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PEERS is a platform that enables sharing of information on parameters that affect the robustness of preclinical data.

What problem is PEERS trying to solve?


Information about parameters and factors that determine experimental robustness and therefore can influence the outcome of an experiment is either unclear or not available to scientists. The level of detail to inform about these parameters and factors is often not provided in most scientific publications. Scientists therefore often rely on their personal experience and personal communications. As a result, scientists have only limited access to relevant information and have little opportunity to learn from each other on how to increase the robustness and reproducibility of their studies or support translation to clinical programs.

How does PEERS work?

PEERS is like a WiKi on how to design, conduct and analyze experiments to increase data robustness. PEERS allows users to search for factors and parameters that are of relevance to their experiments and gives guidance and advice on how to leverage these factors to increase the quality, robustness and reproducibility of research.

PEERS allows users to:

  • Search for factors and parameters that are of relevance to their experiments 
  • Find recommendations and best practices on experimental design, execution and data analysis for specific in vitro methods or in vivo models
  • Share experiences and knowledge to help others build high-quality, reproducible data sets
  • Cite contributions 
  • Increase the quality, robustness and reproducibility of research


This work was funded by Cohen Veterans Bioscience and grants COH-0011 from Steven A. Cohen.

About Cohen Veterans Bioscience

Cohen Veterans BioscienceCohen Veterans Bioscience is a non-profit 501(c)(3) biomedical research and technology organization dedicated to advancing brain health by fast-tracking precision diagnostics and tailored therapeutics. Learn More at