| Literature DB >> 27473014 |
Kyle Saylor1, Chenming Zhang2.
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.Entities:
Keywords: Anti-nicotine antibodies; Nicotine dependence; Nicotine disposition; Nicotine vaccine; PBPK; Physiologically based pharmacokinetic model
Mesh:
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Year: 2016 PMID: 27473014 PMCID: PMC5344185 DOI: 10.1016/j.taap.2016.07.017
Source DB: PubMed Journal: Toxicol Appl Pharmacol ISSN: 0041-008X Impact factor: 4.219