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Application of a physiologically-based pharmacokinetic model for the prediction of bumetanide plasma and brain concentrations in the neonate

Overview of attention for article published in Biopharmaceutics & Drug Disposition, February 2018
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  • Good Attention Score compared to outputs of the same age (67th percentile)

Mentioned by

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4 tweeters

Citations

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7 Dimensions

Readers on

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27 Mendeley
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Title
Application of a physiologically-based pharmacokinetic model for the prediction of bumetanide plasma and brain concentrations in the neonate
Published in
Biopharmaceutics & Drug Disposition, February 2018
DOI 10.1002/bdd.2119
Pubmed ID
Authors

Maria D. Donovan, Khaled Abduljalil, John F. Cryan, Geraldine B. Boylan, Brendan T. Griffin

Abstract

Bumetanide is a loop diuretic that is proposed to possess a beneficial effect on disorders of the central nervous system, including neonatal seizures. Therefore, prediction of unbound bumetanide concentrations in brain is relevant from a pharmacological prospective. A physiologically-based pharmacokinetic (PBPK) model was developed for the prediction of bumetanide disposition in plasma and brain in adult and pediatric populations. A compound file was built for bumetanide integrating physicochemical data and in vitro data. Bumetanide concentration profiles were simulated in both plasma and brain using Simcyp PBPK model. Simulations of plasma bumetanide concentrations were compared against plasma levels published in literature. The model performance was verified with data from adult studies before predictions in the pediatric population were undertaken. The adult and pediatric intravenous models predicted pharmacokinetic factors, namely area under the concentration-time curve, maximum concentration in plasma and time to maximum plasma concentration, within two-fold of observed values. However, predictions of plasma concentrations within the neonatal intravenous model did not produce a good fit with observed values. The PBPK approach used in this study produced reasonable predictions of plasma concentrations of bumetanide, except in the critically ill neonatal population. This PBPK model requires more information regarding metabolic intrinsic clearance and transport parameters prior to further validation of drug disposition predictions in the neonatal population. Given the lack of information surrounding certain parameters in this special population, the model is not appropriately robust to support the recommendation of a suitable dose of bumetanide for use as an adjunct antiepileptic in neonates.

Twitter Demographics

The data shown below were collected from the profiles of 4 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 27 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 22%
Professor > Associate Professor 3 11%
Student > Doctoral Student 3 11%
Researcher 3 11%
Student > Bachelor 2 7%
Other 7 26%
Unknown 3 11%
Readers by discipline Count As %
Pharmacology, Toxicology and Pharmaceutical Science 7 26%
Medicine and Dentistry 7 26%
Agricultural and Biological Sciences 2 7%
Mathematics 1 4%
Neuroscience 1 4%
Other 0 0%
Unknown 9 33%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 12 February 2018.
All research outputs
#3,381,189
of 12,498,628 outputs
Outputs from Biopharmaceutics & Drug Disposition
#62
of 301 outputs
Outputs of similar age
#111,015
of 340,840 outputs
Outputs of similar age from Biopharmaceutics & Drug Disposition
#1
of 3 outputs
Altmetric has tracked 12,498,628 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 301 research outputs from this source. They receive a mean Attention Score of 3.6. 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 340,840 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them