Toxicological Assessment of Flavor Ingredients in E-Vapor Products.

Many flavor ingredients are often used in potentially reduced-risk tobacco products (such as e-vapor products). Although most are "generally recognized as safe (GRAS)" when used in food, there is limited information available on their 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 large number of individual flavor ingredients available and their potential combinations render classical toxicological assessment approaches impractical, as they may require years of preclinical investigations and thousands of laboratory animals. Therefore, 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 other structurally related flavor ingredients of their respective Flavor Groups. This approach is explained in a step-wise manner and exemplified by 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 in understanding the health risks of many flavor ingredients while also minimizing the need for laboratory animals.

A comprehensive physiologically based pharmacokinetic (PBPK) model for nicotine in humans from using nicotine-containing products with different routes of exposure.

Physiologically based pharmacokinetic (PBPK) modeling can be a useful tool for characterizing nicotine pharmacokinetics (PK) from use of tobacco products. We expand a previously published PBPK model to simulate a nicotine PK profile, following single or multiple use of various tobacco products [cigarettes, smokeless tobacco, and electronic nicotine delivery systems, or a nicotine inhaler (NICOTROL)] The uptake route in the model was designed to allow for three uptake compartments: buccal cavity (BC), upper respiratory tract (URT) (conducting and transitional airways) and lower respiratory tract (alveolar region). Within each region, the model includes product-specific descriptions of the flux of nicotine into plasma, as well as the flux of nicotine from the BC and URT to the gastrointestinal tract. These descriptions are based on regional deposition and diffusion models of nicotine into plasma, which depends on the product type. Regional deposition flux combined with regional differences in physiological parameters (e.g., blood perfusion ratio and tissue thickness) play a key role in the product-specific PK profile of nicotine. The current model describes the slower flux of nicotine into plasma across the BC and URT, as well as the rapid flux known to occur in the alveolar region. Overall, the addition of the BC and respiratory tract compartments to the nicotine model provided simulation results that are comparable to the nicotine time-course plasma concentrations reported from clinical studies for the four product categories simulated.

The impact of cigarette and e-cigarette use history on transition patterns: a longitudinal analysis of the population assessment of tobacco and health (PATH) study, 2013-2015.

BACKGROUND: Population models have been developed to evaluate the impact of new tobacco products on the overall population. Reliable input parameters such as longitudinal tobacco use transitions are needed to quantify the net population health impact including the number of premature deaths prevented, additional life years, and changes in cigarette smoking prevalence. METHODS: This secondary analysis assessed transition patterns from PATH wave 1 (2013-14) to wave 2 (2014-15) among adult exclusive cigarette smokers, exclusive e-cigarette users, and dual users. Transition probabilities were calculated by taking into account factors including cigarette smoking and e-cigarette use histories and experimental or established use behaviors. Multinomial logistic regression models were constructed to further evaluate factors associated with transition patterns. RESULTS: Differential transition probabilities emerged among study subgroups when taking into account cigarette smoking and e-cigarette use histories and experimental or established use behaviors. For example, overall 45% of exclusive e-cigarette users in wave 1 continued using e-cigarettes exclusively in wave 2. However, we observed approximately 11 to 14% of wave 1 exclusive experimental e-cigarette users continued to use e-cigarette exclusively in wave 2, compared to about 62% of exclusive established e-cigarette users. The history of cigarette smoking and e-cigarette use is another important factor associated with transition patterns. Among experimental e-cigarette users, 7.5% of individuals without a history of cigarette smoking transitioned to exclusive cigarette smoking, compared to 30% of individuals with a history of cigarette smoking. Additionally, 1.3% of exclusive cigarette smokers in wave 1 transitioned to exclusive e-cigarette use, with the highest transition probability (3.7%) observed in the established cigarette smoker with a history of e-cigarette use subgroup. CONCLUSIONS: Product use histories and current use behaviors are important factors influencing transitions between product use states. Given that experimental users' transition behaviors may be more variable and more influenced by tobacco use history, long-term predictions made by population models could be improved by the use of transition probabilities from established users. As transition patterns might be changing over time, long-term transition patterns can be examined through analysis of future waves of PATH data.

E-cigarette use and onset of first cigarette smoking among adolescents: An empirical test of the 'common liability' theory.

Background: E-cigarettes have become the most commonly used tobacco products among youth in the United States (US) recently. It is not clear whether there is a causal relationship between e-cigarette use and the onset of cigarette smoking. The "common liability" theory postulates that the association between e-cigarette use and cigarette smoking can be attributed to a common risk construct of using tobacco products. This study aims to investigate the relationship between ever e-cigarette use and cigarette smoking onset in the US using a structural equation modeling approach guided by the "common liability" theory. Methods: The study population is non-institutionalized civilian adolescents living in the US, sampled in the longitudinal Population Assessment of Tobacco and Health study. Information about tobacco product use was obtained via confidential self-report. A structural equation modeling approach was used to estimate the relationship between e-cigarette use at wave 1 and the onset of cigarette smoking at wave 2 after controlling for a latent construct representing a "common liability to use tobacco products." Results:  After controlling for a latent construct representing a "common liability to use tobacco products", ever e-cigarette use does not predict the onset of cigarette smoking (ß=0.10, 95% CI= -0.09, 0.29, p=0.299). The latent "common liability to use tobacco products" is a robust predictor for the onset of cigarette smoking (ß=0.42; 95% CI=0.08, 0.76; p=0.015). Conclusions: Findings from this study provide supportive evidence for the 'common liability' underlying observed associations between e-cigarette use and smoking onset.

