Tutorial: Understanding the transport, deposition, and translocation of particles in human respiratory systems using Computational Fluid-Particle Dynamics and Physiologically Based Toxicokinetic models

Abstract

Dynamic modeling of how particulate matter (PM) transport, deposit, and translocate from human respiratory systems to systemic regions subject to indoor and outdoor exposures are essential for case-specific lung dosimetry predictions and occupational health risk assessments. Because of the invasive nature and imaging resolution limitations of existing in vitro and in vivo methods, Computational Fluid-Particle Dynamics plus Physiologically Based Pharmacokinetic/Toxicokinetic (CFPD-PBPK/TK) models have been employed to predict the fate of the respirable aerosols for decades. This paper presents a guide on how to use the multiscale CFPD-PBPK/TK models to predict lung dosimetry and systemic translocations quantitatively with 3D subject-specific human respiratory systems. The tutorial aims to clarify possibly ambiguous concepts. The step-by-step modeling procedure should help researchers set up the CFPD-PBPK/TK model accurately, following the standard model validation and verification (V&V) processes, and to bring the lung dosimetry predictions to health endpoints. Starting from the fundamentals of CFPD and PBPK/TK governing equations, the tutorial covers the problem identification, pre-processing, solving, and post-processing steps to perform a computational lung aerosol dynamics simulations, emphasizing on (a) the importance of correct reconstruction and mesh generation of the pulmonary airways; (b) the significance of choosing the appropriate turbulence model to predict the laminar-to-turbulence pulmonary airflow regimes; and (c) the standard (V&V) procedures of submodels in the CFPD-PBPK/TK modeling framework. The tutorial also highlights the deficiencies of current CFPD-PBPK/TK models, clarifies the missing biomechanisms and aerosol dynamics in the respiratory systems that need to be considered to build the next-generation virtual human whole-lung models.