The present paper explores the use of the branches of the Medical Subject Headings (MeSH) classification of MEDLINE/PubMed for operationalizing demand for innovation, supply, and technological contexts in terms of “Diseases” (branch C), “Drugs and Chemicals” (branch D), “Analytic, Diagnostic, and Therapeutic Techniques and Equipment” (branch E), respectively. Using a triple-helix model, synergy among these three interacting knowledge spaces can be measured as reduction of uncertainty (mutual redundancy) among the co-evolutions. We analyze three biomedical research areas that have gone through breakthrough discoveries and technological developments (also honored with Nobel Prizes): (i) Human Papilloma Virus (HPV—identified as the main cause of cervical cancer), (ii) RNA interference (RNAi—a biological process involved with gene expression), and (iii) Magnetic Resonance Imaging (MRI—a diagnostic technology). Periods of (statistically significant) synergy among demand, supply, and technological context can be indicated in each of these research areas. We found these to be associated with historical transitions in their respective trajectories. Among the pairwise configurations, the demand-technology provides the strongest link, followed by supply- demand, and with the supply-technology channel being the weakest.
Alexander M. Petersen, Daniele Rotolo, Loet Leydesdorff
triple helix; Medical Subject Headings; MEDLINE/PubMed; synergy; innovation; knowledge order; mutual information; dynamic vocabulary; redundancy