01 / TRANSLATION
Animal-to-Human PK Extrapolation
Integrate species physiology, clearance pathways, protein binding, permeability, and tissue partitioning to project human concentration–time profiles and exposure ranges.
Model-Informed Drug Development
PBPK Modeling and Simulation Service
Translate in vitro ADME, physicochemical, preclinical, and clinical data into mechanistic predictions of drug exposure across organs, species, dosing regimens, and patient populations.
From Parameters to Decisions
Mechanistic PK Predictions Beyond a Single Concentration–Time Curve
A physiologically based pharmacokinetic model connects drug-specific properties with anatomically and physiologically realistic compartments. This allows project teams to investigate why exposure changes—not only whether it changes.
CD ComputaBio integrates molecular descriptors, experimental ADME data, formulation information, tissue characteristics, enzyme and transporter pathways, and available PK observations into fit-for-purpose PBPK models. The resulting framework can support candidate comparison, human translation, interaction risk assessment, formulation strategy, dose selection, and special-population planning.
Each project is structured around a specific development question. We avoid unnecessary model complexity and focus model qualification on the exposure metrics and decisions that matter to your program.
Service Coverage
PBPK Capabilities Aligned with Drug Development Decisions
Flexible project modules can be used independently or combined into an integrated modeling program.
02 / DOSE
First-in-Human Dose Support
Evaluate plausible starting-dose and escalation scenarios against projected systemic or tissue exposure, therapeutic windows, and parameter uncertainty.
03 / INTERACTIONS
Drug–Drug Interaction Simulation
Assess victim and perpetrator risks involving CYP enzymes, UGT pathways, transporters, time-dependent inhibition, induction, and active metabolites.
04 / ABSORPTION
Oral Absorption and PBBM
Connect dissolution, solubility, precipitation, intestinal permeability, first-pass metabolism, particle properties, and formulation variables with oral exposure.
05 / POPULATIONS
Special-Population Prediction
Explore pediatric, geriatric, renal impairment, hepatic impairment, pregnancy, obesity, or disease-specific physiological changes when suitable data are available.
06 / DISTRIBUTION
Tissue and Target-Site Exposure
Estimate organ-specific concentrations and tissue partitioning to support efficacy, safety, delivery-route, and local-exposure questions.
07 / BIOLOGICS
Biologics and Complex Modalities
Develop fit-for-purpose models for antibodies, peptides, proteins, conjugates, or other modalities with target-mediated disposition or tissue-specific processes.
08 / TRIALS
Virtual Clinical Trial Simulation
Generate virtual-population exposure distributions and evaluate covariates, variability, dose regimens, sampling schedules, and trial scenarios.
09 / QUALIFICATION
Model Verification and Reporting
Document model assumptions, parameter sources, calibration, verification datasets, sensitivity analysis, uncertainty, limitations, and decision relevance.
Project Workflow
From Development Question to Decision-Ready PBPK Evidence
1
Define
Clarify the decision, compound, population, route, and exposure endpoint.
2
Collect
Review physicochemical, ADME, formulation, animal, and clinical data.
3
Build
Construct and parameterize the mechanistic PBPK model.
4
Verify
Compare simulations with independent PK datasets and exposure metrics.
5
Explore
Run dose, DDI, formulation, population, or uncertainty scenarios.
6
Deliver
Provide traceable files, results, interpretation, and next-step guidance.
Application Scenarios
Where PBPK Can Reduce Development Uncertainty
Candidate Prioritization
Compare projected exposure, tissue distribution, clearance sensitivity, and dose feasibility before committing to costly experiments.
Clinical Dose Planning
Evaluate single-dose and multiple-dose regimens, accumulation, steady state, and target-exposure attainment.
DDI Risk Management
Identify likely interaction mechanisms, sensitive scenarios, and data gaps that should be addressed experimentally.
Formulation Strategy
Assess how solubility, particle size, release, precipitation, permeability, and food effects may change oral absorption.
Population Bridging
Explore physiological differences across age groups, disease states, and organ function to inform dose-adjustment hypotheses.
Experiment Prioritization
Use sensitivity and uncertainty analyses to determine which input parameters most strongly influence the decision.
Project Inputs
Data We Can Integrate
Projects can begin with incomplete datasets. Data suitability and uncertainty are evaluated before model construction.
| Data Category | Examples | How It Supports the Model |
|---|---|---|
| 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-drug exposure, enzyme contribution, and IVIVE. |
| Transporter and DDI | Inhibition, induction, substrate data, Ki/IC50, time-dependent inhibition | Supports mechanistic interaction simulations and pathway attribution. |
| Preclinical PK | IV and oral concentration–time data, dose, formulation, bioavailability, tissue data | Enables model calibration, species verification, and translation assessment. |
| Clinical PK | Single- and multiple-dose PK, mass balance, food effect, DDI, organ impairment | Supports human-model verification, refinement, and scenario qualification. |
| Formulation | Dose form, dissolution, particle size, release profile, precipitation, excipients | Enables oral absorption and PBBM analyses linked to product performance. |
Project Outputs
Transparent Models, Traceable Assumptions, Actionable Conclusions
Deliverables are tailored to the intended use of the model and the maturity of the available data.
01Qualified Model Package
02Scenario Simulations
03Decision Summary
- ✓Model Files and Parameter TablesStructured model assets, parameter values, units, data sources, and assumptions.
- ✓Verification and Diagnostic ResultsObserved-versus-predicted plots, exposure comparisons, residual evaluation, and model performance discussion.
- ✓Scenario and Virtual-Population OutputsConcentration–time profiles, exposure distributions, dose comparisons, and relevant endpoint summaries.
- ✓Sensitivity and Uncertainty AnalysisIdentification of influential parameters, plausible prediction intervals, and high-value data gaps.
- ✓Technical Report and Executive InterpretationMethods, results, limitations, model applicability, conclusions, and recommended next steps.
MechanisticModels connect molecular and physiological drivers to observed exposure.
Fit-for-PurposeComplexity is matched to the development question and available evidence.
Data-AwareUncertainty and missing inputs are identified rather than hidden.
Decision-ReadyResults are translated into practical experimental and development choices.
Frequently Asked Questions
PBPK Modeling Project FAQ
Can a PBPK project start before clinical PK data are available?
Yes. Early models can integrate physicochemical properties, in vitro ADME, formulation data, and animal PK to support human translation and experimental planning. Predictions should be updated as human data become available.
What is the difference between PBPK and population PK modeling?
PBPK is primarily mechanistic and represents organs, tissues, physiology, and drug-specific processes. Population PK typically uses a more empirical compartmental structure to quantify variability and covariate effects from observed clinical data. The approaches can be complementary.
Can you work with incomplete or uncertain input data?
Yes. We first assess which inputs are essential, which can be estimated, and which create material uncertainty. Sensitivity analysis can then prioritize the experiments most likely to improve confidence.
Can PBPK be used for antibodies or complex modalities?
Yes, but model structure and required data differ from conventional small-molecule PBPK. Target-mediated disposition, FcRn recycling, tissue convection, binding, catabolism, or payload release may need to be represented.
What should be included in an initial project inquiry?
Please provide the compound or modality, development stage, intended decision, administration route, species or population of interest, available ADME/PK data, formulation information, and desired timeline or deliverables.
Start a PBPK Project
Turn Disconnected ADME and PK Data into a Testable Exposure Strategy
Share your compound information, available datasets, and development question. Our scientists will define a fit-for-purpose PBPK scope, identify critical data gaps, and recommend a practical modeling plan.
