An open-source SQL database schema for integrated clinical and translational data management in clinical trials.

IF 2.2 3区 医学 Q3 MEDICINE, RESEARCH & EXPERIMENTAL
Umar Niazi, Charlotte Stuart, Patricia Soares, Vincent Foure, Gareth Griffiths
{"title":"An open-source SQL database schema for integrated clinical and translational data management in clinical trials.","authors":"Umar Niazi, Charlotte Stuart, Patricia Soares, Vincent Foure, Gareth Griffiths","doi":"10.1177/17407745241304331","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"17407745241304331"},"PeriodicalIF":2.2000,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical Trials","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/17407745241304331","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MEDICINE, RESEARCH & EXPERIMENTAL","Score":null,"Total":0}
引用次数: 0

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.

求助全文
约1分钟内获得全文 求助全文
来源期刊
Clinical Trials
Clinical Trials 医学-医学:研究与实验
CiteScore
4.10
自引率
3.70%
发文量
82
审稿时长
6-12 weeks
期刊介绍: Clinical Trials is dedicated to advancing knowledge on the design and conduct of clinical trials related research methodologies. Covering the design, conduct, analysis, synthesis and evaluation of key methodologies, the journal remains on the cusp of the latest topics, including ethics, regulation and policy impact.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信