PV-OWL——通过基于语义的网络平台进行药物警戒监测,在开放数据源和社交媒体上对药物相关不良反应进行持续和综合监测

C. Piccinni, E. Poluzzi, Mirko Orsini, S. Bergamaschi
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引用次数: 4

摘要

最近的欧盟药物警戒条例[条例(EU) 1235/2010,指令2010/84/EU]要求制药公司和公共卫生机构保持最新的药物安全信息,监测所有可用的数据源。在这里,我们提出了我们的项目,旨在通过整合公共数据库、科学文献和社交媒体的信息,开发一个持续监测药物不良反应(药物警戒)的网络平台。该项目将首先扫描有关药物不良事件的所有可用数据源,包括公开数据(例如FAERS - FDA不良事件报告系统、医学文献、社交媒体等)和专有数据(例如出院医院记录、药物处方档案、电子健康记录),这些数据需要与各自的数据所有者达成协议。随后,药物警戒专家将对识别药物和不良事件的代码进行半自动映射,以建立基于网络平台的词库。在这些初步活动之后,信号的产生和优先排序将是项目的核心。这项任务将得出每个纳入数据源的风险置信度评分和一个综合的全局评分,表明特定药物与不良事件之间可能存在的关联。软件框架MOMIS是一个开源数据集成系统,将允许异构和分布式数据源的半自动虚拟集成。将开发一个基于MOMIS的网络平台,能够合并有关不良事件的许多异构数据集。该平台将由外部专业主体(临床研究人员、药物警戒领域的公共或私营雇员)进行测试。该项目将提供a)一种创新的方式,在意大利首次将不同的数据库连接起来,以获得新的安全指标;B)一个网络平台,可以快速方便地整合所有可用数据,有助于验证和验证信号检测中产生的假设。最后,统一安全指标(全球风险评分)的发展将为广泛的专业和非专业用户(如患者、监管机构、临床医生、律师、人类科学家)提供一个引人注目的、易于理解的可视化格式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PV-OWL — Pharmacovigilance surveillance through semantic web-based platform for continuous and integrated monitoring of drug-related adverse effects in open data sources and social media
The recent EU regulation on Pharmacovigilance [Regulation (EU) 1235/2010, Directive 2010/84/EU] imposes both to Pharmaceutical companies and Public health agencies to maintain updated safety information of drugs, monitoring all available data sources. Here, we present our project aiming to develop a web platform for continuous monitoring of adverse effects of medicines (pharmacovigilance), by integrating information from public databases, scientific literature and social media. The project will start by scanning all available data sources concerning drug adverse events, both open (e.g., FAERS — FDA Adverse Event Reporting Systems, medical literature, social media, etc.) and proprietary data (e.g., discharge hospital records, drug prescription archives, electronic health records), that require agreement with respective data owners. Subsequent, pharmacovigilance experts will perform a semi-automatic mapping of codes identifying drugs and adverse events, to build the thesaurus of the web based platform. After these preliminary activities, signal generation and prioritization will be the core of the project. This task will result in risk confidence scores for each included data source and a comprehensive global score, indicating the possible association between a specific drug and an adverse event. The software framework MOMIS, an open source data integration system, will allow semi-automatic virtual integration of heterogeneous and distributed data sources. A web platform, based on MOMIS, able to merge many heterogeneous data sets concerning adverse events will be developed. The platform will be tested by external specialized subjects (clinical researchers, public or private employees in pharmacovigilance field). The project will provide a) an innovative way to link, for the first time in Italy, different databases to obtain novel safety indicators; b) a web platform for a fast and easy integration of all available data, useful to verify and validate hypothesis generated in signal detection. Finally, the development of the unified safety indicator (global risk score) will result in a compelling, easy-to-understand, visual format for a broad range of professional and not professional users like patients, regulatory authorities, clinicians, lawyers, human scientists.
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