The emphasis on AI in clinical development continues to centre around achieving operational excellence, particularly in patient recruitment and
clinical data management. The life sciences industry is under increasing pressure to transition to the next phase of digital transformation by identifying practical AI implementations. Industry leaders are investing considerable time and resources into balancing AI's potential with realistic, impactful applications. Beyond these objectives, clinical development leaders are now tasked with generating meaningful insights from a wide array of data sources. This has prompted a vigorous exploration of AI use cases that can enhance data quality, improve clinical trial design, and accelerate the delivery of innovative therapies.
