
LE
SD
SD
SD
SD
SD
SD
SD
SD
SD
SD
SD
SD
SD
SD
Sex
F
M
F
M
F
M
F
M
F
M
F
M
F
M
M
M
M
M
M
F
F
F
F
Age
(Weeks)
13
43
43
9
9
35
35
52
52
9
9
13
13
NS
17-19
17-19
17-19
17-19
17-19
17-19
17-19
17-19
17-19
Mean BW
(g)
194.00
499.00
319.00
261.65
210.06
524.70
297.25
555.18
324.31
245.45
223.97
366.03
342.24
529.01
442
496
422
454
534
261
304
233
244
n
10
48
45
17
17
17
16
11
13
101
349
143
33
91
20
20
20
20
20
19
19
20
18
Mean Organ
Weight (%BW)
0.68
0.73
0.74
0.68
0.69
0.59
0.68
0.53
0.64
0.91
0.83
0.79
0.78
0.73
0.81
0.77
0.83
0.81
0.75
0.88
0.81
0.88
0.86
Reference
Feron et al. (1973)
Farmer (1974)
Farmer (1974)
Kozma et al. (1969)
Kozma et al. (1969)
Kozma et al. (1969)
Kozma et al. (1969)
Kozma et al. (1969)
Kozma et al. (1969)
Frank (1976)
Frank (1976)
Frank (1976)
Frank (1976)
Frank (1976)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
-------
Relative Weight (% Body Weight) of the Kidney
in Mice, Rats, and Dogs
Species
Rat
Dog
Dog
Dog
Dog
Dog
Dog
Dog
Dog
Dog
Strain
SD
NS
Beagle
Mongrel
Beagle
Beagle
Beagle
Beagle
Beagle
Beagle
Sex
F
F
M
M/F
NS
NS
M
F
M
F
Age
(Weeks)
17-19
NS
62
NS
13
25
NS
NS
NS
NS
Mean BW
(8)
302
11,000
12,900
21,000
4,620
8,130
10,300
8,600
9,872
8,862
n
20
2
4
8
8
15
60
59
25
25
Mean Organ
Weight (%BW)
0.79
0.56
0.53
0.47
0.70
0.59
0.54
0.50
0.52
0.51
Reference
Gur and Waner (1993)
Brody and Spencer (1972)
Mesa et al. (1994)
Quillen and Reid (1988)
Deavers et al. (1972)
Deavers et al. (1972)
Nielson (1974)
Nielson (1974)
Frank (1976)
Frank (1976)
-------
Relative Weight (% Body Weight) of the Liver
in Mice, Rats, and Dogs
Species
Mouse
Mouse
Mouse
Mouse
Mouse
Mouse
Mouse
Mouse
Mouse
Mouse
Mouse
Mouse
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Strain
Swiss
Swiss
Swiss
Swiss
Swiss
Swiss
SW
B6C3F1
AKM
CF-1
Nu/Nu
Balb/c
Holtzman
SD
NS
Wistar
WKY
F-344
Wistar
Wistar
Wistar
SD
SD
Sex
M
M
M
M
M
M
F
M
M
M
F
F
M
M
NS
M
M
M
F
M
F
M
M
Age
(Weeks)
8
12
24
36
52
78
12
NS
7
NS
NS
NS
16
NS
NS
21
21
NS
NS
NS
NS
13
27
Mean BW
(g)
33.97
35.40
41.76
43.83
49.93
47.93
35.00
20-23
22.20
21.00
22.15
22.90
338.00
366.00
355.00
458.00
347.00
250-280
193
329
194
307.21
548.43
n
5
5
5
5
5
5
19
5
9
10
6
3-5
22
8
6
10
10
6
10
10
10
48
48
Mean Organ
Weight (%BW)
5.71
4.97
4.64
4.70
4.19
4.19
6.50
6.33
7.60
7.98
4.29
4.80
4.15
3.40
4.16
3.50
3.30
4.07
4.28
3.32
3.15
4.37
3.18
Reference
DeMarte and Enesco (1986)
DeMarte and Enesco (1986)
DeMarte and Enesco (1986)
DeMarte and Enesco (1986)
DeMarte and Enesco (1986)
DeMarte and Enesco (1986)
Durbin et al. (1992)
Stott et al. (1983)
Kaliss and Pressman (1950)
Friedman (1955)
Baxter et al. (1994)
Bourne et al. (1992)
Caster et al. (1956)
Delp et al. (1991)
