Technology is having an important positive impact on trials—from accelerating the collection of higher quality data to driving more real-time data monitoring and much more. Yet, despite technology’s abundant benefits, the introduction of disparate point systems into clinical trial settings has resulted in unforeseen burdens on sites.
Precision medicine brings about transformational advances in how we treat and prevent disease. While this development is overwhelmingly positive, especially for patients, it creates unintended challenges. As clinical sciences rapidly progress, the processes and technologies that are used to run trials have not kept pace. As a result, we endanger critical advancements in patient care.
Moments of inspiration, education, and connection experienced at the ACRP 2024 conference in Anaheim, Calif., in May have sparked creativity among many of its attendees, including this burst of playful poetry from the Chair of the Association Board of Trustees.
The potential of personalized medicine presents an opportunity for life sciences to leverage big data to target therapies to specific patients better. With artificial intelligence and machine learning technologies continuing to develop, research and development teams can finally bring this vision of personalized medicine to life, provided that the data they are using are clean, standardized, interpretable, and secure.
Is risk-based quality management working? Is it supporting the primary mission of improving quality in clinical trials? To answer these questions, we need to understand the limitations of traditional approaches to quality and explore the latest evidence which demonstrates how the components of centralized monitoring are helping to find the errors that matter.