Why Cross-Species Tables Need Careful Structure
PBPK models use physiological inputs to represent organs and tissues, but a value measured or reported for one species is not automatically an appropriate value for another. A cross-species table helps expose both the similarities and the differences: which organ volumes are available, how tissue composition is represented, and how blood flow is reported. It is a comparison aid, not a recipe for filling gaps by borrowing values from a different species.
The examples below use a single hypothetical teaching dataset. The numbers are invented to demonstrate table construction and calculations; they are not reference values for model development. Real parameter selection requires evaluating the particular data and measurement bases available for the intended species, population, and model. The earlier material on reference physiological profiles, body-size metrics, organ-volume inputs, tissue composition, and blood-flow measurement bases supplies the necessary background for interpreting the table fields.
The reference animals used in this example are a 70 kg adult human, a 0.30 kg rat, a 0.025 kg mouse, a 10 kg dog, and a 5 kg nonhuman primate (NHP). These body masses describe the hypothetical entries; they are not claims that each species has one universal reference body size. A real table would document the relevant population, strain or breed, age, sex, and physiological state when those details are available.
Organ Volumes: Preserve Both the Quantity and the Basis
The table reports organ volume in litres (L). Body mass is included because it helps readers understand the scale of each animal, but the listed volumes are absolute volumes, not volume per kilogram. Displaying the raw quantity first prevents a normalized value from being mistaken for the measured organ volume.
| Species | Body mass (kg) | Liver volume (L) | Kidney volume, combined (L) | Brain volume (L) |
|---|---|---|---|---|
| Human | 70 | 1.50 | 0.310 | 1.40 |
| Rat | 0.30 | 0.0105 | 0.00180 | 0.00190 |
| Mouse | 0.025 | 0.00125 | 0.000350 | 0.000420 |
| Dog | 10 | 0.320 | 0.0550 | 0.0750 |
| NHP | 5 | 0.120 | 0.0250 | 0.0950 |
Each organ definition matters. “Kidney volume, combined” means the two kidneys together; it is not a per-kidney value. A table that mixes combined and individual organ values can produce a twofold discrepancy without any biological difference. Similarly, an organ value reported as mass should not be relabelled as a volume without stating the conversion and its assumptions.
For a descriptive comparison, organ volume may be divided by body mass. This yields volume per unit body mass; it does not, by itself, establish a relationship that can be used to predict values in another species.
Worked Example: Normalizing Liver Volume for a Descriptive Comparison
Using the hypothetical table, calculate liver volume per kilogram for the human and rat entries. Report the units and explain what the comparison does and does not show.
For the human entry:
For the rat entry:
In this illustrative dataset, the rat liver volume per body mass is higher than the human value: 35.0 mL/kg compared with 21.43 mL/kg. This is a descriptive contrast between two entries. It does not establish a general scaling equation, nor does it justify predicting a liver volume for another animal by extending these two values.
Tissue Composition: Percentages Belong to a Defined Tissue
Tissue-composition entries in the next table are percentages of the named tissue, not percentages of the whole animal. Water, lipid, and protein are shown separately; “other” is the remainder needed to total 100%. The categories are presented as mutually exclusive components in this hypothetical table. In actual parameter work, the component definitions and analytical basis must be checked before comparing percentages across sources or species.
| Species | Tissue | Water (%) | Lipid (%) | Protein (%) | Other (%) |
|---|---|---|---|---|---|
| Human | Liver | 70 | 5 | 18 | 7 |
| Rat | Liver | 70 | 5 | 18 | 7 |
| Mouse | Liver | 69 | 6 | 18 | 7 |
| Dog | Liver | 70 | 5 | 18 | 7 |
| NHP | Liver | — | — | — | — |
| Human | Muscle | 76 | 4 | 19 | 1 |
| Rat | Muscle | 75 | 5 | 18 | 2 |
| Mouse | Muscle | 75 | 5 | 18 | 2 |
| Dog | Muscle | — | — | — | — |
| NHP | Muscle | — | — | — | — |
| Human | Adipose | 15 | 80 | 3 | 2 |
| Rat | Adipose | 16 | 79 | 3 | 2 |
| Mouse | Adipose | — | — | — | — |
| Dog | Adipose | 14 | 81 | 3 | 2 |
| NHP | Adipose | — | — | — | — |
A dash indicates an unavailable entry in this teaching table, not a zero percentage and not proof that the parameter cannot be measured. Keeping the missing cells visible is preferable to silently filling them with a value from another species. A complete row should also be checked for internal consistency: the listed percentages should sum to 100% under the stated category convention.
Worked Example: Checking a Tissue-Composition Row
Check the rat adipose row and calculate its “other” fraction from the water, lipid, and protein entries.
The three listed components sum to \(16\%+79\%+3\%=98\%\). Therefore:
The four entries sum to \(16\%+79\%+3\%+2\%=100\%\), so the row is internally consistent. This arithmetic check can detect a transcription error, but it cannot confirm that the component definitions or underlying measurements are comparable across species.
Organ Blood Flows: Keep Fractions Separate From Absolute Flows
The following table gives selected organ flows as percentages of cardiac output. In this hypothetical convention, hepatic flow means total inflow to the liver, including portal and hepatic arterial inflow; portal inflow is not listed again as a separate organ bed. The “other” row is the remainder needed for the displayed distribution to sum to 100%. These are illustrative fractions, not universal species constants.
| Species | Liver (%) | Kidneys (%) | Brain (%) | Skeletal muscle (%) | Adipose (%) | Other (%) | Total (%) |
|---|---|---|---|---|---|---|---|
| Human | 25 | 20 | 14 | 18 | 5 | 18 | 100 |
| Rat | 18 | 15 | 3 | 25 | 4 | 35 | 100 |
| Mouse | 20 | 10 | 3 | 25 | 3 | 39 | 100 |
| Dog | 25 | 17 | 5 | 20 | 4 | 29 | 100 |
| NHP | 22 | 18 | 8 | 22 | 4 | 26 | 100 |
A fraction of cardiac output and an absolute flow are different quantities. If cardiac output is known on the same physiological basis as the flow fraction, absolute flow is calculated by multiplying cardiac output by that fraction expressed as a proportion. The units of the result are the units of cardiac output.
