Pharmacovigilance in the digital age: gaining insight from social media data
Pharmacovigilance is essential for protecting patient health by monitoring and managing medication-related risks. Traditional methods like spontaneous reporting systems and clinical trials are valuable for identifying adverse drug events, but face delays in data access. Social media platforms, with...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2025-05-01
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| Series: | Experimental Biology and Medicine |
| Subjects: | |
| Online Access: | https://www.ebm-journal.org/articles/10.3389/ebm.2025.10555/full |
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| author | Fan Dong Wenjing Guo Jie Liu Tucker A. Patterson Huixiao Hong |
| author_facet | Fan Dong Wenjing Guo Jie Liu Tucker A. Patterson Huixiao Hong |
| author_sort | Fan Dong |
| collection | DOAJ |
| description | Pharmacovigilance is essential for protecting patient health by monitoring and managing medication-related risks. Traditional methods like spontaneous reporting systems and clinical trials are valuable for identifying adverse drug events, but face delays in data access. Social media platforms, with their real-time data, offer a novel avenue for pharmacovigilance by providing a wealth of user-generated content on medication usage, adverse drug events, and public sentiment. However, the unstructured nature of social media content presents challenges in data analysis, including variability and potential biases. Advanced techniques like natural language processing and machine learning are increasingly being employed to extract meaningful information from social media data, aiding in early adverse drug event detection and real-time medication safety monitoring. Ensuring data reliability and addressing ethical considerations are crucial in this context. This review examines the existing literature on the use of social media data for drug safety analysis, highlighting the platforms involved, methodologies applied, and research questions explored. It also discusses the challenges, limitations, and future directions of this emerging field, emphasizing the need for ethical principles, transparency, and interdisciplinary collaboration to maximize the potential of social media in enhancing pharmacovigilance efforts. |
| format | Article |
| id | doaj-art-4fb302c4988e45d3bc4f1705e38ab6b5 |
| institution | DOAJ |
| issn | 1535-3699 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Experimental Biology and Medicine |
| spelling | doaj-art-4fb302c4988e45d3bc4f1705e38ab6b52025-08-20T03:12:24ZengFrontiers Media S.A.Experimental Biology and Medicine1535-36992025-05-0125010.3389/ebm.2025.1055510555Pharmacovigilance in the digital age: gaining insight from social media dataFan DongWenjing GuoJie LiuTucker A. PattersonHuixiao HongPharmacovigilance is essential for protecting patient health by monitoring and managing medication-related risks. Traditional methods like spontaneous reporting systems and clinical trials are valuable for identifying adverse drug events, but face delays in data access. Social media platforms, with their real-time data, offer a novel avenue for pharmacovigilance by providing a wealth of user-generated content on medication usage, adverse drug events, and public sentiment. However, the unstructured nature of social media content presents challenges in data analysis, including variability and potential biases. Advanced techniques like natural language processing and machine learning are increasingly being employed to extract meaningful information from social media data, aiding in early adverse drug event detection and real-time medication safety monitoring. Ensuring data reliability and addressing ethical considerations are crucial in this context. This review examines the existing literature on the use of social media data for drug safety analysis, highlighting the platforms involved, methodologies applied, and research questions explored. It also discusses the challenges, limitations, and future directions of this emerging field, emphasizing the need for ethical principles, transparency, and interdisciplinary collaboration to maximize the potential of social media in enhancing pharmacovigilance efforts.https://www.ebm-journal.org/articles/10.3389/ebm.2025.10555/fulldrug safetyartificial intelligencemachine learningnatural language processingsocial mediapost-market surveillance |
| spellingShingle | Fan Dong Wenjing Guo Jie Liu Tucker A. Patterson Huixiao Hong Pharmacovigilance in the digital age: gaining insight from social media data Experimental Biology and Medicine drug safety artificial intelligence machine learning natural language processing social media post-market surveillance |
| title | Pharmacovigilance in the digital age: gaining insight from social media data |
| title_full | Pharmacovigilance in the digital age: gaining insight from social media data |
| title_fullStr | Pharmacovigilance in the digital age: gaining insight from social media data |
| title_full_unstemmed | Pharmacovigilance in the digital age: gaining insight from social media data |
| title_short | Pharmacovigilance in the digital age: gaining insight from social media data |
| title_sort | pharmacovigilance in the digital age gaining insight from social media data |
| topic | drug safety artificial intelligence machine learning natural language processing social media post-market surveillance |
| url | https://www.ebm-journal.org/articles/10.3389/ebm.2025.10555/full |
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