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Anonymisation of Imaging Data - Started Q1 2024
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Clinical Visual Analytics for Review and Submission (CVARS) – Started Q1 2022 | |
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The scope of this project remains flexible, but initially we plan a literature review. The types of image files will be reviewed (X-rays, (f)MRIs, CT scans, etc.), their formats (DICOM, NIfTI, etc.), their positions (limbs, heads, organs, etc.) and all associated metadata. There will also be a discussion on data handling, storage and transfer. Any existing guidance and repositories will be reviewed. We will then focus on use cases that will have the most impact based on interest and complexity. Any use cases being presented will be in the context of a request alongside clinical data, in keeping with the main drivers behind the Data Transparency Working Group. There will be a strong focus on processing metadata associated with images as that is where the strengths of the Working Group lie (processing and anonymising data) and where most of the risk lies in the sharing of images.
Development of an open-source tool and package to enable generation of identified interactive plots for clinical review and direct inclusion in submissions to regulatory agencies. The initial scope is to develop a package to generate interactive forest and volcano plots for adverse events and FDA Medical Queries (FMQs) analysis outputs for inclusion in submissions to the FDA. This work is a collaboration among the American Statistical Association (ASA), PHUSE and the FDA. | Current Status:
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Communication of Version Metadata for Open-Source Languages – Started Q | |
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Project Scope: This project aims to develop a new template or enhance an existing one such as the Study Data Standardisation Plan (SDSP) or Analysis Data Reviewer’s Guide (ADRG), to ensure that metadata pertaining to the versions of statistical packages and procedures is consistently documented in alignment with health authority expectations. This standardised template will streamline the submission of clinical study metadata to health authorities as part of the regulatory review process. | Current Status:
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Literature review
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Comparing Analysis Method Implementations in Software (CAMIS) – Started Q | |
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The EU Clinical Trial Regulation (CTR) has sweeping new requirements for the publication of clinical trial documents of trials conducted in the European Union. Documents will be subject to publication earlier in clinical development than before, and documents like the Investigator’s Brochure will be routinely published for the first time.
The EU CTR has important implications for the planning of trials in the EU and for how sponsors prepare clinical trial documents. Stakeholders include any sponsor conducting an EU trial, including pharmaceutical and biotechnology companies and academic institutions. The initial deliverable for this project may build on a poster previously prepared by this Working Group outlining avenues of data disclosure.
Types of document to be published under the EU CTR, their possible timelines for publication, the deferral mechanism for protecting confidential commercial information (CCI), which documents can be redacted for CCI and which cannot, and protection of personal protected data.
Comparing Analysis Method Implementations in Software (CAMIS) has evolved from the Clinical Statistical Reporting in a Multilingual World project. Several discrepancies have been discovered in statistical analysis results between different programming languages, even in fully qualified statistical computing environments. Subtle differences exist between the fundamental approaches implemented by each language, yielding differences in results which are each correct in their own right. The fact that these differences exist causes unease on the behalf of sponsor companies when submitting to a regulatory agency, as it is uncertain if the agency will view these differences as problematic. Understanding the agency’s expectations will contribute significantly to enabling the broader adoption of multiple programming languages in the production of data submission packages for regulatory review The CAMIS project seeks to clearly define this problem and provide a framework for assessing the fundamental differences for a particular statistical analysis across languages. In this context, the risk of interpreting numerical differences in analysis results due solely to differences in programming language can be mitigated, instilling confidence in both the sponsor company and the agency during the review period. This will be accomplished by:
The CAMIS repository to document known differences is now live and open for community contributions. | Current Status:
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Literature review
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Experience in processing metadata associated with imaging
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Current Status:
1.Publish Video 3: ‘What is Clinical Data?’
2.Publish PHUSE-MRCT Infographics Collaboration
3.Finalise the script for the last three videos in our series:
-Video 4: ‘Journey of a Data Point’
-Video 5: ‘What is Data Sharing?’
-Video 6: ‘What is Data Privacy?’Teal Enhancements for Cross-Industry Adoption – Started Q | |
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To create engaging content on data privacy and data sharing that can be understood and used by the general population (any member of the public regardless of their sector or profession) covering topics such as what is being done to share clinical trial data and information, where data goes and how it is used, what data privacy is, why it is needed, why it is important and the differences between mandatory vs. voluntary data sharing. The project is to follow a similar approach to the Data Transparency (DT) Terminology Harmonisation project, this time aiming towards a more general audience to address commonly asked questions surrounding data privacy and data sharing. The Terminology Harmonisation project creates an excellent set of deliverables better suited for those who work with data sharing on a more technical level.
Research: Conduct a detailed analysis of the current teal framework and identify areas where flexibility can be introduced. A Proof-of-Concept will be provided after research. Development: Create new functionalities that allow for the re-formatting, post-processing, and decoration of outputs generated by existing teal modules. Testing: Develop test cases to ensure the new functionalities are compatible with existing modules and meet the customisation needs of different companies. Documentation: Update the framework's documentation to include instructions on how to use the new features. Training & Support: Provide training and ongoing support to users within the pharma industry to facilitate the adoption of the enhanced teal framework. | Current Status:
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