1. What Makes a PBPK Model Physiological?
Physiologically based pharmacokinetic (PBPK) models describe drug disposition using information about both the drug and the biological system in which the drug moves. Rather than representing the body only as abstract kinetic compartments, a whole-body PBPK model represents organs and tissues as model components connected by physiological blood flows.
FDA describes PBPK modeling as an approach that integrates drug-specific information with system-specific physiological information to mechanistically describe pharmacokinetic and pharmacodynamic behavior.
A whole-body PBPK model represents organs and tissues as connected physiological systems. Blood flow provides the principal transport pathway between many compartments.
2. System Parameters vs. Drug Parameters
A central concept in PBPK modeling is the separation between system-specific information and drug-specific information.
| System-specific information | Drug-specific information |
|---|---|
| Organ volumes | Molecular weight |
| Organ and tissue blood flows | LogP / lipophilicity |
| Cardiac output | pKa and ionization |
| Hematocrit | Plasma protein binding |
| Enzyme and transporter abundance | Membrane permeability |
| Plasma protein concentrations | Tissue partitioning properties |
| Gastrointestinal physiology | Solubility and dissolution properties |
| Renal function | Intrinsic metabolic or transporter clearances |
This separation is one of the major reasons PBPK models can be useful for extrapolation. The same drug-specific information can potentially be evaluated under different physiological scenarios—for example, different ages, organ functions, or body compositions—provided the model appropriately represents those physiological changes.
System parameters are therefore not merely nuisance inputs. They define the biological environment in which the drug is assumed to behave.
3. How Are Organs Represented?
In a whole-body PBPK model, organs and tissues are commonly represented as compartments connected through blood circulation. Each organ may have its own volume, blood flow, tissue composition, drug concentration, and processes for uptake, metabolism, or excretion.
A simple organ mass-balance equation can be written conceptually as:
where \(A_i\) is the amount of drug in organ \(i\), \(Q_i\) is its blood flow, \(C_{in,i}\) and \(C_{out,i}\) represent incoming and outgoing concentrations, and \(R_i\) represents net drug removal or other irreversible processes within the organ.
The exact equations depend on the chosen PBPK structure. For example, a perfusion-limited model and a permeability-limited model describe tissue exchange differently.
4. Blood Flow Is the Transport Network
Blood flow is one of the defining physiological features of a whole-body PBPK model. Cardiac output determines the overall amount of blood circulating through the systemic system, while individual organs receive fractions of that flow.
For a simplified organ:
where \(Q_i\) is organ blood flow, \(f_i\) is the fraction of cardiac output directed to the organ, and \(Q_{CO}\) is cardiac output.
Across the organs represented in a model, the flows are constrained by the circulation:
The exact treatment depends on how pulmonary, systemic, portal, and other circulatory pathways are represented.
| Physiological quantity | Role in PBPK modeling |
|---|---|
| Cardiac output | Determines the overall systemic blood-flow scale |
| Organ blood flow | Controls delivery of drug to individual tissues in flow-limited models |
| Portal flow | Provides a specific pathway connecting gastrointestinal organs to the liver |
| Pulmonary flow | Connects venous return and arterial circulation through the lungs |
Changes in physiology that alter cardiac output or organ perfusion can therefore change the predicted distribution of drug even if the drug itself has not changed.
5. Organ and Tissue Volumes
Organ volume determines how much drug can be represented within a tissue compartment and contributes to the relationship between amount and concentration.
At its simplest:
where \(C_i\) is tissue concentration, \(A_i\) is the amount of drug in the tissue, and \(V_i\) is tissue volume.
Unlike a classical compartment model, PBPK models can assign different volumes to different organs. Liver, kidney, muscle, adipose tissue, brain, skin, and other tissues therefore need not share a common apparent volume.
Physiological changes in body size or composition can consequently affect model predictions. For example, changes in adipose mass can influence the representation of a lipophilic drug, while changes in organ size may alter the concentration associated with a given amount of drug.
6. Tissue Partitioning
Drug concentrations are not necessarily the same in plasma and tissues. PBPK models therefore need a mechanism for representing how a drug distributes between blood and individual tissues.
A commonly used quantity is the tissue-to-plasma partition coefficient, often written \(K_p\):
The exact definition and implementation depend on the model structure and concentration basis.
Partitioning can depend on physicochemical properties such as lipophilicity and ionization as well as tissue composition. Differences in water, lipid, protein, and other tissue components can therefore influence how a compound distributes throughout the body.
