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Current Drug Targets

Editor-in-Chief

ISSN (Print): 1389-4501
ISSN (Online): 1873-5592

Mini-Review Article

Drug Repurposing Using FDA Adverse Event Reporting System (FAERS) Database

Author(s): Robert Morris, Rahinatu Ali and Feng Cheng*

Volume 25, Issue 7, 2024

Published on: 02 April, 2024

Page: [454 - 464] Pages: 11

DOI: 10.2174/0113894501290296240327081624

Price: $65

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Abstract

Drug repurposing is an emerging approach to reassigning existing pre-approved therapies for new indications. The FDA Adverse Event Reporting System (FAERS) is a large database of over 28 million adverse event reports submitted by medical providers, patients, and drug manufacturers and provides extensive drug safety signal data. In this review, four common drug repurposing strategies using FAERS are described, including inverse signal detection for a single disease, drug-drug interactions that mitigate a target ADE, identifying drug-ADE pairs with opposing gene perturbation signatures and identifying drug-drug pairs with congruent gene perturbation signatures. The purpose of this review is to provide an overview of these different approaches using existing successful applications in the literature. With the fast expansion of adverse drug event reports, FAERS-based drug repurposing represents a promising strategy for discovering new uses for existing therapies.

Graphical Abstract

[1]
Mohs RC, Greig NH. Drug discovery and development: Role of basic biological research. Alzheimers Dement 2017; 3(4): 651-7.
[http://dx.doi.org/10.1016/j.trci.2017.10.005] [PMID: 29255791]
[2]
Xue H, Li J, Xie H, Wang Y. Review of Drug Repositioning Approaches and Resources. Int J Biol Sci 2018; 14(10): 1232-44.
[http://dx.doi.org/10.7150/ijbs.24612] [PMID: 30123072]
[3]
Khatoon Z, Figler B, Zhang H, Cheng F. Introduction to RNA-Seq and its applications to drug discovery and development. Drug Dev Res 2014; 75(5): 324-30.
[http://dx.doi.org/10.1002/ddr.21215] [PMID: 25160072]
[4]
Jourdan JP, Bureau R, Rochais C, Dallemagne P. Drug repositioning: A brief overview. J Pharm Pharmacol 2020; 72(9): 1145-51.
[http://dx.doi.org/10.1111/jphp.13273] [PMID: 32301512]
[5]
Savoia D. New antimicrobial approaches: Reuse of Old Drugs. Curr Drug Targets 2016; 17(6): 731-8.
[http://dx.doi.org/10.2174/1389450116666150806124110] [PMID: 26245476]
[6]
Al-Bari AA. Facts and Myths: Efficacies of Repurposing Chloroquine and Hydroxychloroquine for the Treatment of COVID-19. Curr Drug Targets 2020; 21(16): 1703-21.
[http://dx.doi.org/10.2174/1389450121666200617133142] [PMID: 32552642]
[7]
Apaydın ÇB, Çınar G, Cihan-Üstündağ G. Small-molecule antiviral agents in ongoing clinical trials for COVID-19. Curr Drug Targets 2021; 22(17): 1986-2005.
[http://dx.doi.org/10.2174/1389450122666210215112150] [PMID: 33588727]
[8]
Kulkarni VS, Alagarsamy V, Solomon VR, Jose PA, Murugesan S. Drug Repurposing: An effective tool in modern drug discovery. Russ J Bioorganic Chem 2023; 49(2): 157-66.
[http://dx.doi.org/10.1134/S1068162023020139] [PMID: 36852389]
[9]
