Evidence map›Paper›PMID 34617262›Full record

ArticleClinical pharmacokinetics2022

Development and Evaluation of a Virtual Population of Children with Obesity for Physiologically Based Pharmacokinetic Modeling.

Jacqueline G Gerhart, Fernando O Carreño, Andrea N Edginton, Jaydeep Sinha, Eliana M Perrin, Karan R Kumar, Aruna Rikhi, Christoph P Hornik, Vincent Harris, Samit Ganguly and 3 more

Open access · hybridAbstract read
In one paragraph

Article in Clinical pharmacokinetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
4.2field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

32 citing papers in PubMed, 37 citations in OpenAlex.

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  14. Creativity in Pediatric Clinical Pharmacology: Study Design and Oral Dosage Forms.The journal of pediatric pharmacology and therapeutics : JPPT : the official journal of PPAG · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 5 institutions in 2 countries.

Jacqueline G GerhartDivision of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, The University of North Carolina at Chapel Hill, 301 Pharmacy Lane, Campus Box #7569, Chapel Hill, NC, 27599-7569, USA.
Fernando O CarreñoDivision of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, The University of North Carolina at Chapel Hill, 301 Pharmacy Lane, Campus Box #7569, Chapel Hill, NC, 27599-7569, USA.
Andrea N EdgintonSchool of Pharmacy, University of Waterloo, Waterloo, ON, Canada.
Jaydeep SinhaDivision of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, The University of North Carolina at Chapel Hill, 301 Pharmacy Lane, Campus Box #7569, Chapel Hill, NC, 27599-7569, USA.
Eliana M PerrinDepartment of Pediatrics, School of Medicine and School of Nursing, Johns Hopkins University, Baltimore, MD, USA.
Karan R KumarDuke Clinical Research Institute, Durham, NC, USA.
Aruna RikhiDuke Clinical Research Institute, Durham, NC, USA.
Christoph P HornikDuke Clinical Research Institute, Durham, NC, USA.
Vincent HarrisDivision of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, The University of North Carolina at Chapel Hill, 301 Pharmacy Lane, Campus Box #7569, Chapel Hill, NC, 27599-7569, USA.
Samit GangulyDivision of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, The University of North Carolina at Chapel Hill, 301 Pharmacy Lane, Campus Box #7569, Chapel Hill, NC, 27599-7569, USA.
Michael Cohen-WolkowiezDuke Clinical Research Institute, Durham, NC, USA.
Daniel GonzalezDivision of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, The University of North Carolina at Chapel Hill, 301 Pharmacy Lane, Campus Box #7569, Chapel Hill, NC, 27599-7569, USA. daniel.gonzalez@unc.edu.ORCID 0000-0001-5522-5686
Best Pharmaceuticals for Children Act—Pediatric Trials Network Steering Committee
University of North Carolina at Chapel Hill · USDuke University · USClinical Research Institute · USJohns Hopkins University · USUniversity of Waterloo · CA

Funding

Physiologically-Based Pharmacokinetic Modeling to Guide Drug Dosing in Children with ObesityR01HD096435 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI DUMOND, JULIE BRUMER · 2018 to 2022
$2.0M
Enhancement Training for the Next Generation of Translational Ph.D. ScientistsT32GM122741 · NIGMS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI WOLBERG, ALISA S., YEH, JEN JEN · 2018 to 2022
$898k
NICHD NIH HHS HHSN275201000003CNICHD NIH HHS HHSN275201000003INICHD NIH HHS R01 HD096435NIGMS NIH HHS T32 GM122741
6 · The paper itself

Abstract

BACKGROUND AND

objectiveWhile one in five children in the USA are now obese, and more than three-quarters receive at least one drug during childhood, there is limited dosing guidance for this vulnerable patient population. Physiologically based pharmacokinetic modeling can bridge the gap in the understanding of how pharmacokinetics, including drug distribution and clearance, changes with obesity by incorporating known obesity-related physiological changes in children. The objective of this study was to develop a virtual population of children with obesity to enable physiologically based pharmacokinetic modeling, then use the novel virtual population in conjunction with previously developed models of clindamycin and trimethoprim/sulfamethoxazole to better understand dosing of these drugs in children with obesity.

methodsTo enable physiologically based pharmacokinetic modeling, a virtual population of children with obesity was developed using national survey, electronic health record, and clinical trial data, as well as data extracted from the literature. The virtual population accounts for key obesity-related changes in physiology relevant to pharmacokinetics, including increased body size, body composition, organ size and blood flow, plasma protein concentrations, and glomerular filtration rate. The virtual population was then used to predict the pharmacokinetics of clindamycin and trimethoprim/sulfamethoxazole in children with obesity using previously developed physiologically based pharmacokinetic models.

resultsModel simulations predicted observed concentrations well, with an overall average fold error of 1.09, 1.24, and 1.53 for clindamycin, trimethoprim, and sulfamethoxazole, respectively. Relative to children without obesity, children with obesity experienced decreased clindamycin and trimethoprim/sulfamethoxazole weight-normalized clearance and volume of distribution, and higher absolute doses under recommended pediatric weight-based dosing regimens.

conclusionsModel simulations support current recommended weight-based dosing in children with obesity for clindamycin and trimethoprim/sulfamethoxazole, as they met target exposure despite these changes in clearance and volume of distribution.

Indexed as

ClindamycinObesityBody CompositionChildGlomerular Filtration RateHumansModels, BiologicalTrimethoprim, Sulfamethoxazole Drug CombinationClindamycinTrimethoprim, Sulfamethoxazole Drug Combination

Identifiers

PMID34617262
PMCPMC8813791
OpenAlexW3203265145

What Socratic holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.