Hensel E C, Robinson R J
Department of Mechanical Engineering, Rochester Institute of Technology, Rochester, NY, United States.
Toxicol Rep. 2025 Jan 5;14:101898. doi: 10.1016/j.toxrep.2025.101898. eCollection 2025 Jun.
A secondary analysis was conducted using puff topography and salivary cotinine biomarker data from a prior two arm, two period cross-over study conducted in the natural environment over 17 days which enrolled 55 Juul electronic cigarette users. The study expands upon a previously validated behavior-based yield (BBY) which quantified aerosol emissions from a Juul ecig as a function of user behavior. A Pharmacokinetic Behavior-Based Yield (PkBBY) model is introduced which models the uptake of nicotine into the body and its subsequent metabolic decay into cotinine. A subset of the available participant data was used to train the PkBBY model and identify three parameters: a gain reflecting the conversion of nicotine into salivary cotinine concentration, and the half-lives of nicotine and salivary cotinine in the body. A separate subset of the available data was used for assessing performance of the PkBBY model against salivary cotinine biomarkers of exposure.
Model training demonstrated the PkBBY model was able to predict the bedtime salivary cotinine of participants within + /- 220 ng/mL 95 % confidence interval on the regression, based on their observed puff topography. The training algorithm estimated the conversion from nicotine ingested into the concentration of salivary cotinine as 28.8 [(ng/mL cotinine)/(mg nicotine ingested)], and the half-lives of nicotine and cotinine to be 4.4 and 49 [hours], respectively. The one-to-one intraclass correlation coefficient of the model applied to the assessment data set was 0.6, indicating moderate agreement between the predictions and the observed biomarkers, Limitations of the model associated with the data available for secondary analysis are discussed.
The PkBBY model was internally validated and shows promise as a tool for establishing a causal relationship between puffing behavior and an established biomarker of nicotine exposure. Further work is needed to develop personalized PkBBY model parameters to account for variations in participant metabolism factors.
使用来自之前一项双臂、两阶段交叉研究的抽吸地形和唾液可替宁生物标志物数据进行二次分析。该研究在自然环境中进行了17天,招募了55名Juul电子烟使用者。该研究扩展了先前经过验证的基于行为的产率(BBY),该产率将Juul电子烟的气溶胶排放量量化为用户行为的函数。引入了基于药代动力学行为的产率(PkBBY)模型,该模型模拟尼古丁在体内的摄取及其随后代谢降解为可替宁的过程。使用可用参与者数据的一个子集来训练PkBBY模型,并确定三个参数:一个反映尼古丁转化为唾液可替宁浓度的增益,以及尼古丁和唾液可替宁在体内的半衰期。使用可用数据的另一个子集来评估PkBBY模型针对暴露的唾液可替宁生物标志物的性能。
模型训练表明,PkBBY模型能够根据观察到的抽吸地形,在回归的95%置信区间内,在±220 ng/mL范围内预测参与者的睡前唾液可替宁。训练算法估计,摄入的尼古丁转化为唾液可替宁浓度的转化率为28.8[(ng/mL可替宁)/(mg摄入的尼古丁)],尼古丁和可替宁的半衰期分别为4.4小时和49小时。应用于评估数据集的模型的组内相关系数为0.6,表明预测值与观察到的生物标志物之间具有中等一致性。讨论了与可用于二次分析的数据相关的模型局限性。
PkBBY模型经过内部验证,有望作为一种工具,用于建立抽吸行为与已确定的尼古丁暴露生物标志物之间的因果关系。需要进一步开展工作,以开发个性化的PkBBY模型参数,以考虑参与者代谢因素的变化。