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A Triple Helix Model of Medical Innovation: Supply, Demand, and Technological Capabilities in terms of Medical Subject Headings

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  • Alexander Petersen

    (Laboratory for the Analysis of Complex Economic Systems, IMT Institute for Advanced Studies, Lucca, Italy)

  • Daniele Rotolo

    (SPRU, Science Policy Research Unit, University of Sussex, Brighton, United Kingdom)

  • Loet Leydesdor

    (Amsterdam School of Communication Research (ASCoR), University of Amsterdam, Amsterdam, Netherlands)

Abstract

We develop a model of innovation that enables us to trace the interplay among three key dimensions of the innovation process: (i) demand of and (ii) supply for innovation, and (iii) technological capabil- ities available to generate innovation in the forms of products, processes, and services. Building on triple helix research, we use entropy statistics to elaborate an indicator of mutual information among these dimensions that can provide indication of reduction of uncertainty. To do so, we focus on the medical context, where uncertainty poses signi cant challenges to the governance of innovation. We use the Medical Subject Headings (MeSH) of MEDLINE/PubMed to identify publications classi ed within the categories \Diseases" (C), \Drugs and Chemicals" (D), \Analytic, Diagnostic, and Ther- apeutic Techniques and Equipment" (E) and use these as knowledge representations of demand, supply, and technological capabilities, respectively. Three case-studies of medical research areas are used as representative 'entry perspectives' of the medical innovation process. These are: (i) human papilloma virus, (ii) RNA interference, and (iii) magnetic resonance imaging. We nd statistically signi cant periods of synergy among demand, supply, and technological capabilities (C??D??E) that point to three-dimensional interactions as a fundamental perspective for the understanding and gov- ernance of the uncertainty associated with medical innovation. Among the pairwise con gurations in these contexts, the demand-technological capabilities (C??E) provided the strongest link, followed by the supply-demand (D ?? C) and the supply-technological capabilities (D ?? E) channels.

