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Review
. 2024 Sep 3:15:1450529.
doi: 10.3389/fgene.2024.1450529. eCollection 2024.

A comprehensive review of artificial intelligence for pharmacology research

Bing Li  1 , Kan Tan  1 , Angelyn R Lao  2 , Haiying Wang  3 , Huiru Zheng  3 , Le Zhang  1
Affiliations
Review

A comprehensive review of artificial intelligence for pharmacology research

Bing Li et al. Front Genet. .

Abstract

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; clinical pharmacology; compound pharmacokinetic prediction; drug discovery; pharmacology.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.

Figures

FIGURE 1
FIGURE 1
The relationship between artificial intelligence, machine learning, and deep learning and the applications of artificial intelligence in pharmacology research.
FIGURE 2
FIGURE 2
Timeline of the development and application of artificial intelligence.
FIGURE 3
FIGURE 3
Illustration for pre-screening DNN model.
See this image and copyright information in PMC

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