Artificial intelligence approaches for anti-addiction drug discovery.

Journal: Digital discovery
Published Date: Jun 11, 2025

Abstract

Drug addiction remains a complex global public health challenge, with traditional anti-addiction drug discovery hindered by limited efficacy and slow progress in targeting intricate neurochemical systems. Advanced algorithms within artificial intelligence (AI) present a transformative solution that boosts both speed and precision in therapeutic development. This review examines how artificial intelligence serves as a crucial element in developing anti-addiction medications by targeting the opioid system along with dopaminergic and GABAergic systems, which are essential in addiction pathology. It identifies upcoming trends promising in studying less-researched addiction-linked systems through innovative general-purpose drug discovery techniques. AI holds the potential to transform anti-addiction research by breaking down conventional limitations, which will enable the development of superior treatment methods.

Authors

  • Dong Chen
    School of Basic Medical Sciences, Health Science Center, Ningbo University, Ningbo, China.
  • Jian Jiang
    Eye Center of Xiangya Hospital, Central South University, Changsha, Hunan, China.
  • Nicole Hayes
    Department of Mathematics, Michigan State University, MI 48824, USA.
  • Zhe Su
    School of Medicine, Southern University of Science and Technology, Shenzhen, 518055, Guangdong, People's Republic of China. su_zhe@126.com.
  • Guo-Wei Wei
    Department of Mathematics, Department of Electrical and Computer Engineering, Department of Biochemistry and Molecular Biology, Michigan State University, MI 48824, USA.

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