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  • Alexander Petersen & Daniele Rotolo & Loet Leydesdor, 2016. "A Triple Helix Model of Medical Innovation: Supply, Demand, and Technological Capabilities in terms of Medical Subject Headings," SPRU Working Paper Series 2016-01, SPRU - Science Policy Research Unit, University of Sussex Business School.
    • Handle: RePEc:sru:ssewps:2016-01
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    2. Yaqub, Ohid & Coburn, Josie & Moore, Duncan A.Q., 2023. "Knowledge spillovers from HIV research-funding," SocArXiv gcuhn, Center for Open Science.
    3. Petersen, Alexander M. & Rotolo, Daniele & Leydesdorff, Loet, 2016. "A triple helix model of medical innovation: Supply, demand, and technological capabilities in terms of Medical Subject Headings," Research Policy, Elsevier, vol. 45(3), pages 666-681.
    4. François Lafond & Daniel Kim, 2019. "Long-run dynamics of the U.S. patent classification system," Journal of Evolutionary Economics, Springer, vol. 29(2), pages 631-664, April.
    5. Loet Leydesdorff & Igone Porto-Gomez, 2019. "Measuring the expected synergy in Spanish regional and national systems of innovation," The Journal of Technology Transfer, Springer, vol. 44(1), pages 189-209, February.
    6. Nicola Grassano & Daniele Rotolo & Joshua Hutton & Frédérique Lang & Michael M. Hopkins, 2017. "Funding Data from Publication Acknowledgments: Coverage, Uses, and Limitations," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(4), pages 999-1017, April.
    7. 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).
    8. Altaf, Aqsa & Hassan, Ibn e & Batool, Sana, 2019. "The role of ORIC in the evolution of the triple helix culture of innovation: The case of Pakistan," Technology in Society, Elsevier, vol. 56(C), pages 157-166.
    9. Ivanova, Inga & Strand, Øivind & Kushnir, Duncan & Leydesdorff, Loet, 2017. "Economic and technological complexity: A model study of indicators of knowledge-based innovation systems," Technological Forecasting and Social Change, Elsevier, vol. 120(C), pages 77-89.
    10. Inga Ivanova & Øivind Strand & Loet Leydesdorff, 2019. "What Is the Effect of Synergy Provided by International Collaborations on Regional Economies?," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 10(1), pages 18-34, March.
    11. Inga Ivanova & Nataliya Smorodinskaya & Loet Leydesdorff, 2020. "On measuring complexity in a post-industrial economy: the ecosystem’s approach," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(1), pages 197-212, February.
    12. Ryosuke L. Ohniwa & Aiko Hibino, 2019. "Generating process of emerging topics in the life sciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(3), pages 1549-1561, December.
    13. Hoppmann, Joern, 2021. "Hand in hand to Nowhereland? How the resource dependence of research institutes influences their co-evolution with industry," Research Policy, Elsevier, vol. 50(2).
    14. Yuti Ariani Fatimah & Saurabh Arora, 2016. "Nonhumans in the Practice of Development: Material Agency and Friction in a Small-Scale Energy Program in Indonesia," SPRU Working Paper Series 2016-04, SPRU - Science Policy Research Unit, University of Sussex Business School.
    15. Ke, Qing, 2020. "An analysis of the evolution of science-technology linkage in biomedicine," Journal of Informetrics, Elsevier, vol. 14(4).
    16. Jordan A. Comins & Loet Leydesdorff, 2017. "Citation algorithms for identifying research milestones driving biomedical innovation," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(3), pages 1495-1504, March.
    17. Matthew L. Wallace & Ismael Rafols, 2016. "Shaping the Agenda of a Grand Challenge: Institutional Mediation of Priorities in Avian Influenza Research," SPRU Working Paper Series 2016-02, SPRU - Science Policy Research Unit, University of Sussex Business School.
    18. Kevin W. Boyack, 2017. "Thesaurus-based methods for mapping contents of publication sets," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 1141-1155, May.
    19. Ávila-Robinson, Alfonso & Islam, Nazrul & Sengoku, Shintaro, 2019. "Co-evolutionary and systemic study on the evolution of emerging stem cell-based therapies," Technological Forecasting and Social Change, Elsevier, vol. 138(C), pages 324-339.
    20. Loet Leydesdorff & Jordan A. Comins & Aaron A. Sorensen & Lutz Bornmann & Iina Hellsten, 2016. "Cited references and Medical Subject Headings (MeSH) as two different knowledge representations: clustering and mappings at the paper level," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 2077-2091, December.
    21. Li, Xin & Tang, Xuli, 2021. "Characterizing interdisciplinarity in drug research: A translational science perspective," Journal of Informetrics, Elsevier, vol. 15(4).
    22. Alexander M. Petersen & Mohammed E. Ahmed & Ioannis Pavlidis, 2021. "Grand challenges and emergent modes of convergence science," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-15, December.
    23. Proksch, Dorian & Busch-Casler, Julia & Haberstroh, Marcus Max & Pinkwart, Andreas, 2019. "National health innovation systems: Clustering the OECD countries by innovative output in healthcare using a multi indicator approach," Research Policy, Elsevier, vol. 48(1), pages 169-179.
    24. Ryosuke L. Ohniwa & Kunio Takeyasu & Aiko Hibino, 2022. "Researcher dynamics in the generation of emerging topics in life sciences and medicine," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(2), pages 871-884, February.
    25. Porto-Gomez, Igone & Zabala-Iturriagagoitia, Jon Mikel & Leydesdorff, Loet, 2019. "Innovation systems in México: A matter of missing synergies," Technological Forecasting and Social Change, Elsevier, vol. 148(C).

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    More about this item

    Keywords

    triple helix; Medical Subject Headings; MEDLINE/PubMed; synergy; innovation; knowledge order; mutual information; dynamic vocabulary; redundancy.;
    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

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