Ali Salehi PhD, Mohamadi A. Sarkar PhD, FCP, Jennifer H. Smith PhD, Ali A. Rostami PhD
{"title":"Physiologically Based Pharmacokinetic Modeling to Predict Nicotine Pharmacokinetics of Nicotine Pouches Under Naturalistic Use Conditions","authors":"Ali Salehi PhD, Mohamadi A. Sarkar PhD, FCP, Jennifer H. Smith PhD, Ali A. Rostami PhD","doi":"10.1002/jcph.70038","DOIUrl":null,"url":null,"abstract":"<p>Adult users of traditional tobacco products like combustible cigarettes (CC) or moist smokeless tobacco (MST) products can reduce exposure to toxicants by switching to potentially less harmful alternatives such as tobacco-free nicotine pouches (NP). Nicotine exposure assessment is an important consideration to determine the switching potential of NPs. These measurements are often conducted using randomized clinical studies. However, characterizing nicotine exposure under real-world use conditions can further inform these assessments. We propose a framework based on physiologically based pharmacokinetic (PBPK) modeling that integrates typical use patterns and clinical pharmacokinetic (PK) data to predict nicotine exposure under actual use conditions. A tissue permeation model precedes the PBPK modeling and is characterized by two physiological parameters, nicotine diffusivity, and effective tissue thickness, which were determined and validated using literature data. A product-specific tissue uptake fraction was determined by regression of nicotine pharmacokinetics measured under controlled use conditions and applied consistently for alternative use scenario analyses. Nicotine PK profiles were predicted under various use scenarios for cigarette smoking or MST use and compared to that from the use of two NPs, namely on!<sup>®</sup> and on! PLUS™ NPs (Test Products). The nicotine PK parameters predicted under real-world use conditions were not higher for Test Products relative to cigarettes or MST. The proposed modeling here can further inform nicotine exposure under actual use conditions. PBPK modeling can be a fit-for-purpose tool for predicting nicotine exposure under various use scenarios.</p>","PeriodicalId":22751,"journal":{"name":"The Journal of Clinical Pharmacology","volume":"65 10","pages":"1297-1309"},"PeriodicalIF":0.0000,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://accp1.onlinelibrary.wiley.com/doi/epdf/10.1002/jcph.70038","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Journal of Clinical Pharmacology","FirstCategoryId":"1085","ListUrlMain":"https://accp1.onlinelibrary.wiley.com/doi/10.1002/jcph.70038","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Adult users of traditional tobacco products like combustible cigarettes (CC) or moist smokeless tobacco (MST) products can reduce exposure to toxicants by switching to potentially less harmful alternatives such as tobacco-free nicotine pouches (NP). Nicotine exposure assessment is an important consideration to determine the switching potential of NPs. These measurements are often conducted using randomized clinical studies. However, characterizing nicotine exposure under real-world use conditions can further inform these assessments. We propose a framework based on physiologically based pharmacokinetic (PBPK) modeling that integrates typical use patterns and clinical pharmacokinetic (PK) data to predict nicotine exposure under actual use conditions. A tissue permeation model precedes the PBPK modeling and is characterized by two physiological parameters, nicotine diffusivity, and effective tissue thickness, which were determined and validated using literature data. A product-specific tissue uptake fraction was determined by regression of nicotine pharmacokinetics measured under controlled use conditions and applied consistently for alternative use scenario analyses. Nicotine PK profiles were predicted under various use scenarios for cigarette smoking or MST use and compared to that from the use of two NPs, namely on!® and on! PLUS™ NPs (Test Products). The nicotine PK parameters predicted under real-world use conditions were not higher for Test Products relative to cigarettes or MST. The proposed modeling here can further inform nicotine exposure under actual use conditions. PBPK modeling can be a fit-for-purpose tool for predicting nicotine exposure under various use scenarios.