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Research synergy and drug development: Bright stars in neighboring constellations

机译：研究协同作用和药物开发：邻近星座中的亮星

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Drug discovery and subsequent availability of a new breakthrough therapeutic or ‘cure’ is a compelling example of societal benefit from research advances. These advances are invariably collaborative, involving the contributions of many scientists to a discovery network in which theory and experiment are built upon. To document and understand such scientific advances, data mining of public and commercial data sources coupled with network analysis can be used as a digital methodology to assemble and analyze component events in the history of a therapeutic. This methodology is extensible beyond the history of therapeutics and its use more generally supports (i) efficiency in exploring the scientific history of a research advance (ii) documenting and understanding collaboration (iii) portfolio analysis, planning and optimization (iv) communication of the societal value of research. Building upon prior art, we have conducted a case study of five anti-cancer therapeutics to identify the collaborations that resulted in the successful development of these therapeutics both within and across their respective networks. We have linked the work of over 235,000 authors in roughly 106,000 scientific publications that capture the research crucial for the development of these five therapeutics. Applying retrospective citation discovery, we have identified a core set of publications cited in the networks of all five therapeutics and additional intersections in combinations of networks. We have enriched the content of these networks by annotating them with information on research awards from the US National Institutes of Health (NIH). Lastly, we have mapped these awards to their cognate peer review panels, identifying another layer of collaborative scientific activity that influenced the research represented in these networks.
机译：药物的发现以及随后新的突破性治疗方法或“治愈方法”的可用性是研究进展带来社会利益的令人信服的例子。这些进步总是合作的，涉及许多科学家对基于理论和实验的发现网络的贡献。为了记录和理解这种科学进步，可以将公共和商业数据源的数据挖掘与网络分析一起用作一种数字方法，以组合和分析治疗史中的组分事件。这种方法可以扩展到治疗史之外，并且更广泛地用于支持（i）探索研究进展的科学历史的效率（ii）记录和理解合作（iii）资产组合分析，计划和优化（iv）沟通研究的社会价值。在现有技术的基础上，我们对五种抗癌疗法进行了案例研究，以鉴定导致这些疗法在各自网络内和跨网络成功开发的合作。我们已经将大约236,000名作者的工作与大约106,000种科学出版物相链接，这些出版物涵盖了对这五种疗法的发展至关重要的研究。应用回顾性引文发现，我们确定了所有五种疗法的网络以及网络组合中其他交叉口引用的一组核心出版物。我们通过为来自美国国立卫生研究院（NIH）的研究奖励信息提供注释来丰富这些网络的内容。最后，我们将这些奖项分配给了其相关的同行评审小组，确定了影响这些网络中代表的研究的另一层合作科学活动。

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