7. Perfusion-Limited vs. Permeability-Limited Distribution
One important modeling choice is how drug moves between blood and tissue.
Perfusion-limited models
In a simplified perfusion-limited representation, tissue uptake is assumed to be sufficiently rapid that blood flow is the dominant limitation. Tissue concentration is therefore closely connected to the concentration delivered by blood and the tissue partition relationship.
Permeability-limited models
In a permeability-limited model, movement across a physiological barrier is explicitly represented. The rate of transfer can depend on permeability, surface area, membrane transport, or other processes rather than being determined by blood flow alone.
| Feature | Perfusion-limited | Permeability-limited |
|---|---|---|
| Main limitation | Blood delivery | Exchange across a barrier |
| Typical representation | Rapid tissue equilibration assumption | Explicit uptake and/or efflux process |
| Complexity | Lower | Higher |
| Potential use | Many systemic tissues when rapid exchange is a reasonable approximation | Barriers or tissues where transport is mechanistically important |
The appropriate representation depends on the scientific question and the drug's properties. More mechanistic detail is useful only when it adds information that can be supported by data or established biological knowledge.
8. The Liver: Blood Flow, Enzymes, and Metabolism
The liver is often a major site of drug metabolism and is therefore a central physiological component of PBPK models.
A PBPK liver model may incorporate several distinct pieces of information:
- Hepatic blood flow determines delivery of drug to the liver.
- Intrinsic metabolic clearance describes the capacity of metabolic pathways to eliminate drug independently of overall organ blood flow.
- Enzyme abundance or activity can provide a physiological basis for scaling metabolic capacity.
- Plasma protein binding can affect the fraction of drug available for hepatic uptake and metabolism.
- Transporters may contribute to hepatic uptake or efflux.
- Liver volume and composition determine the physical representation of the organ.
For a simplified well-stirred hepatic model, hepatic clearance can be represented conceptually as:
where \(Q_H\) is hepatic blood flow, \(f_u\) is the unbound fraction in blood or plasma according to the model convention, and \(CL_{int}\) is intrinsic hepatic clearance.
This equation illustrates why hepatic physiology matters. Clearance can depend on both how much drug reaches the liver and the liver's intrinsic capacity to eliminate it.
9. The Kidney: Filtration, Secretion, and Reabsorption
The kidneys provide another major physiological pathway for drug elimination.
A mechanistic renal model can distinguish several processes:
| Process | Physiological concept | Potential model representation |
|---|---|---|
| Glomerular filtration | Filtration of unbound drug from plasma | Related to glomerular filtration rate and unbound concentration |
| Active secretion | Transport-mediated movement into renal tubular fluid | Transporter-mediated clearance |
| Reabsorption | Movement from tubular fluid back into systemic circulation | Passive or active reabsorption process |
For a drug eliminated predominantly by filtration, a simplified filtration relationship is:
This provides a direct example of how a physiological parameter can influence predicted drug exposure. If renal function changes, the model can incorporate an altered GFR or other renal parameters to evaluate the resulting change in elimination.
10. The Gastrointestinal System
For oral administration, the gastrointestinal tract becomes an important physiological system in the model.
Unlike a simple first-order absorption model, a mechanistic PBPK absorption model can represent physiological processes such as:
- Gastric emptying.
- Intestinal transit.
- Regional intestinal pH.
- Fluid volume.
- Drug dissolution.
- Solubility and precipitation.
- Intestinal permeability.
- Intestinal metabolism.
- Transporter activity.
- Food-related changes in gastrointestinal physiology.
A simplified conceptual sequence is:
This is one reason PBPK models can be useful for investigating formulation and biopharmaceutic questions. The model can connect drug product characteristics with physiological processes that occur before systemic exposure is observed.
11. Brain, Adipose, Muscle, Skin, and Other Tissues
A whole-body PBPK model does not have to treat every tissue identically. Different organs can have different volumes, blood flows, tissue composition, partition coefficients, and permeability characteristics.
| Tissue | Physiological feature that may matter |
|---|---|
| Brain | Blood-brain barrier, cerebral blood flow, tissue composition |
| Adipose | Lipid content, tissue volume, blood flow, lipophilic drug partitioning |
| Muscle | Large tissue mass and physiologically variable blood flow |
| Skin | Blood flow, tissue composition, and relevance for dermal exposure |
| Heart | Cardiac blood flow and tissue distribution |
| Bone | Tissue composition and relatively specialized distribution behavior |
The point is not that every PBPK model must include all these tissues at maximum mechanistic detail. Rather, the model structure can be adapted to the scientific question.
