Recommendations for the Use of Social Media in Pharmacovigilance: Lessons from IMI WEB-RADR

Overview

Journal Drug Saf

Specialties Pharmacology
Toxicology

Date 2019 Aug 26

PMID 31446567

Citations 34

Authors

John van Stekelenborg

Johan Ellenius

Simon Maskell

Tomas Bergvall

Ola Caster

Nabarun Dasgupta

Juergen Dietrich

Sara Gama

David Lewis

Victoria Newbould

Sabine Brosch

Carrie E Pierce

Gregory Powell

Alicia Ptaszynska-Neophytou

Antoni F Z Wisniewski

Phil Tregunno

G Niklas Noren

Munir Pirmohamed

Affiliations

Soon will be listed here.

Abstract

Over a period of 3 years, the European Union's Innovative Medicines Initiative WEB-RADR project has explored the value of social media (i.e., information exchanged through the internet, typically via online social networks) for identifying adverse events as well as for safety signal detection. Many patients and clinicians have taken to social media to discuss their positive and negative experiences of medications, creating a source of publicly available information that has the potential to provide insights into medicinal product safety concerns. The WEB-RADR project has developed a collaborative English language workspace for visualising and analysing social media data for a number of medicinal products. Further, novel text and data mining methods for social media analysis have been developed and evaluated. From this original research, several recommendations are presented with supporting rationale and consideration of the limitations. Recommendations for further research that extend beyond the scope of the current project are also presented.

Citing Articles

Real-World Evidence of Bevacizumab and Panitumumab Drug Resistance and Drug Ineffectiveness from EudraVigilance Database.

Vonica R, Morgovan C, Butuca A, Pumnea M, Cipaian R, Frum A Cancers (Basel). 2025; 17(4).

PMID: 40002260 PMC: 11853327. DOI: 10.3390/cancers17040663.

Bidirectional Long Short-Term Memory-Based Detection of Adverse Drug Reaction Posts Using Korean Social Networking Services Data: Deep Learning Approaches.

Lee C, Lee S, Song M, Kim J, Lee S JMIR Med Inform. 2024; 12:e45289.

PMID: 39565685 PMC: 11601139. DOI: 10.2196/45289.

Knowledge, Attitude, and Practice Regarding Pharmacovigilance and Barriers to Reporting Adverse Drug Reactions Among the General Population in Saudi Arabia.

Alshehri H, Alharbi A, Alqethami N, Alnuhait M, AlShammari A, Alotaibi A Risk Manag Healthc Policy. 2024; 17:2557-2572.

PMID: 39493376 PMC: 11531241. DOI: 10.2147/RMHP.S484223.

The Value of Social Media Analysis for Adverse Events Detection and Pharmacovigilance: Scoping Review.

Golder S, OConnor K, Wang Y, Klein A, Hernandez G JMIR Public Health Surveill. 2024; 10:e59167.

PMID: 39240684 PMC: 11415724. DOI: 10.2196/59167.

Developing Causality and Severity Assessment Frameworks for Food Safety Signals Using Social Media Reviews: A Technical Report Based on Data From an Urban Indian Suburb.

Prabhune A, Sri Hari V, Sethiya N, Gauniyal M Cureus. 2024; 16(7):e64426.

PMID: 39130955 PMC: 11317103. DOI: 10.7759/cureus.64426.

References

Harpaz R, DuMouchel W, Schuemie M, Bodenreider O, Friedman C, Horvitz E . Toward multimodal signal detection of adverse drug reactions. J Biomed Inform. 2017; 76:41-49. PMC: 8502488. DOI: 10.1016/j.jbi.2017.10.013. View

Cobert B, Silvey J . The Internet and drug safety: what are the implications for pharmacovigilance?. Drug Saf. 1999; 20(2):95-107. DOI: 10.2165/00002018-199920020-00001. View

Sloane R, Osanlou O, Lewis D, Bollegala D, Maskell S, Pirmohamed M . Social media and pharmacovigilance: A review of the opportunities and challenges. Br J Clin Pharmacol. 2015; 80(4):910-20. PMC: 4594734. DOI: 10.1111/bcp.12717. View

Hazell L, Shakir S . Under-reporting of adverse drug reactions : a systematic review. Drug Saf. 2006; 29(5):385-96. DOI: 10.2165/00002018-200629050-00003. View

Tregunno P, Fink D, Fernandez-Fernandez C, Lazaro-Bengoa E, Noren G . Performance of probabilistic method to detect duplicate individual case safety reports. Drug Saf. 2014; 37(4):249-58. DOI: 10.1007/s40264-014-0146-y. View

