Open ScienceOngoing
SHARE-CTD
SHARE-CTD – Sharing and re-using clinical trial data to maximise impact
Background / Rationale of the SHARE-CTD Consortium
Implementing clinical trial data sharing requires training of a new generation of biomedical researchers. SHARE-CTD, a Marie Skłodowska-Curie doctoral network funded by the European Union involving academic and non-academic partners, is a project on Open Science that will provide specific role models for an active participation in implementing Open Science in medical research.
In this way, principal investigators and eleven doctoral students in different European countries will work on research projects that explore many dimensions of clinical trial data sharing, with the goal of preparing students for future careers in clinical trial data sharing and reuse.
Objectives of the SHARE-CTD Consortium
SHARE-CTD aims to train a new generation of biomedical researchers with a deep understanding of processes, values, and merits of clinical trial data sharing. In order to gain a comprehensive understanding, they will be trained in different areas like data science, trial regulatory, meta-research, as well as ethical, legal and social issues.
SHARE-CTD’s research projects will look at best practices and will measure the impact of preparing data for sharing and of using shared data.
The QUEST Center is participating in this consortium with the project Automated screening tools for identifying data sharing, data-re-use and common reporting problems in clinical trials, led by Tracey Weissgerber.
Another PI of the consortium at the BIH is Fabian Prasser.
Background of the Project
In recent years, there has been a growing emphasis on data sharing and transparency in clinical research to improve the quality, reproducibility, and public accessibility of clinical trial findings. However, ensuring proper data sharing and reporting practices remains a significant challenge.
For example, many clinical trial datasets are not being deposited in public repositories or are not being shared in a way that enables effective reuse. Additionally, inconsistent reporting of key trial elements, as specified by guidelines like CONSORT, can limit the ability to fully assess and interpret trial results. This project aims to address these issues by developing automated screening tools to identify problems related to data sharing, data reuse, and CONSORT reporting in clinical trial publications and preprints. By creating these automated capabilities, the project seeks to facilitate greater transparency and improve the overall quality and utility of clinical trial reporting, with important implications for enhancing the integrity, accessibility, and impact of evidence generated through clinical research.
Objectives of the Project
- To extend existing automated manuscript screening tools to detect open data deposited in clinical trial repositories with controlled access (e.g. YODA) and to develop a new tool to detect re-use of clinical trial data deposited in a public repository or a repository with controlled access
- To develop new automated tools for detecting reporting of CONSORT elements
- To use these new tools to assess data sharing, data re-use and reporting quality of clinical trials, and encourage preprint authors to improve clinical trial reporting
- To use these tools for Meta-Research studies to assess the prevalence and impact of data sharing and data re-use in clinical trials
Expected Results / Implications / Perspectives of the Project
According to our goals, expected results are:
- To develop Automated screening tools that will detect data sharing, data re-use, and reporting of CONSORT items in clinical trial preprints and papers
- To integrate new tools into the ScreenIT pipeline, which will facilitate use of these tools for Meta-Research and for interventions to improve data sharing, data re-use and reporting
- To perform Meta-Research on the prevalence and impact of data sharing and data re-use in clinical trials (Protocols and SAPs)
