A mechanistic framework for a priori pharmacokinetic predictions of orally inhaled drugs

TL;DR

This paper presents a comprehensive mechanistic mathematical framework for predicting pulmonary pharmacokinetics of inhaled drugs, integrating key processes without individual data fitting, and evaluates its predictions against clinical data.

Contribution

The work introduces a physiologically-structured population model that systematically predicts inhaled drug PK and identifies key optimization parameters without parameter fitting.

Findings

Predicted lung retention profiles of insoluble particles

Predicted PK differences between drugs and patient groups

Identified key parameters impacting drug absorption and systemic exposure

Abstract

The fate of orally inhaled drugs is determined by pulmonary pharmacokinetic (PK) processes such as particle deposition, pulmonary drug dissolution, and mucociliary clearance. Although each single process has been systematically investigated, a quantitative understanding on their interaction remains limited and hence identifying optimal drug and formulation characteristics for orally inhaled drugs is still challenging. To investigate this complex interplay, the pulmonary processes can be integrated into mathematical models. However, existing modeling attempts considerably simplify these processes or are not systematically evaluated against (clinical) data. In this work, we developed a mathematical framework based on physiologically-structured population equations to integrate all relevant pulmonary processes mechanistically. A tailored numerical resolution strategy was chosen and the mechanistic model was evaluated systematically against different clinical datasets. Without any parameter estimation based on individual study data, the developed model simultaneously predicted (1) lung retention profiles of inhaled insoluble particles, (2) particle size-dependent PK of inhaled monodisperse particles, (3) PK differences between inhaled fluticasone propionate and budesonide, and (4) PK differences between healthy volunteers and asthmatic patients. Finally, to identify the most impactful optimization criteria for orally inhaled drugs, we investigated the impact of input parameters on both pulmonary and systemic exposure. Solubility of the inhaled drug did not have any relevant impact on local and systemic PK. Instead, pulmonary dissolution rate, particle size, tissue affinity, and systemic clearance were impactful potential optimization parameters. In the future, the developed prediction framework should be considered a powerful tool to identify optimal drug and formulation characteristics.