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Importance of scientific collaboration in contemporary drug discovery and development: a detailed network analysis

Authors
  • Cheng, Feixiong1, 2, 3
  • Ma, Yifang4, 5
  • Uzzi, Brian5
  • Loscalzo, Joseph6
  • 1 Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, 44195, USA , Cleveland (United States)
  • 2 Case Western Reserve University, Cleveland, OH, 44195, USA , Cleveland (United States)
  • 3 Case Western Reserve University School of Medicine, Cleveland, OH, 44106, USA , Cleveland (United States)
  • 4 Southern University of Science and Technology, Shenzhen, 518055, China , Shenzhen (China)
  • 5 Northwestern University, Evanston, IL, 60208, USA , Evanston (United States)
  • 6 Brigham and Women’s Hospital, Harvard Medical School, 75 Francis St., Boston, MA, 02115, USA , Boston (United States)
Type
Published Article
Journal
BMC Biology
Publisher
Springer (Biomed Central Ltd.)
Publication Date
Oct 13, 2020
Volume
18
Issue
1
Identifiers
DOI: 10.1186/s12915-020-00868-3
Source
Springer Nature
Keywords
License
Green

Abstract

BackgroundGrowing evidence shows that scientific collaboration plays a crucial role in transformative innovation in the life sciences. For example, contemporary drug discovery and development reflects the work of teams of individuals from academic centers, the pharmaceutical industry, the regulatory science community, health care providers, and patients. However, public understanding of how collaborations between academia and industry catalyze novel target identification and first-in-class drug discovery is limited.ResultsWe perform a comprehensive network analysis on a large scientific corpus of collaboration and citations (97,688 papers with 1,862,500 citations from 170 million scientific records) to quantify the success trajectory of innovative drug development. By focusing on four types of cardiovascular drugs, we demonstrate how knowledge flows between institutions to highlight the underlying contributions of many different institutions in the development of a new drug. We highlight how such network analysis could help to increase industrial and governmental support, and improve the efficiency or accelerate decision-making in drug discovery and development.ConclusionWe demonstrate that network analysis of large public databases can identify and quantify investigator and institutional relationships in drug discovery and development. If broadly applied, this type of network analysis may help to enhance public understanding of and support for biomedical research, and could identify factors that facilitate decision-making in first-in-class drug discovery among academia, the pharmaceutical industry, and healthcare systems.

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