In this video interview, Jeff Sidell, PhD, chief technology officer, Advarra, discusses the concept of data exhaust and how managing it can be simplified with artificial intelligence.
In a recent video interview with Applied Clinical Trials, Jeff Sidell, PhD, chief technology officer, Advarra, discussed current challenges in clinical research technology. He highlighted the overabundance of systems and emphasized the need for integration to streamline processes and reduce administrative overhead. Sidell also discussed the potential of AI, particularly predictive analytics, to automate repetitive tasks, enhancing efficiency and quality.
A transcript of Sidell’s conversation with ACT can be found below.
ACT: What challenges does industry need to address before it can utilize the full potential of artificial intelligence?
Sidell: I'll go back to integration. If you don't have a seamless, or at least somewhat seamless process from end to end, then the data you're producing—people call it data exhaust—the data that you're producing as a side effect of following those processes is going to be scattered. It's going to be siloed. You're going to have to integrate it together. It's a huge challenge, and it's a big expense, and a lot of clinical trials sites and even sponsors are not going to pay the money to do that. If you can first integrate the systems together and then look at the data exhaust, that's the data that you use to train models to mimic processes. Once they've achieved the integration aspect, then it's straightforward, simple, but not easy, to train the models, deploy them, deploy them correctly, so that there's appropriate oversight and achieve the benefits.
