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Building a disease knowledge environment to lay the foundations for in s#7/co drug discovery and translational medicine

机译:建立疾病知识环境,为s#7 / co药物发现和转化医学奠定基础

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摘要

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.
机译:在过去的十年中,每年新药批准的数量一直在减少。尽管这部分是由于法规要求的增加,但也应该认识到,制药行业正在努力为研发管线提供新型分子实体。由于生物医学信息的密度和复杂性经常阻止研究人员有效地提取相关知识以促进创新并支持明智的决策,因此创新差距正在扩大。在本文中,我们讨论了围绕疾病的生物医学知识汇编策略如何提供框架来提高制药行业的生产率。目的是在病理生理学相关的背景下系统地构建多学科数据,以最大化其治疗潜力。我们预测,通过这种方式,该行业最终应该能够利用-omics领域和高通量技术带来的投资回报,而这些领域近年来并未达到其期望。此外,我们希望在生物医学信息管理方式方面提出的战略性改变将支持未来计算机和系统生物学方法的发展,并促进转化研究。

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