Skip to content

The Clinical Trial Enterprise: Can AI Fix It?

Artificial Intelligence (AI) is reasonably well established in discovery and preclinical research, with success in areas such as target identification and molecular modeling. However, in clinical development, adoption has been fragmented and challenging to embed across the lifecycle. 

Read the full article by Rob DiCicco from Drug Discovery News here.

Related Blog Posts

Enough, already: the problem with clinical trial data collection

The clinical research ecosystem has never been more technologically capable — or more burdened by its own ambition. In December 2025, the Tufts Center for the Study of Drug Development and our team at TransCelerate published research that suggests nearly 30% of the data collected in clinical trials do not directly inform key decisions, yet patients are…

2026 DIA Global Annual Meeting: What the FDA’s Real-Time Data Push Actually Means for Sponsors and CROs

In this video interview from the 2026 DIA Global Annual Meeting, Kevin Bugin, head of global regulatory policy and intelligence at Amgen and executive sponsor of TransCelerate’s Embedded Pragmatic Trials initiative, reframes the FDA’s continuous review expectations around real-time evidence generation and explains why quality by design—not data cleanup—is what regulators are now demanding. Watch…