10.29.26 -- AI, Digital Twins, And RWE Put Trial Evidence Under Scrutiny

A former Bayer medical affairs lead examines why budget holders, not data experts, often control critical data-quality decisions and what that means for trials.

Disconnected systems force site staff to bridge workflow gaps. Explore why reducing silos, rather than adding technology, matters for trial execution.

Prepare for 2027 by auditing real-world data sources and closing traceability gaps. Explore how guidance, AI, and data are reshaping evidence strategy.

Explore how AI automates tasks across protocol creation, validation, and analysis to speed trial and registry builds while preserving team control.

Five case studies show how sponsors and CROs shortened startup and maintained strong eCOA adherence in weight-loss and diabetes trials.

Learn how structured oversight, transparency, and collaboration support compliance, address bias, and build trust in clinical research AI.

Jonathan Andrus argues for protocol-driven eSource to reduce transcription, align site workflows, and improve data quality and real-time visibility.