Jansky and Hart (1968)
Nishiyama et al. (1976)
Nishiyama et al. (1976)
Stott et al. (1983)
Peters and Boyd (1966)
Feronet al. (1973)
Feron et al. (1973)
Farris et al. (1993)
Farris et al. (1993)
-------
Relative Weight (% Body Weight) of the Liver
in Mice, Rats, and Dogs
Species
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rai
Strain
SD
SD
F344
F344
F344
F344
F344
Wistar
Wistar
BHE
BHE
LE
LE
LE
LE
LE
LE
SD
SD
SD
SD
SD
SD
Sex
M
M
M
M
M
M
M
M
F
M
F
M
F
M
F
M
F
M
F
M
F
M
M
Age
(Weeks)
NS
NS
2-4
6
11-13
18-20
28-30
13
13
43
43
9
9
35
35
52
52
9
9
13
13
NS
17-19
Mean BW
(g)
405.50
366.70
275.00
340.00
408.00
387.00
336.00
329.00
194.00
499.00
319.00
262.00
210.00
525.00
297.00
555.18
324.31
245.45
223.97
366.03
342.24
529.01
442
n
3
3
4
4
4
4
4
10
10
48
45
17
17
17
16
11
13
101
349
143
33
91
20
Mean Organ
Weight (%BW)
2.55
3.53
3.78
3.41
3.11
3.54
4.34
3.32
3.15
3.57
3.62
2.67
2.78
2.60
2.99
2.14
2.50
5.16
4.03
4.45
3.92
4.00
4.39
Reference
Satterwhite and Boudinot (1992)
Satterwhite and Boudinot (1992)
Coniglio et al. (1979)
Coniglio et al. (1979)
Coniglio et al. (1979)
Coniglio et al. (1979)
Coniglio et al. (1979)
Feron et al. (1973)
Feron et al. (1973)
Farmer (1974)
Farmer (1974)
Kozma et al. (1969)
Kozma et al. (1969)
Kozma et al. (1969)
Kozma et al. (1969)
Kozma et al. (1969)
Kozma et al. (1969)
Frank (1976)
Frank (1976)
Frank (1976)
Frank (1976)
Frank (1976)
Gur and Waner (1993)
-------
Relative Weight (% Body Weight) of the Liver
in Mice, Rats, and Dogs
Species
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Dog
Dog
Dog
Dog
Dog
Dog
Dog
Dog
Dog
Strain
SD
SD
SD
SD
SD
SD
SD
SD
SD
NS
Beagle
Mongrel
Beagle
Beagle
Beagle
Beagle
Beagle
Beagle
Sex
M
M
M
M
F
F
F
F
F
F
M
M/F
NS
NS
M
F
M
F
Age
(Weeks)
17-19
17-19
17-19
17-19
17-19
17-19
17-19
17-19
17-19
NS
62
NS
13
25
NS
NS
NS
NS
Mean BW
(g)
496
422
454
534
261
304
233
244
302
11,000
12,900
21,000
4,620
8,130
10,300
8,600
9,872
8,862
n
20
20
20
20
19
19
20
18
20
2
4
8
8
15
60
59
25
25
Mean Organ
Weight (%BW)
4.16
3.62
4.35
4.10
4.15
4.17
3.97
4.15
4.24
3.22
3.66
2.94
3.61
3.11
3.20
3.10
3.35
3.44
Reference
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Brody and Spencer (1972)
Mesa et al. (1994)
Quillen and Reid (1988)
Deavers et al. (1972)
Deavers et al. (1972)
Nielson (1974)
Nielson (1974)
Frank (1976)
Frank (1976)
-------
Relative Weight (% Body Weight) of the Lungs
in Mice, Rats, and Dogs
Species
Mouse
Mouse
Mouse
Mouse
Mouse
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Dog
Dog
Dog
Dog
Strain
CF-1
ARM
B6C3F1
Nu/Nu
Balb/c
Holtzman
SD
NS
Wistar
WKY
F-344
Wistar
Wistar
LE
LE
LE
LE
LE
LE
NS
Beagle
Mongrel
Beagle
Sex
M
M
M
F
F
M