Rossello A, Nuti E, Ferrini S, Fabbi M. Targeting ADAM17 sheddase activity in cancer. Curr Drug Targets 2016; 17(16): 1908-27.
[http://dx.doi.org/10.2174/1389450117666160727143618] [PMID: 27469341]
[10]
Kesselheim AS, Tan YT, Avorn J. The roles of academia, rare diseases, and repurposing in the development of the most transformative drugs. Health Aff 2015; 34(2): 286-93.
[http://dx.doi.org/10.1377/hlthaff.2014.1038] [PMID: 25646109]
[11]
Krishnamurthy N, Grimshaw AA, Axson SA, Choe SH, Miller JE. Drug repurposing: A systematic review on root causes, barriers and facilitators. BMC Health Serv Res 2022; 22(1): 970.
[http://dx.doi.org/10.1186/s12913-022-08272-z] [PMID: 35906687]
[12]
Gong J, Chen Y, Pu F, et al. Understanding membrane protein drug targets in computational perspective. Curr Drug Targets 2019; 20(5): 551-64.
[http://dx.doi.org/10.2174/1389450120666181204164721] [PMID: 30516106]
[13]
Khanna N, Kumar A, Pawar SV. A review on rheumatoid arthritis interventions and current developments. Curr Drug Targets 2021; 22(4): 463-83.
[http://dx.doi.org/10.2174/1389450121999201125200558] [PMID: 33243118]
[14]
Turabi KS, Deshmukh A, Paul S, et al. Drug repurposing : An emerging strategy in cancer therapeutics. Naunyn Schmiedebergs Arch Pharmacol 2022; 395(10): 1139-58.
[http://dx.doi.org/10.1007/s00210-022-02263-x] [PMID: 35695911]
[15]
Alakwaa FM. Repurposing didanosine as a potential treatment for covid-19 using single-cell rna sequencing data. mSystems 2020; 5(2): e00297-20.
[http://dx.doi.org/10.1128/mSystems.00297-20] [PMID: 32291351]
[16]
Rabie AM. Efficacious preclinical repurposing of the nucleoside analogue didanosine against COVID-19 polymerase and exonuclease. ACS Omega 2022; 7(25): 21385-96.
[http://dx.doi.org/10.1021/acsomega.1c07095] [PMID: 35785294]
[17]
Cao B, Wang Y, Lu H, et al. Oral simnotrelvir for adult patients with mild-to-moderate Covid-19. N Engl J Med 2024; 390(3): 230-41.
[http://dx.doi.org/10.1056/NEJMoa2301425] [PMID: 38231624]
[18]
Ma L, Li Q, Xie Y, et al. Repurposing of HIV/HCV protease inhibitors against SARS-CoV-2 3CLpro. Antiviral Res 2022; 207: 105419.
[http://dx.doi.org/10.1016/j.antiviral.2022.105419] [PMID: 36155070]
[19]
Araújo HM, de Moura GA, Rocha YM, Viana Rodrigues JP, Nicolete R. Oxadiazole derivatives as anticancer and immunomodulatory agents: A systematic review. Curr Med Chem 2023; 30(30): 3472-85.
[http://dx.doi.org/10.2174/0929867329666220929145619] [PMID: 36177625]
[20]
Ayoup MS, ElShafey MM, Abdel-Hamid H, et al. Repurposing 1,2,4-oxadiazoles as SARS-CoV-2 PLpro inhibitors and investigation of their possible viral entry blockade potential. Eur J Med Chem 2023; 252: 115272.
[http://dx.doi.org/10.1016/j.ejmech.2023.115272] [PMID: 36966652]
[21]
Chatterjee B, Thakur SS. Remdesivir and Its Combination With Repurposed Drugs as COVID-19 Therapeutics. Front Immunol 2022; 13: 830990.
[http://dx.doi.org/10.3389/fimmu.2022.830990] [PMID: 35634324]
[22]
Li X, Kong B, Sun Y, Sun F, Yang H, Zheng S. Synergistic potential of teriflunomide with fluconazole against resistant Candida albicans in vitro and in vivo. Front Cell Infect Microbiol 2023; 13: 1282320.
