Importance of e-liquid preparation and stability characterization for a combinatorial safety assessment approach of flavors in e-liquids
Numerous flavorings are generally recognized as safe for use in food, but there is limited information available to evaluate their potential toxicity by inhalation. Consequently, gaining information on individual flavor safety levels is of significant relevance to define appropriate use of flavors in potentially reduced-risk products (PRRPs), such as electronic cigarettes.
Safety assessment requires pre-clinical studies; considering the large number of potential flavorings, appropriate selection of representative candidates to subject to such studies is a key first step. In addition, it is critical to characterize the test items, including the verification of batch consistency, throughout the study. In this study, we propose a unique combinatorial flavor group-based approach to acquire information on the safety of flavors ingested via inhalation. Using this approach, we clustered 246 flavoring substances into 38 groups of structurally related substances (based on groups defined in European Commission regulation No 1565/2000). From each group, we selected the flavor group representative (FGR) with the predicted worst toxicological profile, aiming to use the toxicological information acquired on the FGRs to predict the toxicity of structurally related flavoring substances within the same group. To reduce complexity of test item preparation, we split the 38 FGRs into six concentrated “pre-blends” based on structural moiety, solubility, and chemical reactivity, and assessed their stability. These pre-blend solutions were stable for up to 28 days. Finally, we mixed those pre-blends to obtain two e-liquid solutions containing all the FGRs. The final formulation containing nicotine was stable for up to three days and the formulation without nicotine was stable for up to ten days. Our research demonstrated the advantages of mixing selected representatives into concentrated and stable pre-blends, thus avoiding laborious daily solution preparation and minimizing efforts and costs associated to batch characterization.