{"title":"Feasibility assessment of a pharmaco-kinetic behavior based yield model of salivary cotinine among tobacco users","authors":"E.C. Hensel , R.J. Robinson","doi":"10.1016/j.toxrep.2025.101898","DOIUrl":null,"url":null,"abstract":"<div><h3>Methods</h3><div>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.</div></div><div><h3>Results</h3><div>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.</div></div><div><h3>Conclusions</h3><div>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.</div></div>","PeriodicalId":23129,"journal":{"name":"Toxicology Reports","volume":"14 ","pages":"Article 101898"},"PeriodicalIF":0.0000,"publicationDate":"2025-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11787490/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Toxicology Reports","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2214750025000162","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Environmental Science","Score":null,"Total":0}
引用次数: 0
Abstract
Methods
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.
Results
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.
Conclusions
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.