论文标题
硅临床试验中的人工智能：评论
Artificial Intelligence for In Silico Clinical Trials: A Review
论文作者
论文摘要
临床试验是药物开发的重要一步，这通常是昂贵且耗时的。在计算机试验中，是通过模拟和建模作为替代传统临床试验的临床试验进行数字进行的。在计算机试验中支持AI可以通过创建虚拟队列作为控件来增加案例组的规模。此外，它还可以实现试验设计的自动化和优化，并预测试验成功率。本文在三个主要主题下系统地回顾了论文：临床模拟，个性化预测建模和计算机辅助试验设计。我们专注于如何在这些应用程序中应用机器学习（ML）。特别是，我们介绍了机器学习问题的提出和每个任务的可用数据源。最后，我们讨论了现实世界中的硅试验中AI的挑战和机遇。
A clinical trial is an essential step in drug development, which is often costly and time-consuming. In silico trials are clinical trials conducted digitally through simulation and modeling as an alternative to traditional clinical trials. AI-enabled in silico trials can increase the case group size by creating virtual cohorts as controls. In addition, it also enables automation and optimization of trial design and predicts the trial success rate. This article systematically reviews papers under three main topics: clinical simulation, individualized predictive modeling, and computer-aided trial design. We focus on how machine learning (ML) may be applied in these applications. In particular, we present the machine learning problem formulation and available data sources for each task. We end with discussing the challenges and opportunities of AI for in silico trials in real-world applications.
