Long-Term Collaboration Network Based on ClinicalTrials.gov Database in the Pharmaceutical Industry
Heyoung Yang () and
Hyuck Jai Lee ()
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Heyoung Yang: Future Information Research Center, Korea Institute of Science and Technology Information, 66 Hoegi-go, Dongdaemun-gu, Seoul 02456, Korea
Hyuck Jai Lee: Future Information Research Center, Korea Institute of Science and Technology Information, 66 Hoegi-go, Dongdaemun-gu, Seoul 02456, Korea
Sustainability, 2018, vol. 10, issue 2, 1-14
Increasing costs, risks, and productivity problems in the pharmaceutical industry are important recent issues in the biomedical field. Open innovation is proposed as a solution to these issues. However, little statistical analysis related to collaboration in the pharmaceutical industry has been conducted so far. Meanwhile, not many cases have analyzed the clinical trials database, even though it is the information source with the widest coverage for the pharmaceutical industry. The purpose of this study is to test the clinical trials information as a probe for observing the status of the collaboration network and open innovation in the pharmaceutical industry. This study applied the social network analysis method to clinical trials data from 1980 to 2016 in ClinicalTrials.gov. Data were divided into four time periods—1980s, 1990s, 2000s, and 2010s—and the collaboration network was constructed for each time period. The characteristic of each network was investigated. The types of agencies participating in the clinical trials were classified as a university, national institute, company, or other, and the major players in the collaboration networks were identified. This study showed some phenomena related to the pharmaceutical industry that could provide clues to policymakers about open innovation. If follow-up studies were conducted, the utilization of the clinical trial database could be further expanded, which is expected to help open innovation in the pharmaceutical industry.
Keywords: ClinicalTrials.gov; collaboration network; collaborative strategy; pharmaceutical industry; clinical trial study (search for similar items in EconPapers)
JEL-codes: Q Q0 Q2 Q3 Q5 Q56 O13 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:10:y:2018:i:2:p:322-:d:128903
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