Building a disease knowledge environment to lay the foundations for in silico drug discovery and translational medicine

Abstract

The number of new drug approvals per year has been decreasing consistently over the past decade. Although this is due in part to an increase in regulatory requirements, it should also be recognized that the pharmaceutical industry is struggling to feed R&D pipelines with novel molecular entities. The innovation gap is widening as the density and complexity of biomedical information often prevents researchers from efficiently extracting relevant knowledge to foster innovation and support informed decision making. In this article, we discuss how a biomedical knowledge compilation strategy focused around disease can provide a framework to enhance productivity within the pharmaceutical industry. The aim is to systematically structure multidisciplinary data in a pathophysiologically-relevant context in order to maximize its therapeutic potential. We predict that in this way the industry should finally be able to leverage on a return on investment from the -omics fields and high-throughput technologies that have failed to live up to its expectations in recent years. Furthermore, we expect that the proposed strategic change in the way biomedical information is managed will support the development of future in silico and systems biology approaches and promote translational research.

Keywords::

• disease information
• knowledge discovery
• knowledge management
• systems biology
• translational medicine

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