Jason Adamson1,* Xiang Li2,* Huapeng Cui2, David Thorne1, Fuwei Xie2, and Marianna Gaca1
1British American Tobacco, R&D, Southampton, United Kingdom.
2Zhengzhou Tobacco Research Institute of China National Tobacco Corporation, Zhengzhou, PR China.
*Joint first authors.
A VC 10 Smoking Robot was designated to look at the generated aerosol nicotine concentration from different e-cigarettes compared with the 3R4F reference cigarette in two different laboratories. The aerosol was trapped and the nicotine concentration was analysed by different kinds of mass spectometry.
Nicotine assessment across the tested e-cigarette categories showed consistent delivery of nicotine per puff within products and that the method was sensitive enough to detect different levels of nicotine across products. Good overlap in nicotine results were obtained in the two different laboratories.
The e-cigarette category is evolving rapidly, providing consumers with a variety of formats, ranging from cig-alike products to larger, high-powered modular devices. When generating an in vitro assessment approach across such diverse products, dosimetry considerations are paramount. In this article, we have compared nicotine quantification techniques in two studies using a Vitrocell VC 10 Smoking Robot to generate aerosols from different ecigarettes. In Study 1, a 3R4F reference cigarette and four different commercially available e-cigarettes were compared: puff-by-puff nicotine concentration was quantified at the same e-cigarette puffing regime (CRM No81) or with different puff durations, (2 or 3 seconds), comparing 3R4F puff-by-puff yields following ISO and HCI smoking regimes. In Study 2, 3R4F and one e-cigarette were assessed for puff-by-puff nicotine concentration in different locations (China and United Kingdom) comparing different nicotine quantification methods with gas chromatography–mass spectrometry and UPLC-MS/MS used in the two laboratories. Study 1 showed that 3R4F cigarette delivers different nicotine concentrations across the different regimes and puff number, supporting the nicotine methodology; e-cigarettes tested generated different amounts of nicotine across the devices tested, but showed consistent puff-by-puff delivery per device. Study 2 showed positive agreement between results across two different laboratories utilizing different methods for nicotine quantification; statistical analysis, combining all interlaboratory variables, indicated that laboratory differences and the interaction of laboratory and puff number were not significant ( p = 0.067 and 0.960, respectively). These studies will add further knowledge to support the in vitro assessment of novel nicotine products, providing reliability and assurance in the area of in vitro dosimetry.