Harnessing the Power of AI/ML and Risk-informed Strategies to Streamline Clinical Data Management
In today’s fast-paced world, driven by demands for speed and efficiency, the field of clinical development has undergone a remarkable transformation. The way trials are being conducted has changed significantly with decentralized clinical trials (DCT) becoming mainstream and the collection of clinical data from wearables and other remote-monitoring devices becoming common practice. While these advances have made clinical studies more accessible and less burdensome to patients, the volume and variety of clinical data being captured per trial has grown exponentially — and at a faster pace than ever before. Managing this deluge of data has become particularly challenging. In response, roles across data management and clinical teams are evolving by adopting new approaches and technologies.
In this ebook, we explore how artificial intelligence (AI), machine learning (ML), and risk-based methodologies can be leveraged by data management teams to meet the demands of modern clinical trials while ensuring data quality, increasing efficiency, and reducing cycle times.
Download this eBook to gain insights on:
- How increasing trial complexity and data volume are driving the need to harness innovative technologies and approaches across data management and clinical teams
- How leveraging risk-informed strategies and AI/ML capabilities are enabling organizations to increase efficiency and scale for the future-state
- The opportunities for aligning technology and services to streamline processes and increase productivity