1. Chakravarty K, Antontsev VG, Khotimchenko M, Gupta N, Jagarapu A, Bundey Y, et al. Accelerated repurposing and drug development of pulmonary hypertension therapies for COVID-19 treatment using an AI-integrated biosimulation platform. Molecules 2021;26:1912.
[CROSSREF] [PUBMED] [PMC]
2. Spinelli A, Pellino G. COVID-19 pandemic: perspectives on an unfolding crisis. Br J Surg 2020;107:785-7.
[CROSSREF] [PUBMED] [PMC]
3. Jarada TN, Rokne JG, Alhajj R. A review of computational drug repositioning: strategies, approaches, opportunities, challenges, and directions. J Cheminform 2020;12:46.
[CROSSREF] [PUBMED] [PMC]
4. Yeu Y, Yoon Y, Park S. Protein localization vector propagation: a method for improving the accuracy of drug repositioning. Mol Biosyst 2015;11:2096-102.
[CROSSREF] [PUBMED]
5. Saberian N, Peyvandipour A, Donato M, Ansari S, Draghici S. A new computational drug repurposing method using established disease-drug pair knowledge. Bioinformatics 2019;35:3672-8.
[CROSSREF] [PUBMED] [PMC]
6. Mohapatra S, Nath P, Chatterjee M, Das N, Kalita D, Roy P, et al. Repurposing therapeutics for COVID-19: rapid prediction of commercially available drugs through machine learning and docking. PLoS One 2020;15:e0241543.
[CROSSREF] [PUBMED] [PMC]
8. Ghofrani HA, Osterloh IH, Grimminger F. Sildenafil: from angina to erectile dysfunction to pulmonary hypertension and beyond. Nat Rev Drug Discov 2006;5:689-702.
[CROSSREF] [PUBMED] [PMC]
9. Ekman P. Finasteride in the treatment of benign prostatic hypertrophy: an update. New indications for finasteride therapy. Scand J Urol Nephrol Suppl 1999;203:15-20.
[CROSSREF] [PUBMED]
10. Sanchez-Garcia A, Simental-Mendia M, Millan-Alanis JM, Simental-Mendia LE. Effect of sodium-glucose co-transporter 2 inhibitors on lipid profile: a systematic review and meta-analysis of 48 randomized controlled trials. Pharmacol Res 2020;160:105068.
[CROSSREF] [PUBMED]
11. Filippatos TD, Tsimihodimos V, Elisaf MS. Mechanisms of blood pressure reduction with sodium-glucose co-transporter 2 (SGLT2) inhibitors. Expert Opin Pharmacother 2016;17:1581-3.
[CROSSREF] [PUBMED]
12. Ryan D, Acosta A. GLP-1 receptor agonists: nonglycemic clinical effects in weight loss and beyond. Obesity (Silver Spring) 2015;23:1119-29.
[PUBMED] [PMC]
13. Blommel ML, Blommel AL. Pregabalin: an antiepileptic agent useful for neuropathic pain. Am J Health Syst Pharm 2007;64:1475-82.
[CROSSREF] [PUBMED]
14. Paranjpe MD, Taubes A, Sirota M. Insights into computational drug repurposing for neurodegenerative disease. Trends Pharmacol Sci 2019;40:565-76.
[CROSSREF] [PUBMED] [PMC]
15. Xue H, Li J, Xie H, Wang Y. Review of drug repositioning approaches and resources. Int J Biol Sci 2018;14:1232-44.
[CROSSREF] [PUBMED] [PMC]
16. Keiser MJ, Setola V, Irwin JJ, Laggner C, Abbas AI, Hufeisen SJ, et al. Predicting new molecular targets for known drugs. Nature 2009;462:175-81.
[CROSSREF] [PUBMED] [PMC]
17. Iorio F, Bosotti R, Scacheri E, Belcastro V, Mithbaokar P, Ferriero R, et al. Discovery of drug mode of action and drug repositioning from transcriptional responses. Proc Natl Acad Sci U S A 2010;107:14621-6.
[CROSSREF] [PUBMED] [PMC]
18. Tian Z, Teng Z, Cheng S, Guo M. Computational drug repositioning using meta-path-based semantic network analysis. BMC Syst Biol 2018;12(Suppl 9):134.