12. Blood, Plasma, and Protein Binding
Blood is more than a transport medium. PBPK models may need to distinguish plasma from blood and account for how drug distributes between plasma and blood cells.
One commonly encountered quantity is the blood-to-plasma concentration ratio:
Protein binding is also important because the unbound fraction can influence tissue distribution, hepatic metabolism, renal filtration, and transporter-mediated processes.
For example, if \(f_u\) represents the unbound fraction:
The precise implementation depends on the PBPK platform and model. The important conceptual point is that binding and blood/plasma partitioning can connect measurable physicochemical properties to physiological transport and elimination processes.
13. Physiology Is Not the Same for Every Person
One of the most important features of physiological modeling is that physiological parameters can vary across populations.
| Population factor | Potential physiological changes | Potential PK consequence |
|---|---|---|
| Age | Organ size, blood flow, enzyme expression, renal function | Changes in distribution and clearance |
| Body weight | Organ size and tissue mass | Changes in distribution and physiological capacity |
| Obesity | Altered adipose mass and body composition | Potentially altered distribution and physiology |
| Renal impairment | Reduced renal function | Reduced renal elimination for susceptible drugs |
| Hepatic impairment | Altered hepatic function and physiology | Potential changes in metabolism and exposure |
| Pregnancy | Changes in plasma volume, organ function, cardiac output, and other physiology | Potential changes in distribution and clearance |
This is one of the major conceptual differences between a fixed compartmental model and a physiological systems model. Instead of changing a single fitted clearance parameter without specifying why, PBPK modeling can represent changes in the underlying physiological system when appropriate information is available.
14. Mass Balance Connects Physiology to Mathematics
Although PBPK models can contain many organs and physiological inputs, their mathematical foundation is often straightforward: mass balance.
For an organ \(i\), the general idea is:
In differential-equation form:
Blood flows determine many of the input and output terms. Organ volumes convert amounts to concentrations. Partition coefficients describe distribution between compartments. Enzymes and transporters can determine metabolic or transport rates.
Thus, a PBPK model is not simply a collection of physiological numbers. The parameters are connected through equations that enforce conservation of drug mass and represent physiological transport and disposition processes.
15. Worked Example: Why Organ Blood Flow Matters
Consider a simplified organ receiving a blood flow of 1.0 L/min. Suppose the incoming blood concentration is 10 mg/L and the outgoing concentration is 7 mg/L.
Step 1: Drug entering the organ
Step 2: Drug leaving the organ
Step 3: Net removal from blood
Under this simplified steady-flow interpretation, the organ removes 3 mg/min from the blood passing through it.
The example is intentionally simple. In a real PBPK model, the relationship between incoming and outgoing concentration can depend on tissue partitioning, permeability, binding, metabolism, transporters, and the dynamic amount of drug within the organ.
16. What Happens When Physiology Changes?
A major strength of PBPK modeling is the ability to modify system parameters to represent a different physiological scenario.
For example, consider a drug whose elimination depends substantially on renal function. A conceptual PBPK simulation can compare:
| Scenario | System change | Expected model consequence |
|---|---|---|
| Reference adult | Reference renal physiology | Baseline exposure |
| Mild renal impairment | Reduced renal function | Potentially reduced renal elimination |
| Moderate renal impairment | Further reduction in renal function | Potentially greater exposure if renal clearance is important |
| Severe renal impairment | Markedly reduced renal function | Potentially substantial change in exposure depending on elimination pathways |
The model should not simply assume that every drug responds identically to the same physiological change. The predicted effect depends on the fraction of total elimination attributable to the affected pathway and on how that pathway is represented mechanistically.
17. Why Physiological Systems Enable Extrapolation
Because PBPK models explicitly represent physiological systems, they can be used to investigate scenarios in which the system changes while the drug itself remains unchanged.
Examples include:
- Different age groups.
- Pediatric populations.
- Older adults.
- Renal impairment.
- Hepatic impairment.
- Pregnancy.
- Obesity and altered body composition.
- Genetic differences affecting enzyme or transporter activity.
- Drug-drug interactions involving enzyme inhibition or induction.
- Changes in gastrointestinal physiology or formulation conditions.
FDA notes that PBPK modeling can be used to investigate intrinsic and extrinsic factors affecting exposure, including age, organ dysfunction, disease status, genetics, concomitant medications, and food intake.
These applications illustrate a central PBPK concept:
Changing the physiological system can therefore change the predicted PK even when the drug-specific parameters remain unchanged.
