AUTHOR=Sciuscio Davide , Calvino-Martin Florian , Kumar Ashutosh , Langston Timothy B. , Martin Elyette , Marescotti Diego , Mathis Carole , Hoeng Julia , Peitsch Manuel C. , Smith Donna C. , Gogova Maria , Vanscheeuwijck Patrick , Lee Kyeonghee M. 

TITLE=Toxicological Assessment of Flavor Ingredients in E-Vapor Products

JOURNAL=Frontiers in Toxicology

VOLUME=Volume 4 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/toxicology/articles/10.3389/ftox.2022.878976

DOI=10.3389/ftox.2022.878976

ISSN=2673-3080

ABSTRACT=Flavor ingredients are an important characteristic of reduced risk products (RRPs) because of their potential to increase product acceptance by adult smokers and enable them to switch away from cigarettes. There are many flavor ingredients that can potentially be used in RRPs and, although most are “generally recognized as safe (GRAS)” when used in food, there is limited information available on the long-term health effects when delivered by inhalation. While obtaining route-of-exposure-specific toxicological data on flavor ingredients is critical to product evaluation, the number of individual flavor ingredients and the magnitude of potential flavor combinations render classical approaches impractical, as they may require years of preclinical investigations and thousands of laboratory animals. We propose a pragmatic approach in which flavor ingredients are initially assigned to groups of structurally related compounds (Flavor Groups), from which flavor group representatives (FGR) are then selected and tested individually and as a mixture in vitro and in vivo. The premise is that structurally related compounds would have comparable metabolic and biological activity and that the data generated using FGRs could support the toxicological assessment of all other structurally related flavor ingredients in Flavor Groups. This approach is explained in a tiered manner with a case study, along with its strengths, limitations as well as recommendations for further confirmatory testing. Once completed, this FGR approach could significantly reduce the time and resources required for filling the data gap on the health risk of many flavor ingredients while also minimizing the need for laboratory animals.