Advancements in AI for optimal clinical trial site identification: Turning Big Data into actionable intel

Despite advancing technologies, clinical trials still struggle to meet patient enrollment goals. Slow enrollment directly impacts schedule and budget, with each day of delay carrying cripplingly high costs. Successful, timely patient recruitment is directly linked to effective clinical trial site identification and selection. Conversely, selecting the wrong site can negatively impact recruitment or result in total failure to enroll patients.

Join the featured speaker to learn how advancements in AI can help pharma and biotech identify the best sites for their clinical trials through the harnessing of Big Data. Topics and learnings include:

• Insights on transitioning from a state of data overload to one of data driven, informed decision-making
• The role of artificial intelligence in optimising clinical trial site identification and selection
• Expected and unexpected downstream benefits of an AI-enabled site selection strategy

Speaker

Travis Caudill, Vice President Feasibility, Site Identification & Clinical Informatics, ICON

Travis Caudill has over 17 years’ experience in clinical trial strategy, global feasibility and site identification and is an expert in clinical trial modelling and simulation. As Vice President, Feasibility and Clinical Informatics at ICON, he oversees a team of world-class feasibility experts and data scientists who process, interrogate and analyse data to support effective data driven decisions for pharma, biotech and medical device sponsors.

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