In a video interview prior to the 2026 DPHARM conference, Andrea Valente, CEO of uMotif, explains why the real technology challenge isn't usability alone—it's making it easier for patients and sites to interact more effectively with each other.
News|Videos|September 23, 2024
The Use of Artificial Intelligence in Clinical Trial Enrollment
Author(s)Don Tracy, Associate Editor
In an interview with Applied Clinical Trials Associate Editor Don Tracy, Sonia Lwoff, director, clinical operations, Rho, discusses the potential for artificial intelligence in clinical trial decision-making and enrollment.
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ACT: Is there any potential for the use of AI when it comes to decision-making and enrollment?
Lwoff: In the trial development process, AI algorithms can analyze existing data to predict trial outcomes and identify optimal trial designs. It's already occurring and when it comes to patient recruitment and enrollment, AI can accelerate recruitment efforts by analyzing electronic health records and other data sources to identify potential participants who may meet the eligibility criteria for one trial. It's already occurring and when it comes to patient recruitment and enrollment, AI can accelerate recruitment efforts by analyzing electronic health records and other data sources to identify potential participants who may meet the eligibility criteria for one trial. Some site networks are already working with AI to check on their medical records to identify patients. However, we need to be mindful of how this data is being used at hospitals. There are some data privacy considerations. AI can process also and analyze data in real time and detect anomalies and potential issues more quickly than the traditional methods. Last but not least, AI may also be used to analyze previous trials data to start using it for site selection and to predict which sites may perform optimally in a given trial based on the previous experience with those sites.
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