M
NS
M
M
M
M
F
M
F
M
F
M
F
F
M
M/F
M
Age
(Weeks)
NS
7
NS
NS
NS
16
NS
NS
21
21
NS
13
13
9
9
35
35
52
52
NS
62
NS
NS
Mean BW
(g)
21.00
22.20
20-23
22.15
22.90
338.00
366.00
355.00
458.00
347.00
250-280
329.00
194.00
261.65
210.06
524.70
297.25
555.18
324.31
IKOOO
12,900
2 1 .000
1 1 ,500
n
10
9
5
6
3-5
22
8
6
10
10
6
10
10
17
17
17
16
11
13
2
4
8
20
Mean Organ
Weight (%BW)
0.70
0.71
0.66
0.86
0.71
0.56
0.37
0.60
0.39
0.37
0.43
0.45
0.58
0.57
0.61
0.46
0.57
0.45
0.52
0.97
0.75
0.88
0.65
Reference
Friedman (1955)
Kaliss and Pressman (1950)
Stott et al. (1983)
Baxter et al. (1994)
Bourne et al. (1992)
Caster et al. (1956)
Delp et al. (1991)
Jansky and Hart (1968)
Nishiyama et al. (1976)
Nishiyama et al. (1976)
Stott et al. (1983)
Feron et al. (1973)
Feron et al. (1973)
Kozma et al. (1969)
Kozma et al. (1969)
Kozma et al. (1969)
Kozma et al. (1969)
Kozma et al. (1969)
Kozma et al. (1969)
Brody and Spencer (1972)
Mesa et al. (1994)
Quillen and Reid (1988)
Park et al. (1974)
-------
Relative Weight (% Body Weight) of the Lungs
in Mice, Rats, and Dogs
Species
Dog
Dog
Dog
Dog
Dog
Dog
Dog
Dog
Dog
Dog
Strain
Beagle
Beagle
Beagle
Beagle
Beagle
Beagle
Beagle
Beagle
Beagle
Beagle
Sex
F
M
F
F
NS
NS
M
F
M
F
Age
(Weeks)
NS
NS
NS
NS
13
25
NS
NS
NS
NS
Mean BW
(g)
10,600
11,000
8,300
8,400
4,620
8,130
10,300
8,600
9,872
8,862
n
20
21
50
22
8
15
60
59
25
25
Mean Organ
Weight (%BW)
0.62
0.85
0.72
0.90
1.07
1.03
0.75
0.77
0.77
0.78
Reference
Park et al. (1974)
Bair and Willard (1962)
Bair and Willard (1962)
Hadidian and Pawlowski (1964)
Deavers et al. (1972)
Deavers et al. (1972)
Nielson (1974)
Nielson (1974)
Frank (1976)
Frank (1976)
-------
Relative Weight (% Body Weight) of the Muscle
in Mice, Rats, and Dogs
Species
Mouse
Mouse
Mouse
Mouse
Rat
Rat
Dog
Dog
Dog
Dog
Dog
Dog
Dog
Dog
Dog
Dog
Dog
Dog
Dog
Dog
Dog
Dog
Dug
Strain
SW
CF-1
Nu/Nu
Balb/c
Holtzman
SD
Mongrel
Beagle
Beagle
Beagle
Beagle
Beagle
Beagle
Beagle
Beagle
Beagle
Beagle
Beagle
Beagle
Beagle
Beagle
Beagle
Beagle
Sex
F
M
F
F
M
M
M/F
M
M
M
F
F
F
F
F
F
F
F
F
F
F
F
F
Age
(Weeks)
12
NS
NS
NS
16
NS
NS
12
12
14
17
17
34
34
58
58
70
80
112
123
164
226
388
Mean BW
(g)
35.00
21.00
22.15
22.90
338.00
366.00
21,000
9,410
4,452
6,544
5,128
5,370
7,711
9,796
7,248
6,218
7,982
8,595
9,027
10,987
15,510
9.881
10.873
n
19
10
6
3-5
22
8
8
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Mean Organ
Weight (%BW)
38.80
39.90
35.77
39.13
45.50
35.36
39.69
49.20
35.20
38.00
41.00
40.80
46.80
54.40
46.20
45.80
49.00
51.10
47.60
47.80
53.50
40.50
49.50
Reference
Durbin et al. (1992)
Friedman (1955)
Baxter et al. (1994)
Bourne et al. (1992)
Caster et al. (1956)
Delp et al. (1991)
