In a recent video interview with Applied Clinical Trials, Kyle McAllister, co-founder, CEO, Trially, discussed the impact of funding cuts on underrepresented populations in medical research, emphasizing the importance of diversity-focused research. He highlighted the challenges created by budget cuts, particularly in patient recruitment and retention, due to reduced support staff. McAllister noted that artificial intelligence (AI) and new technologies like telemedicine are crucial for addressing these challenges by automating tasks and improving efficiency. He provided examples of AI’s success in reducing chart review time and increasing patient enrollment in studies.
ACT: How are clinical trial sites and sponsors adapting to these constraints?
McAllister: Ultimately, they’re doing more with less, like I said before, they’re resource constrained, and they’re doing more with less, which looks like a lot of things, but it’s leveraging new technologies like telemedicine or other tools that could decrease the cost of the actual care being provided, so cost containment measures, using remote monitoring tools, using teams that didn’t previously work together across multiple types of studies or departments. We’ve seen sites turning more towards industry sponsored trials to drive more revenue and ultimately cover some of the research they’re doing that was NIH and other government funded research, essentially using pharma money to keep the lights on and keep things moving forward. Not all that’s terrible, like the idea of moving towards more efficiency and finding ways to drive more revenue to keep things more sustainable, there’s some positive things in that, but I think the one of the big potential conflicts is it creates is a lot of the shift towards more industry sponsored research means the institutional priorities being shifted away from public interest focused research. Like I said, there’s some pro in that, but there’s also some real conflict and concern.
I think the brutal reality for a lot of sites is they’re being forced to adapt in ways that aren’t great, like they’re having to cut staff, they’re having to close departments, they’re having to close research programs. I think there is a lot of, I’ll say, research capacity that disappears with that, that it’s going to take time to grow back. There’s just research capacity that can’t be covered, and we’re in an age where it’s easier and easier to find new molecules, find new things to do research on, and this infrastructure that was there to actually run that research is being whittled back. Sites are doing heroic work out there, but I worry that heroism isn’t a sustainable staffing model.