Clinical Research is a fascinating industry, because 99.9% of human beings interact with it throughout their lives. However, very few understand the effort to bring a new medical product to patients in need, and an even smaller number have thought about, or remotely understand, the pivotal role Clinical Data Management (CDM) professionals play in this endeavor. Ranging from sharing hands-on experiences to providing concrete examples of how to propel one’s CDM career, Mastering Clinical Data Management: The Background, Experience, and Soft Skills Needed to Succeed in CDM is a glimpse of the author’s three-decades-long experience in the field.
Decentralized Clinical Trials (DCTs), Risk-Based Quality Management (RBQM), examining the trustworthiness of the data used in clinical research, or illustrating the use of Artificial Intelligence (AI) in CDM are just a few examples of topics this book not only covers, but also explains for all competency levels through real-life examples. Despite Clinical Research in general, and the profession of CDM in particular, being a heavily regulated and tech-driven environment, this book uses every opportunity to emphasize the importance of the human in the loop. Therefore, in addition to gaining more insights into the fascinating world of CDM, this book provides the perfect “How to” of advancing one’s career and learning the art of CDM.
The goal is to provide valuable insights for all levels of CDM professionals and those individuals that might consider a career in CDM.
Key Features
- Provides insight into clinical data and its importance as never seen before
- Draws on 35 years of hands-on CDM experience
- Provides guidance and many examples of crucial soft skills needed to succeed in CDM
- Provides arguments for all CDMs to excel in their current work environment
- Reflects on the current regulatory framework and how it can benefit CDM
Table of Contents:
Introduction and Acknowledgements Chapter 1: The Role of CDM in Clinical Research and Why It Matters Chapter 2: Dissecting Clinical Data to Its “Atomic” Structure. The Case for AI and ML in CDM Chapter 3: Demystifying Risk-Based Quality Management (RBQM) and Why CDM Should Lead It Chapter 4: Technology Overload – How to Avoid Common Pitfalls Chapter 5: Clinical Data Management Versus Clinical Data Science Chapter 6: Demystifying DCTs (Decentralized Clinical Trials) Chapter 7: Stepping Out of the Shadow Chapter 8: Becoming a Clinical Data Science Advocate Chapter 9: From Programmer to Executive – A Personal Story
About the Author :
Michael Goedde is Certified Clinical Data Manager with 35 years of experience in the pharmaceutical and biotechnology industry. His expertise ranges from hands-on clinical data management (CDM) activities to executive roles with responsibility for large international teams and strategic positioning for the companies he engages with. Michael has dedicated his professional career to the advancement of CDM as a recognized and respected profession in our industry, as well as providing mentoring for the next generation of CDM enthusiasts.
Review :
"I have known Michael for over two decades, and throughout that time I have admired his vision, expertise, and dedication to advancing our profession. When he shared his idea for a book on best practices in clinical data management, I immediately saw the value it could bring to the industry and was honored to be invited to contribute as a reviewer. As a long-standing leader in the Society for Clinical Data Management (SCDM), Michael has a unique perspective on the evolving needs of our field. This book will serve as a much-needed, practical guide for ensuring high-quality, on-time clinical data deliverables—an essential part of bringing new treatments to patients around the world. I wish him great success in bringing this important work to publication."
Jonathan Andrus, Co-CEO, CRIO & Treasurer, SCDM
"I had the pleasure of reporting to Michael when we both worked at PRA/ICON. We built a strong relationship during that tenure and continue to stay in touch to exchange new perspectives in our industry. I was very excited when Michael mentioned to me earlier about his idea to put together a book on best practices in clinical data management. The industry is lacking a concise guide at this stage, and this reference book will fill a much-needed gap in clinical data management. I felt honored when Michael invited me to write a chapter for the book.
As one of the leaders in the Society for Clinical Data Management (SCDM), the clinical data management industry's recognized forum for nurturing best practices, Michael has a unique lens into the needs of the industry. I am confident that the book he is striving to get published will assist personnel in the industry in practicing end-to-end data management steps that will ensure on-time, high-quality deliverables. Clinical Data Management deliverables will be a key factor in bringing much0needed cures to patients worldwide."
Zia Haque, Head of Data Management at Otsuka-US Pharmaceuticals
"As Chief Data strategist and solutions officer I see too many companies not fully understanding the importance and value in their data. This starts with having a better understanding of best practices in data management, and where clinical data science is taking us as an industry. With publications like this book, written by experts such as Michael, which brings the data delivery and quality aspects to life through easy reading (including practical examples), the industry is one step closer to getting true value out of their data."
Tanya du Plessis, Bioforum
