A time-scaled convolution approach to construct IVIVC for enteric-coated acetylsalicylic acid tablets

Area of Science:

• Pharmacokinetics
• Drug Delivery Systems
• Computational Modeling

Background:

• Establishing reliable in vitro-in vivo correlations (IVIVC) is crucial for drug product development.
• Enteric-coated formulations require specialized dissolution testing to predict in vivo performance.
• Existing dissolution methods may not fully capture the complex release characteristics of enteric-coated drugs.

Purpose of the Study:

• To construct and validate a scaled convolution-based IVIVC model for enteric-coated acetylsalicylic acid tablets.
• To evaluate the performance of different in vitro dissolution methods in predicting in vivo pharmacokinetic parameters.
• To assess the model's compliance with US Food and Drug Administration (FDA) IVIVC guidance.

Main Methods:

• Development of a scaled convolution-based IVIVC model.
• In vitro dissolution testing using United States Pharmacopoeia (USP) method, Fasted State Simulated Intestinal Fluid (FaSSIF), and a novel in-house method.
• In vivo pharmacokinetic data collection from human subjects in a fasted state.

Main Results:

• The IVIVC model demonstrated high predictive accuracy when utilizing data from the novel in-house dissolution method.
• Average prediction error for Cmax and AUC was below 10%, with a maximum error below 15%.
• The model successfully met the internal validation criteria set by the FDA for IVIVC.

Conclusions:

• A novel in vitro dissolution method, when integrated into a scaled convolution model, provides a robust IVIVC for enteric-coated acetylsalicylic acid.
• The developed IVIVC model offers a reliable tool for predicting drug performance and ensuring product quality.
• This approach facilitates regulatory compliance and streamlines drug development processes.