Social Media Listening for Routine Post-Marketing Safety Surveillance
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Post-marketing safety surveillance primarily relies on data from spontaneous adverse event reports, medical literature, and observational databases. Limitations of these data sources include potential under-reporting, lack of geographic diversity, and time lag between event occurrence and discovery. There is growing interest in exploring the use of social media (‘social listening’) to supplement established approaches for pharmacovigilance. Although social listening is commonly used for commercial purposes, there are only anecdotal reports of its use in pharmacovigilance. Health information posted online by patients is often publicly available, representing an untapped source of post-marketing safety data that could supplement data from existing sources.
The objective of this paper is to describe one methodology that could help unlock the potential of social media for safety surveillance.
A third-party vendor acquired 24 months of publicly available Facebook and Twitter data, then processed the data by standardizing drug names and vernacular symptoms, removing duplicates and noise, masking personally identifiable information, and adding supplemental data to facilitate the review process. The resulting dataset was analyzed for safety and benefit information.
In Twitter, a total of 6,441,679 Medical Dictionary for Regulatory Activities (MedDRA®) Preferred Terms (PTs) representing 702 individual PTs were discussed in the same post as a drug compared with 15,650,108 total PTs representing 946 individual PTs in Facebook. Further analysis revealed that 26 % of posts also contained benefit information.
Social media listening is an important tool to augment post-marketing safety surveillance. Much work remains to determine best practices for using this rapidly evolving data source.
KeywordsSocial Medium Anatomical Therapeutic Chemical Indicator Score Proportional Reporting Ratio Twitter Data
The authors thank many curators who have contributed to training the classifier, including Chi Bahk, Wenjie Bao, Anne Czernek, Michael Gilbert, Melissa Jordan, Christopher Menone, and Carly Winokur.
Compliance with Ethical Standards
GlaxoSmithKline paid for the research presented in this paper, including responding to reviewer comments during manuscript preparation. All work was conducted by the authors listed. Development of the social listening platform was funded in part by the US FDA under contract with Epidemico, Inc. prior to initiation and continuing throughout this research. Additional development funds for the social listening platform are provided to Epidemico, Inc. through a public–private partnership, but were not used to directly support the specific content of this research. This collaborative effort is provided via the WEB-RADR project, which is supported by the Innovative Medicines Initiative Joint Undertaking (IMI JU) under Grant Agreement No. 115632, resources of which are composed of financial contributions from the European Union’s Seventh Framework Programme (FP7/2007-2013) and EFPIA companies’ in kind contribution. Neither the FDA, WEB-RADR, nor IMI JU had any role in this research.
Conflict of interest
Gregory Powell, Harry Seifert, Tjark Reblin, Phil Burstein, James Blowers, Alan Menius, Jeffery Painter, Michele Thomas, and Heidi Bell were employees of or contractors to GlaxoSmithKline during the study. Carrie Pierce, Harold Rodriguez, John Brownstein, Clark Freifeld, and Nabarun Dasgupta are employees of or contractors to Epidemico, Inc., a technology company intending to commercialize the software platform used in this research.
- 1.World Health Organization. The importance of PV: safety monitoring of medical products. World Health Organization, United Kingdom. 2002. http://apps.who.int/medicinedocs/pdf/s4893e/s4893e.pdf. Accessed 7 Dec 2015.
- 2.Food and Drug Administration Amendments Act of 2007. 2007. http://www.fda.gov/RegulatoryInformation/Legislation/SignificantAmendmentstotheFDCAct/FoodandDrugAdministrationAmendmentsActof2007/FullTextofFDAAALaw/default.htm. Accessed 16 Sept 2015.
- 5.Stang PE, Ryan PB, Racoosin JA, Overhage JM, Hartzema AG, Reich C, et al. Advancing the science for active surveillance: rationale and design for the Observational Medical Outcomes Partnership. Ann Intern Med. 2010;153(9):600–6. doi: 10.7326/0003-4819-153-9-201011020-00010.CrossRefPubMedGoogle Scholar
- 7.Pew Research Internet Project. Health Fact Sheet: Highlights of the Pew Internet Project’s research related to health and healthcare. http://www.pewinternet.org/fact-sheets/health-fact-sheet. Accessed 7 Aug 2015.
- 9.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. 2015:1–9. doi: 10.1517/14740338.2015.1096342.
- 18.Majumder MS, Kluberg S, Santillana M, Mekaru S, Brownstein JS. ebola outbreak: media events track changes in observed reproductive number. PLoS Curr. 2014;2015:7. doi: 10.1371/currents.outbreaks.e6659013c1d7f11bdab6a20705d1e865.Google Scholar
- 21.Robinson G. A statistical approach to the spam problem. Linux J. 2003;2003(107):3.Google Scholar
- 30.Abou Taam M, Rossard C, Cantaloube L, Bouscaren N, Roche G, Pochard L, et al. Analysis of patients’ narratives posted on social media websites on benfluorex’s (Mediator(R)) withdrawal in France. J Clin Pharm Ther. 2014;39(1):53–5. doi: 10.1111/jcpt.12103.
- 46.Avillach P, Dufour JC, Diallo G, Salvo F, Joubert M, Thiessard F, et al. Design and validation of an automated method to detect known adverse drug reactions in MEDLINE: a contribution from the EU-ADR project. J Am Med Inform Assoc. 2013;20(3):446–52. doi: 10.1136/amiajnl-2012-001083.CrossRefPubMedPubMedCentralGoogle Scholar
- 48.Brown D. Cool Facts About Social Media. 2012. http://dannybrown.me/2012/06/06/52-cool-facts-social-media-2012/. Accessed 16 Oct 2015.
- 49.Beevolve. An Exhaustive Study of Twitter Users Around the World. 2012. http://temp.beevolve.com/twitter-statistics/-c1. Accessed 6 Oct 2015.
- 54.Reese S, Danielian L. Intermedia influence and the drug issue: converging on cocaine. In: Shoemaker P, editor. Communication campaigns about drugs: government, media and the public. Hillsdale: L. Erlbaum Associates; 1989.Google Scholar