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Can Machine Generated Nicotine Yield Predict Human Nicotine Exposure from ENDS?

Principal Investigator: Wallace Pickworth (CTP Contact: Marzena Hiler and Arit Harvanko)
Funding Mechanism: Research Contract
ID Number: HHSF22320170040I
Award Date: 9/30/2021
Institution: Battelle


The goal of this study is to examine whether machine-generated nicotine yield from electronic nicotine delivery systems (ENDS) can predict human exposure to nicotine. Study aims are: (1) to determine whether nicotine yields generated from machine-vaped ENDS are associated with human nicotine exposure following prescribed or ad libitum ENDS use, and (2) to determine which machine-vaping regimes (e.g., CORESTA, intense, playback of human puff topography), if any, are most effective for estimating human exposure to nicotine. Researchers will also investigate how changes in ENDS nicotine yield may affect nicotine pharmacokinetics, pharmacodynamics, non-nicotine HPHC exposure, subjective effects, and puff topography. In this randomized study, 32 current ENDS users (ages 21-65) will complete four experimental visits during which they will use an ENDS containing one of four e-liquid nicotine concentrations (i.e., very low, low, medium, high) under prescribed and ad libitum use conditions; researchers will then measure nicotine pharmacokinetic parameters (e.g., maximum plasma nicotine concentration) to determine nicotine exposure and compare it to machine-generated yields. Results will help determine whether nicotine yield data can be used to estimate human exposure to nicotine from ENDS, whether these data can be used to draw inferences regarding ENDS abuse liability, and whether certain machine-puffing regimens are most suitable for estimating human nicotine exposure from ENDS.
 

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