Accelerating Biomedical Discoveries through Rigor and Transparency

ILAR J. 2017 Jul 1;58(1):115-128. doi: 10.1093/ilar/ilx011.

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.

Keywords: animal models; bias; qualification; quality; reproducibility; rigor; statistics; transparency.

MeSH terms

  • Animals
  • Biomedical Research
  • Disease Models, Animal*
  • Information Storage and Retrieval / standards*
  • Reproducibility of Results