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How pharmaceutical innovation evolves: The path from science to technological development to marketable drugs

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  • Wang, Xuefeng
  • Zhang, Shuo
  • Liu, Yuqin
  • Du, Jian
  • Huang, Heng

Abstract

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.

Suggested Citation

  • Wang, Xuefeng & Zhang, Shuo & Liu, Yuqin & Du, Jian & Huang, Heng, 2021. "How pharmaceutical innovation evolves: The path from science to technological development to marketable drugs," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    • Handle: RePEc:eee:tefoso:v:167:y:2021:i:c:s004016252100130x
    DOI: 10.1016/j.techfore.2021.120698
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    References listed on IDEAS

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    Cited by:

    1. Lu Huang & Yijie Cai & Erdong Zhao & Shengting Zhang & Yue Shu & Jiao Fan, 2022. "Measuring the interdisciplinarity of Information and Library Science interactions using citation analysis and semantic analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6733-6761, November.
    2. Xuefeng Wang & Shuo Zhang & Yuqin liu, 2022. "ITGInsight–discovering and visualizing research fronts in the scientific literature," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6509-6531, November.
    3. Naeini, Ali Bonyadi & Zamani, Mehdi & Daim, Tugrul U. & Sharma, Mahak & Yalcin, Haydar, 2022. "Conceptual structure and perspectives on “innovation management”: A bibliometric review," Technological Forecasting and Social Change, Elsevier, vol. 185(C).
    4. Yoon, Jeeyoung & Syafiandini, Arida Ferti & Song, Min, 2023. "Exploring the knowledge certainty shift: Metaknowledge analysis on drugs via assertion uncertainty burstiness," Journal of Informetrics, Elsevier, vol. 17(2).
    5. Shin, Hyunjin & Woo, Hyun Goo & Sohn, Kyung-Ah & Lee, Sungjoo, 2023. "Comparing research trends with patenting activities in the biomedical sector: The case of dementia," Technological Forecasting and Social Change, Elsevier, vol. 195(C).

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