A review of physiologically based pharmacokinetic modeling of renal drug disposition.

Abstract

The human kidney is a critical organ for the elimination of numerous drugs and metabolites. The mechanisms of renal drug handling are manifold including unbound filtration, transporter-mediated active secretion, bidirectional passive diffusion, and occasionally active reabsorption and renal metabolism. These mechanisms collectively dictate the fate of drugs at various spatiotemporal points as drug molecules travel through the renal vasculature, tubules, and cells, posing a significant challenge in accurately describing and predicting renal drug disposition. Toward this end, a physiologically based kidney model serves as a promising tool to combine the anatomical and physiological features of the kidney (eg, tubular flow rate, pH, and transporter expression) with the unique properties of drugs (eg, protein binding, lipophilicity, ionization, and transporter substrate) to capture the dynamic system-drug interactions. Despite the exciting progress over the past several decades, physiologically based pharmacokinetic modeling has overall been predominantly used to predict intestinal absorption and hepatic drug-drug interaction. In comparison, pharmacokinetic modeling of renal drug handling has been underappreciated. In this review, we first provide an overview of kidney function and physiology, renal clearance mechanisms, and the evolutionary history of the physiologically based mechanistic kidney model. We then summarize the recent efforts spent in different areas of kidney model application, particularly: (1) renal transporter-mediated drug-drug interaction, (2) disease effect from both renal and hepatic impairment, and (3) model applications across the lifespan (eg, pediatrics and geriatrics). Finally, we identify remaining knowledge gaps, future directions, and potential model utilities. SIGNIFICANCE STATEMENT: This review summarizes pharmacokinetic model case studies that are related to renal drug disposition, illustrating the current framework of modeling renal drug handling, highlighting knowledge gaps in predicting renal transporter-mediated drug-drug interactions, and modeling the effects of disease and age on renal drug handling. A discussion on robust model validation and areas for future directions is also provided.