Introducing the Dynamic Well-Stirred Model for Predicting Hepatic Clearance and Extraction Ratio

Area of Science:

• Pharmacokinetics
• Drug Metabolism
• Biopharmaceutical Sciences

Background:

• The traditional well-stirred model (WSM) uses unbound drug fraction (fu) to predict hepatic clearance, assuming instantaneous drug-protein binding equilibrium.
• This assumption may lead to inaccuracies, particularly for highly bound drugs, potentially underestimating free drug concentrations.

Purpose of the Study:

• To introduce and validate a dynamic well-stirred model (dWSM) that incorporates dynamic free fraction (fD) to better account for drug-protein binding kinetics.
• To compare the predictive accuracy of dWSM against WSM for hepatic clearance and liver extraction ratio across a diverse range of drugs.

Main Methods:

• Theoretical analysis comparing the impact of fu and fD on intrinsic clearance.
• In vitro experiments using recombinant CYP3A4 with highly bound midazolam and highly free verapamil.
• Validation of dWSM using in vitro microsomal clearance data from 36 diverse drugs.

Main Results:

• Dynamic free fraction (fD) accurately corrects albumin binding effects on intrinsic clearance for both highly bound and highly free drugs.
• The traditional unbound fraction (fu) over-corrects for highly bound drugs like midazolam.
• dWSM significantly improved the prediction accuracy of human hepatic clearance and liver extraction ratio compared to WSM.

Conclusions:

• The dWSM, utilizing fD, provides a more broadly applicable and accurate method for predicting hepatic clearance, especially for drugs with varying protein binding characteristics.
• Drug plasma protein binding kinetics are crucial for accurate hepatic clearance prediction, and dWSM addresses limitations of the traditional WSM.