药物安全至关重要，在药物发现，开发和分娩中的各个阶段。在整个跨度中，与非结构化的文本一起产生和寻求与安全相关的数据 - 内部安全报告，科学文献，个人案例安全报告，临床研究者手册，患者论坛，社交媒体，会议摘要。
在这十万页面上进行智能搜索可以提供信息以提供关键决策支持。生命科学公司正在积极寻求创新技术，以应对管理新的和不同来源的安全相关数据增加的挑战。必威官方在线我们的许多客户都使用语词的力量Natural Language Processing(NLP) platform to transform the unstructured text into actionable structured data that can be rapidly visualized and analyzed, at every stage through the safety lifecycle of a drug. This webinar will present an overview of customer success stories, to show best practice use of this Artificial Intelligence (AI) technology to advance drug safety.
你会学到什么？
- How natural language processing (NLP) text mining can extract structured data from unstructured text in scientific papers, clinical trial databases, internal safety reports, FDA drug labels, and more.
- How big pharma access internal data silos and external data sources for safety decision making. Use cases from top pharma and the FDA will be discussed.
Who should attend?
Anyone with an interest in getting better value from both internal and external textual information and integrating diverse data sets to provide knowledge relevant to drug safety and risk prediction.
- Specifically, informaticians, information professionals, researchers, with responsibility for:
- Risk profiles for targets in early drug discovery
- Preclinical and clinical drug safety
- Safety assessment across the pipeline
Speakers
Jane Reed
Director of Life Science Linguamatics, an IQVIA company
Kaitlyn Whyte
Application Scientist Linguamatics, an IQVIA company