ECNP Preclinical Network Data Prize

What is believed to be the world’s first prize for published “negative” scientific results, the “ECNP Preclinical Network Data Prize” has been announced by the ECNP’s Preclinical Data Forum. The €10,000 prize, aimed initially at neuroscience research, is to encourage publication of data where the results do not confirm the expected outcome or original hypothesis.

“Negative” findings – most often seen when researchers are unable to confirm or replicate previous results – are often not submitted for publication. Studies with positive results are several times more likely to be published than those which do not result in a positive result. As a consequence, these data are effectively lost to science, which may lead other scientists to waste time and effort trying to duplicate literature results. A recent paper* estimated that this costs the US economy alone, $28bn each year, similar in scale to the total $35bn National Institute of Health annual budget**.

According to Dr Thomas Steckler (ECNP Preclinical Data Forum co-Chair, Janssen Pharmaceutica NV):
“Science is historically self-correcting. This process is most effective when both positive and negative results are published. However, negative results are less likely to get published because they are often believed to generate less “value” for an individual scientist, organization or journal. Indeed, compared with the positive data, negative data may appear less exciting, are less likely to open new avenues of research and therefore new funding opportunities. Unpublished data is effectively a waste of valuable real and human capital, particularly in the face of the reproducibility challenge currently discussed in various fields of science: reproducibility in neuroscience has come under particular focus in recent years. It’s startling to realize that over 50% of published biomedical data cannot be reproduced*”.

The €10,000 annual prize money comes from sponsorship from the Cambridge, MA-based charity, Cohen Veterans Bioscience. It will be awarded by the ECNP’s Preclinical Data Forum, which is a mixed industry and academic group which aims to improve the replicability and reliability of scientific data, especially in drug development.

Dr Anton Bespalov (ECNP Preclinical Data Forum Co-Chair, PAASP), added
There are hundreds of drug trials which have failed in the last few years. Analysis of the factors that led to these failures is very often compromised by the biased representation of the early, preclinical work. The prize aims to emphasize to scientists and academic publishers that there is real value in publishing all the results, not just the headline-grabbing positive results”.

Advisory board

  • Celso Arango (ECNP)
  • Glenn Begley (BioCurate)
  • Ulrich Dirnagl (Charite)
  • Jonathan Flint (Oxford University)
  • Magali Haas (Cohen Veterans Bioscience)
  • Veronique Kiermer (PLoS)
  • Malcolm Macleod (Edinburgh University)
  • IJsbrand Jan Aalbersberg (Elsevier)   

Call for nominations


Publication Award

The ECNP Preclinical Data Forum opens a call for the nominations for the best publication of negative results in neuroscience. The award itself will be a monetary prize of 10,000 (ten thousand) Euro, made available through a generous sponsorship support provided by the Cohen Veterans Bioscience (https://www.cohenveteransbioscience.org/).

Read press release


Who may apply

Applications should be submitted by the first or corresponding author of a publication that:

  • Was written in English and was published or is accepted for publication in a peer-reviewed journal that is CURRENTLY listed by Web of Science and Scopus
  • Date of publication is not older than 1 January 2012
  • Reports results of a non-clinical study (or set of studies)
  • Is not a review
  • Is a full-length paper with detailed materials and methods section(s) (within the body of the paper or as supplementary information) 

It is expected the authors of to-be-nominated papers are confident that technical failures are not the reason for obtaining results. Further, the authors of to-be-nominated papers should be willing to share raw data with the third parties (if requested and not part of the publication).    


How to apply

Corresponding authors may nominate their papers by sending the PDF of the paper to Dr Anton Bespalov via e-mail, executive partner of the Award. Please include an accompanying letter indicating why you think the paper merits the award.  


Timelines

The call is open immediately after the publication of this announcement and will close on 30 June 2018.  The review committee will select and inform the winner by 1 August 2018.
The public announcement and presentation of the Award will take place in October 2018, during the ECNP Congress in Barcelona. The winner will be invited to present a talk. 
Travel and accommodation expenses will be covered by the ECNP, an Information Partner of the Award.


More information

Please contact Dr Anton Bespalov (PAASP) via e-mail.  

About ECNP
The European College of Neuropsychopharmacology (ECNP) is the parent organization hosting the Preclinical Data Forum Network. The ECNP is an independent scientific association dedicated to the science and treatment of disorders of the brain. It is the largest non-institutional supporter of applied and translational neuroscience research and education in Europe. Read more

About Cohen Veterans Bioscience
Cohen Veterans Bioscience is a national, nonpartisan 501(c)(3) research organization dedicated to fast-tracking the development of diagnostic tests and personalized therapeutics for the millions of veterans and civilians who suffer the devastating effects of trauma-related and other brain disorders. To support & learn more about our research efforts, visit www.cohenveteransbioscience.org .


References
*Kaiser, Science June 9th 2015. See http://www.sciencemag.org/news/2015/06/study-claims-28-billion-year-spent-irreproducible-biomedical-research  
** Science, July 17th, 2017
http://www.sciencemag.org/news/2017/07/house-bill-gives-nih-3-raise-blocks-cuts-overhead-payments