Quillen and Reid (1988)
Andersen and Goldman (1974)
Andersen and Goldman (1974)
Andersen and Goldman (1974)
Andersen and Goldman (1974)
Andersen and Goldman (1974)
Andersen and Goldman (1974)
Andersen and Goldman (1974)
Andersen and Goldman (1974)
Andersen and Goldman (1974)
Andersen and Goldman (1974)
Andersen and Goldman (1974)
Andersen and Goldman (1974)
Andersen and Goldman (1974)
Andersen and Goldman (1974)
Andersen and Goldman (1974)
Andersen and Goldman (1974)
-------
Relative Weight (% Body Weight) of the Ovaries
in Mice, Rats, and Dogs
Species
Mouse
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Dog
Strain
C57BL
Wistar
SD
SD
SD
SD
SD
Wistar
Beagle
Sex
F
F
F
F
F
F
F
F
F
Age
(Weeks)
NS
13
17-19
17-19
17-19
17-19
17-19
NS
NS
Mean BW
-------
Relative Weight (% Body Weight) of the Skin
in Mice, Rats, and Dogs
Species
Mouse
Mouse
Mouse
Mouse
Mouse
Rat
Rat
Rat
Rat
Rat
Rat
Dog
Strain
SW
CF-1
B6C3F1
Nu/Nu
Balb/c
Holtzman
SD
NS
F-344
SD
SD
Mongrel
Sex
F
M
M
F
F
M
M
NS
M
M
M
M/F
Age
(Weeks)
12
NS
NS
NS
NS
16
NS
NS
NS
13
27
NS
Mean BW
(g)
35.00
21.00
20-23
22.15
22.90
338.00
366.00
355.00
250-280
307.21
548.43
21,000
n
19
10
5
6
3-5
22
8
6
6
48
48
8
Mean Organ
Weight (%BW)
18.00
12.86
20.80
13.27
17.73
18.00
19.07
17.89
23.60
15.80
19.79
9.10
Reference
Durbin et al. (1992)
Friedman (1955)
Stott et al. (1988)
Baxter et al. (1994)
Bourne et al. (1992)
Caster et al. (1956)
Delp et al. (1991)
Jansky and Hart (1968)
Stott et al. (1983)
Farris et al. (1993)
Farris et al. (1993)
Quillen and Reid (1988)
-------
Relative Weight (% Body Weight) of the Thyroid
in Mice, Rats, and Dogs
Species
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Dog
Dog
Strain
Wistar
Wistar
SD
SD
SD
SD
SD
SD
SD
SD
SD
SD
'NS
Mongrel
Sex
M
F
M
M
M
M
M
F
F
F
F
F
F
M/F
Age
(Weeks)
13
13
17-19
17-19
17-19
17-19
17-19
17-19
17-19
17-19
17-19
17-19
NS
NS
Mean BW
(g)
329.00
194.00
442
496
422
454
534
261
304
233
244
302
11,000
21,000
n
10
10
20
20
20
20
20
19
18
20
18
20
2
8
Mean Organ
Weight (%BW)
0.0021
0.0044
0.005
0.004
0.005
0.004
0.004
0.008
0.007
0.009
0.008
0.007
0.0074
0.0081
Reference
Feron et al. (1973)
Feron et al. (1973)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Brody and Spencer (1972)
Quillen and Reid (1988)
-------
Relative Weight (% Body Weight) of the Spleen
in Mice, Rats, and Dogs
Species
Mouse
Mouse
Mouse
Mouse
Mouse
Mouse
Mouse
Mouse
Mouse
Mouse
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rai
Rat
Strain
CF-1
AKM
Swiss
Swiss
Swiss
Swiss
Swiss
Swiss
Nu/Nu
Balb/c
Holtzman
SD
NS
Wistar
WKY
Wistar
Wistar
LE
LE
I.E
LE
Sex
M
M
M
M
M
M
M
M
F
F
M
M
NS
M
M
M
F
M
F
M
F
Age
(Weeks)
NS
7
8
12
24
36
52
78
NS
NS
16
NS
NS
