What data do I need to start an IVIVC project?

You typically need in vitro dissolution profiles for at least three formulations with distinct release rates, along with corresponding in vivo plasma concentration–time data from preclinical or human studies. Additional information on drug permeability, solubility, and formulation composition is helpful for absorption PBPK approaches. The exact requirements are scoped during an initial consultation.

How is the model validated?

Validation follows regulatory guidance and typically involves internal validation (fitting a subset of data) and external validation (predicting an independent batch). Prediction errors for AUC and Cmax are calculated; a common acceptance criterion is average absolute prediction error below 10% for AUC and 15% for Cmax. The validation plan is tailored to your dataset size and development stage.

What types of formulations can you model?

We work with immediate-release and extended-release oral solid dosage forms, including matrix and multiparticulate tablets, as well as long-acting injectables. The same deconvolution and absorption PBPK methodologies apply, though adaptation is needed for non-oral routes. Please contact us to discuss your specific product type.

How long does an IVIVC modeling project take?

The timeline depends on data availability, model complexity, and validation requirements. A typical project involving deconvolution-based level A correlation and validation can be scoped in weeks after data receipt. More complex absorption PBPK models may require additional time. Specific timelines are defined in the project agreement.

Do you provide training on using the model?

Our deliverables include a detailed report and the model files (if developed in open-source platforms). We also offer a consultation session to walk through the results and explain how to apply the model for future predictions. Extended training can be arranged as part of the project scope.

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IVIVC Modeling and Translational Pharmacokinetics Service

IVIVC & Translational PK

Establish predictive in vitro-in vivo correlations and translate formulation performance into human pharmacokinetic predictions to streamline non-oral drug development.

Level A IVIVC model development using deconvolution or absorption PBPK approaches
Translational scaling from preclinical species to human PK predictions
Model validation with internal or external datasets for regulatory confidence
Biorelevant dissolution testing integration for mechanistic understanding
Regulatory documentation support for biowaiver and scale-up submissions

Get Started

Why Model IVIVC for Your Formulation?

IVIVC is a predictive mathematical framework linking in vitro drug release to in vivo absorption, enabling formulation optimization and reducing clinical bioequivalence study needs.

Reduce costly and time-consuming clinical bioequivalence studies
Optimize formulation attributes early in development
Meet regulatory expectations for biowaiver and post-approval changes
Leverage mechanistic absorption PBPK models for deeper insight

Predictive

Regulatory

Insight

Our Approach

Integrated IVIVC Modeling Framework

We combine in vitro dissolution testing, pharmacokinetic data analysis, and advanced modeling to build robust correlations that accelerate formulation development.

Core IVIVC Pipeline

Establish a point-to-point level A correlation using the traditional deconvolution/convolution methodology. This approach directly links in vitro dissolution profiles to in vivo input rates and predicts plasma concentration–time curves.

Biorelevant dissolution profiling with multiple release rates
Deconvolution of plasma data to estimate in vivo absorption
Level A correlation fitting and internal validation
Convolution to predict PK from new dissolution profiles
Prediction error assessment for AUC and Cmax

Absorption PBPK Integration

For complex formulations, we build mechanistic absorption PBPK models that incorporate dissolution data as an input. This approach accounts for gastrointestinal physiology and drug properties to simulate absorption and disposition.

Parameterization of GI tract physiology and drug permeability
Incorporation of dissolution profiles as time-dependent input
Optimization of absorption scaling factors
Sensitivity analysis for formulation and physiological variables
Comparison with deconvolution-based IVIVC for best fit

Biopredictive Quality

We ensure dissolution methods are developed under biorelevant conditions to maximize correlation with in vivo data, using media that simulate gastrointestinal pH and composition.

Statistical Rigor

Model validation employs internal datasets (e.g., three dissolution rates) and external predictions to assess % prediction error for AUC and Cmax, following regulatory guidance.

Translational Insight

Our modeling incorporates allometric scaling and species-specific physiology to extend IVIVC from preclinical to human predictions, supporting first-in-human dose selection.

Deliverables

What You Receive

Our service provides a comprehensive package that documents the modeling process, results, and regulatory-ready summaries.

Data and Model Deliverables

IVIVC model report (deconvolution and/or absorption PBPK)
Predicted plasma concentration–time curves
Goodness-of-fit plots and prediction error tables
Sensitivity analysis for key formulation parameters
All intermediate datasets in standard formats

Reporting and Support

Regulatory documentation summary suitable for submission
Consultation on dissolution method optimization
Interpretation of model results for formulation decisions
Ongoing support for scale-up or post-approval changes

Service Scope

Customizable Project Parameters

Each IVIVC project is scoped to your specific drug product, formulation types, and development stage. Below are typical elements addressed during consultation.

