Aggregating and analysing clinical trials data from multiple public registers using R package ctrdata

Abstract The ctrdata package has been created to boost the use of data available in public registers of clinical trials. It enables user-friendly, reproducible workflows to identify trials of interest, download protocol- and results-related data, and conduct sophisticated analyses, across multiple registers and trials. ctrdata works in the widely used R environment, and its databases can be used with other tools. The package is open source with a permissive licence, to facilitate collaboration. This report provides an overview of ctrdata, including its implementation, cases of interest to researchers in public health, medicines, and regulatory science, as well as potential limitations and further developments. At this time, ctrdata works with the European Union (EU) Clinical Trials Information System (CTIS), the EU Clinical Trials Register (EUCTR), the US Clinicaltrials.Gov (CTGOV), and the ISRCTN—the UK’s Clinical Study Registry. The registers are complementary in scope and scientific value, yet differences in data models, variable definitions, search parametrisations, and retrieval options hamper efficient scientific workflows, calling for a scientific-technical, programmatic solution and driving the development of ctrdata. By employing ctrdata to comprehensively use and easily leverage trial register data, researchers can effectively address a variety of questions, gain useful insights into evolving policies and practices of drug development, and inform further clinical research. Patients and their organisations, developers, policymakers, and other interested parties can build on ctrdata to create solutions for their use cases.

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Publication Details

Journal
Research Synthesis Methods
Published
2025-12-04
DOI
https://doi.org/10.1017/rsm.2025.10061
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
0.00

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article

Aggregating and analysing clinical trials data from multiple public registers using R package ctrdata

Ralf Herold
Research Synthesis Methods
Scientific Computing and Data Management
article

Aggregating and analysing clinical trials data from multiple public registers using R package ctrdata

Ralf Herold
article en

Abstract

Abstract The ctrdata package has been created to boost the use of data available in public registers of clinical trials. It enables user-friendly, reproducible workflows to identify trials of interest, download protocol- and results-related data, and conduct sophisticated analyses, across multiple registers and trials. ctrdata works in the widely used R environment, and its databases can be used with other tools. The package is open source with a permissive licence, to facilitate collaboration. This report provides an overview of ctrdata, including its implementation, cases of interest to researchers in public health, medicines, and regulatory science, as well as potential limitations and further developments. At this time, ctrdata works with the European Union (EU) Clinical Trials Information System (CTIS), the EU Clinical Trials Register (EUCTR), the US Clinicaltrials.Gov (CTGOV), and the ISRCTN—the UK’s Clinical Study Registry. The registers are complementary in scope and scientific value, yet differences in data models, variable definitions, search parametrisations, and retrieval options hamper efficient scientific workflows, calling for a scientific-technical, programmatic solution and driving the development of ctrdata. By employing ctrdata to comprehensively use and easily leverage trial register data, researchers can effectively address a variety of questions, gain useful insights into evolving policies and practices of drug development, and inform further clinical research. Patients and their organisations, developers, policymakers, and other interested parties can build on ctrdata to create solutions for their use cases.

Research Synthesis Methods
European Medicines Agency (NL)
Universität Wien
Openalex Percentile: Top 65%
Scientific Computing and Data Management
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