21
21
13
13
9
9
35
35
Mean BW
(g)
21.00
22.20
33.97
35.40
41.76
43.83
49.93
47.93
22.15
22.90
338.00
366.00
355.00
458.00
347.00
329.00
194.00
261.65
210.06
524.70
297.25
n
10
9
5
5
5
5
5
5
6
3-5
22
8
6
10
10
10
10
17
17
17
16
Mean Organ
Weight (%BW)
0.50
0.37
0.29
0.28
0.26
0.21
0.16
0.24
0.45
0.70
0.21
0.21
0.24
0.22
0.16
0.18
0.19
0.19
0.22
0.13
0.17
Reference
Friedman (1955)
Kaliss and Pressman (1950)
DeMarte and Enesco (1986)
DeMarte and Enesco (1986)
DeMarte and Enesco (1986)
DeMarte and Enesco (1986)
DeMarte and Enesco (1986)
DeMarte and Enesco (1986)
Baxter et al. (1994)
Bourne et al. (1992)
Caster et al. (1956)
Delp et al. (1991)
Jansky and Hart (1968)
Nishiyama et al. (1976)
Nishiyama et al. (1976)
Feron et al. (1973)
Feron et al. (1973)
Kozma et al. (1969)
Kozma et al. (1969)
Kozma et al. (1969)
Kozma et al. (1969)
-------
Relative Weight (% Body Weight) of the Spleen
in Mice, Rats, and Dogs
Species
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Dog
Dog
Dog
Dog
Dog
Dog
Strain
LE
LE
SD
SD
SD
SD
SD
SD
SD
SD
SD
SD
SD
SD
SD
SD
SD
NS
Beagle
Mongrel
Beagle
Beagle
Beagle
Sex
M
F
M
F
M
F
M
M
M
M
M
M
F
F
F
F
F
F
M
M/F
NS
NS
M
Age
(Weeks)
52
52 .
9
9
13
13
NS
17-19
17-19
17-19
17-19
17-19
17-19
17-19
17-19
17-19
17-19
NS -
62
NS
13
25
NS
Mean BW
(g)
555.18
324.31
245.45
223.97
366.03
342.24
529.01
442
496
422
454
534
261
304
233
244
302
11,000
12,900
2 1 ,000
4.620
8,130
10.300
n
11
13
38
107
48
4
24
20
19
20
20
20
19
19
19
18
20
2
4
8
8
15
56
Mean Organ
Weight (%BW)
0.13
0.18
0.34
0.30
0.25
0.25
0.21
0.18
0.16
0.17
0.17
0.17
0.19
0.19
0.21
0.19
0.21
0.21
0.35
0.39
0.24
0.21
0.25
Reference
Kozma et al. (1969)
Kozma et al. (1969)
Frank (1976)
Frank (1976)
Frank (1976)
Frank (1976)
Frank (1976)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Brody and Spencer (1972)
Mesa et al. (1994)
Quillen and Reid (1988)
Deavers et al. (1972)
Deavers et al. (1972)
Nielson (1974)
-------
Relative Weight (% Body Weight) of the Spleen
in Mice, Rats, and Dogs
Species
Dog
Dog
Dog
Strain
Beagle
Beagle
Beagle
Sex
F
M
F
Age
(Weeks)
NS
NS
NS
MeanBW
(g)
8,600
9,872
8,862
n
55
17
17
Mean Organ
Weight (%BW)
0.26
0.25
0.25
Reference
Nielson (1974)
Frank (1976)
Frank (1976)
-------
Relative Weight (% Body Weight) of the Testes
in Mice, Rats, and Dogs
Species
Mouse
Mouse
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Dog
Dog
Strain
AKM
B6C3F1
Holtzman
SD
NS
Wistar
WKY
F-344
Wistar
LE
LE
LE
SD
SD
SD
SD
SD
SD
SD
SD
Beagle
Beagle
Sex
M
M
M
M
NS
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
Age
(Weeks)
7
NS
16
NS
NS
21
21
NS
13
9
35
52
9
13
NS
17-19
17-19
17-19
17-19
17-19
NS
NS
MeanBW
(g)
22.20
20-23
338.00
366.00
