Title:Artificial Intelligence in Drug Discovery: A Bibliometric Analysis and
Literature Review
Volume: 24
Issue: 14
Author(s): Baoyu He, Jingjing Guo, Henry H.Y. Tong and Wai Ming To*
Affiliation:
- Faculty of Business, Macao Polytechnic University, Macao, China
Keywords:
Drug discovery, artificial intelligence, AI, bibliometric, Scopus, VOSviewer.
Abstract: Drug discovery is a complex and iterative process, making it ideal for using artificial
intelligence (AI). This paper uses a bibliometric approach to reveal AI's trend and underlying structure
in drug discovery (AIDD). A total of 4310 journal articles and reviews indexed in Scopus were
analyzed, revealing that AIDD has been rapidly growing over the past two decades, with a significant
increase after 2017. The United States, China, and the United Kingdom were the leading countries
in research output, with academic institutions, particularly the Chinese Academy of Sciences
and the University of Cambridge, being the most productive. In addition, industrial companies, including
both pharmaceutical and high-tech ones, also made significant contributions. Additionally,
this paper thoroughly discussed the evolution and research frontiers of AIDD, which were uncovered
through co-occurrence analyses of keywords using VOSviewer. Our findings highlight that
AIDD is an interdisciplinary and promising research field that has the potential to revolutionize drug
discovery. The comprehensive overview provided here will be of significant interest to researchers,
practitioners, and policy-makers in related fields. The results emphasize the need for continued investment
and collaboration in AIDD to accelerate drug discovery, reduce costs, and improve patient
outcomes.