[CROSSREF] [PUBMED] [PMC]
19. Wu Z, Wang Y, Chen L. Network-based drug repositioning. Mol Biosyst 2013;9:1268-81.
[CROSSREF] [PUBMED]
20. Wu C, Gudivada RC, Aronow BJ, Jegga AG. Computational drug repositioning through heterogeneous network clustering. BMC Syst Biol 2013;7 Suppl 5:S6.
[CROSSREF] [PUBMED]
21. Kanehisa M, Sato Y, Kawashima M, Furumichi M, Tanabe M. KEGG as a reference resource for gene and protein annotation. Nucleic Acids Res 2016;44:D457-62.
[CROSSREF] [PUBMED]
22. Kyoto Encyclopedia of Genes and Genomes. KEGG: Kyoto Encyclopedia of genes and genomes [Internet]. Kyoto: Kanehisa Laboratories; 2021 [cited 2022 Mar 26]. Available from:
https://www.genome.jp/kegg/.
23. Cheng F, Desai RJ, Handy DE, Wang R, Schneeweiss S, Barabasi AL, et al. Network-based approach to prediction and population-based validation of in silico drug repurposing. Nat Commun 2018;9:2691.
[CROSSREF] [PUBMED] [PMC]
24. Emig D, Ivliev A, Pustovalova O, Lancashire L, Bureeva S, Nikolsky Y, et al. Drug target prediction and repositioning using an integrated network-based approach. PLoS One 2013;8:e60618.
[CROSSREF] [PUBMED] [PMC]
25. Goldstein JA, Bastarache LA, Denny JC, Roden DM, Pulley JM, Aronoff DM. Calcium channel blockers as drug repurposing candidates for gestational diabetes: mining large scale genomic and electronic health records data to repurpose medications. Pharmacol Res 2018;130:44-51.
[CROSSREF] [PUBMED] [PMC]
26. Rotermund C, Machetanz G, Fitzgerald JC. The therapeutic potential of metformin in neurodegenerative diseases. Front Endocrinol (Lausanne) 2018;9:400.
[CROSSREF] [PUBMED] [PMC]
28. Fleuren WW, Alkema W. Application of text mining in the biomedical domain. Methods 2015;74:97-106.
[CROSSREF] [PUBMED]
29. Kostoff RN, Briggs MB, Shores DR. Treatment repurposing for inflammatory bowel disease using literature-related discovery and innovation. World J Gastroenterol 2020;26:4889-99.
[CROSSREF] [PUBMED] [PMC]
30. Zhang M, Luo H, Xi Z, Rogaeva E. Drug repositioning for diabetes based on ‘omics’ data mining. PLoS One 2015;10:e0126082.
[CROSSREF] [PUBMED] [PMC]
31. Zhang L, Hu J, Xu Q, Li F, Rao G, Tao C. A semantic relationship mining method among disorders, genes, and drugs from different biomedical datasets. BMC Med Inform Decis Mak 2020;20(Suppl 4):283.
[CROSSREF] [PUBMED] [PMC]
32. Pijl H, Ohashi S, Matsuda M, Miyazaki Y, Mahankali A, Kumar V, et al. Bromocriptine: a novel approach to the treatment of type 2 diabetes. Diabetes Care 2000;23:1154-61.
[CROSSREF] [PUBMED]
33. Napolitano F, Zhao Y, Moreira VM, Tagliaferri R, Kere J, D’Amato M, et al. Drug repositioning: a machine-learning approach through data integration. J Cheminform 2013;5:30.
[CROSSREF] [PUBMED] [PMC]
34. Menden MP, Iorio F, Garnett M, McDermott U, Benes CH, Ballester PJ, et al. Machine learning prediction of cancer cell sensitivity to drugs based on genomic and chemical properties. PLoS One 2013;8:e61318.
[CROSSREF] [PUBMED] [PMC]
35. Koren G, Nordon G, Radinsky K, Shalev V. Identification of repurposable drugs with beneficial effects on glucose control in type 2 diabetes using machine learning. Pharmacol Res Perspect 2019;7:e00529.
[CROSSREF] [PUBMED] [PMC]
36. Ng L, Foo DC, Wong CK, Man AT, Lo OS, Law WL. Repurposing DPP-4 inhibitors for colorectal cancer: a retrospective and single center study. Cancers (Basel) 2021;13:3588.
[CROSSREF] [PUBMED] [PMC]
37. Sanders JM, Monogue ML, Jodlowski TZ, Cutrell JB. Pharmacologic treatments for coronavirus disease 2019 (COVID-19): a review. JAMA 2020;323:1824-36.
