A Triple Helix Model of Medical Innovation: Supply, Demand, and Technological Capabilities in terms of Medical Subject Headings
Alexander M. Petersen, Daniele Rotolo, and Loet Leydesdorff

TL;DR
This paper models medical innovation by analyzing the interactions among demand, supply, and technological capabilities using entropy statistics, revealing periods of significant synergy that inform governance of medical uncertainty.
Contribution
It introduces a novel entropy-based indicator to measure the mutual information among demand, supply, and technological capabilities in medical research, applied to case studies.
Findings
Significant periods of synergy among demand, supply, and technological capabilities.
Demand-technological capabilities (C-E) show the strongest link.
Interactions among the three dimensions help understand and govern medical innovation uncertainty.
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 capabilities 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 significant challenges to the governance of innovation. We use the Medical Subject Headings (MeSH) of MEDLINE/PubMed to identify publications classified within the categories "Diseases" (C), "Drugs and Chemicals" (D), "Analytic, Diagnostic, and Therapeutic Techniques and Equipment" (E) and use these as knowledge representations of demand, supply,…
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