[http://dx.doi.org/10.3389/fcimb.2023.1282320] [PMID: 38169891]
[23]
Rabie AM. Teriflunomide: A possible effective drug for the comprehensive treatment of COVID-19. Curr Res Pharmacol Drug Disc 2021; 2: 100055.
[http://dx.doi.org/10.1016/j.crphar.2021.100055] [PMID: 34870153]
[24]
Berlin JA, Glasser SC, Ellenberg SS. Adverse event detection in drug development: Recommendations and obligations beyond phase 3. Am J Public Health 2008; 98(8): 1366-71.
[http://dx.doi.org/10.2105/AJPH.2007.124537] [PMID: 18556607]
[25]
Derry S, Kong Loke Y, Aronson JK. Incomplete evidence: the inadequacy of databases in tracing published adverse drug reactions in clinical trials. BMC Med Res Methodol 2001; 1(1): 7.
[http://dx.doi.org/10.1186/1471-2288-1-7] [PMID: 11591220]
[26]
Morimoto T, Gandhi TK, Seger AC, Hsieh TC, Bates DW. Adverse drug events and medication errors: detection and classification methods. Qual Saf Health Care 2004; 13(4): 306-14.
[http://dx.doi.org/10.1136/qshc.2004.010611] [PMID: 15289635]
[27]
Nikfarjam A, Ransohoff JD, Callahan A, et al. Early Detection of Adverse Drug Reactions in Social Health Networks: A Natural Language Processing Pipeline for Signal Detection. JMIR Public Health Surveill 2019; 5(2): e11264.
[http://dx.doi.org/10.2196/11264] [PMID: 31162134]
[28]
Montané E, Santesmases J. Adverse drug reactions. Med Clin 2020; 154(5): 178-84.
[PMID: 31771857]
[29]
Onakpoya IJ. Rare adverse events in clinical trials: understanding the rule of three. BMJ Evid Based Med 2018; 23(1): 6.
[http://dx.doi.org/10.1136/ebmed-2017-110885] [PMID: 29367316]
[30]
Curtin F, Schulz P. Assessing the benefit:risk ratio of a drug randomized and naturalistic evidence. Dialogues Clin Neurosci 2011; 13(2): 183-90.
[http://dx.doi.org/10.31887/DCNS.2011.13.2/fcurtin] [PMID: 21842615]
[31]
Hamid AAA, Rahim R, Teo SP. Pharmacovigilance and its importance for primary health care professionals. Korean J Fam Med 2022; 43(5): 290-5.
[http://dx.doi.org/10.4082/kjfm.21.0193] [PMID: 36168900]
[32]
Kürzinger ML, Douarin L, Uzun I, et al. Structured benefit–risk evaluation for medicinal products: Review of quantitative benefit–risk assessment findings in the literature. Ther Adv Drug Saf 2020; 11
[http://dx.doi.org/10.1177/2042098620976951] [PMID: 33343857]
[33]
Hoffman KB, Dimbil M, Tatonetti NP, Kyle RF. A pharmacovigilance signaling system based on fda regulatory action and post-marketing adverse event reports. Drug Saf 2016; 39(6): 561-75.
[http://dx.doi.org/10.1007/s40264-016-0409-x] [PMID: 26946292]
[34]
Sonawane KB, Cheng N, Hansen RA. Serious adverse drug events reported to the fda: analysis of the fda adverse event reporting system 2006-2014 database. J Manag Care Spec Pharm 2018; 24(7): 682-90.
[http://dx.doi.org/10.18553/jmcp.2018.24.7.682] [PMID: 29952714]
[35]
Veronin MA, Schumaker RP, Dixit R. The Irony of MedWatch and the FAERS Database: An Assessment of Data Input Errors and Potential Consequences. J Pharm Technol 2020; 36(4): 164-7.
[http://dx.doi.org/10.1177/8755122520928495] [PMID: 34752566]
[36]
Han L, Ball R, Pamer CA, Altman RB, Proestel S. Development of an automated assessment tool for MedWatch reports in the FDA adverse event reporting system. J Am Med Inform Assoc 2017; 24(5): 913-20.
