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Data Management 101 for drug developers: A peek behind the curtain
Bryan Oronsky1, Erica Burbano1, Meaghan Stirn1
1EpicentRx, Torrey Pines, California, USA.
Clinical and Translational Science
|June 29, 2023
Summary
High-quality clinical data management (CDM) is essential for successful drug development. This review demystifies CDM processes, offering insights for new and experienced professionals in the field.
Area of Science:
- Drug Development
- Clinical Trials
- Data Management
Background:
- Drug development relies heavily on high-quality data, making robust data management practices critical.
- Clinical Data Management (CDM) encompasses the collection, organization, maintenance, and analysis of clinical trial data.
- Understanding CDM is essential for professionals in the pharmaceutical and biotechnology industries.
Approach:
- This review provides a foundational overview of Clinical Data Management (CDM) essentials in the United States.
- It aims to demystify the CDM process for individuals new to drug development.
- Real-world examples from ongoing clinical trials (RRx-001 and AdAPT-001) are included for context.
Key Points:
- Essential CDM practices include case report form design, data entry, capture, validation, medical coding, and database locking.
- Effective CDM ensures data integrity and reliability for regulatory submissions and decision-making.
- The review includes a glossary of key terms and acronyms for clarity.
Conclusions:
- Mastering Clinical Data Management (CDM) is crucial for the success of drug development.
- This review serves as a guide to understanding the core principles and practices of CDM.
- It is relevant for both newcomers and experienced professionals seeking to refresh their knowledge.
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