How pharmaceutical innovation evolves: The path from science to technological development to marketable drugs
How pharmaceutical innovation evolves: The path from science to technological development to marketable drugs
复制标题
制药创新如何演变：从科学到技术开发再到可上市药物的路径
DOI：
10.1016/j.techfore.2021.120698
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发表时间：
2021-06
影响因子：
12
通讯作者：
Huang Heng
中科院分区：
文献类型：
--
作者：
Wang Xuefeng;Zhang Shuo;Liu Yuqin;Du Jian;Huang Heng
生物医学创新是将科学发现转化为疫苗、生物诊断试剂和基因工程药物和疗法的过程，这些药物和疗法可以拯救或改善患者的生命。这种类型的过程是典型的转化研究，然而在生物医学研究领域的许多努力都没有达到预期的结果，有些甚至造成了巨大的时间和资源浪费。较长的研发周期和将基础科学发现的知识转化为实用临床工具的低效方法是失败的主要原因。了解科学研究如何与技术发展共同进化，可以为生物医学创新的道路提供新的和深刻的见解。然而，近年来针对这一方面的研究并不多。因此，本文提出了一个详细追溯美国食品药品监督管理局批准的药物历史的框架。我们以科学论文和专利为数据源，采用定性和定量相结合的方法，分析了从发现到上市药品的创新过程。我们分析的重点是科技文件中的信息，这些信息可以作为翻译研究过程中发现和发展之间相互作用的指示器。然后，熵统计提供共享信息的指示，以便在分析中获得最大效用。包括专家判断在内的分析结果，可能会推动未来对生物医学创新的可能见解，并对政策制定者产生影响。
Biomedical innovation is the process of transforming scientific discoveries into vaccines, biodiagnostic reagents, and genetically-engineered drugs and therapies that save or improve patients’ lives. This type of process is typical of translational research, yet a great many efforts in the field of biomedical research fail to deliver the desired outcomes, and some even result in an enormous waste of time and resources. Long R&D periods and inefficient methods of transforming knowledge from basic scientific findings into practical clinical tools are the main reasons for failure. Understanding how scientific research co-evolves with technological development could provide novel and profound insights along the path of biomedical innovation. However, there are not many researches to deal with this aspect in recent years. Therefore, this paper presents a framework that traces the history of USFDA approved drugs in granular detail. Using scientific papers and patents as data sources, we use qualitative and quantitative techniques to analyze the innovation process from the inception of discovery into a marketable pharmaceutical. The focus of our analysis is the information found in science and technology documents, which can be an indicator of the interplays between discovery and development in a translational research process. Entropy statistics then provide an indication of the shared information for maximum utility in the analysis. The analysis results, which include expert judgments, could drive possible future insights into biomedical innovation with implications for policymakers.
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DOI：
10.1504/ijtm.2009.021519
发表时间：
2009
期刊：
Int. J. Technol. Manag.
影响因子：
--
作者：
Chun-Yao Tseng
通讯作者：
Chun-Yao Tseng
影响因子：
6.4
作者：
Casadevall A;Fang FC
通讯作者：
Fang FC
DOI：
10.1016/s0084-3954(09)79502-8
发表时间：
2010
期刊：
Yearbook of Pediatrics
影响因子：
--
作者：
J. Stockman
通讯作者：
J. Stockman
DOI：
10.1073/pnas.1504955112
发表时间：
2015-09-08
影响因子：
11.1
作者：
Bowen, Anthony;Casadevall, Arturo
通讯作者：
Casadevall, Arturo
影响因子：
4.9
作者：
Lee, E. Sally;McDonald, David W.;Anderson, Nicholas;Tarczy-Hornoch, Peter
通讯作者：
Tarczy-Hornoch, Peter