PBPK Modeling and Simulation Service
Translate in vitro ADME, physicochemical, preclinical, and clinical evidence into mechanistic predictions of exposure across organs, species, dosing regimens, and patient populations.
Mechanistic PK Predictions Beyond a Single Concentration–Time Curve
A physiologically based pharmacokinetic model connects drug-specific properties with anatomically and physiologically realistic compartments. By representing absorption, tissue distribution, metabolism, transport, and excretion as linked processes, PBPK modeling helps a development team examine why exposure changes—not only whether it changes.
As part of our In Silico ADMET Prediction Service, CD ComputaBio integrates molecular descriptors, experimental ADME data, formulation information, tissue physiology, enzyme and transporter pathways, and available PK observations into fit-for-purpose models. The resulting evidence can support candidate comparison, first-in-human translation, interaction risk assessment, dose and regimen selection, formulation strategy, tissue-exposure evaluation, and special-population planning.
Each project begins with an intended decision and a defined context of use. Model complexity, qualification criteria, sensitivity analysis, reporting depth, and post-delivery support are then matched to that purpose. Incomplete inputs are not hidden: their impact is evaluated through scenario ranges and uncertainty analysis, with targeted experiments recommended where new data would materially improve confidence.
Typical Questions We Help Address
- What human exposure may be expected from in vitro and preclinical evidence?
- Which dose and regimen are most likely to reach a target systemic or tissue exposure?
- Could CYP enzymes, transporters, induction, or time-dependent inhibition create clinically relevant DDI risk?
- How might food, formulation, organ impairment, age, pregnancy, obesity, or disease alter PK?
- Which uncertain parameters should be measured before the next development decision?
- What model evidence and documentation are needed for an internal review or regulatory interaction?
PBPK Capabilities Aligned with Drug Development Decisions
Modules can be commissioned independently or combined into a model lifecycle that evolves as new data become available.
Animal-to-Human Translation
Integrate species physiology, clearance pathways, protein binding, permeability, tissue partitioning, and observed animal PK to project plausible human concentration–time profiles and exposure ranges.
First-in-Human Dose Support
Evaluate starting-dose and escalation scenarios against projected exposure, relevant safety margins, pharmacologic targets, and uncertainty. Outputs are decision support and do not replace sponsor medical or regulatory judgment.
Drug–Drug Interaction Simulation
Assess victim and perpetrator risk involving CYPs, UGTs, transporters, induction, reversible or time-dependent inhibition, and active metabolites. Inputs may connect with our CYP Inhibition and Metabolism Prediction Service.
Oral Absorption and PBBM
Connect dissolution, solubility, precipitation, intestinal permeability, first-pass metabolism, particle properties, and formulation variables with oral exposure. Early input gaps may be investigated through Solubility and Permeability Prediction.
Special-Population Prediction
Explore pediatric, geriatric, renal impairment, hepatic impairment, pregnancy, obesity, or disease-related physiology when the intended use and evidence support the extension. Population assumptions and extrapolation limits remain visible.
Tissue and Target-Site Exposure
Estimate organ-specific concentrations and partitioning for efficacy, delivery-route, local exposure, or safety-margin questions, with relevant outputs linked to Drug Tissue Distribution Prediction.
Biologics and Complex Modalities
Develop fit-for-purpose structures for antibodies, proteins, peptides, conjugates, or other modalities when target-mediated disposition, FcRn recycling, tissue convection, binding, catabolism, or payload release must be represented.
Virtual Clinical Trials
Generate virtual-population exposure distributions and test covariates, dose regimens, sampling schedules, inclusion criteria, and trial scenarios. Variability is separated from structural and parameter uncertainty wherever the data permit.
Model Qualification and Reporting
Document parameter provenance, calibration, independent verification, diagnostics, sensitivity analysis, uncertainty, applicability, limitations, software versions, and the relationship between model performance and the intended decision.
