This infrastructure award will maximise the 3Rs potential of undertaking systematic reviews and meta-analyses of animal research.
Systematic reviews and meta-analyses are common practice in clinical research. They remain relatively under-utilised in animal research although recent reviews have illustrated their potential 3Rs benefits for example, supporting a reduction in animal numbers, determining whether high severity tests or multiple tests are necessary, and avoiding the use of uninformative models.
Research details and methods
The award will support the development of online resources and hands on support facilitating the wider use of systematic reviews and meta-analyses by researchers.
Systematic review and meta-analysis can provide empirical evidence of the impact of internal and external validity of in vivo studies across research domains. We spend substantial time supporting those who wish to conduct such reviews in their own fields through methodological advice and support, a data repository, and access to our database.
This database can now be used in the analysis of diverse data, from animal models of stroke to receptor binding assays. It includes data from over 3,000 publications involving over 80,000 animals. Currently, we curate data on MS Access, accessed by external users via a secure remote desktop connection; migration to an SQL server based database will improve system performance, scalability and accessibility. Providing web based access backed up by the support of a research will substantially improve our effectiveness in supporting such activity. We will also provide user manuals, online training materials and telephone advice.
Our support will include systematic reviews and meta-analyses of preclinical studies, with calculation of summary effect sizes and determination in that model system of the impact of study design features and risk of bias items. For a given disease model, we will identify the outcome measure with the smallest variance. This will help reduce the number of animals used in future studies. We will provide information for power calculations, so that the number of animals sacrificed in studies are neither too small to detect reliably the effect being sought or unnecessarily large. We will determine whether high severity, multiple and lengthy experiments provide more information than low severity, single, short experiments. This will inform ethical considerations about the choice of measures to be used, supporting a reduction in the suffering of the animals. We will undertake secondary analyses investigating issues such as publication bias, and improvements in the quality of study reports over time.
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