Computational approach for respiratory hazard identification of flavor chemicals in tobacco products
Flavor chemicals contribute to the appeal and toxicity of e-cigarettes and other tobacco products, and the assortment of flavor chemicals available for use in tobacco products is extensive. FDA scientists used a chemistry-driven computational approach to evaluate flavor chemicals based on intrinsic hazardous structures and reactivity of chemicals (Goel et al. 2022). A library of 3,012 unique flavor chemicals was evaluated based on physicochemical properties, GHS health hazard classification, structural alerts linked to the chemical’s reactivity, instability, or toxicity, and substructures shared with known respiratory toxicants. Computational analysis of the constructed flavor library flagged 638 chemicals with GHS classified respiratory health hazards, 1,079 chemicals with at least one structural alert, and 2,297 chemicals with substructures of concern. From further analysis of a subset of 173 chemicals, four general structures with an increased potential for respiratory toxicity were identified. This study indicated that computational methods are efficient tools for hazard identification and understanding structure-toxicity relationship. With appropriate context of use and interpretation, in silico methods may provide scientific evidence to support toxicological evaluations of chemicals in or emitted from tobacco products.