Cigarettes with different nicotine levels affect sensory perception and levels of biomarkers of exposure in adult smokers.

INTRODUCTION: Few clinical studies involving cigarettes have provided a comprehensive picture of smoke exposure, test article characterization, and insights into sensory properties combined. The purpose of these pilot studies was to determine whether cigarettes with different levels of nicotine but similar tar levels would affect sensory experience or smoking behavior so as to significantly alter levels of selected biomarkers of exposure (BOE). METHODS: In 2 confined, double-blind studies, 120 adult smokers switched from Marlboro Gold cigarettes at baseline to either 1 of 2 lower nicotine cigarettes or 1 of 2 higher nicotine cigarettes and then to the other cigarette after 5 days. Urinary excretion of exposure biomarkers (nicotine equivalents [NE], total and free 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol [NNAL], 1-hydroxypyrene, and 3-hydroxypropyl mercapturic acid) as well as carboxyhemoglobin and plasma cotinine were measured at baseline, Day 5, and Day 10. Daily cigarette consumption was monitored and sensory characteristics were rated for each cigarette. RESULTS: With higher nicotine yield, urine NE, urine total NNAL, and plasma cotinine increased while nonnicotine BOE decreased without changes in cigarette consumption. In contrast, with lower nicotine yield, urine NE, urine total NNAL, and plasma cotinine dropped while nonnicotine BOE and cigarettes per day increased. Higher nicotine cigarettes were rated harsher and stronger than at baseline while lower nicotine cigarettes were less strong. All 4 test cigarettes were highly disliked. CONCLUSIONS: These studies demonstrate that abrupt increases or decreases in nicotine and the resulting sensory changes impact BOE through changes in intensity or frequency of smoking.

Evaluation of the effect of ammonia on nicotine pharmacokinetics using rapid arterial sampling.

INTRODUCTION: The nicotine bolus theory states that the dependence-producing potential of cigarettes relates to a rapid increase in nicotine at brain receptor sites. It has been suggested that ammonia, a compound typically found in tobacco products, further increases the amount of nicotine absorbed and its absorption rate. The aim of this study was to determine whether different ammonia yields in cigarettes affected the rate or amount of nicotine absorption from the lungs to arterial circulation. METHODS: 34 adult smokers received 3 separate puffs from each of 2 test cigarettes with different ammonia yields (ammonia in smoke: 10.1 µg per cigarette vs. 18.9 µg per cigarette), followed by rapid radial arterial blood sampling (maximum one sample per second) with 30 min between puffs. Arterial blood samples were assayed for nicotine by liquid chromatography tandem mass spectrometry. Pharmacokinetic modeling was performed and the two test cigarettes were assessed for bioequivalence. RESULTS: No significant differences were found in area under the curve, C(max), or T((max)) and the 2 test cigarettes were found to be bioequivalent based on 2 one-sided tests at a significance level of 5%. In addition, the zero-order rate constant (k(0)) obtained from the initial slope of the curves and the model-dependent first-order rate constant (k(a)) were not significantly different. CONCLUSIONS: This study provides strong evidence that the different ammonia yields of the test cigarettes had no impact on nicotine pharmacokinetics; thus, the ammonia did not increase the rate or amount of nicotine absorption from a puff of cigarette smoke.

Rapid automated blood sampling system for pharmacokinetics studies of cigarette smoking.

INTRODUCTION: We developed an automated sampling system to allow multiple, discrete blood samples from a human participant to be collected rapidly and immediately following cigarette smoke exposure. We reported the details of the sampling system along with the results of a pilot study for evaluation of the system. METHODS: Components of the system include silastic tubing, solenoid pinch valves, a peristaltic pump, and a fraction collector. This system incorporates a smoking machine that allows precise delivery of cigarette smoke through a mouthpiece and intricate timing to correlate blood samples with smoke inhalation. All components are controlled via integration from a user interface and are fully customizable. We performed several tests to evaluate the equipment, including tubing dead volume, leakage tests, and sample reproducibility. We also performed a pilot study with 6 adult smokers, who received 6 controlled puffs of a research test cigarette. Each inhalation was followed by radial arterial blood collection (1 sample per second tapered to 1 sample every 4 s) for 1 min. Samples were evaluated for nicotine via liquid chromatography-tandem mass spectrometric methods. RESULTS: Sampling times and volumes were sufficient for nicotine analysis. No adverse effects were seen in the pilot study, and a 30-min washout period was deemed appropriate between puffs. A significant rise in plasma nicotine levels above baseline after inhalation of smoke was consistently detected in all participants. DISCUSSION: The unique advantage of this system is to allow rapid blood sampling after a puff of cigarette smoke, with the benefits of reproducibility, reduction in labor intensity, and high temporal resolution.