[http://dx.doi.org/10.1093/jamia/ocx022] [PMID: 28371826]
[37]
Kessler DA. Introducing MEDWatch. JAMA 1993; 269(21): 2765-8.
[http://dx.doi.org/10.1001/jama.1993.03500210065033] [PMID: 8492403]
[38]
Veronin MA, Schumaker RP, Dixit RR, Elath H. Opioids and frequency counts in the us food and drug administration adverse event reporting system (FAERS) database: a quantitative view of the epidemic. Drug Healthc Patient Saf 2019; 11: 65-70.
[http://dx.doi.org/10.2147/DHPS.S214771] [PMID: 31695510]
[39]
Khaleel MA, Khan AH, Ghadzi SMS, Adnan AS, Abdallah QM. A standardized dataset of a spontaneous adverse event reporting system. Healthcare 2022; 10(3): 420.
[http://dx.doi.org/10.3390/healthcare10030420] [PMID: 35326898]
[40]
Bu K, Patel D, Morris R, et al. Dysphagia risk in patients prescribed rivastigmine: A systematic analysis of fda adverse event reporting system. J Alzheimers Dis 2022; 89(2): 721-31.
[http://dx.doi.org/10.3233/JAD-220583] [PMID: 35964196]
[41]
Morris R, Luboff H, Jose RP, et al. Bradycardia due to donepezil in adults: Systematic analysis of fda adverse event reporting system. J Alzheimers Dis 2021; 81(1): 297-307.
[http://dx.doi.org/10.3233/JAD-201551] [PMID: 33780370]
[42]
Hsu SY, Morris R, Cheng F. Signaling pathways regulated by silica nanoparticles. Molecules 2021; 26(5): 1398.
[http://dx.doi.org/10.3390/molecules26051398] [PMID: 33807638]
[43]
Morris RTM, Aponte N, Salcedo M, et al. The association between warfarin usage and international normalized ratio increase: systematic analysis of FDA Adverse Event Reporting System (FAERS). 2023, 3, 39. J Cardiov Aging 2023; 3(39)
[PMID: 38235056]
[44]
Böhm R, Bulin C, Waetzig V, Cascorbi I, Klein HJ, Herdegen T. Pharmacovigilance-based drug repurposing: The search for inverse signals via OpenVigil identifies putative drugs against viral respiratory infections. Br J Clin Pharmacol 2021; 87(11): 4421-31.
[http://dx.doi.org/10.1111/bcp.14868] [PMID: 33871897]
[45]
Hosomi K, Fujimoto M, Ushio K, Mao L, Kato J, Takada M. An integrative approach using real-world data to identify alternative therapeutic uses of existing drugs. PLoS One 2018; 13(10): e0204648.
[http://dx.doi.org/10.1371/journal.pone.0204648] [PMID: 30300381]
[46]
Ko M, Oh JM, Kim IW. Drug repositioning prediction for psoriasis using the adverse event reporting database. Front Med 2023; 10: 1159453.
[http://dx.doi.org/10.3389/fmed.2023.1159453] [PMID: 37035327]
[47]
Liu Y, Liu Y, Fan R, et al. Pharmacovigilance-based drug repurposing: searching for putative drugs with hypohidrosis or anhidrosis adverse events for use against hyperhidrosis. Eur J Med Res 2023; 28(1): 95.
[http://dx.doi.org/10.1186/s40001-023-01048-z] [PMID: 36829251]
[48]
Wang K, Wan M, Wang RS, Weng Z. Opportunities for web-based drug repositioning: searching for potential antihypertensive agents with hypotension adverse events. J Med Internet Res 2016; 18(4): e76.
[http://dx.doi.org/10.2196/jmir.4541] [PMID: 27036325]
[49]
