This white paper demonstrates how applying FAIR data principles—Findable, Accessible, Interoperable, and Reusable—improves clinical data management and analytics. Modern trials generate data from diverse sources such as decentralized sites, wearables, and third-party labs, creating complexity and delays. The paper explains how centralized platforms like Signals Clinical harmonize and standardize data from day one, enabling early signal detection and efficient analysis. AI and machine learning further enhance harmonization and safety monitoring when applied to clean, structured data. By prioritizing FAIR practices, organizations reduce manual effort, accelerate study timelines, improve regulatory readiness, and enhance patient safety throughout the clinical lifecycle.

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