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REVIEW article

Front. Genet.
Sec. Computational Genomics
Volume 15 - 2024 | doi: 10.3389/fgene.2024.1450529

A comprehensive review of artificial intelligence for pharmacology research

Provisionally accepted
Bing Li Bing Li 1Kan Tan Kan Tan 1Angelyn R. Lao Angelyn R. Lao 2Haiying Wang Haiying Wang 3Huiru Zheng Huiru Zheng 3*Le Zhang Le Zhang 1*
  • 1 College of Computer Science, Sichuan University, Chengdu, Sichuan Province, China
  • 2 Department of Mathematics and Statistics, College of Science, De La Salle University, Manila, National Capital Region, Philippines
  • 3 School of Computing, Ulster University, Belfast, United Kingdom

The final, formatted version of the article will be published soon.

    With the innovation and advancement of artificial intelligence, more and more artificial intelligence techniques are employed in drug research, biomedical frontier research, and clinical medicine practice, especially, in the field of pharmacology research. Thus, this review focuses on the applications of artificial intelligence in drug discovery, compound pharmacokinetic prediction, and clinical pharmacology. We briefly introduced the basic knowledge and development of artificial intelligence, presented a comprehensive review, and then summarized the latest studies and discussed the strengths and limitations of artificial intelligence models. Additionally, we highlighted several important studies and pointed out possible research directions.

    Keywords: artificial intelligence, Pharmacology, Drug Discovery, compound pharmacokinetic prediction, Clinical Pharmacology

    Received: 17 Jun 2024; Accepted: 26 Aug 2024.

    Copyright: © 2024 Li, Tan, Lao, Wang, Zheng and Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Huiru Zheng, School of Computing, Ulster University, Belfast, United Kingdom
    Le Zhang, College of Computer Science, Sichuan University, Chengdu, 610065, Sichuan Province, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.