When a sponsor looks at a study, what do they actually see? Seth Halvorson of WCG put it plainly: “It’s almost like the tip of the iceberg, and then the size of the iceberg underneath the water.” Sponsors get the roll-up. Sites live below the waterline, and as Halvorson said, the two “are living in two different realities.”
That gap was the starting point for our recent panel, a follow-up to AMRC’s whitepaper, What Sponsors Don’t See: The Systems Behind Clinical Trial Delivery. Maxine Lai (CRIO), Seth Halvorson (WCG), Sweta Pittala (Velocity) and Katrinka Ellena (Javara) joined AMRC’s Emma Davidson to talk about the data sites collect every day, and why so little of it reaches the people planning the trial.
Sweta summarized the problem succinctly. “Sponsors typically see lagging indicators of study performance, like enrollment numbers, or the milestones, or protocol deviations,” she said, “but sites manage the leading indicators that ultimately drive those outcomes.” She believes better access to startup data is the answer. “By the time recruitment misses a target, the root cause may have been underlying for 60 or 90 days already.”
Seth agreed. His advice to sponsors was to “get upstream where you can divert the course, and it’s easy, and it’s small. You don’t have to try to do it at the mouth of the river, where it’s flooding into the ocean.” After all, he pointed out, “bad news early is good news.”
The relationship gets harder when a sponsor requires a site to run the study on mandated systems, layered onto the stack the site already uses. Seth’s view was that this rarely needs to happen: “There are better ways of doing things,” he said, “without asking somebody to just upend the way they operate to operate in a different name-brand system.” And the cost of that redundancy doesn’t stay with the site. As Katrinka put it, “It isn’t just site burden. It’s also a study burden.” Maxine, who worked as a clinical research coordinator before joining CRIO, offered a simpler starting point for sponsors: “asking what tech solution the network is using already, and then looking for ways to support them in that.”
Of course, any conversation about data was unlikely to avoid AI, and Sweta highlighted how much the architecture underneath it matters. “Your AI is only as valuable as the data ecosystem supporting it. When the data remains fragmented because of newly introduced systems, the insights remain fragmented as well.”
So, what’s the fix? The panel agreed it comes down to talking earlier. “The most expensive protocol amendment will be the one after the study goes live,” Sweta said. “The least expensive one is the one that could be prevented while you’re still designing the study.”
Emma summarized the discussion. “We need more data,” she said. “We don’t need all of the data.” The goal is partnership, standardization, and knowing why you need a metric before you ask for it.
Watch the full conversation on demand.
