Evidence map›Paper›PMID 40347000›Full record

ArticleJournal of clinical pharmacology2025

Physiologically Based Pharmacokinetic Modeling to Predict Nicotine Pharmacokinetics of Nicotine Pouches Under Naturalistic Use Conditions.

Ali Salehi, Mohamadi A Sarkar, Jennifer H Smith, Ali A Rostami

Abstract read
In one paragraph

Article in Journal of clinical pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Ali SalehiAltria Client Services LLC, Center for Research & Technology, Richmond, VA, USA.ORCID 0000-0003-3242-8186
Mohamadi A SarkarAltria Client Services LLC, Center for Research & Technology, Richmond, VA, USA.
Jennifer H SmithAltria Client Services LLC, Center for Research & Technology, Richmond, VA, USA.
Ali A RostamiAltria Client Services LLC, Center for Research & Technology, Richmond, VA, USA.

Funding

Altria Client Services, LLC
6 · The paper itself

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!

Indexed as

Models, BiologicalNicotineTobacco, SmokelessAdultFemaleHumansMaleMiddle AgedTissue DistributionTobacco ProductsYoung AdultNicotineclinical pharmacology (CPH)drug abusemodeling and simulationPBPKpharmacoepidemiology (PHE)

Identifiers

PMID40347000
PMCPMC12484417

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.