Parameter	Typical Project Scope
IVIVC Level	Level A (point-to-point correlation); Level B or C if required for early development
Modeling Approaches	Deconvolution/convolution, absorption PBPK modeling, or hybrid
Formulation Types	Immediate-release, extended-release (matrix, multiparticulate), long-acting injectables
In Vitro Data	Biorelevant dissolution profiles under multiple conditions; media optimization included
In Vivo Data	Plasma PK data from preclinical species or human subjects (single or multiple dose levels)
Validation Strategy	Internal (training/test split) and external (independent batch) validation as data permits
Regulatory Support	Documentation for biowaiver requests, scale-up changes, or site transfers
Software Platform	Commercially available PBPK platforms (e.g., Gastroplus, Simcyp) or custom R/Python scripts
Deliverables Format	PDF report, raw data files, model source code, and presentation-ready figures

Workflow

How We Build Your IVIVC Model

Our streamlined process moves from data collection to validated model, ensuring robust correlation between laboratory observations and clinical outcomes.

In Vitro Dissolution Profiling

Conduct dissolution tests under biorelevant conditions (e.g., USP apparatus, FaSSIF/FeSSIF media) to capture release profiles across multiple time points for at least three distinct release rates.

In Vivo PK Data Deconvolution

Deconvolve plasma concentration–time data using numerical methods (e.g., Loo-Riegelman or Wagner-Nelson) to estimate the fraction absorbed or in vivo input rate as a function of time.

Establish Level A Correlation

Plot fraction absorbed against fraction dissolved at corresponding times; fit a linear or nonlinear regression model to define the point-to-point relationship and compute correlation parameters.

Convolution or Absorption PBPK Modeling

Use the established correlation to convolve new dissolution profiles into predicted plasma curves, or build an absorption PBPK model that uses dissolution as a time-dependent input for mechanistic simulation.

Validation and Sensitivity Analysis

Validate model predictions against internal (training) and external (independent) datasets; assess prediction errors for AUC and Cmax; perform sensitivity analysis on formulation variables and physiological parameters.

Applications

How IVIVC Drives Drug Development Decisions

Our modeling service supports key milestones across the pharmaceutical lifecycle, from preclinical formulation screening to post-approval changes.

Rapidly Screen and Optimize Formulations

Use IVIVC to link formulation attributes (e.g., polymer type, drug loading) to in vivo performance, enabling data-driven selection of lead candidates without extensive animal or human studies.

Identify critical formulation parameters affecting absorption
Reduce the number of in vivo studies needed for optimization
Accelerate decision-making between prototype formulations

Support Regulatory Biowaiver Requests

Regulatory agencies accept validated IVIVC models as a surrogate for bioequivalence studies. Our documentation aligns with FDA and EMA guidance to strengthen biowaiver submissions.

Provide level A correlation evidence for biowaiver justification
Draft regulatory summary sections for IND/NDA submissions
Reduce need for in vivo BE studies for minor formulation changes

Manage Scale-Up and Site Changes

When manufacturing scale, site, or equipment changes occur, an IVIVC model can predict whether these changes alter in vivo performance, supporting waivers for in vivo studies.

Evaluate impact of manufacturing changes on release profiles
Predict in vivo exposure for new batches
Support post-approval change submissions with modeling evidence

FAQ

Frequently Asked Questions

Common inquiries about IVIVC modeling and our service approach.

You typically need in vitro dissolution profiles for at least three formulations with distinct release rates, along with corresponding in vivo plasma concentration–time data from preclinical or human studies. Additional information on drug permeability, solubility, and formulation composition is helpful for absorption PBPK approaches. The exact requirements are scoped during an initial consultation.
Validation follows regulatory guidance and typically involves internal validation (fitting a subset of data) and external validation (predicting an independent batch). Prediction errors for AUC and Cmax are calculated; a common acceptance criterion is average absolute prediction error below 10% for AUC and 15% for Cmax. The validation plan is tailored to your dataset size and development stage.
We work with immediate-release and extended-release oral solid dosage forms, including matrix and multiparticulate tablets, as well as long-acting injectables. The same deconvolution and absorption PBPK methodologies apply, though adaptation is needed for non-oral routes. Please contact us to discuss your specific product type.
The timeline depends on data availability, model complexity, and validation requirements. A typical project involving deconvolution-based level A correlation and validation can be scoped in weeks after data receipt. More complex absorption PBPK models may require additional time. Specific timelines are defined in the project agreement.
Our deliverables include a detailed report and the model files (if developed in open-source platforms). We also offer a consultation session to walk through the results and explain how to apply the model for future predictions. Extended training can be arranged as part of the project scope.

Scientific Literature

References

Siemons M, Schroyen B, Darville N, et al. Role of Modeling and Simulation in Preclinical and Clinical Long-Acting Injectable Drug Development. The AAPS journal. 2023;25(6):99. View on PubMed
Pepin XJH, Dressman J, Parrott N, et al. In Vitro Biopredictive Methods: A Workshop Summary Report. Journal of pharmaceutical sciences. 2021;110(2):567-583. View on PubMed

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