Celebrating the 2nd Edition of a Landmark Book in Adaptive Designs

We are delighted to share that Gernot Wassmer, together with Werner Brannath, has published the second edition of their monograph:

Group Sequential and Confirmatory Adaptive Designs in Clinical Trials
(Springer Series in Pharmaceutical Statistics)

At RPACT we are especially happy that this second edition integrates extensive R code examples using our package rpact.

Thorough Adaptive Designs Coverage

Adaptive designs are more relevant than ever. Since the first edition of the book, numerous high-impact publications have highlighted their practical importance across many contexts — from general application guidance to studies impacted by COVID-19 and modern platform trial settings.

Adaptive designs are a generalization of classical group sequential designs. Hence, the book continues to begin with a rigorous foundation in group sequential methods before expanding into adaptive extensions. The book offers:

A comprehensive methodological reference
A bridge between statistical theory and practical application
A unified framework spanning group sequential, adaptive, and optimal designs
Clear guidance for real-world trial planning and analysis

For statisticians, clinical trial designers, and researchers, the integration of rpact code examples is a major step forward. It transforms the book from a theoretical resource into a hands-on toolkit.

What’s New in the Second Edition?

The second edition is both more practical and more software-oriented. Among the many updates:

⭐ Extensive R Code Examples Using `rpact`

This is the biggest highlight for us and for many practitioners.

The book now contains detailed, reproducible R code using the rpact package (Wassmer & Pahlke, 2025), allowing readers to:

Recreate nearly all calculations and tables from the book
Explore adaptive design methodology interactively
Understand concepts such as futility bounds, β-spending, delayed response designs, optimal adaptive designs, and more — directly in R using rpact

In addition, the authors kept the required R knowledge minimal. Even better:

The online Shiny app RPACT Cloud is available, making many calculations accessible without writing code.

This makes the monograph uniquely suitable for statisticians in both academic and industry settings.

Further Key Enhancements

Part I — Group Sequential Designs and Extensions

Comprehensive overview of β-spending function approaches
Introduction to delayed response designs
Improved calculations for survival designs
New section: sample size calculations for count data

Part II — Optimal Adaptive Designs

A brand-new chapter dedicated to optimal designs, including: - The foundational framework by Brannath & Bauer (2004) - Modern extensions from Pilz et al. (2019), Kunzmann et al. (2022), Brannath et al. (2024), and others

Part III — Additional Material and Unified Notation

More consistent notation across chapters
Supplemental derivations
Software code used for calculations now included in the text

Acknowledgments

The authors express gratitude to the many colleagues who contributed through reviews, discussions, software development, and feedback. Special thanks also go to the publisher, the editorial team, and the many contributors who helped refine this edition.

Explore the Book

If you’re interested in adaptive designs, confirmatory clinical trials, or applying rpact in practice, we highly recommend exploring the new edition:

📘 Book Link:
doi.org/10.1007/978-3-031-89669-9

Congratulations again to Gernot Wassmer and Werner Brannath on this impressive achievement — and thank you for showcasing rpact throughout this edition.