Integrating Systems Biology and Artificial Intelligence in Traditional Pharmacy Research: Advancements, Challenges, and Opportunities

Document Type : Commentary-Article


1 Phytopharmaceutical Technology and Traditional Medicine Incubator, Shiraz University of Medical Sciences, Shiraz, Iran

2 Department of Pharmaceutical Biotechnology, School of Pharmacy, Shiraz University of Medical Sciences, Shiraz, Iran

3 Department of Phytopharmaceuticals, School of Pharmacy, Shiraz University of Medical Sciences, Shiraz, Iran



In the age of artificial intelligence (AI) and biomedical big data, network pharmacology represents a breakthrough in traditional medicine (TM) research. The emergence of interdisciplinary frontiers, such as bioinformatics and systems medicine, has led to a new pharmaceutical research generation that emphasize networks and systems (1) (2). In recent years, TM researchers have shown great interest in exploring AI technologies as an emerging discipline (3). The network pharmacology field has proven to be an effective means of elucidating the mechanisms of traditional herbal medicine and traditional pharmacy (4). The primary focus is to modernize TM by incorporating cutting-edge techniques in genomics, metabolomics, and systems biology. This will enable a fresh look at the knowledge and insights offered by TM (5).
Systems biology, which takes a holistic approach, is a crucial research methodology for understanding the TM pharmacology. To successfully integrate systems biology into TM, it is necessary to combine computational technologies with holistic insights (6). By constructing a network of interrelated "herb-compound-target-pathway" relationships, this technique provides a holistic understanding of the mechanisms underlying traditional medicine. The integration of computational techniques into the network pharmacology has led to a significant improvement in the accuracy and efficiency of active constituent screening and target identification, surpassing previous levels of performance (4). On the other hand, there has been a gradual increase in the global studies of traditional medicinal plants due to their natural sources and wide variety. These plants are capable of complementing modern pharmacological approaches (7-10).


Ghazaleh Mosleh (Google Scholar)

Shiva Hemmati (Google Scholar)

Abdolali Mohagheghzadeh (Google Scholar)


1.    Lai X, Wang X, Hu Y, Su S, Li W, Li S. Editorial: Network Pharmacology and Traditional Medicine. Front Pharmacol. 2020 Aug 4;11:1194. 
2.    Bahari F, Yavari M. Hot and Cold Theory: Evidence in Systems Biology. Adv Exp Med Biol. 2021;1343:135-160. doi: 10.1007/978-3-030-80983-6_9. PMID: 35015281.
3.    Wu C, Chen J, Lai-Han Leung E, Chang H, Wang X. Editorial: Artificial Intelligence in Traditional Medicine. Front Pharmacol. 2022 Aug 4;13:933133. doi: 10.3389/fphar.2022.933133. 
4.    Wang YX, Yang Z, Wang WX, Huang YX, Zhang Q, Li JJ, Tang YP, Yue SJ. Methodology of network pharmacology for research on Chinese herbal medicine against COVID-19: A review. J Integr Med. 2022 Nov;20(6):477-487. 
5.    Efferth T, Xu AL, Lee DYW. Combining the wisdoms of traditional medicine with cutting-edge science and technology at the forefront of medical sciences. Phytomedicine. 2019 Nov;64:153078. 
6.    Lee S. Systems Biology - A Pivotal Research Methodology for Understanding the Mechanisms of Traditional Medicine. J Pharmacopuncture. 2015 Sep;18(3):11-8. 
7.    Yi F, Li L, Xu LJ, Meng H, Dong YM, Liu HB, Xiao PG. In silico approach in reveal traditional medicine plants pharmacological material basis. Chin Med. 2018 Jun 19;13:33. doi: 10.1186/s13020-018-0190-0. 
8.    Mosleh G, Badr P, Zaeri M, Mohagheghzadeh A. Potentials of Antitussive Traditional Persian Functional Foods for COVID-19 Therapy. Front Pharmacol. 2021 Jul 16;12:624006. 
9.    Mosleh G, Zaeri M, Hemmati S, Mohagheghzadeh A. A comprehensive review on rhubarb astringent/ laxative actions and the role of aquaporins as hub genes. Phytochem Rev. 2022;12.
10.    Mosaddeghi P, Eslami M, Farahmandnejad M, Akhavein M, Ranjbarfarrokhi R, Khorraminejad-Shirazi M, et al. A systems pharmacology approach to identify the autophagy-inducing effects of Traditional Persian medicinal plants. Sci Rep. 2021 Jan 11;11(1):336. 
11.    Wang Y, Fan X, Qu H, Gao X, Cheng Y. Strategies and techniques for multi-component drug design from medicinal herbs and traditional Chinese medicine. Curr Top Med Chem. 2012;12(12):1356-62. doi: 10.2174/156802612801319034. 
12.    Hu R, Ren G, Sun G, Sun X. TarNet: An Evidence-Based Database for Natural Medicine Research. PLoS One. 2016 Jun 23;11(6):e0157222. doi: 10.1371/journal.pone.0157222. 
13.    Shi SH, Cai YP, Cai XJ, Zheng XY, Cao DS, Ye FQ, et al. A network pharmacology approach to understanding the mechanisms of action of traditional medicine: Bushenhuoxue formula for treatment of chronic kidney disease. PLoS One. 2014 Mar 5;9(3):e89123.