Yang Y, Wang S F, Zhan S Y
National Institute of Health Data Science, Peking University, Beijing 100191, China.
Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, Chian.
Beijing Da Xue Xue Bao Yi Xue Ban. 2021 Jun 18;53(3):623-627. doi: 10.19723/j.issn.1671-167X.2021.03.031.
Post-marketing surveillance is the principal means to ensure drug use safety. The spontaneous report is the essential method of post-marketing surveillance for drug safety. Often, most spontaneous reports come from medical staff and sometimes come from patients who use the drug. The posts published by individuals on social media platforms that contain drugs and related adverse reaction content have gradually been seen as a new data source similar to spontaneous reports from drug users in recent years. Those user-generated posts potentially provide researchers and regulators with new opportunities to conduct post-marketing surveillance for drug safety from patients' perspectives mostly rather than medical professionals and can afford the possibility theoretically to discover drug-related safety issues earlier than traditional methods. Social media data as a new data source for safety signal detection and signal reinforcement have the unique advantages, such as population coverage, type of drugs, type of adverse reactions, data timeliness and quantity. Most of the social media data used in post-marketing surveillance research for drug safety are still text data in English, and even multiple languages are used by different people worldwide on several social media platforms. Unfortunately, there is still a controversy in the academic circles whether social media data can be used as reliable data sources for routine post-marketing surveillance for drug safety. A couple of obstacles of data, methods and ethics must be overcome before leveraging social media data for post-marketing surveillance. The number of Chinese social media users is large, and the social media data in the Chinese language is rapidly snowballing, which can be employed as the potential data source for post-marketing surveillance for drug safety. However, due to the Chinese language's specific characteristics, the text's diversity is different from the English text, and there is not enough accepted corpus in medical scenarios. Besides, the lack of domestic laws and regulations on privacy and security protection of social media data poses more challenges for applying Chinese social media data for post-market surveillance. The significance of social media data to post-marketing surveillance for drug safety is undoubtedly significant. It will be an essential development direction for future research to overcome the challenges of using social media data by developing new technologies and establishing new mechanisms.
上市后监测是确保用药安全的主要手段。自发报告是药品安全上市后监测的基本方法。通常,大多数自发报告来自医务人员,有时也来自使用该药物的患者。近年来,个人在社交媒体平台上发布的包含药品及相关不良反应内容的帖子逐渐被视为一种类似于药品使用者自发报告的新数据源。这些用户生成的帖子有可能为研究人员和监管机构提供新的机会,主要从患者而非医学专业人员的角度对药品安全进行上市后监测,并且理论上有可能比传统方法更早地发现与药物相关的安全问题。社交媒体数据作为安全信号检测和信号强化的新数据源具有独特优势,如人群覆盖范围、药物类型、不良反应类型、数据及时性和数量等。用于药品安全上市后监测研究的社交媒体数据大多仍是英文文本数据,甚至在多个社交媒体平台上全球不同的人使用多种语言。不幸的是,社交媒体数据能否作为药品安全常规上市后监测的可靠数据源在学术界仍存在争议。在利用社交媒体数据进行上市后监测之前,必须克服数据、方法和伦理方面的一些障碍。中国社交媒体用户数量庞大,中文社交媒体数据正在迅速增长,可作为药品安全上市后监测的潜在数据源。然而,由于中文的特定特性,文本的多样性与英文文本不同,且在医学场景中缺乏足够的公认语料库。此外,国内缺乏关于社交媒体数据隐私和安全保护的法律法规,这给应用中文社交媒体数据进行上市后监测带来了更多挑战。社交媒体数据对药品安全上市后监测的意义无疑是重大的。通过开发新技术和建立新机制来克服使用社交媒体数据的挑战将是未来研究的一个重要发展方向。