18. How Much Physiological Detail Is Necessary?
A PBPK model can range from a relatively compact representation to a highly detailed whole-body model. More detail is not automatically better.
| Level of representation | Example | Potential purpose |
|---|---|---|
| Minimal PBPK | Several lumped tissue groups | Capture key distribution processes with fewer compartments |
| Organ-level PBPK | Liver, kidney, muscle, adipose, brain, etc. | Represent organ-specific physiology |
| Detailed organ models | Multiple subregions within an organ | Represent regional transport or metabolism |
| Suborgan/cellular models | Interstitial and intracellular spaces | Address questions requiring finer mechanistic detail |
The appropriate level of complexity depends on the intended use, the available evidence, and whether the additional parameters can be identified or justified.
19. How Do We Know the Physiological System Is Adequate?
A PBPK model should not be accepted simply because it contains physiologically realistic inputs. The model must also produce predictions that are appropriate for its intended use.
Evaluation can include:
- Checking physiological inputs. Are organ volumes, blood flows, enzyme abundances, and other system parameters appropriate for the modeled population?
- Checking drug inputs. Are physicochemical, binding, permeability, metabolism, and transporter parameters supported by evidence?
- Comparing predictions with observed PK. Do simulated concentration-time profiles adequately describe relevant clinical observations?
- Testing across scenarios. Does the model behave plausibly when physiological or drug conditions change?
- Assessing sensitivity. Which physiological and drug parameters have the greatest influence on the prediction?
- Documenting assumptions. Are the structural choices and sources of input parameters transparent?
FDA's PBPK guidance emphasizes clear documentation of the model, its inputs, methods, results, discussion, and supporting information when PBPK analyses are submitted for regulatory purposes.
20. Which Physiological Parameters Matter Most?
Not every physiological parameter contributes equally to a particular prediction. Sensitivity analysis can help determine which inputs have the greatest influence on model outputs.
For example, depending on the drug and endpoint, model predictions may be particularly sensitive to:
- Hepatic blood flow.
- Renal filtration capacity.
- Intrinsic metabolic clearance.
- Fraction unbound.
- Tissue partition coefficients.
- Organ volumes.
- Enzyme abundance.
- Transporter activity.
- Gastrointestinal transit or pH.
- Membrane permeability.
A conceptual local sensitivity measure can be written as:
where \(Y\) is a model output and \(p\) is an input parameter.
Sensitivity analysis helps distinguish parameters that are important to a prediction from parameters that have little practical influence under the scenario being studied.
21. Physiological Parameters Are Not Just Fitted Coefficients
In a conventional compartmental model, a parameter such as clearance may be estimated directly from concentration-time data. In PBPK modeling, many system parameters are instead supplied from independent physiological or experimental information.
This distinction creates an important conceptual difference:
| Traditional PK parameter | PBPK system representation |
|---|---|
| Clearance estimated from observed PK | Organ-specific elimination mechanisms represented explicitly |
| Volume of distribution estimated as a lumped quantity | Organ volumes and tissue partitioning represented individually |
| Absorption rate constant | GI physiology, dissolution, permeability, transit, and related processes |
| Single patient clearance | Physiological determinants of clearance represented through mechanisms |
This does not mean PBPK models contain no fitted parameters. They may include estimated or calibrated parameters, and some physiological or drug-specific quantities may be uncertain. Rather, the model attempts to anchor important components in independently informed biological quantities.
22. What Physiological Systems in PBPK Models Do Not Guarantee
Adding physiological detail does not automatically make a model correct.
- Physiological realism is not sufficient by itself. The drug-specific mechanisms must also be represented appropriately.
- Reference physiology may not represent every population. Special populations can require specific physiological assumptions.
- Input uncertainty propagates into predictions. Uncertain organ flows, enzyme abundance, partition coefficients, or other parameters can affect the final result.
- Not every biological mechanism is known. A PBPK model remains a simplification of a complex biological system.
- More compartments create more assumptions. Additional structure can introduce additional uncertainty and computational requirements.
- Prediction outside the validated domain requires caution. A model evaluated in one population or scenario may not automatically be reliable in another.
23. A Practical Workflow for Building the Physiological System
- Define the intended use. Decide what clinical or development question the model must answer.
- Define the population. Specify species, age range, body size, sex where relevant, and physiological condition.
- Select the physiological structure. Determine which organs, tissues, and pathways need explicit representation.
- Assign organ volumes and blood flows. Use appropriate physiological reference information.
