Development and uptake of an online systematic review platform: the early years of the CAMARADES Systematic Review Facility (SyRF)

Preclinical research is a vital step in the drug discovery pipeline and more generally in helping to better understand human disease aetiology and its management. Systematic reviews (SRs) can be powerful in summarising and appraising this evidence concerning a specific research question, to highlight areas of improvements, areas for further research and areas where evidence may be sufficient to take forward to other research domains, for instance clinical trial. Guidance and tools for preclinical research synthesis remain limited despite their clear utility. We aimed to create an online end-to-end platform primarily for conducting SRs of preclinical studies, that was flexible enough to support a wide variety of experimental designs, was adaptable to different research questions, would allow users to adopt emerging automated tools and support them during their review process using best practice. In this article, we introduce the Systematic Review Facility (https://syrf.org.uk), which was launched in 2016 and designed to support primarily preclinical SRs from small independent projects to large, crowdsourced projects. We discuss the architecture of the app and its features, including the opportunity to collaborate easily, to efficiently manage projects, to screen and annotate studies for important features (metadata), to extract outcome data into a secure database, and tailor these steps to each project. We introduce how we are working to leverage the use of automation tools and allow the integration of these services to accelerate and automate steps in the systematic review workflow.

[1]  Jing Liao,et al.  Machine learning algorithms for systematic review: reducing workload in a preclinical review of animal studies and reducing human screening error , 2019, Systematic Reviews.

[2]  Malcolm R. Macleod,et al.  A “LIVING” EVIDENCE SUMMARY OF PRIMARY RESEARCH RELATED TO COVID-19 , 2020 .

[3]  D. Finn,et al.  A protocol for the systematic review and meta-analysis of studies in which cannabinoids were tested for antinociceptive effects in animal models of pathological or injury-related persistent pain , 2019, Pain reports.

[4]  D. Moher,et al.  Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement , 2009, BMJ : British Medical Journal.

[5]  Murat Sariyar,et al.  The RecordLinkage Package: Detecting Errors in Data , 2010, R J..

[6]  J. Sluijter,et al.  The transverse aortic constriction heart failure animal model: a systematic review and meta-analysis , 2020, Heart Failure Reviews.

[7]  M. Briel,et al.  Dissemination Bias in Systematic Reviews of Animal Research: A Systematic Review , 2014, PloS one.

[8]  U. Dirnagl,et al.  Systematic review of guidelines for internal validity in the design, conduct and analysis of preclinical biomedical experiments involving laboratory animals , 2020, BMJ Open Science.

[9]  S. Ananiadou,et al.  Risk of bias reporting in the recent animal focal cerebral ischaemia literature , 2017, Clinical science.

[11]  Jing Liao,et al.  Automation of citation screening in pre-clinical systematic reviews , 2018, bioRxiv.

[12]  André Bleich,et al.  Software tools for literature screening in systematic reviews in biomedical research. , 2019, ALTEX.

[13]  M. Macleod,et al.  D-galactose-induced brain ageing model: A systematic review and meta-analysis on cognitive outcomes and oxidative stress indices , 2017, PloS one.

[14]  M. Macleod,et al.  Edinburgh Research Explorer Systematic Review and Meta-analysis of the Efficacy of Interleukin-1 Receptor Antagonist in Animal Models of Stroke: an Update , 2022 .

[15]  Alison O'Mara-Eves,et al.  The development and evaluation of an online application to assist in the extraction of data from graphs for use in systematic reviews , 2018, Wellcome open research.

[16]  The development and evaluation of an online application to assist in the extraction of data from graphs for use in systematic reviews , 2018, Wellcome Open Research.

[17]  M. Macleod,et al.  Understanding in vivo modelling of depression in non-human animals: a systematic review protocol , 2016 .