An open-source SQL database schema for integrated clinical and translational data management in clinical trials.
Unlocking the power of personalised medicine in oncology hinges on the integration of clinical trial data with translational data (i.e. biospecimen-derived molecular information). This combined analysis allows researchers to tailor treatments to a patient's unique biological makeup. However, current...
| Publicado en: | Clinical Trials Vol. 22; no. 3; pp. 374 - 378 |
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| Autores principales: | , , , , |
| Formato: | pictorial tables/charts Journal Article |
| Publicado: |
Sage Publications, Ltd.
Jun2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=185307204&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 185307204 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 17407745 AB6 jtl: Clinical Trials issn: 17407745 maglogo: N pubinfo: dt: Jun2025 vid: 22 iid: 3 pid: 33180 pub: Sage Publications, Ltd. place: <Blank> artinfo: ui: 185307204 181878950 185307204 185307204 10.1177/17407745241304331 185307204 ppf: 374 ppct: 4 formats: tig: atl: An open-source SQL database schema for integrated clinical and translational data management in clinical trials. aug: au: Niazi, Umar Stuart, Charlotte Soares, Patricia Foure, Vincent Griffiths, Gareth affil: Cancer Research UK Southampton Clinical Trials Unit, MP131, Southampton General Hospital, University of Southampton, Southampton, UK sug: subj: Clinical Trials Data Management Methods Management Information Systems Research, Medical Resource Databases United Kingdom Communication Individualized Medicine Cost Effectiveness Analysis Security Measures Information Storage Methods Information Retrieval Methods Software ab: Unlocking the power of personalised medicine in oncology hinges on the integration of clinical trial data with translational data (i.e. biospecimen-derived molecular information). This combined analysis allows researchers to tailor treatments to a patient's unique biological makeup. However, current practices within UK Clinical Trials Units present challenges. While clinical data are held in standardised formats, translational data are complex, diverse, and requires specialised storage. This disparity in format creates significant hurdles for researchers aiming to curate, integrate and analyse these datasets effectively. This article proposes a novel solution: an open-source SQL database schema designed specifically for the needs of academic trial units. Inspired by Cancer Research UK's commitment to open data sharing and exemplified by the Southampton Clinical Trials Unit's CONFIRM trial (with over 150,000 clinical data points), this schema offers a cost-effective and practical 'middle ground' between raw data and expensive Secure Data Environments/Trusted Research Environments. By acting as a central hub for both clinical and translational data, the schema facilitates seamless data sharing and analysis. Researchers gain a holistic view of trials, enabling exploration of connections between clinical observations and the molecular underpinnings of treatment response. Detailed instructions for setting up the database are provided. The open-source nature and straightforward design ensure ease of implementation and affordability, while robust security measures safeguard sensitive data. We further showcase how researchers can leverage popular statistical software like R to directly query the database. This approach fosters collaboration within the academic discovery community, ultimately accelerating progress towards personalised cancer therapies. pubtype: Academic Journal doctype: pictorial tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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