Battini V, Rocca S, Guarnieri G, et al. On the potential of drug repurposing in dysphagia treatment: New insights from a real-world pharmacovigilance study and a systematic review. Front Pharmacol 2023; 14: 1057301.
[http://dx.doi.org/10.3389/fphar.2023.1057301] [PMID: 36937893]
[50]
Battini V, Van Manen RP, Gringeri M, et al. The potential antidepressant effect of antidiabetic agents: New insights from a pharmacovigilance study based on data from the reporting system databases FAERS and VigiBase. Front Pharmacol 2023; 14: 1128387.
[http://dx.doi.org/10.3389/fphar.2023.1128387] [PMID: 36873988]
[51]
Wakai E, Suzumura Y, Ikemura K, et al. An integrated in silico and in vivo approach to identify protective effects of palonosetron in cisplatin-induced nephrotoxicity. Pharmaceuticals 2020; 13(12): 480.
[http://dx.doi.org/10.3390/ph13120480] [PMID: 33419241]
[52]
Xu D, Ham AG, Tivis RD, et al. MSBIS: A multi-step biomedical informatics screening approach for identifying medications that mitigate the risks of metoclopramide-induced tardive dyskinesia. EBioMedicine 2017; 26: 132-7.
[http://dx.doi.org/10.1016/j.ebiom.2017.11.015] [PMID: 29191560]
[53]
Zamami Y, Niimura T, Kawashiri T, et al. Identification of prophylactic drugs for oxaliplatin-induced peripheral neuropathy using big data. Biomed Pharmacother 2022; 148: 112744.
[http://dx.doi.org/10.1016/j.biopha.2022.112744] [PMID: 35240525]
[54]
de Anda-Jáuregui G, Guo K, McGregor BA, Hur J. Exploration of the anti-inflammatory drug space through network pharmacology: Applications for drug repurposing. Front Physiol 2018; 9: 151.
[http://dx.doi.org/10.3389/fphys.2018.00151] [PMID: 29545755]
[55]
Subramanian A, Narayan R, Corsello SM, et al. A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles. Cell 2017; 171(6): 1437-1452.e17.
[http://dx.doi.org/10.1016/j.cell.2017.10.049] [PMID: 29195078]
[56]
Wang Z, Clark NR, Ma’ayan A. Drug-induced adverse events prediction with the LINCS L1000 data. Bioinformatics 2016; 32(15): 2338-45.
[http://dx.doi.org/10.1093/bioinformatics/btw168] [PMID: 27153606]
[57]
Montastruc JL, Sommet A, Bagheri H, Lapeyre-Mestre M. Benefits and strengths of the disproportionality analysis for identification of adverse drug reactions in a pharmacovigilance database. Br J Clin Pharmacol 2011; 72(6): 905-8.
[http://dx.doi.org/10.1111/j.1365-2125.2011.04037.x] [PMID: 21658092]
[58]
Pushpakom S, Iorio F, Eyers PA, et al. Drug repurposing: progress, challenges and recommendations. Nat Rev Drug Discov 2019; 18(1): 41-58.
[http://dx.doi.org/10.1038/nrd.2018.168] [PMID: 30310233]
[59]
Dias P, Penedones A, Alves C, Ribeiro C, Marques F. The role of disproportionality analysis of pharmacovigilance databases in safety regulatory actions: a systematic review. Curr Drug Saf 2015; 10(3): 234-50.
[http://dx.doi.org/10.2174/1574886310666150729112903] [PMID: 26219291]
[60]
Moreland-Head LN, Coons JC, Seybert AL, Gray MP, Kane-Gill SL. Use of disproportionality analysis to identify previously unknown drug-associated causes of cardiac arrhythmias using the food and drug administration adverse event reporting system (faers) database. J Cardiovasc Pharmacol Ther 2021; 26(4): 341-8.
[http://dx.doi.org/10.1177/1074248420984082] [PMID: 33403858]
[61]
