Li Bing, Tan Kan, Lao Angelyn R, Wang Haiying, Zheng Huiru, Zhang Le
College of Computer Science, Sichuan University, Chengdu, China.
Department of Mathematics and Statistics, De La Salle University, Manila, Philippines.
Front Genet. 2024 Sep 3;15:1450529. doi: 10.3389/fgene.2024.1450529. eCollection 2024.
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.
随着人工智能的创新与进步，越来越多的人工智能技术被应用于药物研究、生物医学前沿研究以及临床医学实践中，尤其是在药理学研究领域。因此，本综述聚焦于人工智能在药物发现、化合物药代动力学预测以及临床药理学方面的应用。我们简要介绍了人工智能的基础知识与发展情况，进行了全面综述，然后总结了最新研究，并讨论了人工智能模型的优势与局限性。此外，我们突出了几项重要研究，并指出了可能的研究方向。
