Global research trends of artificial intelligence applied in drug design: A bibliometric analysis based on Vosviewer and Citespace

Abstract

With the development of artificial intelligence technology, the application of artificial intelligence in drug design has received increasing attention from researchers. The process of new drug development is characterized by high costs, time-consuming and labor-intensive, and low success rate. The application of artificial intelligence technology in drug design can reduce the uncertainty in the drug development process, especially in target identification, small molecule drug screening, and drug property prediction, thereby shortening the research and development cycle of new drugs and improving research and development efficiency. In this study, 772 articles collected from the database from 2003 to 2022 were selected as the research objects, aiming to explore the bibliometric indicators of the application of artificial intelligence in drug discovery, such as countries/regions, institutions, authors, journals, categories, references, and co-authorship, co-occurrence, and co-citation of keywords. The study aims to investigate the research progress and prospects of artificial intelligence technology in the field of drug design through bibliometric methods. The results show that in the field of artificial intelligence-assisted drug design, the most influential scientist globally is "Schneider, Gisbert" from Swiss Federal Institute of Technology, the most influential research institution is University of Pittsburgh, and the most influential country is the USA. Artificial intelligence-assisted drug design mainly focuses on four aspects: small molecule drug screening, peptide drug development, protein crystal structure prediction, and candidate drug formulation optimization. In the future, artificial intelligence will play a more important role in accelerating drug design processes, personalized drug therapy, and optimization of drug combination therapy.

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