355.00
458.00
347.00
250-280
329.00
261.65
524.70
555.18
245.45
366.03
529.01
442
496
422
454
534
10300
9,872
n
9
5
22
8
6
10
10
6
10
17
17
11
101
143
91
20
20
20
20
20
61
25
Mean Organ
Weight (%BW)
0.49
0.75
0.94
0.36
1.73
0.76
0.77
1.03
0.82
1.08
0.71
0.62
1.00
0.99
0.77
0.77
0.74
0.86
0.76
0.71
0.19
0.14
Reference
KaJiss and Pressman (1950)
Stottetal. (1983)
Caster et al. (1956)
Delp et al. (1991)
Jansky and Hart (1968)
Nishiyama et al. (1976)
Nishiyama et al. (1976)
Stottetal. (1983)
Feron et al. (1973)
Kozma et al. (1969)
Kozma et al. (1969)
Kozma et al. (1969)
Frank (1976)
Frank (1976)
Frank (1976)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Gur and Waner (1993)
Nielson (1974)
Frank (1976)
-------
Relative Weight (% Body Weight) of the Thymus
in Mice, Rats, and Dogs
Species
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Strain
Holtzman
NS
Wistar
WKY
F-344
Wistar
Wistar
Sex
M
NS
M
M
M
M
F
Age
(Weeks)
16
NS
21
21
NS
13
13
Mean BVV
(g)
338.00
355.00
458.00
347.00
250-280
329.00
194.00
n
22
6
10
10
6
10
10
Mean Organ
Weight (%BW)
0.13
0.15
0.100
0.123
Reference
Caster et al. (1956)
Jansky and Hart (1968)
Nishiyama et al. (1976)
Nishiyama et al. (1976)
Stott et al. (1983)
Feron et al. (1973)
Feron et al. (1973)
-------
APPENDIX B
Cardiac Output and Regional Blood Flow Distribution
in Mice, Rats, and Dogs
-------
CARDIAC OUTPUT IN UNANESTHETIZED
MICE, RATS, AND DOGS
Species
Mouse
Mouse
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Rat
Dog
Strain
C3H/HeJ
C3H/HeN
F344
F344
F344
SD
SD
SD
SD
Wistar
WKY
NS
Mongrel
Sex
M
M
M
M
M
M
M
M
M
M
M
NS
M/F
Age (Weeks)
NS
6-8
17
52
87
NS
29
55
73
NS
52
NS
NS
Mean BW (g)
25-30
23.3
290
363
400
366
415
473
491
512
447
355
21,000
n
10
6
8
10
11
24
8
5
8
5
6
7
8
Mean CO (ml/min)
16
11.97
84.0
98.0
100.0
131.0
107.0
119.3
119.0
134.0
110.7
101.1
2,936.0
Reference
Barbee et al. (1992)
Wang et al. (1993)
Hachamovitch et al. (1989)
Hachamovitch et al. (1989)
Hachamovitch et al. (1989)
Delp et al. (1991)
Tsuchiya et al. (1977)
Tsuchiyaetal. (1977)
Tsuchiya et al. (1977)
Coleman (1974)
Tsuchiya et al. (1977)
Jansky and Hart (1968)
Quillen and Reid (1988)
-------
CARDIAC OUTPUT DISTRIBUTION IN MICE
REFERENCE
Barbee et al., 1992
Wang et al., 1993
Mean
SD
FLOW DISTRIBUTION (% of Cardiac Output)
Muscle Adrenal
12.2
19.6
15.9
5.2
Brain
3.5
3.1
3.3
0.3
Fat Heart
7.2
5.9
6.6
0.9
Kidney Lung Bone
11.1
7.0 0.5
9.1 0.5
2.9 -
Skin Haa
8.3
3.3 2.0
5.8 2.0
3.5
Splanchnic
13.9
14.2
14.1
0.2
Total
Liverb
16.2
16.2
Hepatic artery
Hepatic artery and Splanchnic flow
CARDIAC OUTPUT DISTRIBUTION IN RATS
REFERENCE
Carmichael et al., 1978
Carmichael et al., 1978
Delp et al., 1991
