Publishing confirming and non-confirming data.

Bruce Alberts,Alexander Kamb

doi:10.12688/f1000research.7847.1

Bruce Alberts, Alexander Kamb

Open Access

https://doi.org/10.12688/f1000research.7847.1

Copy DOI

Abstract

This editorial introduces the Preclinical Reproducibility and Robustness channel on F1000Research, which has been created to encourage and facilitate open and transparent publication and discussion of confirmatory and non-confirmatory studies in biomedical research.

Highlights

This article is an Editorial and has not been subject to external peer review
Editorial In 2012 Begley and Ellis shocked the academic community by reporting that scientists at Amgen, a major biotech company, could not replicate the findings of nearly 90% of 53 high-profile oncology publications[1]
Many intriguing, but non-robust conclusions that remain unchallenged in the biomedical literature create opportunity costs for drug development, forcing both the biopharmaceutical industry and academic scientists to devote major resources to validating, rather than extending, results

Summary

Introduction

This article is an Editorial and has not been subject to external peer review. Any comments on the article can be found at the end of the article. Editorial In 2012 Begley and Ellis shocked the academic community by reporting that scientists at Amgen, a major biotech company, could not replicate the findings of nearly 90% of 53 high-profile oncology publications[1]. New efforts have begun to explicitly repeat a sample of the research reported in high-profile publications.

Results

Conclusion