Data Automation in Prospective Studies and Registries

This research white paper discusses OM1's innovative approach to data automation in prospective studies and registries. It outlines the challenges faced in traditional clinical research, particularly in post-marketing and safety studies, which are often labor-intensive and costly. The paper highlights the 21st Century Cures Act and the FDA's Real-World Evidence (RWE) Program, emphasizing the need for efficient real-world data for regulatory decision-making. OM1's strategy employs automation and artificial intelligence (AI) to streamline data collection and processing, ensuring regulatory compliance while enhancing cost-effectiveness and patient-centricity. The document details the methods of passive and active data collection, the role of AI in improving data completeness, and the importance of maintaining traceability and auditability in data management. Additionally, it discusses the cost efficiencies gained through automation and the diverse purposes of registries in the medical product lifecycle, including safety monitoring and effectiveness evaluation.