Time Scaling for In Vitro-In Vivo Correlation: the Inverse Release Function (IRF) Approach

Area of Science:

• Biopharmaceutics
• Pharmacokinetics
• Drug Delivery Systems

Background:

• In vitro-in vivo correlations (IVIVC) link drug dissolution to in vivo plasma concentration.
• Level A IVIVC establishes a direct relationship between in vitro dissolution and in vivo absorption.
• Current Level A IVIVC methods face challenges due to time scale differences, impacting predictive accuracy.

Purpose of the Study:

• To introduce a novel inverse release function (IRF) method for time scaling in IVIVC.
• To enhance the predictive capacity of Level A IVIVC by utilizing complete in vitro and in vivo data.
• To improve the accuracy of predicting in vivo drug behavior from in vitro dissolution data.

Main Methods:

• Development of a mathematically closed inverse release function (IRF) for time scaling.
• Application of the IRF method to establish Levy's plot for improved IVIVC.
• Comparison of standard Level A regression with the IRF method using extended-release formulation data.

Main Results:

• Standard Level A regression resulted in prediction errors exceeding 10% for Cmax.
• The IRF method successfully generated in vitro times equivalent to in vivo absorption percentages.
• IRF-based Level A correlations demonstrated nearly negligible prediction errors, significantly improving accuracy.

Conclusions:

• The inverse release function (IRF) method offers a robust approach to time scaling for enhanced IVIVC.
• This novel method improves the predictive power of Level A IVIVC, crucial for formulation development.
• The IRF method supports regulatory biowaiver applications by providing reliable in vitro-to-in vivo predictions.