Computational modeling of lung deposition of inhaled particles in chronic obstructive pulmonary disease (COPD) patients: identification of gaps in knowledge and data

Abstract

Computational modeling together with experimental data are essential to assess the risk for particulate matter mediated lung toxicity and to predict the efficacy, safety and fate of aerosolized drug molecules used in inhalation therapy. In silico models are widely used to understand the deposition, distribution, and clearance of inhaled particles and aerosols in the human lung. Exacerbations of chronic obstructive pulmonary disease (COPD) have been reported due to increased particulate matter related air pollution episodes. Considering the profound functional, anatomical and structural changes occurring in COPD lungs, the relevance of the existing in silico models for mimicking diseased lungs warrants reevaluation. Currently available computational modeling tools were developed for the healthy adult (male) lung. Here, we analyze the major alterations occurring in the airway structure, anatomy and pulmonary function in the COPD lung, as compared to the healthy lung. We also scrutinize the various physiological and particle characteristics that influence particle deposition, distribution and clearance in the lung. The aim of this review is to evaluate the availability of the fundamental knowledge and data required for modeling particle deposition in a COPD lung departing from the existing healthy lung models. The extent to which COPD pathophysiology may affect aerosol deposition depends on the relative contribution of several factors such as altered lung structure and function, bronchoconstriction, emphysema, loss of elastic recoil, altered breathing pattern and altered liquid volumes that warrant consideration while developing physiologically relevant in silico models.