Malik et al., 1976
Nishiyama et al., 1976
Nishiyama et al., 1976
Sasaki et al., 1971
Tsuchiyaet al., 1978
Mean
SEM
FLOW DISTRIBUTION (% of Cardiac Output)
Muscle Adrenal
— —
—
0.2
—
0.3
0.2
—
—
27.8 0.3
0. 1
Brain
—
—
2.3
—
1.5
1.9
2.6
1.6
2.0
0.3
Fat Heart
5.7
4.5
7.0 5.1
4.5
5.0
5.8
5.1
5.0
7.0 5.1
0. 1
Kidney
—
—
14.0
9.5
19.0
19.0
11.6
16.4
14.1
1.9
Lung Bone Skin
—
—
1.3 12.2 5.8
3.0
2.0
1 .6
1.1
2.9
2.1 12.2 5.8
0.4
HAa
—
—
1.5
2.1
1.6
—
0.8
5.8
2.1
1.0
Splanchnic
—
—
17.1
17.0
17.8
16.3
12.3
11.1
15.3
1.2
Liverb
22.1
20.7
18.6
19.1
19.0
17.0
13.1
16.9
18.3
—
Hepatic artery
Hepatic artery and Splanchnic How
-------
CARDIAC OUTPUT DISTRIBUTION IN DOGS
REFERENCE
Muscle Adrenal Brain Fat
Quillen et al., 1988 21.7 0.2 2.0
FLOW DISTRIBUTION (% of Cardiac Output)
Heart Kidney
4.6 17.3
Lung Bone Skin
8.8 — 6.0
HAa Splanchnic
4.6 25.1
Liverb
29.7
" Hepatic artery
b Hepatic artery and Splanchnic flow
-------
APPENDIX C
Organ Weight Values for Species Other Than
Mice, Rats, and Dogs
Interspecies Allometric Equations
for Organ Weight
-------
Relative Organ Weight (% Body Weight) Values for Other Species
Adrenals
Bone
Brain
GI Tract
Stomach
Small Intestine
Large Intestine
Heart
Kidney
Liver
Lung
Muscle
Pancreas
Reproductive Organs
Ovaries
Testes
Skin
Spleen
Thymus
Thyroid
Body Weight (g) (kg)
Age (weeks)
Si rain
SLA
n
Gerbil
Zeeman (1967) Breazile &
Brown (1976)
Male Female
0.05 ± 0.01 0.05 ± 0.01 0.08
7.11
1.24 ± 0.16 1.58 ± 0.07 0.48
3.16
0.05
3.11
0.37 ± 0.04 0.35 ± 0.04
0.77 ± 0.06 0.74 ± 0.08 0.68
3.22 ± 0.24 2.87 ± 0.08 4.72
0.56
35.56
0.28
1.37 ± 0.15
0.13 ± 0.40 0.13 ± 0.02
0.01
77 66 900
NS NS NS
NS
M l: NS
5 5 NS
Guinea Pig
Altaian & Katz
(1977)
Male
0.05
0.42
1.46
0.32
0.63
0.51
0.21
0.55
2.95
0.47
0.05
0.30
0.05
0.06
1054
62
B/Lac
M
9
Female
0.10
0.41
1.87
0.43
0.75
0.69
0.25
0.56
3.40
0.52
0.02
0.07
0.07
1027
77
B/Lac
F
1 1
Goat
Neff-Davis
et al. (1975)
6.30
0.29
6.40 .
0.48
0.35
1.95
0.88
45.50
9.20
0.25
39
NS
NS
NS
NS
Hamster
Altman & Katz Kowaleski
(1977) (1969)
Male Female Male Female
0.02 0.01
0.38 0.34 0.28
0.45 0.47 0.71 0.64
3.76 3.76 4.48 3.67
0.48 0.48
0.02
1.81
0.08 0.11
94.7 109.5 135 153
14 14 17 17
ALAC/Lac ALAC/Lac M. quratas M. quratas
M F M F
26 28 18 15
-------
Relative Organ Weight (% Body Weight) Values for Other Species
Adrenals
Bone
Brain
GI Tract
Stomach
Small Intestine
Large Intestine
Heart
Kidney
Liver
Lung
Muscle
Pancreas
Reproductive Organs
Ovaries
Testes
Skin
Spleen
Thymus
Thyroid
Body Weight (g) (kg)
Age (weeks)
Strain
Sex
n
Horse
Webb and Weaver (1979)
14.60
0.21
5.80
0.66
0.36
1.30
0.89
40.10
7.40
l.ll
308
NS
NS
NS
NS
Rabbit Ox
Kozma et al. (1974) Matthews et al.