Peng L, Xiao K, Ottaviani S, Stebbing J, Wang YJ. A real-world disproportionality analysis of FDA Adverse Event Reporting System (FAERS) events for baricitinib. Expert Opin Drug Saf 2020; 19(11): 1505-11.
[http://dx.doi.org/10.1080/14740338.2020.1799975] [PMID: 32693646]
[62]
Farcaş A, Măhălean A, Bulik NB, Leucuta D, Mogoșan C. New safety signals assessed by the Pharmacovigilance Risk Assessment Committee at EU level in 2014–2017. Expert Rev Clin Pharmacol 2018; 11(10): 1045-51.
[http://dx.doi.org/10.1080/17512433.2018.1526676] [PMID: 30269618]
[63]
Insani WN, Pacurariu AC, Mantel-Teeuwisse AK, Gross-Martirosyan L. Characteristics of drugs safety signals that predict safety related product information update. Pharmacoepidemiol Drug Saf 2018; 27(7): 789-96.
[http://dx.doi.org/10.1002/pds.4446] [PMID: 29797381]
[64]
Noguchi Y, Yoshizawa S, Aoyama K, Kubo S, Tachi T, Teramachi H. Verification of the “Upward Variation in the Reporting Odds Ratio Scores” to Detect the Signals of Drug–Drug Interactions. Pharmaceutics 2021; 13(10): 1531.
[http://dx.doi.org/10.3390/pharmaceutics13101531] [PMID: 34683823]
[65]
Trillenberg P, Sprenger A, Machner B. Sensitivity and specificity in signal detection with the reporting odds ratio and the information component. Pharmacoepidemiol Drug Saf 2023; 32(8): 910-7.
[http://dx.doi.org/10.1002/pds.5624] [PMID: 36966482]
[66]
van Puijenbroek EP, Bate A, Leufkens HGM, Lindquist M, Orre R, Egberts ACG. A comparison of measures of disproportionality for signal detection in spontaneous reporting systems for adverse drug reactions. Pharmacoepidemiol Drug Saf 2002; 11(1): 3-10.
[http://dx.doi.org/10.1002/pds.668] [PMID: 11998548]
[67]
Tenny S. Disclosure: Mary Hoffman declares no relevant financial relationships with ineligible companies. In StatPearls: Treasure Island (FL) ineligible companies 2024.
[68]
Rothman KJ, Lanes S, Sacks ST. The reporting odds ratio and its advantages over the proportional reporting ratio. Pharmacoepidemiol Drug Saf 2004; 13(8): 519-23.
[http://dx.doi.org/10.1002/pds.1001] [PMID: 15317031]
[69]
Wang L, Rastegar-Mojarad M, Ji Z, et al. Detecting pharmacovigilance signals combining electronic medical records with spontaneous reports: A Case study of conventional disease-modifying antirheumatic drugs for rheumatoid arthritis. Front Pharmacol 2018; 9: 875.
[http://dx.doi.org/10.3389/fphar.2018.00875] [PMID: 30131701]
[70]
Kerr S, Greenland S, Jeffrey K, et al. Understanding and reporting odds ratios as rate-ratio estimates in case-control studies. J Glob Health 2023; 13: 04101.
[http://dx.doi.org/10.7189/jogh.13.04101] [PMID: 37712381]
[71]
Li H, Zhang M, Jiao X, et al. Using disproportionality analysis to explore the association between periostitis and triazole antifungals in the FDA Adverse Event Reporting System Database. Sci Rep 2023; 13(1): 4475.
[http://dx.doi.org/10.1038/s41598-023-27687-0] [PMID: 36934109]
[72]
Takada M, Fujimoto M, Motomura H, Hosomi K. Inverse Association between Sodium Channel-Blocking Antiepileptic Drug Use and Cancer: Data mining of spontaneous reporting and claims databases. Int J Med Sci 2016; 13(1): 48-59.