- Define tissue distribution properties. Specify partitioning and, when needed, permeability or transporter processes.
- Represent elimination pathways. Incorporate hepatic, renal, intestinal, or other relevant mechanisms.
- Represent special physiology. Modify system parameters when modeling pregnancy, pediatrics, organ impairment, obesity, or another special population.
- Connect drug-specific information. Combine physicochemical and ADME information with the physiological system.
- Simulate and evaluate. Compare model predictions with available observations.
- Perform sensitivity and uncertainty analysis. Identify which physiological assumptions drive the prediction.
- Document the model. Clearly describe sources, assumptions, equations, parameters, and intended use.
24. From Physiology to a PBPK Prediction
Consider a hypothetical orally administered drug.
The model begins with a drug product entering the gastrointestinal tract. GI physiology determines dissolution, transit, and absorption. Absorbed drug enters the portal circulation and reaches the liver. Hepatic blood flow and intrinsic metabolic capacity influence hepatic elimination. Drug reaching systemic circulation is distributed according to organ blood flows, tissue volumes, permeability, and partitioning. Renal physiology contributes additional elimination.
At every stage, physiological parameters determine how quickly and how extensively drug moves through the system.
The resulting model can produce predicted concentration-time profiles in plasma and, depending on model structure, in individual organs and tissues.
25. Key Takeaways
- PBPK models integrate drug-specific information with system-specific physiological information.
- Whole-body PBPK models commonly represent organs and tissues as compartments connected through physiological blood flows.
- Organ volume determines the physical scale of a tissue compartment and contributes to the relationship between drug amount and concentration.
- Blood flow provides a major transport mechanism connecting organs throughout the body.
- Tissue partitioning describes how drug distributes between plasma or blood and individual tissues.
- Perfusion-limited and permeability-limited models make different assumptions about what controls tissue exchange.
- The liver can incorporate blood flow, intrinsic metabolic clearance, enzymes, transporters, binding, and other physiological mechanisms.
- The kidney can represent filtration, secretion, and reabsorption processes.
- GI physiology can influence oral absorption through dissolution, pH, transit, permeability, metabolism, transporters, and related processes.
- Physiological parameters vary across populations, making PBPK models useful for investigating special populations when the relevant biology is adequately represented.
- Mass-balance differential equations connect physiological parameters to predicted drug concentrations.
- More physiological detail is not automatically better; model complexity should be justified by the intended use and available evidence.
- Physiological realism does not guarantee predictive accuracy. System inputs, drug-specific inputs, structural assumptions, and model evaluation all matter.
- Sensitivity and uncertainty analysis can identify which physiological assumptions have the greatest influence on a prediction.
- The ultimate value of a physiological PBPK system is its ability to connect changes in biology to quantitative predictions of drug disposition.
Where to Go Next
After understanding the physiological system, the next step is to examine how drug-specific properties are connected to that system.
A natural progression is to study tissue-to-plasma partition coefficients, followed by perfusion-limited and permeability-limited distribution, hepatic clearance models, renal clearance models, gastrointestinal absorption, and the use of in vitro data for in vitro–in vivo extrapolation (IVIVE).
These concepts provide the mechanistic bridge between a PBPK model's physiological framework and the physicochemical and ADME properties of an individual drug.
References
- U.S. Food and Drug Administration. Physiologically Based Pharmacokinetic Analyses — Format and Content: Guidance for Industry. 2018. FDA guidance.
- U.S. Food and Drug Administration. Program of Physiologically Based Pharmacokinetic and Pharmacodynamic Modeling (PBPK Program). FDA PBPK Program.
- Sager JE, Yu J, Ragueneau-Majlessi I, Isoherranen N. Physiologically Based Pharmacokinetic (PBPK) Modeling and Simulation Approaches: A Systematic Review of Published Models, Applications, and Model Verification. Drug Metabolism and Disposition. 2015;43(11):1823–1837. PubMed Central.
- Lin Z. Advance in physiologically based pharmacokinetic modelling: from the organ level to suborgan level based on experimental data. The Journal of Physiology. 2017;595(24):7265–7266. PubMed Central.
- Aarons L. Physiologically based pharmacokinetic modelling: a sound mechanistic basis is needed. British Journal of Clinical Pharmacology. 2005;60(6):581–583. PubMed Central.
- U.S. Food and Drug Administration. The Use of Physiologically Based Pharmacokinetic Analyses — Biopharmaceutics Applications for Oral Drug Product Development, Manufacturing Changes, and Controls. 2020. FDA guidance.