All Times EDT
Keywords: Drug Development, Machine Learning
As the technology advances, tools, such as machine learning, super learner, are gradually employed as applications of artificial intelligence to develop biomarkers for qualification or for drug development, e.g., hepatologic biomarker, radiographic biomarker. The clinical utility includes but are not limited to disease diagnosis and characterization, monitoring disease progression, and prediction of treatment response. The benefits of high dimensional algorithm-guided approach stem from high computing power and the availability of web-based communication during development and for clinical use. From a public health stand point, these tools are attractive and can benefit clinical community as well as patient community. To advance the artificial intelligence field with a better understanding on their clinical utilities, in this roundtable, we share experience from academia, pharmaceutical industry and regulatory perspectives in supporting clinical research and drug development across multiple therapeutic areas.