Excitement Around the Current State of Clinical Technology

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In part 1 of this video interview, Melissa Easy, VP commercial, digital products & solutions, IQVIA highlights how patients, sites, and sponsors can benefit from recent advancements such as AI and LLMs.

ACT: With all of the advancements in artificial intelligence (AI) and large language models (LLMs) lately, what excites you most about the current state of clinical technology?

Easy: A great question—I think what excites me the most is that we truly have an opportunity to alleviate the challenges that we have in a really meaningful way for stakeholders. I'm focusing—at the moment, in my mind—on patients, sites, and sponsors. I think not only can we make trials more accessible, but a lot less burdensome, and I think it's different for all the different stakeholders. If I think about patients, for example, and I think about how AI can really help with trial efficiency, but also patient centricity at the same time. Not only can AI help us identify the right patients, so real, precise matching, which can help us accelerate recruitment, which in turn makes a study much faster, but it can even really help with the communication, specifically to patients, like really focused on different cohorts and what they're going to need. I think that's quite exciting.

If I think about sites, I think of everything that we're doing with AI and LLMs around how it can be an aggregator and a connector, really helping sites focus on the tasks they actually need to perform across all the different technologies that we do as an industry, have a habit of throwing at them, because I think that this will lead to significant reduction in burden for sites, which is something that we continually, in the industry, year after year, hear as a complaint from sites.

When I even think about what excites me for sponsors and AI and LLMs, I sit back and I think, well, a sponsors main job is really that oversight. It's a regulatory imperative for them running a trial. I feel like you can have GenAI and conversational AI really come together to automate tasks for peak efficiency and safety. For example, with GenAI, if we think about all the different sources of data, the volume of data—how we can really now spot patterns, assess risks, and look at outcomes. We used to rely on humans to do it, and it would take days and days. Now we're talking about minutes or hours depending upon what we're actually doing, and even conversational AI to really help with real-time monitoring and protocol adherence, etc. So, for me, overall, regardless of the stakeholder, I think it's really talking about that streamlining of processes and really getting products to market faster and to really helping the patients that need these products. I'm generally excitable, but there you have that one.

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