Adam Ferguson, University of California San Francisco, San Fransisco, USA

Datasharing and bioinformatics for previously funded projects

Funded in: 2012, 2013, 2014

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Spinal cord injury produces numerous and complex biological changes. Preclinical researchers investigate the effects of experimental therapies by taking a broad range of outcome measures. These include, among others, functional recovery, electrophysiological parameters (like electromyography) and histological examinations.

However in most cases only a subset of these outcome measures reveal an improvement that can be unequivocally linked to the experimental treatment being tested. Based on these “limited” observations, it is therefore almost impossible to predict the real chances for a given experimental treatment to be successful within a human clinical trial.

The group working on this project has begun building a shared database repository of raw preclinical and clinical data with 8 research centers in the United States. It will now extend this effort to also include the data from European research centers. The long-term goal is to develop standardized experimental paradigms and to identify outcome measures that will allow cross-species comparison and injury type comparison.

Since many factors are involved in spinal cord injury, multivariate statistical pattern detectors may provide a robust assessment to determine which outcome measures truly describe the SCI syndrome and will reveal conserved (‘syndromic’) patterns for functional recovery.

This platform is expected to promote translational therapeutic development, and therefore increase the chances of an experimental treatment to successfully reach a clinically meaning endpoint. Add-on value of this approach (Datasharing and Bioinformatics) might be generated further by its extension to previously funded WfL-Projects (SCI-‘syndromics’) after approval of participating, Wfl-funded scientists.