The complexity of initiating clinical studies continues to grow. The complexity is a confluence of complicated protocols, globalization, and regulatory changes, all at a time when there is intense pressure to restrain costs and shorten timelines. The key to reducing these complexities is the ability to use machine learning to gain critical operational insights, which will allow organizations to learn and adapt. The insights gained will allow organizations to transition from subjective decisions to data-driven decisions.
In October 2020, Ed Miseta had the opportunity to sit down with Jennifer Goldsack of DiMe, Nechama Katan of Pfizer, Alex Zhavoronkov of Insilico Medicine, and Elvin Thalund of Oracle Health Sciences to discuss this topic.