[PUBMED]
38. Gao J, Tian Z, Yang X. Breakthrough: chloroquine phosphate has shown apparent efficacy in treatment of COVID-19 associated pneumonia in clinical studies. Biosci Trends 2020;14:72-3.
[CROSSREF] [PUBMED]
39. Gautret P, Lagier JC, Parola P, Hoang VT, Meddeb L, Mailhe M, et al. Hydroxychloroquine and azithromycin as a treatment of COVID-19: results of an open-label non-randomized clinical trial. Int J Antimicrob Agents 2020;56:105949.
[CROSSREF] [PUBMED] [PMC]
40. Baruah P, Das A, Paul D, Chakrabarty S, Aguan K, Mitra S. Sulfonylurea class of antidiabetic drugs inhibit acetylcholinesterase activity: unexplored auxiliary pharmacological benefit toward Alzheimer’s disease. ACS Pharmacol Transl Sci 2021;4:193-205.
[CROSSREF] [PUBMED] [PMC]
41. Xu H, Aldrich MC, Chen Q, Liu H, Peterson NB, Dai Q, et al. Validating drug repurposing signals using electronic health records: a case study of metformin associated with reduced cancer mortality. J Am Med Inform Assoc 2015;22:179-91.
[CROSSREF] [PUBMED]
42. Sharma S, Nozohouri S, Vaidya B, Abbruscato T. Repurposing metformin to treat age-related neurodegenerative disorders and ischemic stroke. Life Sci 2021;274:119343.
[CROSSREF] [PUBMED] [PMC]
43. Moulton CD, Hopkins C, Ismail K, Stahl D. Repositioning of diabetes treatments for depressive symptoms: a systematic review and meta-analysis of clinical trials. Psychoneuroendocrinology 2018;94:91-103.
[CROSSREF] [PUBMED]
44. Wahlqvist ML, Lee MS, Chuang SY, Hsu CC, Tsai HN, Yu SH, et al. Increased risk of affective disorders in type 2 diabetes is minimized by sulfonylurea and metformin combination: a population-based cohort study. BMC Med 2012;10:150.
[CROSSREF] [PUBMED] [PMC]
45. Rao PPN, Pham AT, Shakeri A, El Shatshat A, Zhao Y, Karuturi RC, et al. Drug repurposing: dipeptidyl peptidase IV (DPP4) inhibitors as potential agents to treat SARS-CoV-2 (2019-nCoV) infection. Pharmaceuticals (Basel) 2021;14:44.
[CROSSREF] [PUBMED] [PMC]
46. Bonora BM, Raschi E, Avogaro A, Fadini GP. SGLT-2 inhibitors and atrial fibrillation in the Food and Drug Administration adverse event reporting system. Cardiovasc Diabetol 2021;20:39.
[CROSSREF] [PUBMED] [PMC] [PDF]
47. Pintana H, Apaijai N, Chattipakorn N, Chattipakorn SC. DPP-4 inhibitors improve cognition and brain mitochondrial function of insulin-resistant rats. J Endocrinol 2013;218:1-11.
[CROSSREF] [PUBMED]
48. Markaki I, Winther K, Catrina SB, Svenningsson P. Repurposing GLP1 agonists for neurodegenerative diseases. Int Rev Neurobiol 2020;155:91-112.
[CROSSREF] [PUBMED]
49. Daghlas I, Karhunen V, Ray D, Zuber V, Burgess S, Tsao PS, et al. Genetic evidence for repurposing of GLP1R (glucagon-like peptide-1 receptor) agonists to prevent heart failure. J Am Heart Assoc 2021;10:e020331.
[CROSSREF] [PUBMED] [PMC]
50. Foltynie T, Athauda D. Repurposing anti-diabetic drugs for the treatment of Parkinson’s disease: rationale and clinical experience. Prog Brain Res 2020;252:493-523.
[CROSSREF] [PUBMED]
51. Rameshrad M, Razavi BM, Lalau JD, De Broe ME, Hosseinzadeh H. An overview of glucagon-like peptide-1 receptor agonists for the treatment of metabolic syndrome: a drug repositioning. Iran J Basic Med Sci 2020;23:556-68.
[PUBMED] [PMC]
52. Levy P, Jellinger PS. The potential role of colesevelam in the management of prediabetes and type 2 diabetes mellitus. Postgrad Med 2010;122(3 Suppl):1-8.
