IDEAS home Printed from https://ideas.repec.org/a/hig/fsight/v14y2020i3p55-70.html
   My bibliography  Save this article

The Next Pharmaceutical Path: Determining Technology Evolution in Drug Delivery Products Fabricated with Additive Manufacturing

Author

Listed:
  • Jessica Mancilla-de-la-Cruz

    (Tecnologico de Monterrey (Mexico))

  • Marisela Rodriguez-Salvador

    (Tecnologico de Monterrey (Mexico))

  • Laura Ruiz-Cantu

    (University of Nottingham (UK))

Abstract

Additive manufacturing (AM) is increasingly gaining a presence in the pharmaceutical industry, specifically in the reconfiguration of drug delivery systems wherein new products are being developed for administering pharmaceuticals inside the body, and drug testing systems wherein complex tissues are created to analyze medical treatments. This paper proposes a novel methodology of Competitive Technology Intelligence (CTI) to uncover the evolution of new drug delivery products where additive manufacturing is present. Using the multiple linear regression analysis and hype cycle model as a conceptual basis, we processed data from scientific papers and patents indexed by Scopus and PatSnap for the period of 2004–2019. The outcomes of this study can create a relevant knowledge base for decision-making on introducing novel technologies such as AM. Industrial and academic communities are devoting important efforts toward the advancement of AM in the health industry, especially pharmaceuticals. It is expected that this technology will bring new solutions to address fundamental global health problems. However, this technology is still in its very early stage. Therefore, investments should focus on research and development (R&D) to build a solid foundation for commercialization in the next decade.

Suggested Citation

  • Jessica Mancilla-de-la-Cruz & Marisela Rodriguez-Salvador & Laura Ruiz-Cantu, 2020. "The Next Pharmaceutical Path: Determining Technology Evolution in Drug Delivery Products Fabricated with Additive Manufacturing," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 14(3), pages 55-70.
    • Handle: RePEc:hig:fsight:v:14:y:2020:i:3:p:55-70
    as

    Download full text from publisher

    File URL: https://foresight-journal.hse.ru/data/2020/09/22/1584486699/5-Rodriguez-55-70.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. van Lente, Harro & Spitters, Charlotte & Peine, Alexander, 2013. "Comparing technological hype cycles: Towards a theory," Technological Forecasting and Social Change, Elsevier, vol. 80(8), pages 1615-1628.
    2. Dedehayir, Ozgur & Steinert, Martin, 2016. "The hype cycle model: A review and future directions," Technological Forecasting and Social Change, Elsevier, vol. 108(C), pages 28-41.
    3. White, Gareth R.T. & Samuel, Anthony, 2019. "Programmatic Advertising: Forewarning and avoiding hype-cycle failure," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 157-168.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. White, Gareth R.T. & Samuel, Anthony, 2019. "Programmatic Advertising: Forewarning and avoiding hype-cycle failure," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 157-168.
    2. Shi, Yuwei & Herniman, John, 2023. "The role of expectation in innovation evolution: Exploring hype cycles," Technovation, Elsevier, vol. 119(C).
    3. Kriechbaum, Michael & Posch, Alfred & Hauswiesner, Angelika, 2021. "Hype cycles during socio-technical transitions: The dynamics of collective expectations about renewable energy in Germany," Research Policy, Elsevier, vol. 50(9).
    4. Kriechbaum, Michael & López Prol, Javier & Posch, Alfred, 2018. "Looking back at the future: Dynamics of collective expectations about photovoltaic technology in Germany & Spain," Technological Forecasting and Social Change, Elsevier, vol. 129(C), pages 76-87.
    5. Uddin, Md Hamid & Mollah, Sabur & Ali, Md Hakim, 2020. "Does cyber tech spending matter for bank stability?," International Review of Financial Analysis, Elsevier, vol. 72(C).
    6. Hashemi, Fariba & Gallay, Olivier & Hongler, Max-Olivier, 2021. "Opinion formation dynamics — Swift collective disillusionment triggered by unmet expectations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 569(C).
    7. Thomas Davenport & Abhijit Guha & Dhruv Grewal & Timna Bressgott, 2020. "How artificial intelligence will change the future of marketing," Journal of the Academy of Marketing Science, Springer, vol. 48(1), pages 24-42, January.
    8. Hopkins, Debbie & Schwanen, Tim, 2023. "Sociotechnical expectations of vehicle automation in the UK trucking sector," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    9. Mejía, Cristian & Kajikawa, Yuya, 2019. "Technology news and their linkage to production of knowledge in robotics research," Technological Forecasting and Social Change, Elsevier, vol. 143(C), pages 114-124.
    10. Bjerkan, Kristin Ystmark & Ryghaug, Marianne, 2021. "Diverging pathways to port sustainability: How social processes shape and direct transition work," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    11. Jun, Seung-Pyo & Yoo, Hyoung Sun & Choi, San, 2018. "Ten years of research change using Google Trends: From the perspective of big data utilizations and applications," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 69-87.
    12. Gkoumas, Konstantinos & van Balen, Mitchell & Tsakalidis, Anastasios & Pekar, Ferenc, 2022. "Evaluating the development of transport technologies in European research and innovation projects between 2007 and 2020," Research in Transportation Economics, Elsevier, vol. 92(C).
    13. Giones, Ferran & Brem, Alexander, 2017. "From toys to tools: The co-evolution of technological and entrepreneurial developments in the drone industry," Business Horizons, Elsevier, vol. 60(6), pages 875-884.
    14. Dehler-Holland, Joris & Schumacher, Kira & Fichtner, Wolf, 2021. "Topic Modeling Uncovers Shifts in Media Framing of the German Renewable Energy Act," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 2(1).
    15. Stöcker, Claudia & Bennett, Rohan & Koeva, Mila & Nex, Francesco & Zevenbergen, Jaap, 2022. "Scaling up UAVs for land administration: Towards the plateau of productivity," Land Use Policy, Elsevier, vol. 114(C).
    16. Abdul-Manan, Amir F.N., 2017. "Lifecycle GHG emissions of palm biodiesel: Unintended market effects negate direct benefits of the Malaysian Economic Transformation Plan (ETP)," Energy Policy, Elsevier, vol. 104(C), pages 56-65.
    17. Mulley, Corinne & Nelson, John D. & Ho, Chinh & Hensher, David A., 2023. "MaaS in a regional and rural setting: Recent experience," Transport Policy, Elsevier, vol. 133(C), pages 75-85.
    18. René Lezama-Nicolás & Marisela Rodríguez-Salvador & Rosa Río-Belver & Iñaki Bildosola, 2018. "A bibliometric method for assessing technological maturity: the case of additive manufacturing," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(3), pages 1425-1452, December.
    19. Xiaoli Wang & Yun Liu & Lingdi Chen & Yifan Zhang, 2022. "Correlation Monitoring Method and model of Science-Technology-Industry in the AI Field: A Case of the Neural Network," SAGE Open, , vol. 12(4), pages 21582440221, December.
    20. Kalghatgi, Gautam, 2018. "Is it really the end of internal combustion engines and petroleum in transport?," Applied Energy, Elsevier, vol. 225(C), pages 965-974.

    More about this item

    Keywords

    competitive technology intelligence; additive manufacturing; patent analysis; hype cycle; 3D printing; pharmacy; targeted drug delivery; new treatments;
    All these keywords.

    JEL classification:

    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hig:fsight:v:14:y:2020:i:3:p:55-70. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Nataliya Gavrilicheva or Mikhail Salazkin (email available below). General contact details of provider: https://edirc.repec.org/data/hsecoru.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.