FEB 03, 2016 09:00 AM PST
Keynote: Risks of Bias in in vivo research - and what to do about them
Presented at the Laboratory Animal Sciences Virtual Event
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  • Professor of Neurology and Translational Neuroscience, Centre for Clinical Brain Sciences, University of Edinburgh
      Malcolm Macleod is Professor in Neurology and Translational Neuroscience at the Centre for Clinical Brain Sciences, University of Edinburgh, and Head of Neurological Diseases and Stroke at NHS Forth Valley. After undergraduate medicine (including an intercollated degree in Pharmacology) he trained in Internal Medicine before a PhD in the Butcher lab investigating the neuroprotective actions of FK506. This was followed by post-doctoral work in the Seckl lab defining a neuroprotective role for increased expression of the mineralocorticoid receptor.

      While this work continued he completed his training in Neurology, including a pivotal sabbatical year with Donnan at the National Stroke Research Institute, Melbourne, Australia. During this time he began an involvement with stroke clinical trials, and it was in an effort to identify suitable drugs for such clinical trials that he started to develop techniques to allow the systematic review and meta-analysis of data from animal studies.

      This led to the founding of the Collaborative Approach to Meta-analysis and Review of Animal Data from Experimental Studies (CAMARADES) in 2005. Since then these approaches have found application in a diversity of models, and the CAMARADES group, under his leadership, have build up considerable expertise in this area. He was on the writing committee for the Landis guidelines, contributed to the Lancet "Waste in Research" series, and is an investigator on the MultiPART program developing structures for multicentre animal studies. He is a member of the UK MHRA Commission for Human Medicines and the UK Home Office Animals in Science Committee, and is co-Chief Investigator of EuroHYP-1, a European RCT of brain cooling for stroke.

    Translational failure in biomedicine has led to much soul-searching about the causes for this. Amongst many others (misunderstanding of statistical tests, vibration of effects, flexibility in data analysis, HARKing) there is a primary problem with bias in the way in which animal studies are planned, conducted and analysed. Reporting of measures to reduce the risk of bias  is poor, and the most parsimonious explanation for this is that the measures were not taken (rather than not reported). Studies at such risk of bias give inflated estimates of biological effects. 
    Risk of bias is a pervasive problem across institutions, journals, and research fields, and attempts to improve research quality have, to date, had little apparent effect. It seems that “on the street”, scientists still feel that the pressure to publish novel findings in journals of high impact is substantially greater than the pressure to conduct their research to the highest (or even to moderately high) quality; and in response to these competing pressures research quality remains low. 
    To secure greatest value from the resources invested in research (including animals), this needs to be changed.

    Two Learning Objectives
    1. Participants will understand the importance, and prevalence, of reporting of measures to reduce the risks of bias in in vivo research
    2. Participants will be aware of some of the proposed strategies to improve the quality of in vivo research

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