From Development Question to Decision-Ready PBPK Evidence
The workflow keeps data audit, model construction, verification, simulation, and interpretation distinct so that conclusions can be traced back to evidence and assumptions.
| Stage | Key Activities | Decision Output |
|---|---|---|
| 1. Context and Endpoint Scoping | Define the compound or modality, route, target population, development or regulatory question, exposure endpoints, and proposed acceptance criteria. | Fit-for-purpose analysis plan and context of use. |
| 2. Data and Metadata Audit | Review physicochemical, in vitro ADME, formulation, transporter, DDI, preclinical, and clinical datasets; reconcile units, study conditions, missing metadata, and potential bias. | Data-suitability assessment, critical gaps, and parameter-source plan. |
| 3. Model Construction | Select organ compartments and mechanistic processes, parameterize physiology and drug properties, define variability, and record assumptions and software settings. | Versioned structural model and parameter table. |
| 4. Calibration and Verification | Use appropriate datasets for calibration, preserve independent data for verification where possible, compare exposure metrics and profiles, and inspect residual or diagnostic behavior. | Qualified model for the specified range and intended application. |
| 5. Scenario and Uncertainty Analysis | Simulate doses, formulations, DDI mechanisms, populations, or tissue exposure; perform local or global sensitivity analyses and evaluate influential assumptions. | Prediction intervals, scenario comparisons, and prioritized data gaps. |
| 6. Interpretation and Reporting | Translate outputs into development implications, state limitations, document model files and versions, and prepare technical or regulatory-oriented reporting. | Decision package, recommendations, and follow-up plan. |
Regulatory-Oriented PBPK Modeling and Documentation
For programs preparing for formal review, the analysis can be structured around the target jurisdiction, intended context of use, development question, and maturity of available evidence.
Submission Strategy and Context of Use
We work with the sponsor to define the question the model is intended to answer, the population and exposure endpoints, the jurisdiction or review setting, and the evidence required to support the proposed use. Data gaps and qualification criteria are identified before model construction wherever possible.
Model Qualification Package
The package can include model structure, assumptions, parameter values and sources, calibration strategy, verification datasets, observed-versus-predicted results, diagnostics, sensitivity analysis, uncertainty evaluation, limitations, and a clear statement of the model's domain of application.
Submission-Ready Documentation
Depending on scope, deliverables may include a PBPK study report, methods and assumptions, parameter provenance tables, verification results, simulation summaries, and figures or tables suitable for incorporation into sponsor-controlled regulatory documents.
Regulatory Question Support
Optional support can address consolidated sponsor, consultant, or reviewer questions through technical explanations, additional scenarios, parameter-source clarification, sensitivity analyses, revised figures, and draft modeling responses.
Expert Review and Signed Technical Reports
Each final report is subject to scientific and technical quality review. When included in the agreed scope, the report can be reviewed and signed by an appropriately qualified PBPK, pharmacokinetics, pharmacology, or toxicology expert. The reviewer's role, relevant qualification, review date, report version, and scope of review can be identified on a signature page.
Toxicology expert review is particularly relevant when a project involves toxicokinetic interpretation, organ exposure, safety margins, or toxicology-related regulatory questions. The exact reviewer credentials and availability are confirmed during project scoping; the page does not imply that every report carries a statutory certification or that a technical signature constitutes regulatory approval.
Data We Can Integrate
A project can begin with incomplete evidence. We first determine which inputs are essential, which can be estimated with defensible uncertainty, and which missing values materially limit the intended decision.
| Data Category | Examples | Model Contribution |
|---|---|---|
| Molecular and Physicochemical | Molecular weight, pKa, logP/logD, solubility, permeability, charge state | Supports absorption, membrane partitioning, distribution, and route-specific behavior. |
| In Vitro ADME | Microsomal or hepatocyte stability, plasma protein binding, blood-to-plasma ratio, CYP phenotyping | Informs clearance, free exposure, pathway contribution, and IVIVE. |
| Transporter and DDI | Substrate, inhibition, induction, Ki/IC50, kinact/KI, active-metabolite data | Enables mechanistic victim and perpetrator simulations and pathway attribution. |
| Preclinical PK | IV and oral profiles, dose, formulation, bioavailability, mass balance, tissue data | Supports calibration, species verification, process identification, and human translation. |
| Clinical PK | Single- and multiple-dose PK, DDI, food effect, organ impairment, population covariates | Supports human verification, refinement, qualification, and prospective scenarios. |
| Formulation and Product | Dose form, dissolution, particle size, release profile, precipitation, excipients | Enables oral absorption and PBBM questions linked to product performance. |
Transparent Models, Traceable Assumptions, Actionable Conclusions
Final deliverables are tailored to the intended use, model maturity, software environment, data rights, and agreed handover requirements.
Model Files and Parameter Tables
Structured model assets, parameter values, units, sources, assumptions, physiological population settings, and software/version records. Editable file delivery and commercial software requirements are confirmed in the proposal.
