The Economics of Reproducibility in Preclinical Research by Leonard P. Freedman, Iain M. Cockburn, Timothy S. Simcoe. PLOS Published: June 9, 2015 DOI: 10.1371/journal.pbio.1002165.
Abstract:
Low reproducibility rates within life science research undermine cumulative knowledge production and contribute to both delays and costs of therapeutic drug development. An analysis of past studies indicates that the cumulative (total) prevalence of irreproducible preclinical research exceeds 50%, resulting in approximately US$28,000,000,000 (US$28B)/year spent on preclinical research that is not reproducible—in the United States alone. We outline a framework for solutions and a plan for long-term improvements in reproducibility rates that will help to accelerate the discovery of life-saving therapies and cures.
The authors find four categories of irreproducibility:
(1) study design, (2) biological reagents and reference materials, (3) laboratory protocols, and (4) data analysis and reporting.
But only address “(1) study design, (2) biological reagents and reference materials.”
Once again, documentation doesn’t make the cut. 🙁
I find that curious because judging just from the flood of social media data, people in general spend a good part of every day capturing and transmitting information. Where is the pain point between that activity and formal documentation that makes the later into an anathema?
Documentation, among other things, could lead to higher reproducibility rates for medical and other research areas, to say nothing of saving data scientists time puzzling out data and/or programmers debugging old code.
Sites like “Rap Genius” seem to be devoted to lowering that pain point. Unfortunately, annotations are siloed by document.
Comment by shunting — June 21, 2015 @ 1:55 pm