Why Sponsors Must Act Now to Stay Competitive

In a recent video interview with Applied Clinical Trials, Angela Zubel, chief development officer, Debiopharm, described 2026 as an implementation year for AI and advanced analytics in drug development. She explained that many technologies had moved beyond pilot testing and were ready for broader adoption across clinical operations. Zubel highlighted opportunities to shorten timelines, reduce costs, and improve oversight through real-time monitoring, AI-supported site selection, and predictive analytics for compound prioritization. While acknowledging ongoing limitations in predictive modeling—particularly in oncology—she emphasized the importance of organizational openness to innovation. Sponsors that proactively standardized data, adopted practical AI tools, and experimented responsibly, she noted, were already seeing measurable gains in efficiency and competitiveness.

Editor's note: This transcript is a lightly edited rendering of the original audio/video content. It may contain errors, informal language, or omissions as spoken in the original recording.

ACT: What should sponsors and trial teams be preparing for now to stay competitive as new technologies reshape clinical development workflows?

Zubel: To stay competitive, sponsors and trial teams need to be open to innovation and not delay adoption out of caution.

Some organizations prefer a wait-and-see approach, hoping to choose the most successful tools later. That may work for large companies, but as a smaller organization, we’ve benefited from testing and implementing solutions quickly. We’ve already seen significant efficiencies.

For example, we’ve standardized our databases, which allows us to review data in real time instead of waiting for CRO data transfers. That alone has improved our data oversight dramatically. We’re also using AI tools for tasks like medical writing, drafting protocols, preparing investigator brochures, and generating repetitive documentation.

These tools allow us to work more efficiently, reduce manual effort, and require fewer personnel for routine tasks. The challenge now is selecting the right solutions, because there are many innovative companies in the space and it’s difficult to predict which will ultimately lead.

But if you’re willing to experiment responsibly, the savings in time and cost are already very clear.