Pfizer R&D, Lake Forest, Illinois, USA.
Pfizer Business Technology, Artificial Intelligence Center of Excellence, La Jolla, California, USA.
Clin Pharmacol Ther. 2019 Apr;105(4):954-961. doi: 10.1002/cpt.1255. Epub 2018 Dec 11.
Automation of pharmaceutical safety case processing represents a significant opportunity to affect the strongest cost driver for a company's overall pharmacovigilance budget. A pilot was undertaken to test the feasibility of using artificial intelligence and robotic process automation to automate processing of adverse event reports. The pilot paradigm was used to simultaneously test proposed solutions of three commercial vendors. The result confirmed the feasibility of using artificial intelligence-based technology to support extraction from adverse event source documents and evaluation of case validity. In addition, the pilot demonstrated viability of the use of safety database data fields as a surrogate for otherwise time-consuming and costly direct annotation of source documents. Finally, the evaluation and scoring method used in the pilot was able to differentiate vendor capabilities and identify the best candidate to move into the discovery phase.
药品安全案例处理自动化代表着影响公司整体药物警戒预算最强成本驱动因素的重大机会。进行了一项试点研究,以测试使用人工智能和机器人流程自动化来自动化处理不良事件报告的可行性。该试点范式被用于同时测试三个商业供应商的解决方案。结果证实了使用基于人工智能的技术来支持从不良事件源文件中提取和评估案例有效性的可行性。此外,该试点还证明了使用安全数据库数据字段作为替代否则耗时且昂贵的源文件直接注释的可行性。最后,试点中使用的评估和评分方法能够区分供应商的能力,并确定进入发现阶段的最佳候选者。