↓ Skip to main content

Pharmacokinetic–Pharmacodynamic Modeling in Pediatric Drug Development, and the Importance of Standardized Scaling of Clearance

Overview of attention for article published in Clinical Pharmacokinetics, April 2018
Altmetric Badge

About this Attention Score

  • Good Attention Score compared to outputs of the same age (67th percentile)
  • Good Attention Score compared to outputs of the same age and source (70th percentile)

Mentioned by

policy
1 policy source
twitter
3 X users

Citations

dimensions_citation
57 Dimensions

Readers on

mendeley
119 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Pharmacokinetic–Pharmacodynamic Modeling in Pediatric Drug Development, and the Importance of Standardized Scaling of Clearance
Published in
Clinical Pharmacokinetics, April 2018
DOI 10.1007/s40262-018-0659-0
Pubmed ID
Authors

Eva Germovsek, Charlotte I. S. Barker, Mike Sharland, Joseph F. Standing

Abstract

Pharmacokinetic/pharmacodynamic (PKPD) modeling is important in the design and conduct of clinical pharmacology research in children. During drug development, PKPD modeling and simulation should underpin rational trial design and facilitate extrapolation to investigate efficacy and safety. The application of PKPD modeling to optimize dosing recommendations and therapeutic drug monitoring is also increasing, and PKPD model-based dose individualization will become a core feature of personalized medicine. Following extensive progress on pediatric PK modeling, a greater emphasis now needs to be placed on PD modeling to understand age-related changes in drug effects. This paper discusses the principles of PKPD modeling in the context of pediatric drug development, summarizing how important PK parameters, such as clearance (CL), are scaled with size and age, and highlights a standardized method for CL scaling in children. One standard scaling method would facilitate comparison of PK parameters across multiple studies, thus increasing the utility of existing PK models and facilitating optimal design of new studies.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 119 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 119 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 16%
Researcher 19 16%
Other 10 8%
Student > Master 9 8%
Student > Bachelor 7 6%
Other 16 13%
Unknown 39 33%
Readers by discipline Count As %
Pharmacology, Toxicology and Pharmaceutical Science 44 37%
Medicine and Dentistry 15 13%
Nursing and Health Professions 3 3%
Agricultural and Biological Sciences 3 3%
Immunology and Microbiology 2 2%
Other 8 7%
Unknown 44 37%
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 04 December 2022.
All research outputs
#6,009,600
of 23,221,875 outputs
Outputs from Clinical Pharmacokinetics
#466
of 1,503 outputs
Outputs of similar age
#104,260
of 327,691 outputs
Outputs of similar age from Clinical Pharmacokinetics
#8
of 27 outputs
Altmetric has tracked 23,221,875 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 1,503 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.7. This one has gotten more attention than average, scoring higher than 68% 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 327,691 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 27 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.