Verification and Diagnostic Results
Observed-versus-predicted plots, exposure-metric comparisons, residual or diagnostic assessments, qualification criteria, and a discussion of performance in relation to the intended application.
Scenario and Virtual-Population Outputs
Concentration–time profiles, exposure distributions, dose and regimen comparisons, DDI ratios, organ concentrations, and other endpoint summaries selected during scoping.
Sensitivity and Uncertainty Analysis
Identification of influential parameters, plausible prediction ranges, structural assumptions, extrapolation limits, and experiments most likely to improve confidence.
Technical Report and Executive Interpretation
Methods, parameter provenance, results, limitations, applicability, decision implications, and recommended next steps, with optional regulatory-oriented structure.
Version and Review Record
Defined model/report versions, change history, reviewer roles, approval or signature page when included, and a traceable record of post-review revisions.
Support Beyond Final Delivery
A PBPK model is often most valuable as a maintained program asset rather than a one-time report. Support terms are defined before project start so expectations remain clear.
Technical Walkthrough
A closeout meeting can explain model structure, major assumptions, diagnostics, uncertainty, appropriate interpretation, and practical use of the delivered outputs.
Defined Revision Support
Consolidated report, figure, or presentation revisions can be included. The number of revision rounds, comment process, response time, and boundary between corrections and new analyses are specified in the proposal.
Model Update and Lifecycle Support
The model can be updated as new in vitro, formulation, preclinical, or clinical evidence becomes available. Version changes and their consequences for earlier conclusions are documented.
Reviewer and Regulatory Q&A
Optional support covers technical questions, additional simulations, reviewer comments, parameter-source explanations, and model or document updates after the initial delivery.
Support periods, included revision rounds, meetings, new-data updates, additional simulations, regulatory-response work, model-file handover, and software-license responsibilities are confirmed for each project.
Mechanistic Structure Must Be Matched by Verification
PBPK models organize physiology, drug properties, and biological processes into linked compartments, but anatomical detail alone does not establish predictive reliability. A model must be evaluated against data relevant to the intended use. Where possible, calibration and verification datasets are separated, performance is assessed for relevant concentration–time profiles and exposure metrics, and uncertainty is propagated into decision scenarios.
The open-access study below illustrates a multi-compartment model used across species and subsequently assessed with observed PK data. Its service implication is broader than the specific compound: compartment selection, parameter provenance, species assumptions, elimination pathways, and verification evidence should remain visible rather than being collapsed into a single fitted curve.
Select the Modeling Depth That Matches Your Decision
Final scope is customized; these engagement levels help teams distinguish exploratory modeling from a fully documented regulatory-support program.
Exploratory PBPK Assessment
Designed for early programs or incomplete data. Includes data audit, preliminary structure, scenario ranges, sensitivity analysis, major assumptions, and a prioritized plan for filling high-impact gaps.
Decision-Support PBPK Program
Includes model construction, calibration and verification, agreed dose/DDI/formulation/population scenarios, uncertainty evaluation, model assets, and a technical decision report.
Regulatory-Support Package
Adds regulatory-oriented qualification and reporting, enhanced provenance and version records, expert review or signed reporting when agreed, and defined support for technical questions or additional simulations.
PBPK Modeling Project FAQ
Related ADMET and Pharmacokinetic Services
PBPK is strongest when upstream property, metabolism, distribution, and safety evidence is aligned with the intended simulation.
Scientific References and Regulatory Guidance
- Tan Z, Zhang Y, Wang C, Sun L. Physiologically Based Pharmacokinetic Modeling of Cefadroxil in Mouse, Rat, and Human to Predict Concentration–Time Profile at Infected Tissue. Frontiers in Pharmacology. 2021;12:692741. https://doi.org/10.3389/fphar.2021.692741. Distributed under the Creative Commons Attribution License (CC BY).
- European Medicines Agency. Guideline on the reporting of physiologically based pharmacokinetic (PBPK) modelling and simulation. EMA scientific guideline.
- U.S. Food and Drug Administration. Physiologically Based Pharmacokinetic Analyses — Format and Content: Guidance for Industry. Regulatory expectations should be interpreted for the applicable jurisdiction and current submission context.
Request a PBPK Project Assessment
Share your compound or modality, development stage, intended decision, administration route, target species or population, available ADME/PK data, formulation information, target jurisdiction if applicable, desired deliverables, and timeline. Not all inputs are required for an initial discussion—we can begin with a feasibility and data-gap assessment.
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