Worked Example: Converting a Rat Renal Flow Fraction to Absolute Flow
Suppose, for this hypothetical example, rat cardiac output is \(0.200\ \text{L/min}\), and use the table's renal flow fraction of 15%. Calculate the combined kidney flow.
Convert the percentage to a proportion and multiply:
Since \(1\ \text{L}=1000\ \text{mL}\), this is \(30.0\ \text{mL/min}\). It is the combined flow to both kidneys under the stated convention. It is not a flow per kidney, and the calculation does not provide a cardiac output; that value was supplied as an assumption for the example.
Coverage Is Part of the Comparison
A table can appear complete while concealing that some species have fewer tissue-specific entries or less consistent measurement bases. The coverage summary below describes the availability of entries in this hypothetical compilation. “Complete” means that entries are present for the selected rows in this table; “partial” means some selected entries are absent. Neither label is a judgment of data quality or a statement about the precision of the values.
| Species | Organ volumes | Tissue composition | Flow distribution | Visible limitation in this table |
|---|---|---|---|---|
| Human | Complete | Complete | Complete | No missing entries among the selected fields |
| Rat | Complete | Complete | Complete | No missing entries among the selected fields |
| Mouse | Complete | Partial | Complete | Adipose composition is unavailable |
| Dog | Complete | Partial | Complete | Muscle composition is unavailable |
| NHP | Complete | Partial | Complete | Liver, muscle, and adipose composition are unavailable |
Coverage should be recorded at the parameter level where possible, not just as one label for an entire species. A species may have a well-populated organ-volume table but sparse composition data. Also distinguish “not reported,” “not measured,” and “not applicable” when the available information supports that distinction. Do not convert an unknown value to zero, and do not assume that an empty cell can be repaired by copying a human value.
Before comparing entries, check that each one refers to the same organ definition, units, and measurement basis. For example, a flow fraction cannot be directly compared with an absolute flow, and a tissue composition percentage cannot be interpreted as a fraction of whole-body mass. If entries differ in whether they describe combined organs, a particular animal population, or a particular physiological state, those differences belong in the table notes.
A Practical Comparison Workflow
Write down whether the entry is an absolute organ volume, a tissue composition percentage, a flow fraction, or an absolute flow. State which organ or tissue is included.
Retain units with every value. Note whether an organ value is combined or per organ, and whether a flow is a fraction or a volume per time.
Distinguish an available value from a missing value. Add population or physiological-state notes where known, rather than implying that one entry represents every animal of that species.
Check percentage totals and unit conversions. Describe what the displayed entries show without treating a table ratio as a general prediction rule for other sizes or species.
This workflow is useful because a numerical contrast can be correct arithmetically and still be misleading biologically if its entries use different definitions. It also makes the limits of a comparison visible. The later material on allometric scaling addresses how physiological quantities may be related to body size; a simple cross-species table should not be used as a substitute for that analysis.
Common Pitfalls and Limits
- Filling gaps with another species’ value. A missing NHP composition entry is not evidence that human or dog composition is an adequate replacement. Keep the gap visible unless a justified modeling decision is made.
- Mixing absolute values and normalized values. Liver volume in L and liver volume in mL/kg answer different questions. Label each quantity and its units.
- Confusing a percentage with a measurement. A 15% renal flow fraction does not equal 15 mL/min; an absolute flow requires cardiac output and compatible measurement bases.
- Reading a descriptive contrast as a scaling law. A higher value per kilogram in one example does not provide an exponent, a trend across species, or a basis for extrapolation.
- Assuming every table value is equally supported. A populated cell may still have limited coverage, a different definition, or a different physiological context. A coverage label is useful but does not replace those details.
Check Your Understanding
Answer each question using the definitions and illustrative values in this tutorial. The solutions follow the questions.
- A hypothetical mouse liver volume is \(0.00125\ \text{L}\) and body mass is \(0.025\ \text{kg}\). Calculate liver volume per kilogram in mL/kg.
- In the human muscle row, what percentage is “other” if water is 76%, lipid is 4%, and protein is 19%?
- If hypothetical dog cardiac output is \(2.00\ \text{L/min}\), use the table's kidney flow fraction to calculate combined kidney flow in mL/min.
- What does the dash in the NHP liver-composition row mean, and what does it not mean?
- Why should the rat and human liver-volume-per-kilogram values not be used alone to predict an organ volume for a third species?
Solutions. (1) Convert to mL and divide by body mass: \(0.00125\ \text{L}\times1000=1.25\ \text{mL}\); \(1.25/0.025=50.0\ \text{mL/kg}\). (2) \(100\%-76\%-4\%-19\%=1\%\). (3) The dog kidney fraction is 17%, so \(2.00\ \text{L/min}\times0.17=0.340\ \text{L/min}=340\ \text{mL/min}\). (4) It means the entry is unavailable in this table; it does not mean zero composition or that the parameter is impossible to measure. (5) Those two values are a descriptive comparison, not a fitted relationship across species. Predicting another species requires an explicitly justified method, not direct extrapolation from two entries.