(1975)
Male Female
0.36 0.37 12.70
0.06
3.80
0.20 0.20 0.37
0.52 0.51 0.24
2.87 3.28 1.22
0.71
38.50
0.01
0.109
8.30
0.04 0.04 0.16
0.15 0.16
0.01 0.01
2.78 2.54 620
NS NS
NZW NZW
M F
23 21
-------
Adrenals
Bone
Brain
GI Tract
Stomach
Small Intestine
Large Intestine
Heart
Kidney
Liver
Lung
Muscle
Pancreas
Reproductive Organs
Ovaries
Testes
Skin
Spleen
Thymus
Thyroid
Body Weight (kg)
Age (yr)
Strain
Sex
n
Relative Organ Weight (%
Baboon
Mahaney et al. Frank (1976)
(1993"-b)
Male Female Male Female
0.03 ± 0.01 0.03 ± 0.01 0.02 0.02
1.67 ±0.12 1.50 ±0.13 2.50 2.40
1.20 ± 0.02 0.69 ±0.14 0.42 0.42
0.75 ± 0.24 0.57 ±0.15 0.42 0.46
3.95 ± 1.10 2.99 ± 0.78 2.35 2.44
1.91 ± 0.42 1.20 ± 0.40 0.54 0.58
0.25 ± 0.05 0.18 ± 0.03
0.01
0.58 ±0.12 0.07
0.36 ±0.12 0.21 ± 0.09 0.09 0.10
0.02 ± 0.01
25 15 3.5 3.25
N9 N9 NS NS
M F M F
25 29
Body Weight) Values for Nonhuman Primates
Rhesus Monkey
Fremming Kerr et al. (1969)
et al. (1955)
Male Female
0.03 0.03 ± 0.01 0.04 ± 0.02
1.69 1.38 ± 0.43 1.61 ± 0.59
3.34
0.38 0.45 ± 0.12 0.39 ± 0.09
0.38 0.40 ± 0.13 0.48 ± 0.25
2.56 2.39 ± 0.56 2.56 ± 0.93
0.88 0.92 ± 0.37 1.00 ± 0.41
0.21
0.07 0.08 ± 0.04 0.08 ± 0.05 .
0.02 ± 0.01 0.02 ± 0.02
0.01
5.72 6.19 5.59
NS NS NS
M M F
66 27 15
Squirrel
Beischer and
Furry (1964)
Male Female
0.05 0.03
3.50 3.48
0.54 0.47
0.59 0.53
3.12 2.64
0.84 0.72
0.04
0.43
0.26 0.24
0.61 0.62
NS NS
M F
7 3
Monkey
Middleton and
Rosal (1972)
Male Female
0.03 0.03
3.08 3.47
0.43 0.42
0.39 0.46
2.44 3.02
0.69 0.71
0.14
0.41
0.13 0.14
0.78 0.66
NS NS
M F
40 40
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Interspecies Allometric Equations
Adipose Tissue
Adrenal
Bone (Skeleton)
Brain
Gastrointestinal Tract
Heart
Kidney
Liver
Lung
Skin
Spleen
Thyroid
67.10BW""0
0.63 BW0-920
0.27 BW0-800
61.00BW1-090
15.40 BW0760
10.90 BW0-753
9.30 BW0-730
74.00 BW0*40
5.75 BW0980
4.34 BW1-000
5.80 BW0-980
7.52 BW0-850
7,32 BW0-850
7.10BW0-850
7.30 BW0-850
33.40 BW0-870
37.00 BW0-849
35.44 BW0870
11.57BW0-990
7.72 BW1-030
11.30BW0-990
139.00 BW0-942
2.50 BW1 -02
0.13BW092
For Organ Weight
Pitts and Bullard (1968)
Adolph (1949)
Stahl (1965)
Prange et al. (1979)
Adolph (1949)
Martin (1981)
Stahl (1965)
Adolph (1949)
Adolph (1949)
Holtet al. (1968)
Stahl (1967)
Adolph (1949)
Brody (1945)
Prothero (1984)
Stahl (1965)
Adolph (1949)
Boxenbaum (1980)
Prothero (1982)
Adolph (1949)
Bennett and Tenney (1982)
Stahl (1967)
Paceetal. (1979)
Stahl (1965)
Stahl (1965)
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