53. Magkou D, Tziomalos K. Antidiabetic treatment, stroke severity and outcome. World J Diabetes 2014;5:84-8.
[CROSSREF] [PUBMED] [PMC]
54. Kobayashi Y, Banno K, Kunitomi H, Tominaga E, Aoki D. Current state and outlook for drug repositioning anticipated in the field of ovarian cancer. J Gynecol Oncol 2019;30:e10.
[CROSSREF] [PUBMED]
55. Xu H, Li J, Jiang X, Chen Q. Electronic health records for drug repurposing: current status, challenges, and future directions. Clin Pharmacol Ther 2020;107:712-4.
[CROSSREF] [PUBMED]
56. Oprea TI, Bauman JE, Bologa CG, Buranda T, Chigaev A, Edwards BS, et al. Drug repurposing from an academic perspective. Drug Discov Today Ther Strateg 2011;8:61-9.
[CROSSREF] [PUBMED] [PMC]
57. ChEMBL. ChEMBL database [Internet]. Hinxton: The European Bioinformatics Institute (EMBL-EBI); 2018 [cited 2022 Mar 26]. Available from:
https://www.ebi.ac.uk/chembl/.
59. Seiler KP, George GA, Happ MP, Bodycombe NE, Carrinski HA, Norton S, et al. ChemBank: a small-molecule screening and cheminformatics resource database. Nucleic Acids Res 2008;36:D351-9.
[CROSSREF] [PUBMED]
60. U.S. National Library of Medicine. clinicaltrials.gov [Internet]. Bethesda: National Library of Medicine; 2021 [cited 2022 Mar 26]. Available from:
https://clinicaltrials.gov/.
62. DrugBank. DrugBank online: database for drug and drug target info [Internet]. Alberta: DrugBank; 2017 [cited 2022 Mar 26]. Available from:
https://go.drugbank.com/.
63. Xu R, Wang Q. Large-scale combining signals from both biomedical literature and the FDA Adverse Event Reporting System (FAERS) to improve post-marketing drug safety signal detection. BMC Bioinformatics 2014;15:17.
[CROSSREF] [PUBMED] [PMC]
65. Gene ontology. The gene ontology resource [Internet]. Bar Harbor: The Gene Ontology Consortium; 2021 [cited 2022 Mar 26]. Available from:
http://www.geneontology.org/.
66. MedHelp. Be your healthiest [Internet]. San Francisco: MedHelp; 2021 [cited 2022 Mar 26]. Available from:
https://www.medhelp.org/.
68. MedlinePlus. Health information from the National library of medicine [Internet]. Bethesda: National Library of Medicine; 2021 [cited 2022 Mar 26]. Available from:
https://medlineplus.gov/.
69. Lowe HJ, Barnett GO. Understanding and using the medical subject headings (MeSH) vocabulary to perform literature searches. JAMA 1994;271:1103-8.
[CROSSREF] [PUBMED]
70. Hamosh A, Scott AF, Amberger JS, Bocchini CA, McKusick VA. Online Mendelian Inheritance in Man (OMIM), a knowledgebase of human genes and genetic disorders. Nucleic Acids Res 2005;33:D514-7.
[CROSSREF] [PUBMED]
71. PharmGKB. Search pharmGKB [Internet]. Stanford: PharmGKB; 2021 [cited 2022 Mar 26]. Available from:
https://www.pharmgkb.org/.
72. Thorn CF, Klein TE, Altman RB. PharmGKB: the Pharmacogenomics Knowledge Base. Methods Mol Biol 2013;1015:311-20.
[CROSSREF] [PUBMED] [PMC]
75. National Library of Medicine. PubMed [Internet]. Bethesda: National Library of Medicine; 2021 [cited 2022 Mar 26]. Available from:
https://pubmed.ncbi.nlm.nih.gov/.
76. Malas TB, Vlietstra WJ, Kudrin R, Starikov S, Charrout M, Roos M, et al. Drug prioritization using the semantic properties of a knowledge graph. Sci Rep 2019;9:6281.
[CROSSREF] [PUBMED] [PMC]
77. Rindflesch TC, Kilicoglu H, Fiszman M, Rosemblat G, Shin D. Semantic medline: an advanced information management application for biomedicine. Inf Serv Use 2011;31:15-21.
