Exploring in vitro to in vivo extrapolation for exposure and health impacts of e-cigarette flavor mixtures

• Published in: Toxicology in vitro 2021-04, Vol.72, p.105090-105090, Article 105090
• Main Authors: Chang, Xiaoqing, Abedini, Jaleh, Bell, Shannon, Lee, K. Monica
• Format: Article
• Language: English
• Subjects: Acute toxicity; Assaying; Biocompatibility; Cartridges (explosive); Complexity; Cytotoxicity; Electronic cigarette (EC); Electronic cigarettes; Estimates; Exposure; Extrapolation; Flavor; Hazard identification; In vivo methods and tests; IVIVE; Mixtures; Modelling; NAMs; Pharmacokinetics; Plasma levels; Risk assessment; Smoking; Toxicity
• ISSN: 0887-2333; 1879-3177
• DOI: 10.1016/j.tiv.2021.105090

In vitro to in vivo extrapolation (IVIVE) leverages in vitro biological activities to predict corresponding in vivo exposures, therefore potentially reducing the need for animal safety testing that are traditionally performed to support the hazard and risk assessment. Interpretation of IVIVE predictions are affected by various factors including the model type, exposure route and kinetic assumptions for the test article, and choice of in vitro assay(s) that are relevant to clinical outcomes. Exposure scenarios are further complicated for mixtures where the in vitro activity may stem from one or more components in the mixture. In this study, we used electronic cigarette (EC) aerosols, a complex mixture, to explore impacts of these factors on the use of IVIVE in hazard identification, using open-source pharmacokinetic models of varying complexity and publicly available data. Results suggest in vitro assay selection has a greater impact on exposure estimates than modeling approaches. Using cytotoxicity assays, high exposure estimates (>1000 EC cartridges (pods) or > 700 mL EC liquid per day) would be needed to obtain the in vivo plasma levels that are corresponding to in vitro assay data, suggesting acute toxicity would be unlikely in typical usage scenarios. When mechanistic (Tox21) assays were used, the exposure estimates were much lower for the low end, but the range of exposure estimate became wider across modeling approaches. These proof-of-concept results highlight challenges and complexities in IVIVE for mixtures. •IVIVE utilizes in vitro bioactivity to support hazard screening and risk assessment.•IVIVE of mixtures can generate a range of exposure estimates.•Exposure estimates are more sensitive to the selection of in vitro assay than kinetic model.