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The ‘pre’-revolution: Preregistration and preprints in biomedical research
Preprints, preregistration of study protocols (and in particular Registered Reports) are novel publishing formats that are currently gaining substantial traction. Besides rating the research question and soundness of methodology over outstanding significance of the results, they can help with antagonizing inadequate statistical power, selective reporting of results, undisclosed analytic flexibility, as well as publication bias. Preregistration works well when a clear hypothesis, primary outcome, and mode of analysis can be formulated. But is it also applicable and useful in discovery research, which develops theories and hypotheses, measurement techniques, and generates evidence that justifies further research? In my talk I will will argue that preregistration and registered reports, in combination with preprints, will revolutionize the way we disseminate and discuss scientific results, and that only slight modifications are needed to harness the potential of preregistration and make exploratory research more trustworthy and useful.
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Speakers

Prof. Ul­rich Dirnagl
@Charité Universitätsmedizin Berlin
At the Charité Universitätsmedizin Berlin Prof. Ul­rich Dirnagl serves as Director of the Department of Experimental Neurology. The research of Ulrich Dirnagl is focused on stroke, cerebral blood flow regulation, and brain imaging. In preclinical models as well as clinical trials he and his coworkers and collaborators explore mechanisms by which brain ischemia leads to cell death, and develops novel methods to intercept mechanisms of damage in acute brain damage, as well as to foster regeneration and repair of the lesions. Since 2017 he is also the founding director of the QUEST Center for Transforming Biomedical Research at the Berlin Institute of Health. QUEST (Quality-Ethics – Open Science – Translation) aims at overcoming the roadblocks in translational medicine by increasing the value and impact of biomedical research through maximizing the quality, reproducibility, generalizability, and validity of research.