Explore on artificial intelligence in Drug Design: Bibliometric study
Code: G-1505
Authors: Amir Hami ℗, Seyed Ali Fatemi Aghda, Mehdi Zahedian, Mohammad-Javad Niazi, Sajjad Bahariniya *, Shadi Hazhir
Schedule: Not Scheduled!
Tag: Drug Discovery
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Abstract:
Abstract
Background and aims: In recent years, artificial intelligence has been recognized as a transformative tool in drug design. The aim of this study is to identify research patterns, prominent authors, and key publications in the field of artificial intelligence and drug design. The results of this study can help decision-makers in the pharmaceutical industry to identify new trends in the drug design process. Method: This study used a small amount of bibliometrics. The Web of Science Core Collection database was selected for data extraction. The data extraction date was March 14, 2025. A comprehensive search strategy and keywords related to artificial intelligence and drug design were used to retrieve all articles. Terms were selected using Medical Subject Headings (MeSH) and for a more precise search, synonyms of drug design and artificial intelligence were also used. Finally, 1927 publications were transferred to Biblioshiny and VOSviewer software for bibliometric analysis. Results: The first article on drug design and artificial intelligence was published in 1991 and the publication trend continued until 2025. The annual growth rate of these articles was 12.39%. These articles were published by 477 journals and 5988 authors. The Journal of Chemical Information and Modeling played an important role in the publication of these articles with 130 articles. China, the United States and India are the most active countries in producing these articles. The Chinese Academy of Sciences was the most active among the institutions and the Schneider Gisbert author in producing these articles. The most frequently used keywords in these articles are: «Machine Learning», «Drug Design», «Deep Learning», «Artificial Intelligence», «Drug Discovery», «Virtual Screening», «Structure-Based Drug Design», «Computer-Aided Drug Design», «Molecular Dynamics» and «Bioinformatics». Conclusion: The relationship between AI and drug design has attracted increasing attention over the past two decades, and its recent expansion demonstrates that researchers have recently become interested in this area. Identifying leading universities, authors, journals, keywords, and countries in the field facilitates global collaboration among researchers, especially those who are younger. Finally, the results of the present study indicate the very important place of artificial intelligence in drug design.
Keywords
Artificial Intelligence, Drug Design, Bibliometrics
