AI-Powered Clinical Trial Site Selection: Leqvio Cardiovascular Trial

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AI-Powered Clinical Trial Site Selection: Leqvio Cardiovascular Trial

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Swiss drugmaker Novartis turned to AI in 2023 when starting a 14,000-person, late-stage cardiovascular outcomes trial for its cholesterol drug Leqvio. Chief Medical Officer Shreeram Aradhye said the typical four- to six-week site selection process became a two-hour meeting, as AI helped identify higher-performing sites and allowed Novartis to close participant enrollment with only 13 patients above its trial target. The traditional clinical trial site selection process involves extensive manual review of potential research sites based on historical performance, patient populations, and infrastructure. Novartis deployed AI to analyze multiple data points across candidate sites, predicting which locations would deliver higher enrollment rates and better quality data. This AI-driven approach represents a significant shift in how pharmaceutical companies approach clinical trial design. By reducing the site selection timeline from weeks to hours, Novartis accelerated the trial initiation phase considerably. The AI system evaluated factors including site historical enrollment speeds, patient demographics, investigator experience, and proximity to patient populations. The successful implementation of AI in the Leqvio trial demonstrates how machine learning can optimize operational aspects of drug development beyond the core scientific research. A Novartis spokesperson said the time savings afforded by AI can accumulate to months over a drug-development program, potentially accelerating how quickly new treatments reach patients. Agentic AI could increase clinical development productivity by about 35% to 45% over the next five years, consultancy McKinsey predicted. This case exemplifies the broader trend of pharmaceutical companies leveraging AI for operational efficiency in clinical development.