Assumptions Underlying Hepatic Clearance Models: Recognizing the Influence of Saturable Protein Binding on Driving Force Concentration and Discrimination Between Models of Hepatic Clearance.

Abstract

One underlying assumption of hepatic clearance models is often underappreciated. Namely, plasma protein binding is assumed to be nonsaturable within a given drug concentration range, dependent only on protein concentration and equilibrium dissociation constant. However, in vitro hepatic clearance experiments often use low albumin concentrations that may be prone to saturation effects, especially for high-clearance compounds, where the drug concentration changes rapidly. Diazepam isolated perfused rat liver literature datasets collected at varying concentrations of albumin were used to evaluate the predictive utility of four hepatic clearance models (the well-stirred, parallel tube, dispersion, and modified well-stirred model) while both ignoring and accounting for potential impact of saturable protein binding on hepatic clearance model discrimination. In agreement with previous literature findings, analyses without accounting for saturable binding showed poor clearance prediction using all four hepatic clearance models. Here we show that accounting for saturable albumin binding improves clearance predictions across the four hepatic clearance models. Additionally, the well-stirred model best reconciles the difference between the predicted and observed clearance data, suggesting that the well-stirred model is an appropriate model to describe diazepam hepatic clearance when considering appropriate binding models. SIGNIFICANCE STATEMENT: Hepatic clearance models are vital for understanding clearance. Caveats in model discrimination and plasma protein binding have sparked an ongoing scientific discussion. This study expands the understanding of the underappreciated potential for saturable plasma protein binding. Fraction unbound must correspond to relevant driving force concentration. These considerations can improve clearance predictions and address hepatic clearance model disconnects. Importantly, even though hepatic clearance models are simple approximations of complex physiological processes, they are valuable tools for clinical clearance predictions.