Modeling lung transporters and their influence on inhaled drug disposition

Abstract

Administering drugs via inhalational routes is an attractive approach for treating respiratory diseases. Effective lung delivery provides a rapid therapeutic effect, minimizes systemic toxicities, and enhances overall public health responses, particularly for orally inhaled products during pandemics. However, assessing the pharmacokinetic (PK) properties of inhaled agents within the airway is challenging. In silico modeling, especially using physiologically based pharmacokinetic (PBPK) models, has emerged as a crucial clinical translational tool that integrates in vitro, in vivo, and ex vivo lung model data to improve predictions of lung exposure for inhaled drugs. Developing effective PBPK models requires a deeper understanding of the factors influencing drug disposition. Membrane transporters can significantly impact airway PKs, but there is a knowledge gap regarding their role and expression within the human airways. This review explores the following: (1) preclinical and clinical studies on lung transporter localization, expression, and their potential impact on the PKs of inhaled drugs; (2) conflicting data on transporter expression and localization; and (3) factors influencing transporter expression, such as inflammatory processes and diseases. We summarize the transporters involved in inhaled drug disposition, drug-specific parameters, and current PBPK models and approaches that account for transporter involvement. Only a few studies quantify transporter protein levels in the lung, particularly for respiratory diseases, limiting the ability to incorporate lung expression levels to inform the development of enhanced PBPK models. Overall, a comprehensive understanding of lung transporters and their impact on drug disposition is crucial for estimating and optimizing model-informed dosing of inhaled therapeutics. SIGNIFICANCE STATEMENT: Inhaled drugs are ideal for treating respiratory diseases because they increase drug exposure in the lungs and minimize off-target effects. Speeding up their approval, development, and dosing relies on accurate computational models. This review examines improving these models by integrating knowledge about lung transporters, focusing on understanding, characterizing, and quantifying these transporters and their influence on drug disposition.