Department of Biomedical Sciences and Public Health, School of Medicine and Surgery, Marche Polytechnic University, Ancona, Italy.
Department of Communication and Economics, University of Modena and Reggio Emilia, Reggio Emilia, Italy.
J Eval Clin Pract. 2021 Jun;27(3):504-512. doi: 10.1111/jep.13542. Epub 2021 Feb 11.
RATIONALE, AIMS AND OBJECTIVES: The diversity of types of evidence (eg, case reports, animal studies and observational studies) makes the assessment of a drug's safety profile into a formidable challenge. While frequentist uncertain inference struggles in aggregating these signals, the more flexible Bayesian approaches seem better suited for this quest. Artificial Intelligence (AI) offers great promise to these approaches for information retrieval, decision support, and learning probabilities from data.
E-Synthesis is a Bayesian framework for drug safety assessments built on philosophical principles and considerations. It aims to aggregate all the available information, in order to provide a Bayesian probability of a drug causing an adverse reaction. AI systems are being developed for evidence aggregation in medicine, which increasingly are automated.
We find that AI can help E-Synthesis with information retrieval, usability (graphical decision-making aids), learning Bayes factors from historical data, assessing quality of information and determining conditional probabilities for the so-called 'indicators' of causation for E-Synthesis. Vice versa, E-Synthesis offers a solid methodological basis for (semi-)automated evidence aggregation with AI systems.
Properly applied, AI can help the transition of philosophical principles and considerations concerning evidence aggregation for drug safety to a tool that can be used in practice.
原理、目的和目标：证据类型的多样性（例如，病例报告、动物研究和观察性研究）使得评估药物的安全性概况成为一项艰巨的挑战。虽然频率不确定推理在汇总这些信号时存在困难，但更灵活的贝叶斯方法似乎更适合这项研究。人工智能 (AI) 为这些方法在信息检索、决策支持以及从数据中学习概率方面提供了巨大的潜力。
E-Synthesis 是一种基于哲学原理和考虑的药物安全性评估的贝叶斯框架。它旨在汇总所有可用信息，以提供药物引起不良反应的贝叶斯概率。人工智能系统正在为医学中的证据汇总开发，这些系统越来越自动化。
我们发现人工智能可以帮助 E-Synthesis 进行信息检索、可用性（图形决策辅助）、从历史数据中学习贝叶斯因子、评估信息质量以及确定 E-Synthesis 所谓“因果关系指标”的条件概率。反之，E-Synthesis 为使用人工智能系统进行（半）自动化证据汇总提供了坚实的方法基础。
正确应用时，人工智能可以帮助将哲学原理和考虑证据汇总用于药物安全性的原则和考虑转化为一种可在实践中使用的工具。