Brosch S, de Ferran A, Newbould V, Farkas D, Lengsavath M, Tregunno P . Establishing a Framework for the Use of Social Media in Pharmacovigilance in Europe. Drug Saf. 2019; 42(8):921-930. PMC: 6647461. DOI: 10.1007/s40264-019-00811-8. View

Ghosh R, Lewis D . Aims and approaches of Web-RADR: a consortium ensuring reliable ADR reporting via mobile devices and new insights from social media. Expert Opin Drug Saf. 2015; 14(12):1845-53. DOI: 10.1517/14740338.2015.1096342. View

Ralph Edwards I, Lindquist M . Social media and networks in pharmacovigilance: boon or bane?. Drug Saf. 2011; 34(4):267-71. DOI: 10.2165/11590720-000000000-00000. View

Freifeld C, Brownstein J, Menone C, Bao W, Filice R, Kass-Hout T . Digital drug safety surveillance: monitoring pharmaceutical products in twitter. Drug Saf. 2014; 37(5):343-50. PMC: 4013443. DOI: 10.1007/s40264-014-0155-x. View

10.

Anderson L, Bell H, Gilbert M, Davidson J, Winter C, Barratt M . Using Social Listening Data to Monitor Misuse and Nonmedical Use of Bupropion: A Content Analysis. JMIR Public Health Surveill. 2017; 3(1):e6. PMC: 5311422. DOI: 10.2196/publichealth.6174. View

11.

TenBarge A, Riggins J . Responding to Unsolicited Medical Requests from Health Care Professionals on Pharmaceutical Industry-Owned Social Media Sites: Three Pilot Studies. J Med Internet Res. 2018; 20(10):e285. PMC: 6234341. DOI: 10.2196/jmir.9643. View

12.

Caster O, Dietrich J, Kurzinger M, Lerch M, Maskell S, Noren G . Assessment of the Utility of Social Media for Broad-Ranging Statistical Signal Detection in Pharmacovigilance: Results from the WEB-RADR Project. Drug Saf. 2018; 41(12):1355-1369. PMC: 6223695. DOI: 10.1007/s40264-018-0699-2. View

13.

Powell G, Seifert H, Reblin T, Burstein P, Blowers J, Menius J . Social Media Listening for Routine Post-Marketing Safety Surveillance. Drug Saf. 2016; 39(5):443-54. DOI: 10.1007/s40264-015-0385-6. View

14.

Rezaallah B, Lewis D, Pierce C, Zeilhofer H, Berg B . Social Media Surveillance of Multiple Sclerosis Medications Used During Pregnancy and Breastfeeding: Content Analysis. J Med Internet Res. 2019; 21(8):e13003. PMC: 6702799. DOI: 10.2196/13003. View

15.

Gattepaille L, Vidlin S, Bergvall T, Pierce C, Ellenius J . Prospective Evaluation of Adverse Event Recognition Systems in Twitter: Results from the Web-RADR Project. Drug Saf. 2020; 43(8):797-808. PMC: 7395913. DOI: 10.1007/s40264-020-00942-3. View

16.

Harpaz R, Odgers D, Gaskin G, DuMouchel W, Winnenburg R, Bodenreider O . A time-indexed reference standard of adverse drug reactions. Sci Data. 2015; 1:140043. PMC: 4306188. DOI: 10.1038/sdata.2014.43. View

17.

Chen X, Faviez C, Schuck S, Lillo-Le-Louet A, Texier N, Dahamna B . Mining Patients' Narratives in Social Media for Pharmacovigilance: Adverse Effects and Misuse of Methylphenidate. Front Pharmacol. 2018; 9:541. PMC: 5978246. DOI: 10.3389/fphar.2018.00541. View

18.

Pierce C, Bouri K, Pamer C, Proestel S, Rodriguez H, Van Le H . Evaluation of Facebook and Twitter Monitoring to Detect Safety Signals for Medical Products: An Analysis of Recent FDA Safety Alerts. Drug Saf. 2017; 40(4):317-331. PMC: 5362648. DOI: 10.1007/s40264-016-0491-0. View

19.

Pierce C, de Vries S, Bodin-Parssinen S, Harmark L, Tregunno P, Lewis D . Recommendations on the Use of Mobile Applications for the Collection and Communication of Pharmaceutical Product Safety Information: Lessons from IMI WEB-RADR. Drug Saf. 2019; 42(4):477-489. PMC: 6450855. DOI: 10.1007/s40264-019-00813-6. View