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Active since 2014, PHUSE’s Data Transparency Working Group provides subject matter expertise for the review of draft deliverables and guidance documents from regulatory bodies (such as the EMA and Health Canada), as well as other industry organisations (such as TransCelerate), and academia. Since their inception in 2020, the free-to-attend Data Transparency Events have gone from strength-to-strength. These virtual events have created an unrestrictive space where questions can be asked and challenges addressed. Individuals passionate about the area can come together to share vital knowledge, develop new ideas and spark innovation through presentations, panel discussions and Q&A sessions, alongside experts in the data sharing field. The PHUSE Data Transparency Winter Event will take place from 6–8 February 2024. Data Transparency Events offer you the chance to gain knowledge and experience from a wide data transparency community, allowing you to come together with expects from a variety of companies and backgrounds. During this virtual event, presentations will be delivered across the three days in bitesize chunks from 15:00-17:30 (GMT). There will also be a panel discussion and Q&A session focused on the day's themes.
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Presentation |
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De-identification Beyond Borders: Global Applicability of HIPAA Safe Harbor
The Helping to End Addiction Long-term® Initiative, or NIH HEAL Initiative®, is an NIH-wide effort to speed scientific solutions to stem the national opioid public health crisis, funding over 1,000 projects nationwide. The HEAL Data Ecosystem is an important part of this effort, consisting of partners working together to: 1) aid investigators in making their data findable, accessible, interoperable, and reusable (FAIR); 2) develop the HEAL Data Platform so researchers can discover and compute over HEAL datasets; and 3) translate HEAL research discoveries back to communities and other stakeholders. By empowering researchers to make their HEAL-generated data FAIR, the HEAL Data Ecosystem promotes data sharing. In this presentation, representatives from the HEAL Data Stewardship group will discuss the data sharing practices of the HEAL initiative, the model used for the HEAL Data Ecosystem and how it helps to enable data transparency, and the tools that are available to make HEAL data FAIR.
Speaker(s) | |
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A Cross-sectional Study to Evaluate the Real-World Impact of Clinical Trial Transparency Initiatives | Shalini Dwivedi, Krystelis |
Improving clinical trial transparency enhances the credibility of research, allows for more informed decision-making by healthcare professionals (HCPs) and patients, and contributes to the advancement of scientific knowledge. To drive this, regulatory agencies such as the FDA, EMA, and Health Canada, have implemented policies and regulations covering the registration of clinical trials through to publishing of clinical trial documents and data sharing. It is important to evaluate the real-world impact of these initiatives with key stakeholders. Are HCPs and patients aware of them and how might they be using the information? Do the regulations enable researchers to conduct an independent analysis of clinical trial data?
To assess this, we are conducting a cross-sectional study using survey questionnaires and interviews. The main objectives are to evaluate the:
• Current level of awareness and understanding of clinical trial transparency initiatives (Focus group: HCPs, patients, clinical trial researchers)
• Challenges with data sharing requests (Focus group: Clinical trial sponsors)
• Responsiveness of clinical trial sponsors on data sharing requests (Focus group: Clinical trial researchers) Data collection and analysis is ongoing.
The results of the study will be presented descriptively.
This presentation explores the challenges and insights gained from our experience with anonymising complex health data. The primary focus is on the need for robust technical and organisational measures, such as a secure processing environment, to ensure controlled data access. Implementing these control measures allows us to maximise data utility while minimising risk. We discuss specific technical challenges encountered in the data anonymisation process and assessing the risk of re-identification, particularly in handling longitudinal and various genetic data types. Notably, the lack of clear guidance on identifiability aspects of healthcare data is highlighted. Our findings underscore the critical role of establishing clear internal governance, with well-defined roles and responsibilities, to facilitate a seamless data anonymisation process. Additionally, we emphasise the importance of providing guidance and training for anyone working with anonymised data to dispel common misconceptions surrounding anonymisation.
Balancing Act: The Dynamics of Legislation, AI, and Global Health Data Sharing | Luk Arbuckle, Privacy Analytics |
Challenges and Solutions to Anonymisation of Imaging Data (DICOM) | Diwakar Angra, GENINVO |
DICOM (Digital Imaging and Communications in Medicine) is a standard for the communication and management of medical imaging information and related data. It is widely used in healthcare for exchanging information of X-rays, CT scans, etc. DICOM plays a crucial role in the field of medical imaging, enabling the standardisation of digital medical images and associated information. Anonymising DICOM images is a critical step to protect patient privacy and share DICOM files for research and development purposes. However, there are several challenges such as: editing information of DICOM files, transfer of large data, anonymisation of thousands of files, anonymisation in sync with study dataset and documents etc. To overcome the above challenges there are some solutions available such as: open-source libraries to read and view DICOM files, automation of DICOM editing, Encryption, Raise Awareness, etc. This presentations will be discussing on these challenges and possible solutions to these challenges.
De-identification Beyond Borders: Global Applicability of HIPAA Safe Harbor | Obaraboye Olude, Privacy Analytics |
From Automated to Accountable: Building Responsible AI for Trial Transparency | Woo Song, Xogene |
Good Transparency Practices: A Working Group Update | Abby McDonell, Privacy Analytics and Lauren Hepburn, Rare Disease Sponsor |
Improving Data Findability Through Better Clinical Metadata | Lukasz Kniola, Biogen |
Lessons Learned in Anonymising Complex Health Data – Maximising Data Utility While Minimising Risk | Nuria Mackes, xValue GmbH and Asad Preuss-Dodhy, Roche Diagnostics |
PSURs Public Release – Individual Patient Safety Data Disclosure Across Multiple Transparency Initiatives | Agnieszka Glowinska and Magdalena Majewska, AstraZeneca |
The presentation will provide a summary on the Good Transparency Practice (GTP) working group deliverable. The group created a GTP guidance document that defines a set of best practices for data transparency. By outlining the distinct roles of the Data Controller, Data Anonymiser, and Data Recipient, the project aims to provide a means to achieve accountability and traceability through the anonymisation process, while providing assurance that privacy requirements are upheld.
The HEAL Data Ecosystem: Enabling Data Sharing within the NIH HEAL Initiative® | Zixin Nie, RTI International |
DT Winter Event Sponsors |
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Virtual Event Sponsors |
Sponsorship |
Hosting the Data Transparency Events digitally means that no matter where you are in the world you can participate. It provides the industry with a broader opportunity to share knowledge on a global scale, connecting through the virtual event platform. The sponsor options offer a range of benefits with ample company exposure. See the prospectusfor more detail. |
Data Transparency Working Group Leads |
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