De Pretis Francesco, van Gils Mark, Forsberg Markus M
VTT Technical Research Centre of Finland Ltd, 70210 Kuopio, Finland; Department of Communication and Economics, University of Modena and Reggio Emilia, 42121 Reggio Emilia, Italy.
Faculty of Medicine and Health Technology, Tampere University, 33720 Tampere, Finland.
Trends Pharmacol Sci. 2022 Jun;43(6):473-481. doi: 10.1016/j.tips.2022.03.009. Epub 2022 Apr 27.
Researchers, regulatory agencies, and the pharmaceutical industry are moving towards precision pharmacovigilance as a comprehensive framework for drug safety assessment, at the service of the individual patient, by clustering specific risk groups in different databases. This article explores its implementation by focusing on: (i) designing a new data collection infrastructure, (ii) exploring new computational methods suitable for drug safety data, and (iii) providing a computer-aided framework for distributed clinical decisions with the aim of compiling a personalized information leaflet with specific reference to a drug's risks and adverse drug reactions. These goals can be achieved by using 'smart hospitals' as the principal data sources and by employing methods of precision medicine and medical statistics to supplement current public health decisions.
研究人员、监管机构和制药行业正朝着精准药物警戒方向发展,将其作为药物安全性评估的综合框架,通过在不同数据库中对特定风险群体进行聚类,服务于个体患者。本文通过关注以下方面探讨其实施情况:(i)设计新的数据收集基础设施;(ii)探索适用于药物安全数据的新计算方法;(iii)提供一个用于分布式临床决策的计算机辅助框架,旨在编制一份针对药物风险和药物不良反应的个性化信息手册。这些目标可以通过将“智能医院”作为主要数据源,并采用精准医学和医学统计方法来补充当前的公共卫生决策来实现。