Data Management 101 for drug developers: A peek behind the curtain

Author:

Oronsky Bryan1ORCID,Burbano Erica1,Stirn Meaghan1,Brechlin Joanne1,Abrouk Nacer2,Caroen Scott1,Coyle Angelique1,Williams Jeannie1,Cabrales Pedro3,Reid Tony R.1

Affiliation:

1. EpicentRx Torrey Pines California USA

2. Clinical Trial Innovations Mountain View California USA

3. UCSD Department of Engineering La Jolla California USA

Abstract

AbstractIn drug development a frequently used phrase is “data‐driven”. Just as high‐test gas fuels a car, so drug development “runs on” high‐quality data; hence, good data management practices, which involve case report form design, data entry, data capture, data validation, medical coding, database closure, and database locking, are critically important. This review covers the essentials of clinical data management (CDM) for the United States. It is intended to demystify CDM, which means nothing more esoteric than the collection, organization, maintenance, and analysis of data for clinical trials. The review is written with those who are new to drug development in mind and assumes only a passing familiarity with the terms and concepts that are introduced. However, its relevance may also extend to experienced professionals that feel the need to brush up on the basics. For added color and context, the review includes real‐world examples with RRx‐001, a new molecular entity in phase III and with fast‐track status in head and neck cancer, and AdAPT‐001, an oncolytic adenovirus armed with a transforming growth factor‐beta (TGF‐β) trap in a phase I/II clinical trial with which the authors, as employees of the biopharmaceutical company, EpicentRx, are closely involved. An alphabetized glossary of key terms and acronyms used throughout this review is also included for easy reference.

Publisher

Wiley

Subject

General Pharmacology, Toxicology and Pharmaceutics,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

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