Application of a Language Model Tool for COVID-19 Vaccine Adverse Event Monitoring Using Web and Social Media Content: Algorithm Development and Validation Study
Monitoring the web and social media provides opportunities to observe AEs that may be related to the use of COVID-19 vaccines. The presented analysis demonstrates the ability to use web content and social media as a data source that could contribute to the early observation of AEs and enhance postmarketing surveillance. It could help to adjust signal detection strategies and communication with external stakeholders, contributing to increased confidence in vaccine safety monitoring.
Authors
- Anne-Laure Chabanon (ORCID: https://orcid.org/0000-0002-5866-5801)
- Laurence Serradell (ORCID: https://orcid.org/0000-0003-3683-8086)
- Juhaeri Juhaeri (ORCID: https://orcid.org/0000-0001-8235-8388)
- Cliona Molony (ORCID: https://orcid.org/0000-0003-4578-3910)
- Yuning Chen (ORCID: https://orcid.org/0000-0002-7358-7055)
- Chathuri Daluwatte
- Alena Khromava (ORCID: https://orcid.org/0000-0002-5374-9782)
- Anthony Chan-Ou-Teung
Institutions
- Sanofi (France) (FR)
- Sanofi (Canada) (CA)
- Sanofi (United States) (US)
Publication Details
- Journal
- JMIR Infodemiology
- Published
- 2024-12-20
- DOI
- https://doi.org/10.2196/53424
- Citations
- 2
- Primary Topic
- Pharmacovigilance and Adverse Drug Reactions
- Type
- article
- Field-Weighted Citation Impact
- 0.70
Funders
- Sanofi