Pathology principles and practices for analysis of animal models Journal Article


Authors: Knoblaugh, S. E.; Hohl, T. M.; La Perle, K. M. D.
Article Title: Pathology principles and practices for analysis of animal models
Abstract: Over 60% of NIH extramural funding involves animal models, and approximately 80% to 90% of these are mouse models of human disease. It is critical to translational research that animal models are accurately characterized and validated as models of human disease. Pathology analysis, including histopathology, is essential to animal model studies by providing morphologic context to in vivo, molecular, and biochemical data; however, there are many considerations when incorporating pathology endpoints into an animal study. Mice, and in particular genetically modified models, present unique considerations because these modifications are affected by background strain genetics, husbandry, and experimental conditions. Comparative pathologists recognize normal pathobiology and unique phenotypes that animals, including genetically modified models, may present. Beyond pathology, comparative pathologists with research experience offer expertise in animal model development, experimental design, optimal specimen collection and handling, data interpretation, and reporting. Critical pathology considerations in the design and use of translational studies involving animals are discussed, with an emphasis on mouse models. © The Author(s) 2019. Published by Oxford University Press on behalf of the National Academy of Sciences. All rights reserved. For permissions, please email: journals.permissions@oup.com.
Keywords: phenotype; mice; pathology; translational research; animal models; scoring; genetically modified; preclinical
Journal Title: ILAR Journal
Volume: 59
Issue: 1
ISSN: 1084-2020
Publisher: Oxford University Press  
Date Published: 2018-01-01
Start Page: 40
End Page: 50
Language: English
DOI: 10.1093/ilar/ilz001
PUBMED: 31053847
PROVIDER: scopus
PMCID: PMC6927822
DOI/URL:
Notes: Source: Scopus
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  1. Tobias Martin Hohl
    105 Hohl