Exploration of IVIVC Deconvolution Methods in a PBPK Platform: Case Example with Tofacitinib

Area of Science:

• Pharmacokinetics and Drug Delivery
• Pharmaceutical Sciences
• Biopharmaceutics

Background:

• Modified-release (MR) drug products require understanding in vitro-in vivo correlations for consistent performance.
• In vitro-in vivo correlation (IVIVC) is crucial for optimizing MR formulations and supporting regulatory decisions.
• Tofacitinib was used as a model compound to evaluate deconvolution methodologies.

Purpose of the Study:

• To evaluate three deconvolution methodologies (numerical, compartmental, mechanistic) within GPX™ for IVIVC.
• To assess the ability of these models to predict in vivo drug absorption from in vitro dissolution data.
• To demonstrate the utility of deconvolution-based IVIVC in a physiologically-based pharmacokinetic (PBPK) framework.

Main Methods:

• Developed prototype MR formulations of tofacitinib with varying release rates.
• Conducted a randomized crossover study in healthy volunteers to obtain plasma concentration-time data.
• Applied numerical, compartmental, and mechanistic deconvolution methods to derive in vivo fraction absorbed profiles.
• Simulated plasma concentration-time profiles using convoluted data and compared them to observed clinical data.
• Calculated prediction errors and confidence intervals for pharmacokinetic parameters (Cmax, AUC) to assess bioequivalence.

Main Results:

• Deconvolution methodologies successfully derived in vivo fraction absorbed profiles.
• Simulated plasma profiles showed good agreement with observed clinical data.
• Prediction errors for Cmax and AUC were within acceptable limits, indicating successful bioequivalence assessment.
• The study demonstrated the utility of deconvolution-based IVIVC within a PBPK framework.

Conclusions:

• Deconvolution-based IVIVC models are valuable tools for modified-release drug product development.
• These models facilitate formulation optimization and support regulatory flexibility.
• The approach provides a robust strategy for managing formulation lifecycles and assessing dissolution variability.