Professor Malcolm MacLeod (BSc(Hons) MBChB PhD FRCP Ed FRSB)
Professor of Neurology and Translational Neuroscience

- Centre for Clinical Brain Sciences
- Edinburgh CAMARADES group
- NHS Forth Valley
Contact details
- Email: Malcolm.macleod@ed.ac.uk
CV

Responsibilities & affiliations
- Member, Steering Committee, UK Reproducibility Network
- Convenor, Guarantors or EQIPD (www.eqipd.org)
- Academic Lead for Research Improvement and Research Integrity, University of Edinburgh
Research summary
Every week around 3500 new pieces of research involving animals are published. It is almost impossible for anyone to stay up to date with current knowledge. We have also shown that much of that work is at substantial risk of bias - and the effects observed in animals may be substantially overstated as a consequence.
In our research we are developing tools to provide unbiased summaries of what is already known, including tools to assess whether effects in animals may be overstated. We then use this information to help guide better design of clinical trials testing treatments in humans.
Examples of trials we have helped design using this approach include EuroHYP-1 - a trial of brain cooling in stroke - and MS-SMART, a trial in secondary progressive multiple sclerosis.
Research aims and areas of interest
My group has led the development and application of systematic review and meta-analysis to the analysis of data from animal studies modelling neurological diseases such as stroke. This work allows an overview of how effective the drug is in animals; identification of the limits to efficacy in animals which might be relevant to human clinical trials; and an assessment of the risk that the findings of animal studies are biased because of poor experimental design.
Now we are using this information to provide guidance to those using, funding, publishing and measuring the contribution of research involving animals. With others we are seeking to develop ways of providing real-time summaries of the current state of knowledge to guide future research and to help with research resource allocation decisions. We are also developing techniques of meta-moderation and mediation analysis to better understand pathophysiological pathways in animal models of human diseases such as multiple sclerosis.
I am involved in clinical trials in stroke including EuroHYP-1, a 1500-patient trial of brain cooling for acute ischaemic stroke; FOCUS, a trial of antidepressants following stroke; and phase 1 studies testing the effectiveness of local brain cooling in reducing brain temperature.
Research group members
- Dr Emily Sena, Senior Post Doc and Deputy Group Leader
- Dr Gillian Currie, Post-doc
- Dr Jing Liao, Programmer
- Zsanett Bahor, PhD student
- Alexandra Bannach-Brown, Joint Aarhus-Edinburgh MSc/PhD student
Collaborators
- Prof David Howells, Florey Neurosciences Institute, Melbourne, Australia
- Prof Andrew Rice, Imperial College, London
- Prof Uli Dirnagl, Charite, Berlin
- Prof Greg Wegener, Aarhus University, Denmark
Sources of funding
- European Commission Seventh Framework Programme (FP7)
- NC3Rs (National Centre for the Replacement, Refinement & Reduction of Animals in Research)
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What has preclinical systematic review ever done for us?
In:
BMJ Open Science, vol. 6, pp. e100219
DOI: https://doi.org/10.1136/bmjos-2021-100219
Research output: Contribution to Journal › Article (E-pub ahead of print) -
The reproducibility debate is an opportunity, not a crisis
In:
BMC Research Notes, vol. 15
DOI: https://doi.org/10.1186/s13104-022-05942-3
Research output: Contribution to Journal › Article (Published) -
Want research integrity? Stop the blame game
In:
Nature, vol. 599, pp. 533-533
DOI: https://doi.org/10.1038/d41586-021-03493-4
Research output: Contribution to Journal › Comment/debate (Published) -
Using median survival in meta-analysis of experimental time-to-event data
In:
Systematic Reviews, vol. 10
DOI: https://doi.org/10.1186/s13643-021-01824-0
Research output: Contribution to Journal › Article (Published) -
Risk of Bias Assessment in Preclinical Literature using Natural Language Processing
In:
Research Synthesis Methods
DOI: https://doi.org/10.1002/jrsm.1533
Research output: Contribution to Journal › Article (E-pub ahead of print)