In an interview with ACT editor Andy Studna at DIA 2024, Dabbs, vice president, global product strategy, IQVIA highlights challenges with tech overload and how stakeholders can choose which solution(s) are best for their studies.
ACT: There are a lot of competing tech providers currently out there for clinical trials. What should decision makers be keeping top of mind when choosing which solution(s) are best for them?
Dabbs: Well, I think the first thing that should be top of mind is the problem they're trying to address. It certainly shouldn't be: Is this technology going to work with my existing technology? Is it going to integrate? How am I going to have problems? That should not be what's front of mind. What should be front of mind is, what is the problem I'm trying to solve, which is how we've developed much of our technology, because that's what we've heard, particularly from sponsors.
ACT: Following on that, it seems tech overload is currently a challenge for sites. How can that be alleviated?
Dabbs: Yeah, it's a good point. We had a session some time ago where, to be honest, we realized we were part of the problem, because everybody brings some technology to run clinical research, indeed. Hopefully we're at the stage where clinical research can't be run without technology, and we realized that we had to solve for our sites and our sponsors—this challenge—but we realized the challenge was bigger than us, and so we said, “How can we approach this problem?” And we actually started with end users and sites themselves, and they counseled us on two discrete areas. One is accessing the tool sets that you describe, which indeed have proliferated, and then the second is knowing what to do. How can I speed action and reduce some of the friction? So, we took this approach to be broad from the from the outset, because that's what we had heard from sponsors.
ACT: Looking forward, which area of clinical research do you think has the best potential for utilizing new technology? Why?
Dabbs: There's two primary constituents in research. There's obviously the site and the patient. And many people have strategies focused on those two entities quite rightly, and connecting the experiences that those entities have is very important. One of the mechanisms by which you drive that connectivity, I think, is data and insights on that data, and we have taken the approach to treat analytics, if you like, as a horizontal spanning the research continuum. And so, I think it's no surprise to see more innovation in unlocking the power of data in informing workflows that will happen at, yes, a patient and yes, a site level, but when we can connect some of these data, you will be able to unlock new processes. A great example is how people are generating data for a label, in obviously a clinical setting, and how many of the tools and techniques are then used in a real-world context to provide further evidence of what happened in the clinic, obviously in a post-label setting. And I think analytics is one of the chief drivers of enabling that to happen.