ReviewClinical and translational science2023
Data Management 101 for drug developers: A peek behind the curtain.
Review in Clinical and translational science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed, 3 citations in OpenAlex.
- Data Management 101 for drug developers: A peek behind the curtain.Clinical and translational science · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.