ACT Brief: Risk-Based Monitoring in Global Trials, Patient-Centered AI Design, and Generative AI in Healthcare

This is the Applied Clinical Trials Brief—your fast track to the latest insights shaping clinical operations and drug development.

• In a new contributed article, risk-based monitoring requires integrated data systems across EDC, IRT, eCOA, labs, and safety platforms, validated statistical models, and robust governance to work effectively globally. Sponsors face significant challenges including fragmented data architectures, inconsistent standards adoption, site variability, and vendor complexity, requiring structured risk assessment frameworks and continuous training to succeed.
• In part three of his video interview, Krishna Cheriath, vice president and head of clinical research digital data and AI at Thermo Fisher Scientific, argued that effective patient-centered AI must go beyond direct-to-patient tools to address social determinants of health. Reducing administrative burden on sites allows investigators to focus on patients rather than systems, fundamentally changing how technology serves clinical research.
• In a new contributed article from Pharmaceutical Executive, domain-specific generative AI models grounded in validated clinical evidence are emerging as essential for scaling AI safely across healthcare. Systems like Google's Med-Gemini demonstrate superior performance when trained on real-world medical datasets and constrained to evidence-based sources, outperforming both general-purpose models and human physicians on key clinical metrics.

That's all for today's ACT Brief. Join us tomorrow for more updates shaping clinical operations and drug development. Thanks for listening.