Clinical Trials in the Era of Real-World Evidence - Tapa blanda

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Jie Chen is Chairman and Chief Scientific Officer at Taimei Intelligence Biopharma R&D, Shanghai, and a Visiting Member of the Center for Innovative Study Design at Stanford University. His extensive experience spans biopharmaceutical research, development, real-world evidence studies, and regulatory submissions.

Naitee Ting is Vice President at Veramed Inc. and serves as Adjunct Professor of Biostatistics at the University of Connecticut, Columbia University, and Colorado State University. He brings decades of experience in clinical trial methodology and pharmaceutical development.

Feinan Lu is Director and Head of Biometrics at Impact Therapeutics, Shanghai. She specializes in the statistical methodology underlying clinical trials and real-world evidence studies supporting regulatory decision-making in drug development.

De la contraportada

Integrate RCTs and real-world evidence for stronger regulatory submissions

Since the passage of the 21st Century Cures Act, the landscape of clinical research has transformed dramatically. Today, the integration of real-world data (RWD) and real-world evidence (RWE) with traditional randomized controlled trials (RCTs) is not just innovative - it is essential for modern drug development and regulatory decision-making.

This comprehensive volume bridges the methodologies of conventional RCTs and emerging RWE studies, offering systematic approaches for leveraging diverse data sources throughout the clinical development lifecycle. Grounded in regulatory statistics yet forward-looking in scope, the book explores Stein's continuum of study designs - from traditional RCTs to pragmatic trials and observational studies - and demonstrates how RWD can enhance trial feasibility, inform outcome selection, provide external controls for single-arm trials, and strengthen post-approval safety monitoring.

Readers will find detailed explorations of:

• A history of clinical trials, evidence-based medicine, and the regulatory frameworks governing drug approval
• Treatment switching and estimands in RWE studies
• Advanced analytical considerations including precision medicine, vaccine effectiveness, safety evaluation, and sensitivity analysis
• Practical roadmaps for designing robust RWE studies
• Artificial intelligence and machine learning in clinical research

Designed as both a reference and a graduate-level textbook, this book serves clinical researchers such as clinicians and biostatisticians, regulatory professionals, public health scientists, and industry practitioners seeking to harness the power of RWD and RWE to generate credible, actionable evidence for modern medicine.