Abstract

![Figure][1] CREDIT: COURTESY OF MIN LIU/UNIVERSITY OF CINCINNATI ACADEMIC HEALTH CENTER The NewsFocus story by C. Wald and C. Wu, “Of Mice and Women: The Bias in Animal models” (26 March, p. [1571][2]), is one-sided. We agree that the choice of animal model requires care and that extrapolating data from one sex to the other can be misleading. However, we disagree with their statement that researchers use predominantly male mice because they are “cheaper and easier to work with.” First, many factors influence the choice of research subject. The most obvious are inherent differences in behavior (males fight) and physiology (female hormonal fluctuations); cost (more animals cost more money); and the incidence of strain-specific disorders (such as cancer and epilepsy). Our collective experience is that many researchers select less aggressive females because they can be group-housed to save money. This female bias will persist indefinitely given financial constraints on basic biomedical research, especially in academic laboratories. Second, “best practice” by U.S. federal regulatory agencies and research institutes as well as industry already requires that animal data used to predict human responses be obtained from both sexes. Examples include analysis of genetically engineered animals for translational medicine ([ 1 ][3]) and preclinical studies to investigate chemical carcinogenicity ([ 2 ][4]) or to develop new drugs ([ 3 ][5]) and pesticides ([ 4 ][6]). Definitive information on the role of gender in human disease must be obtained in humans because of intrinsic interspecies physiological differences, but animal studies remain the essential foundation for designing rational human clinical trials. Contributing to the issue of identifying whether there is a male or female bias in modern biomedical research is the consistent failure of researchers to report the critical experimental details—age, sex, strain or stock (with correct nomenclature), animal source, husbandry conditions, and health status—that are necessary to interpret studies. Including experienced comparative pathologists as co-investigators or journal reviewers [such as those recruited through the Center for Genomic Pathology ( )] would substantially enhance study designs and the credibility of data acquisition, analysis, interpretation, and reporting. 1. [↵][7] 1. C. Brayton, 2. M. Justice, 3. C. A. Montgomery , Vet. Pathol. 38, 1 (2001). [OpenUrl][8][Abstract/FREE Full Text][9] 2. [↵][10] U.S. Department of Health and Human Services, National Toxicology Program, “Studies in genetically modified models” ( ). 3. [↵][11] U.S. Department of Health and Human Services, Food and Drug Administration (FDA), “Guidance for industry: S6 preclinical safety evaluation of biotechnology-derived pharmaceuticals” ([www.fda.gov/downloads/RegulatoryInformation/Guidances/UCM129171.pdf][12]). 4. [↵][13] U.S. Environmental Protection Agency (EPA), Chemical Safety and Pollution Prevention, OCSPP Harmonized Test Guidelines ( ). [1]: pending:yes [2]: /lookup/doi/10.1126/science.327.5973.1571 [3]: #ref-1 [4]: #ref-2 [5]: #ref-3 [6]: #ref-4 [7]: #xref-ref-1-1 View reference 1 in text [8]: {openurl}?query=rft.jtitle%253DVeterinary%2BPathology%26rft.stitle%253DVeterinary%2BPathology%26rft.issn%253D0300-9858%26rft.aulast%253DBrayton%26rft.auinit1%253DC.%26rft.volume%253D38%26rft.issue%253D1%26rft.spage%253D1%26rft.epage%253D19%26rft.atitle%253DEvaluating%2BMutant%2BMice%253A%2BAnatomic%2BPathology%26rft_id%253Dinfo%253Adoi%252F10.1354%252Fvp.38-1-1%26rft_id%253Dinfo%253Apmid%252F11199155%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [9]: /lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6NToic3B2ZXQiO3M6NToicmVzaWQiO3M6NjoiMzgvMS8xIjtzOjQ6ImF0b20iO3M6MjU6Ii9zY2kvMzI4LzU5ODIvMTEwMy4xLmF0b20iO31zOjg6ImZyYWdtZW50IjtzOjA6IiI7fQ== [10]: #xref-ref-2-1 View reference 2 in text [11]: #xref-ref-3-1 View reference 3 in text [12]: http://www.fda.gov/downloads/RegulatoryInformation/Guidances/UCM129171.pdf [13]: #xref-ref-4-1 View reference 4 in text

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