4.5 Article

Challenges and opportunities for mining adverse drug reactions: perspectives from pharma, regulatory agencies, healthcare providers and consumers

出版社

OXFORD UNIV PRESS
DOI: 10.1093/database/baac071

关键词

-

资金

  1. Spanish Plan for the Advancement of Language Technology (Plan TL)
  2. Barcelona Supercomputing Center
  3. 2020 Proyectos de I+D+i - RTI Tipo A [PID2020-119266RA-I00]
  4. National Library of Medicine [R15LM013209, R13LM013127]

向作者/读者索取更多资源

Monitoring drug safety is a key concern, and stakeholders are interested in using text mining and AI methods to manage the increasing volume of information on toxicity and adverse events. BioCreative VII organized a panel of experts to explore challenges in mining drug adverse reactions, and this article is a result of their discussion. The highlighted applications showcase the opportunities and challenges for text mining in drug discovery, testing, marketing, and post-market surveillance. Stakeholders are eager to embrace natural language processing and AI tools, creating opportunities for collaboration with regulatory agencies, pharma, and the text mining community.
Monitoring drug safety is a central concern throughout the drug life cycle. Information about toxicity and adverse events is generated at every stage of this life cycle, and stakeholders have a strong interest in applying text mining and artificial intelligence (AI) methods to manage the ever-increasing volume of this information. Recognizing the importance of these applications and the role of challenge evaluations to drive progress in text mining, the organizers of BioCreative VII (Critical Assessment of Information Extraction in Biology) convened a panel of experts to explore 'Challenges in Mining Drug Adverse Reactions'. This article is an outgrowth of the panel; each panelist has highlighted specific text mining application(s), based on their research and their experiences in organizing text mining challenge evaluations. While these highlighted applications only sample the complexity of this problem space, they reveal both opportunities and challenges for text mining to aid in the complex process of drug discovery, testing, marketing and post-market surveillance. Stakeholders are eager to embrace natural language processing and AI tools to help in this process, provided that these tools can be demonstrated to add value to stakeholder workflows. This creates an opportunity for the BioCreative community to work in partnership with regulatory agencies, pharma and the text mining community to identify next steps for future challenge evaluations.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.5
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据