[http://dx.doi.org/10.7150/ijms.13834] [PMID: 26816494]
[73]
Böhm R, von Hehn L, Herdegen T, et al. OpenVigil FDA : Inspection of u.s. american adverse drug events pharmacovigilance data and novel clinical applications. PLoS One 2016; 11(6): e0157753.
[http://dx.doi.org/10.1371/journal.pone.0157753] [PMID: 27326858]
[74]
Huang H, Zhang P, Qu XA, Sanseau P, Yang L. Systematic prediction of drug combinations based on clinical side-effects. Sci Rep 2014; 4(1): 7160.
[http://dx.doi.org/10.1038/srep07160] [PMID: 25418113]
[75]
Li Y, Zhang P, Sun Z, Hu J. Data-driven prediction of beneficial drug combinations in spontaneous reporting systems. AMIA Annu Symp Proc 2017; 2016: 808-17.
[PMID: 28269877]
[76]
McQuade BM, Campbell A. Drug prescribing: drug-drug interactions. FP Essent 2021; 508: 25-32.
[PMID: 34491709]
[77]
Sultana J, Cutroneo P, Trifirò G. Clinical and economic burden of adverse drug reactions. J Pharmacol Pharmacother 2013; 4(1_suppl) (Suppl. 1): S73-7.
[http://dx.doi.org/10.4103/0976-500X.120957] [PMID: 24347988]
[78]
Baniasadi S, Farzanegan B, Alehashem M. Important drug classes associated with potential drug–drug interactions in critically ill patients: highlights for cardiothoracic intensivists. Ann Intensive Care 2015; 5(1): 44.
[http://dx.doi.org/10.1186/s13613-015-0086-4] [PMID: 26603290]
[79]
Carpenter M, Berry H, Pelletier AL. Clinically relevant drug-drug interactions in primary care. Am Fam Physician 2019; 99(9): 558-64.
[PMID: 31038898]
[80]
Doligalski CT, Tong Logan A, Silverman A. Drug interactions: A primer for the gastroenterologist. Gastroenterol Hepatol 2012; 8(6): 376-83.
[PMID: 22933873]
[81]
Zhao M, Ma J, Li M, et al. Cytochrome p450 enzymes and drug metabolism in humans. Int J Mol Sci 2021; 22(23): 12808.
[http://dx.doi.org/10.3390/ijms222312808] [PMID: 34884615]
[82]
Zhou B, Wang R, Wu P, Kong DX. Drug repurposing based on drug-drug interaction. Chem Biol Drug Des 2015; 85(2): 137-44.
[http://dx.doi.org/10.1111/cbdd.12378] [PMID: 24934184]
[83]
Alshammari TM, AlMutairi EN. Use of an entacapone-containing drug combination and risk of death: Analysis of the FDA AERS (FAERS) database. Saudi Pharm J 2015; 23(1): 28-32.
[http://dx.doi.org/10.1016/j.jsps.2014.04.005] [PMID: 25685040]
[84]
Cuadros-Inostroza Á, Caldana C, Redestig H, et al. TargetSearch a Bioconductor package for the efficient preprocessing of GC-MS metabolite profiling data. BMC Bioinformatics 2009; 10(1): 428.
[http://dx.doi.org/10.1186/1471-2105-10-428] [PMID: 20015393]
[85]
Zhao S, Nishimura T, Chen Y, et al. Systems pharmacology of adverse event mitigation by drug combinations. Sci Transl Med 2013; 5(206): 206ra140.
[http://dx.doi.org/10.1126/scitranslmed.3006548] [PMID: 24107779]
[86]
Keenan AB, Jenkins SL, Jagodnik KM, et al. The library of integrated network-based cellular signatures nih program: system-level cataloging of human cells response to perturbations. Cell Syst 2018; 6(1): 13-24.
[http://dx.doi.org/10.1016/j.cels.2017.11.001] [PMID: 29199020]
[87]
Stathias V, Turner J, Koleti A, et al. LINCS Data Portal 2.0: Next generation access point for perturbation-response signatures. Nucleic Acids Res 2020; 48(D1): D431-9.
