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The scientific information landscape and applications to translational research


Investments made in biomedical and translational research have led to advancements in providing insights into the mechanisms and disease relevant markers that are implicated in human pathologies. This advancement has led to innovative approaches in designing basic research and clinical trial strategies that are more effective in translating the discoveries made at the bench to treatments delivered to the bedside.

In order for these advancements to be truly effective, traditional and coveted research silos should be broken down, making these discoveries more available so they may be shared and leveraged across the biomedical research community. This is expected to require a more open and collaborative environment in which privately and publicly funded researchers, primary investigators and clinicians work together through a knowledge exchange where they share and leverage their collective discoveries and insights in designing new, novel and innovative approaches to treating human diseases.

With the advent of this investment in biomedical research, technologies and collaborative networks comes an explosion of data; data derived from many different sources, structured in distinctly different formats, analysed using different tools and interpreted from different perspectives. A translational research informatics (TRI) strategy can be used to help overcome many of these challenges to help realise the potential this information brings to the advancement of new, novel, safe, effective and innovative treatments for human diseases.

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