Web-tool to improve preclinical intervention studies

Published 27 September 2016
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Two Finnish teams at FIMM and TCDM, both being affiliates of EATRIS, have developed a bioinformatics tool to overcome limitations in the experimental design and statistical analysis of preclinical in vivo studies aiming to improve reproducibility, validity and translatability of animal experiments.

The teams headed by Tero Aittokallio and Matti Poutanen recently published a web tool called R-vivo which is a web interface to the open-source R package ‘hamlet’ and freely accessible at http://rvivo.tcdm.fi/. The tool implements a matching-based modelling approach for optimal intervention group allocation, randomization and power calculations in the context of preclinical in vivo studies. It enables researchers to conduct adequately-powered and fully-randomized preclinical intervention studies, with the aim to accelerate the discovery of new therapeutic interventions. The algorithm takes full account of the complex animal characteristics at baseline prior to interventions, increasing statistical power to detect true treatment effects at smaller sample sizes, thereby saving both animal lives and research costs.

The web tool provides the researcher with a variety of features including matching and randomization algorithms, mixed-effect modelling and power analysis, comprehensive data visualizations and an intuitive interface guiding the user in a workflow-like manner. New users are provided with representative example data readily usable from the analysis start page.

The ‘hamlet’ R package can be downloaded from http://cran.r-project.org/package=hamlet and the corresponding publication is available at PubMed Central (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4969752/).