The PEERS database is categorized into in vivo and in vitro experiments and provides lists of factors derived from scientific literature that have been deemed critical for experimentation. The platform is based on a structured and transparent system for rating the strength of evidence related to each identified factor and its relevance for a specific method/model. In this context, the rating procedure will not solely be limited to the PEERS working group but will also allow for a community-based grading of evidence. We here describe a working prototype using the Open Field paradigm in rodents and present the selection of
factors specific to each experimental setup and the rating system. PEERS not only offers users the possibility to search for information to facilitate experimental rigor, but also draws on the engagement of the scientific
community to actively expand the information contained within the platform. Collectively, by helping scientists search for specific factors relevant to their experiments, and to share experimental knowledge in a standardized manner, PEERS will serve as a collaborative exchange and analysis tool to enhance data validity and robustness as well as the reproducibility of preclinical research. PEERS offers a vetted, independent tool by which to judge the quality of information available on a certain test or model, identifies knowledge gaps and provides guidance on the key methodological considerations that should be
prioritized to ensure that preclinical research is conducted to the highest standards and best practice.
The PEERS Consortium is currently funded by Cohen Veterans Bioscience Ltd and grants COH-0011 from Steven A. Cohen.
We would like to thank IJsbrand Jan Aalbersberg, Natasja de Bruin, Philippe Chamiot-Clerc, Anja Gilis, Lieve Heylen, Martine Hofmann, Patricia Kabitzke, Isabel Lefevre, Janko Samardzic, Susanne Schiffmann and Guido Steiner for their valuable input and discussions during the conceptualization of PEERS and the initial phase of the project.
- study design
- quality rating
- study outcome
- animal models