An open-source SQL database schema for integrated clinical and translational data management in clinical trials
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 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.
Open-source SQL database schema for clinical trials, clinical trial data integration with translational data, personalised medicine in clinical research
Niazi, Umar
9ec54da2-033e-4172-9748-5be30b7cd53f
Stuart, Charlotte
734d13d9-fd1f-4c55-ba90-bf1abf303bb4
Griffiths, Gareth
7fd300c0-d279-4ff6-842d-aa1f2b9b864d
Niazi, Umar
9ec54da2-033e-4172-9748-5be30b7cd53f
Stuart, Charlotte
734d13d9-fd1f-4c55-ba90-bf1abf303bb4
Griffiths, Gareth
7fd300c0-d279-4ff6-842d-aa1f2b9b864d
Niazi, Umar, Stuart, Charlotte and Griffiths, Gareth
(2024)
An open-source SQL database schema for integrated clinical and translational data management in clinical trials.
Clinical Trials.
(doi:10.1177/17407745241304331).
Abstract
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.
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e-pub ahead of print date: 25 December 2024
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© The Author(s) 2024.
Keywords:
Open-source SQL database schema for clinical trials, clinical trial data integration with translational data, personalised medicine in clinical research
Identifiers
Local EPrints ID: 497269
URI: http://eprints.soton.ac.uk/id/eprint/497269
ISSN: 1740-7745
PURE UUID: 02b322e2-a6f6-428d-967c-2c726236c03d
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Date deposited: 16 Jan 2025 18:04
Last modified: 22 Aug 2025 02:42
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Author:
Umar Niazi
Author:
Charlotte Stuart
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