Evidence map›Paper›PMID 27473014›Full record

ArticleToxicology and applied pharmacology2016

A simple physiologically based pharmacokinetic model evaluating the effect of anti-nicotine antibodies on nicotine disposition in the brains of rats and humans.

Kyle Saylor, Chenming Zhang

Open access · greenAbstract read
In one paragraph

Article in Toxicology and applied pharmacology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.7field-weighted citation impact, top 26% of its field
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

7 citing papers in PubMed, 14 citations in OpenAlex.

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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

2 authors at 1 institution in 1 country.

Kyle SaylorDepartment of Biological Systems Engineering, Virginia Tech, Seitz Hall, RM 210, 155 Ag Quad Lane, Blacksburg, VA 24061, USA. Electronic address: saylor@vt.edu.
Chenming ZhangDepartment of Biological Systems Engineering, Virginia Tech, Seitz Hall, RM 210, 155 Ag Quad Lane, Blacksburg, VA 24061, USA. Electronic address: chzhang2@vt.edu.
Virginia Tech · US

Funding

Novel Nanovaccines Against Nicotine AddictionU01DA036850 · NIDA · VIRGINIA POLYTECHNIC INST AND ST UNIV · PI ZHANG, CHENMING M · 2014 to 2016
$2.3M
NIDA NIH HHS U01 DA036850
6 · The paper itself

Abstract

Physiologically based pharmacokinetic (PBPK) modeling was applied to investigate the effects of anti-nicotine antibodies on nicotine disposition in the brains of rats and humans. Successful construction of both rat and human models was achieved by fitting model outputs to published nicotine concentration time course data in the blood and in the brain. Key parameters presumed to have the most effect on the ability of these antibodies to prevent nicotine from entering the brain were selected for investigation using the human model. These parameters, which included antibody affinity for nicotine, antibody cross-reactivity with cotinine, and antibody concentration, were broken down into different, clinically-derived in silico treatment levels and fed into the human PBPK model. Model predictions suggested that all three parameters, in addition to smoking status, have a sizable impact on anti-nicotine antibodies' ability to prevent nicotine from entering the brain and that the antibodies elicited by current human vaccines do not have sufficient binding characteristics to reduce brain nicotine concentrations. If the antibody binding characteristics achieved in animal studies can similarly be achieved in human studies, however, nicotine vaccine efficacy in terms of brain nicotine concentration reduction is predicted to meet threshold values for alleviating nicotine dependence.

Indexed as

Models, BiologicalVaccinesAnimalsAntibodiesBrainCotinineHumansNicotineRatsSmokingTissue DistributionAntibodiesCotinineNicotineVaccinesAnti-nicotine antibodiesNicotine dependenceNicotine dispositionNicotine vaccinePBPKPhysiologically based pharmacokinetic model

Identifiers

PMID27473014
PMCPMC5344185
OpenAlexW2499471751

What OpenQuestion holds

Textmetadata
LicenceTDM
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Registered trials

None linked

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.