[http://dx.doi.org/10.1093/nar/gkz1023] [PMID: 31701147]
[88]
Xie Z, Kropiwnicki E, Wojciechowicz ML, et al. Getting Started with LINCS Datasets and Tools. Curr Protoc 2022; 2(7): e487.
[http://dx.doi.org/10.1002/cpz1.487] [PMID: 35876555]
[89]
Zamami Y, Hamano H, Niimura T, et al. Drug-repositioning approaches based on medical and life science databases. Front Pharmacol 2021; 12: 752174.
[http://dx.doi.org/10.3389/fphar.2021.752174] [PMID: 34790124]
[90]
Lamb J. The Connectivity Map: A new tool for biomedical research. Nat Rev Cancer 2007; 7(1): 54-60.
[http://dx.doi.org/10.1038/nrc2044] [PMID: 17186018]
[91]
Lim N, Pavlidis P. Evaluation of connectivity map shows limited reproducibility in drug repositioning. Sci Rep 2021; 11(1): 17624.
[http://dx.doi.org/10.1038/s41598-021-97005-z] [PMID: 34475469]
[92]
Musa A, Ghoraie LS, Zhang SD, et al. A review of connectivity map and computational approaches in pharmacogenomics. Brief Bioinform 2018; 19(3): 506-23.
[PMID: 28069634]
[93]
Al Meslamani AZ. Underreporting of adverse drug events: a look into the extent, causes, and potential solutions. Expert Opin Drug Saf 2023; 22(5): 351-4.
[http://dx.doi.org/10.1080/14740338.2023.2224558] [PMID: 37300402]
[94]
Begley CG, Ashton M, Baell J, et al. Drug repurposing: Misconceptions, challenges, and opportunities for academic researchers. Sci Transl Med 2021; 13(612): eabd5524.
[http://dx.doi.org/10.1126/scitranslmed.abd5524] [PMID: 34550729]
[95]
Scholl JHG, van Puijenbroek EP. The value of time-to-onset in statistical signal detection of adverse drug reactions: a comparison with disproportionality analysis in spontaneous reports from the Netherlands. Pharmacoepidemiol Drug Saf 2016; 25(12): 1361-7.
[http://dx.doi.org/10.1002/pds.4115] [PMID: 27686554]
[96]
Alatawi YM, Hansen RA. Empirical estimation of under-reporting in the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS). Expert Opin Drug Saf 2017; 16(7): 761-7.
[http://dx.doi.org/10.1080/14740338.2017.1323867] [PMID: 28447485]
[97]
García-Abeijon P, Costa C, Taracido M, Herdeiro MT, Torre C, Figueiras A. Factors associated with underreporting of adverse drug reactions by health care professionals: a systematic review update. Drug Saf 2023; 46(7): 625-36.
[http://dx.doi.org/10.1007/s40264-023-01302-7] [PMID: 37277678]
[98]
Potlog Shchory M, Goldstein LH, Arcavi L, Shihmanter R, Berkovitch M, Levy A. Increasing adverse drug reaction reporting How can we do better? PLoS One 2020; 15(8): e0235591.
[http://dx.doi.org/10.1371/journal.pone.0235591] [PMID: 32790671]
[99]
Vallano A, Cereza G, Pedròs C, et al. Obstacles and solutions for spontaneous reporting of adverse drug reactions in the hospital. Br J Clin Pharmacol 2005; 60(6): 653-8.
[http://dx.doi.org/10.1111/j.1365-2125.2005.02504.x] [PMID: 16305591]
[100]
Mirbaha F, Shalviri G, Yazdizadeh B, Gholami K, Majdzadeh R. Perceived barriers to reporting adverse drug events in hospitals: a qualitative study using theoretical domains framework approach. Implement Sci 2015; 10(1): 110.
[http://dx.doi.org/10.1186/s13012-015-0302-5] [PMID: 26250159]

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