Dataset Information

Next-Generation Capabilities in Trusted Research Environments: Interview Study.

ABSTRACT:

Background

A Trusted Research Environment (TRE; also known as a Safe Haven) is an environment supported by trained staff and agreed processes (principles and standards), providing access to data for research while protecting patient confidentiality. Accessing sensitive data without compromising the privacy and security of the data is a complex process.

Objective

This paper presents the security measures, administrative procedures, and technical approaches adopted by TREs.

Methods

We contacted 73 TRE operators, 22 (30%) of whom, in the United Kingdom and internationally, agreed to be interviewed remotely under a nondisclosure agreement and to complete a questionnaire about their TRE.

Results

We observed many similar processes and standards that TREs follow to adhere to the Seven Safes principles. The security processes and TRE capabilities for supporting observational studies using classical statistical methods were mature, and the requirements were well understood. However, we identified limitations in the security measures and capabilities of TREs to support "next-generation" requirements such as wide ranges of data types, ability to develop artificial intelligence algorithms and software within the environment, handling of big data, and timely import and export of data.

Conclusions

We found a lack of software or other automation tools to support the community and limited knowledge of how to meet the next-generation requirements from the research community. Disclosure control for exporting artificial intelligence algorithms and software was found to be particularly challenging, and there is a clear need for additional controls to support this capability within TREs.

SUBMITTER: Kavianpour S

PROVIDER: S-EPMC9533202 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

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Publications

Next-Generation Capabilities in Trusted Research Environments: Interview Study.

Kavianpour Sanaz S Sutherland James J Mansouri-Benssassi Esma E Coull Natalie N Jefferson Emily E

Journal of medical Internet research 20220920 9

<h4>Background</h4>A Trusted Research Environment (TRE; also known as a Safe Haven) is an environment supported by trained staff and agreed processes (principles and standards), providing access to data for research while protecting patient confidentiality. Accessing sensitive data without compromising the privacy and security of the data is a complex process.<h4>Objective</h4>This paper presents the security measures, administrative procedures, and technical approaches adopted by TREs.<h4>Metho ...[more]

PMID: 36125859

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Project description:Background and objectiveLung neoplasia is the leading cause of cancer death worldwide, thus, early detection and accuracy in establishing a diagnosis is paramount. As a consequence of decades of basic and translational studies revealing the genetic basis of lung cancer, a paradigm shift has occurred toward a personalized approach to medicine whereby mutational analysis confers an opportunity for safer, and expedient treatment options. In this context, next-generation sequencing (NGS) has emerged as a vital technological advance, and has become increasingly established as a core method for rapidly and effectively identifying actionable mutations in lung cancer. For these reasons, an updated review of the literature across invasive and non-invasive diagnostic modalities in lung cancer is warranted to inform diagnostic approaches and prompt new investigations. The objective of the present review is to provide a focused update on applications of NGS in lung cancer diagnostics, with a special focus on tissue acquisition methodologies and mutational analysis.MethodsThe search strategy included a survey of the current literature from 2005 to 2024 in PubMed, Medline, Scopus, and Google Scholar. Eligible study types included original research, literature reviews (narrative and systematic), and observational studies. which encompassed findings pertinent to the lung cancer diagnostics, mutational analysis and lung cancer treatment overlapping with applications and use of NGS technologies.Key content and findingsThere are extensive and diverse advantages to the use of NGS in lung cancer diagnostics, especially when compared to traditional sequencing techniques including, speed, effectiveness, easy adoption in the context of analysis of samples prepared for lung cancer diagnosis. Advances in cell-free DNA reinforce the firm role of NGS in novel approaches.ConclusionsNGS implementation is a crucial and beneficial technological leap in lung cancer diagnosis, especially given the environment of novel and established targeted and immune based therapies which require mutational testing. Its numerous benefits such as expedient results and reduced sample requirements will continue to ability optimize lung cancer outcomes by virtue of improved patient safety, reduction of unnecessary procedures, and provision of accurate results.

Dataset Information

Next-Generation Capabilities in Trusted Research Environments: Interview Study.

Background

Objective

Methods

Results

Conclusions

Publications

Next-Generation Capabilities in Trusted Research Environments: Interview Study.

Similar Datasets

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