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.