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Deterministic identifiability of population pharmacokinetic and pharmacokinetic–pharmacodynamic models

Overview of attention for article published in Journal of Pharmacokinetics and Pharmacodynamics, June 2017
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  • Good Attention Score compared to outputs of the same age (66th percentile)

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26 Mendeley
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Article details
Title
Deterministic identifiability of population pharmacokinetic and pharmacokinetic–pharmacodynamic models
Published in
Journal of Pharmacokinetics and Pharmacodynamics, June 2017
DOI 10.1007/s10928-017-9530-4
Pubmed ID
Authors
Abstract

Identifiability is an important component of pharmacokinetic-pharmacodynamic (PKPD) model development. Structural identifiability is concerned with the uniqueness of the model parameters for a set of perfect input-output data and deterministic identifiability with the precision of parameter estimation given imperfect input-output data. We introduce two subcategories of deterministic identifiability, external and internal, and consider factors that distinguish between these forms. We define external deterministic identifiability as a function of externally controllable variables, i.e., the design, and internal deterministic identifiability as a function of the model and its parameter values. The concepts are explored using three common PK and PKPD models, and verified for their precision for the selected set of parameter values under optimal design.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 26 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 6 23%
Student > Bachelor 5 19%
Researcher 4 15%
Student > Master 3 12%
Professor > Associate Professor 2 8%
Other 2 8%
Unknown 4 15%
Readers by discipline
Readers by discipline Count As %
Pharmacology, Toxicology and Pharmaceutical Science 10 38%
Biochemistry, Genetics and Molecular Biology 3 12%
Medicine and Dentistry 2 8%
Mathematics 1 4%
Agricultural and Biological Sciences 1 4%
Other 3 12%
Unknown 6 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 11 July 2017.
All research outputs
#8,203,752
of 28,007,560 outputs
Outputs from Journal of Pharmacokinetics and Pharmacodynamics
#72
of 339 outputs
Outputs of similar age
#111,983
of 339,283 outputs
Outputs of similar age from Journal of Pharmacokinetics and Pharmacodynamics
#2
of 4 outputs
Altmetric has tracked 28,007,560 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 339 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.6. This one has done well, scoring higher than 78% 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 339,283 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 66% of its contemporaries.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.