[CROSSREF]
78. National Library of Medicine. Access to SemRep/SemMedDB/SKR Resources [Internet]. Bethesda: National Library of Medicine; 2021 [cited 2022 Mar 26]. Available from:
https://skr3.nlm.nih.gov/SemMedDB/.
79. Kuhn M, Campillos M, Letunic I, Jensen LJ, Bork P. A side effect resource to capture phenotypic effects of drugs. Mol Syst Biol 2010;6:343.
[CROSSREF] [PUBMED] [PMC]
80. SIDER 4.1. SIDER 4.1 Side effect resource [Internet]. SIDER 4.; 2015 [cited 2022 Mar 26]. Available from:
http://sideeffects.embl.de/.
81. Yao L, Zhang Y, Li Y, Sanseau P, Agarwal P. Electronic health records: implications for drug discovery. Drug Discov Today 2011;16:594-9.
[CROSSREF] [PUBMED]
82. Bate A, Juniper J, Lawton AM, Thwaites RM. Designing and incorporating a real world data approach to international drug development and use: what the UK offers. Drug Discov Today 2016;21:400-5.
[CROSSREF] [PUBMED]
83. Kim HS, Lee S, Kim JH. Real-world evidence versus randomized controlled trial: clinical research based on electronic medical records. J Korean Med Sci 2018;33:e213.
[CROSSREF] [PUBMED] [PMC]
84. Lee S, Kim HS. Prospect of artificial intelligence based on electronic medical record. J Lipid Atheroscler 2021;10:282-90.
[CROSSREF] [PUBMED] [PMC]
85. Ozery-Flato M, Goldschmidt Y, Shaham O, Ravid S, Yanover C. Framework for identifying drug repurposing candidates from observational healthcare data. JAMIA Open 2020;3:536-44.
[CROSSREF] [PUBMED] [PMC]
86. Kim DH, Lee JE, Kim YG, Lee Y, Seo DW, Lee KH, et al. High-throughput algorithm for discovering new drug indications by utilizing large-scale electronic medical record data. Clin Pharmacol Ther 2020;108:1299-307.
[CROSSREF] [PUBMED]
87. Kim HS, Kim DJ, Yoon KH. Medical big data is not yet available: why we need realism rather than exaggeration. Endocrinol Metab (Seoul) 2019;34:349-54.
[CROSSREF] [PUBMED] [PMC]
88. Kim HS, Kim JH. Proceed with caution when using real world data and real world evidence. J Korean Med Sci 2019;34:e28.
[CROSSREF] [PUBMED] [PMC]
89. Shin SY, Kim HS. Data pseudonymization in a range that does not affect data quality: correlation with the degree of participation of clinicians. J Korean Med Sci 2021;36:e299.
[CROSSREF] [PUBMED] [PMC]
90. Nabirotchkin S, Peluffo AE, Rinaudo P, Yu J, Hajj R, Cohen D. Next-generation drug repurposing using human genetics and network biology. Curr Opin Pharmacol 2020;51:78-92.
[CROSSREF] [PUBMED]
91. Denny JC, Ritchie MD, Basford MA, Pulley JM, Bastarache L, Brown-Gentry K, et al. PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene-disease associations. Bioinformatics 2010;26:1205-10.
[CROSSREF] [PUBMED] [PMC]
92. Whirl-Carrillo M, McDonagh EM, Hebert JM, Gong L, Sangkuhl K, Thorn CF, et al. Pharmacogenomics knowledge for personalized medicine. Clin Pharmacol Ther 2012;92:414-7.
[CROSSREF] [PUBMED]
93. Yang L, Agarwal P. Systematic drug repositioning based on clinical side-effects. PLoS One 2011;6:e28025.
[CROSSREF] [PUBMED] [PMC]
94. Lotfi Shahreza M, Ghadiri N, Mousavi SR, Varshosaz J, Green JR. A review of network-based approaches to drug repositioning. Brief Bioinform 2018;19:878-892.
[CROSSREF] [PUBMED]
95. Chen B, Ma L, Paik H, Sirota M, Wei W, Chua MS, et al. Reversal of cancer gene expression correlates with drug efficacy and reveals therapeutic targets. Nat Commun 2017;8:16022.
[CROSSREF] [PUBMED] [PMC]
96. Paik H, Chen B, Sirota M, Hadley D, Butte AJ. Integrating clinical phenotype and gene expression data to prioritize novel drug uses. CPT Pharmacometrics Syst Pharmacol 2016;5:599-607.
[CROSSREF] [PUBMED] [PMC]