Day 1 of 3: Using In Silico and In Vitro Approaches for Next Generation Risk Assessment of Potential

Presentation 1: Arkadiusz K. Kuczaj (University of Twente; Philip Morris Int.)
Title: Accurate aerosol dosimetry predictions using in silico and in vitro approaches for risk assessment methods
Abstract: Aerosol transport and deposition predictions are particularly challenging due to complexities arising from aerosol physics and chemistry processes driven together by the airflow thermodynamics. Existing approaches using experimental in vitro science and computational methods for evolving aerosol dosimetry predictions will be discussed. Special attention will be given towards advancing experimental methods, as well as verification and validation of developed computational models.

Presentation 2: Annie Jarabek (US EPA ORD)
Title: Advancing Application of NAMs and Evidence Integration in Risk Assessment: Dosimetry is Critical to Exposure Alignment
Abstract: Conceptual constructs for source-to-outcome modeling based on aggregate exposure pathway (AEP) and adverse outcome pathway (AOP) frameworks can provide a mechanistic scaffold for evidence integration and application of novel approach methods (NAMs). Dosimetry is critical to achieve exposure alignment across various experimental platforms and inhaled agents. We discuss the conceptual construct, the role of dosimetry models, and illustrate impact by selected integrated approaches to testing and assessments (IATAs).

Presentation 3: Josué Sznitman (Technion Israel Institute of Technology)
Title: Advanced lung-on-chip platforms for preclinical inhalation assays: bridging in vitro and in silico approaches
Abstract: As advanced models capturing the cellular pulmonary make-up at an air-liquid interface , lung-on-chips (LOC) emulate both morphological features and biological functionality of the airway barrier. In this presentation, we discuss recent developments on devising such advanced human-relevant LOC. In an effort to mimic in situ-like inhalation assays, we exemplify how in silico simulations are leveraged to correlate deposition endpoints of inhaled aerosols.