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Updated: Mar 1, 2026

Author Spotlight: Advancing Biomedical Research Through Single Cell Analysis
Published on: December 22, 2023
Accelerating Biomedical Discoveries through Rigor and Transparency
Judith A Hewitt1, Liliana L Brown1, Stephanie J Murphy1
1Office of Biodefense, Research Resources and Translational Research, Division of Microbiology and Infectious Diseases, National Institute of Allergy and Infectious Diseases, Bethesda, MD. Office of Genomics and Advanced Technologies, Division of Microbiology and Infectious Diseases, National Institute of Allergy and Infectious Diseases, Bethesda, MD. Division of Comparative Medicine, Office of Infrastructure Programs, Division of Program Coordination, Planning, and Strategic Initiatives, Office of the Director at the National Institutes of Health, Bethesda, MD. Office of Infrastructure Programs, Division of Program Coordination, Planning, and Strategic Initiatives, Office of the Director, National Institutes of Health, Bethesda, MD. National Institute of Neurological Disorders and Stroke, Bethesda MD.
Abstract:
Difficulties in reproducing published research findings have garnered a lot of press in recent years. As a funder of biomedical research, the National Institutes of Health (NIH) has taken measures to address underlying causes of low reproducibility. Extensive deliberations resulted in a policy, released in 2015, to enhance reproducibility through rigor and transparency. We briefly explain what led to the policy, describe its elements, provide examples and resources for the biomedical research community, and discuss the potential impact of the policy on translatability with a focus on research using animal models. Importantly, while increased attention to rigor and transparency may lead to an increase in the number of laboratory animals used in the near term, it will lead to more efficient and productive use of such resources in the long run. The translational value of animal studies will be improved through more rigorous assessment of experimental variables and data, leading to better assessments of the translational potential of animal models, for the benefit of the research community and society.
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