A narrative review of the application of artificial intelligence and drug repositioning for the identification of fibroblast growth factorreceptor inhibitors

Background and aims: Artificial intelligence refers to the modeling of intelligent behaviorthrough a computer with the least human involvement. Drug repositioning techniques based onartificial intelligence accelerate the process of research and decrease the cost of experimentalstudies. Dysregulation of fibroblast growth factor receptors in a wide range of cancers has beenimplicated and due to their functional importance, have been considered as promising drug targetsfor the therapy of different cancers. In this review, we have summarized small molecule fibroblastgrowth factor receptor inhibitors that progressed using artificial intelligence and repositioningdrugs that are being examined in clinical trials associated with cancer therapy.Method: Specific human and animal studies in the fields of artificial intelligence, computationaldrug design, and drug repurposing or drug repositioning, published in English that were availablebetween ۱۹۹۷ and ۲۰۲۳, contained in PubMed, EMBASE, Web of Science, Scopus and GoogleScholar databases were reviewed. Four keyword groups including: “artificial intelligence”, “computationaldrug design”, “drug repositioning” and “fibroblast growth factor receptors inhibitors”were used in this study. The literature review was conducted on July ۲, ۲۰۲۳. Original and reviewstudies were taken into consideration. Conference reports, articles for which the full text was notavailable, and also study protocols, were excluded. Among the ۴۵۵ articles obtained from the initialsearch, ۱۲۰ articles remained after two stages of screening, which were included in the study.Results: According to published reports, nonselective fibroblast growth factor receptor inhibitorshave the potential to be used for the treatment of cancer and multitarget kinase inhibitors are thefirst drug class to be approved due to more advanced clinical studies. For example, AZD۴۵۴۷ andBGJ۳۹۸ are gradually entering the consumption cycle and are good options as combined treatments.Using drug repositioning based on artificial intelligence, multiple small molecule inhibitorshave been developed and remarkable advances were obtained in second-generation selectivefibroblast growth factor receptor inhibitorsConclusion: A deep understanding of the tissue-specific nature of the fibroblast growth factorsignaling pathway and its integration with artificial intelligence and drug repositioning methodscan help in the more successful to preselect suitable drug targets for inhibition of tumor growthand carcinogenicity in the future.