12.04.25 -- Identify Patient-Centric Risks In The TMF With AI And Automation

Review the current and future applications of RWD/E in drug discovery, clinical research, regulatory review and approval, and its role in promoting health equity and patient and provider access.

In part one of this series, the author dives into how electronic consent platforms are simplifying and improving the trial experience for patients and sites.

Explore how to design ethical, effective, and patient-centric AI-powered recruitment pipelines that truly connect the right patients to the right trials.

Learn about this accessible way to understand what Health Economics and Outcomes Research (HEOR) is, how it’s used, and its impact on people and healthcare systems.

Discover how streamlined workflows and enhanced collaboration between data managers and medical reviewers can boost clinical trial efficiency, improve data quality, and ensure patient safety.

Uncover how an independent confirmation of compliance opened up new opportunities and is instilling confidence in customers who are integrating the eSource system into their software validation strategy.

Centralized eSource systems enable complex clinical trials to align with key regulatory frameworks, including ICH E6(R3), ICH E8(R1), and 21 CFR 312, to meet the highest standards of GCP.

Digitized protocols, enhanced by artificial intelligence (AI), are transforming clinical trial operations by accelerating document generation, system integration, and trial optimization.

Biases, often hidden, can distort vendor selection decisions. Recognizing and addressing them across individuals and teams leads to more objective, aligned, and successful clinical trial outcomes.

To overcome the unprecedented challenges of large-scale global clinical trials, adopting data capture solutions is essential for ensuring the success of critical research initiatives.