过程(计算)
数据科学
计算机科学
管理科学
知识管理
风险分析(工程)
业务
工程类
操作系统
作者
Xuefeng Wang,Shuo Zhang,Yuqin Liu,Jian Du,Heng Huang
标识
DOI:10.1016/j.techfore.2021.120698
摘要
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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