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Modeling of Pharmacokinetics of Cocaine in Human Reveals the Feasibility for Development of Enzyme Therapies for Drugs of Abuse

Overview of attention for article published in PLoS Computational Biology, July 2012
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

news
1 news outlet
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7 X users
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1 patent
pinterest
1 Pinner

Citations

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44 Dimensions

Readers on

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42 Mendeley
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1 CiteULike
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Title
Modeling of Pharmacokinetics of Cocaine in Human Reveals the Feasibility for Development of Enzyme Therapies for Drugs of Abuse
Published in
PLoS Computational Biology, July 2012
DOI 10.1371/journal.pcbi.1002610
Pubmed ID
Authors

Fang Zheng, Chang-Guo Zhan

Abstract

A promising strategy for drug abuse treatment is to accelerate the drug metabolism by administration of a drug-metabolizing enzyme. The question is how effectively an enzyme can actually prevent the drug from entering brain and producing physiological effects. In the present study, we have developed a pharmacokinetic model through a combined use of in vitro kinetic parameters and positron emission tomography data in human to examine the effects of a cocaine-metabolizing enzyme in plasma on the time course of cocaine in plasma and brain of human. Without an exogenous enzyme, cocaine half-lives in both brain and plasma are almost linearly dependent on the initial cocaine concentration in plasma. The threshold concentration of cocaine in brain required to produce physiological effects has been estimated to be 0.22±0.07 µM, and the threshold area under the cocaine concentration versus time curve (AUC) value in brain (denoted by AUC2(∞)) required to produce physiological effects has been estimated to be 7.9±2.7 µM·min. It has been demonstrated that administration of a cocaine hydrolase/esterase (CocH/CocE) can considerably decrease the cocaine half-lives in both brain and plasma, the peak cocaine concentration in brain, and the AUC2(∞). The estimated maximum cocaine plasma concentration which a given concentration of drug-metabolizing enzyme can effectively prevent from entering brain and producing physiological effects can be used to guide future preclinical/clinical studies on cocaine-metabolizing enzymes. Understanding of drug-metabolizing enzymes is key to the science of pharmacokinetics. The general insights into the effects of a drug-metabolizing enzyme on drug kinetics in human should be valuable also in future development of enzyme therapies for other drugs of abuse.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Korea, Republic of 1 2%
United States 1 2%
Slovakia 1 2%
Unknown 39 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 26%
Student > Ph. D. Student 8 19%
Student > Bachelor 4 10%
Student > Master 4 10%
Professor 3 7%
Other 6 14%
Unknown 6 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 10 24%
Chemistry 5 12%
Neuroscience 4 10%
Biochemistry, Genetics and Molecular Biology 3 7%
Pharmacology, Toxicology and Pharmaceutical Science 3 7%
Other 9 21%
Unknown 8 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 17. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 June 2023.
All research outputs
#2,167,496
of 25,887,951 outputs
Outputs from PLoS Computational Biology
#1,884
of 9,065 outputs
Outputs of similar age
#13,179
of 179,631 outputs
Outputs of similar age from PLoS Computational Biology
#14
of 110 outputs
Altmetric has tracked 25,887,951 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,065 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.3. This one has done well, scoring higher than 79% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 179,631 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 110 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.