Evidence map›Paper›PMID 33350478›Full record

ReviewJournal of veterinary pharmacology and therapeutics2021

Physiological parameter values for physiologically based pharmacokinetic models in food-producing animals. Part III: Sheep and goat.

Miao Li, Yu-Shin Wang, Trevor Elwell-Cuddy, Ronald E Baynes, Lisa A Tell, Jennifer L Davis, Fiona P Maunsell, Jim E Riviere, Zhoumeng Lin

Abstract readReview
In one paragraph

Review in Journal of veterinary pharmacology and therapeutics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

19 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

9 authors.

Miao LiInstitute of Computational Comparative Medicine (ICCM), Department of Anatomy and Physiology, College of Veterinary Medicine, Kansas State University, Manhattan, KS, USA.ORCID https://orcid.org/0000-0001-9652-843X
Yu-Shin WangInstitute of Computational Comparative Medicine (ICCM), Department of Anatomy and Physiology, College of Veterinary Medicine, Kansas State University, Manhattan, KS, USA.ORCID https://orcid.org/0000-0003-0649-9634
Trevor Elwell-CuddyInstitute of Computational Comparative Medicine (ICCM), Department of Anatomy and Physiology, College of Veterinary Medicine, Kansas State University, Manhattan, KS, USA.
Ronald E BaynesCenter for Chemical Toxicology Research and Pharmacokinetics, Department of Population Health and Pathobiology, College of Veterinary Medicine, North Carolina State University, Raleigh, NC, USA.ORCID https://orcid.org/0000-0002-7920-9338
Lisa A TellDepartment of Medicine and Epidemiology, School of Veterinary Medicine, University of California-Davis, Davis, CA, USA.ORCID https://orcid.org/0000-0003-1823-7420
Jennifer L DavisDepartment of Biomedical Sciences and Pathobiology, Virginia-Maryland College of Veterinary Medicine, Blacksburg, VA, USA.ORCID https://orcid.org/0000-0002-7930-4589
Fiona P MaunsellDepartment of Large Animal Clinical Sciences, College of Veterinary Medicine, University of Florida, Gainesville, FL, USA.
Jim E RiviereInstitute of Computational Comparative Medicine (ICCM), Department of Anatomy and Physiology, College of Veterinary Medicine, Kansas State University, Manhattan, KS, USA.
Zhoumeng LinInstitute of Computational Comparative Medicine (ICCM), Department of Anatomy and Physiology, College of Veterinary Medicine, Kansas State University, Manhattan, KS, USA.ORCID https://orcid.org/0000-0002-8731-8366

Funding

National Institute of Food and Agriculture 2017-41480-27310National Institute of Food and Agriculture 2018-41480-28805National Institute of Food and Agriculture 2019-41480-30296United States Department of Agriculture
6 · The paper itself

Abstract

This report is the third in a series of studies that aimed to compile physiological parameters related to develop physiologically based pharmacokinetic (PBPK) models for drugs and environmental chemicals in food-producing animals including swine and cattle (Part I), chickens and turkeys (Part II), and finally sheep and goats (the focus of this manuscript). Literature searches were conducted in multiple databases (PubMed, Google Scholar, ScienceDirect, and ProQuest), with data on relevant parameters including body weight, relative organ weight (% of body weight), cardiac output, relative organ blood flow (% of cardiac output), residual blood volume (% of organ weight), and hematocrit reviewed and statistically summarized. The mean and standard deviation of each parameter are presented in tables. Equations describing the growth curves of sheep and goats are presented in figures. When data are sufficient, parameter values are reported for different ages or production classes of sheep, including fetal sheep, lambs, and market-age sheep (mature sheep). These data provide a reference database for developing standardized PBPK models to predict drug withdrawal intervals in sheep and goats, and also provide a basis for extrapolating PBPK models from major species such as cattle to minor species such as sheep and goats.

Indexed as

GoatsModels, BiologicalAnimalsCattleChickensOrgan SizeSheepSwineblood flowfood animal residue avoidance databankfood safetyorgan weightphysiologically based pharmacokinetic model

Identifiers

PMID33350478
PMCPMC8359294

What OpenQuestion holds

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LicenceCC BY-NC
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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 OpenQuestion graph.