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Data Transparency | ||
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The Data Transparency Autumn Event will take place from 16–18 September 2025. 10:00-12:30 (EDT) / 15:00-17:30 (BST) / 16:00-18.30 (CEST)
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New Working Group Lead for Data Transparency
The Data Transparency Working Group welcomes a new lead Abby McDonell!
Abby previously co-led the PHUSE Good Transparency Practice Working Group project, where she helped define best practices for data transparency and created guidance to ensure anonymised data complies with legal requirements while preserving data utility.
Abby is a Senior Program Manager for the Clinical Trial Transparency team at Privacy Analytics. Abby leads teams that leverage advanced AI-enabled technology to deliver anonymisation services for top 10 pharma customers.Real World Evidence | ||
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Community Forum: Getting the RWD We Need – From Both Sponsor and Regulator Perspectives 7 October at 10:00-11:00 (EDT) / 15:00-16:00 (BST) / 16:00-17:00 (CEST)
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Data Transparency |
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The Good Transparency Practicesproject has published a new Guideline. Good Transparency Practice (GTP) is a guideline developed by the PHUSE Data Transparency Working Group to create a set of best practices to govern the anonymisation of clinical trial data, for external sharing or disclosure. Although there are transparency initiatives across the globe, with differing guidelines, the common goal is to uphold patient privacy and data utility to the highest standards. |
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Risk Based Quality Management: SDR/SDV in China Survey | ||
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The Risk Based Quality Management Working Group have produced a survey on the topic of SDR/SDV in China. The goal of this survey is to gain insight into how companies across the industry are implementing SDR and SDV in sites in China. The output of the survey will be used to develop a reference document for informing future study approaches and/or adjusting current approaches to better align with global standards. The closing date for completing the survey: 20 September.
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Call For Volunteers |
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The Applying Advanced Data Privacy Methods to Real World Data (RWD), a new project within theReal World Evidence Working Group, is now calling for volunteers. The goal of this project is to develop a comprehensive, cross-disciplinary resource to support individuals and organisations in applying advanced privacy-preserving techniques to real-world data (RWD). Given the evolving landscape of privacy regulations and the increasing complexity of data sources – including integrating machine learning (ML), artificial intelligence (AI) and large language models (LLMs) into healthcare pipelines – this project will serve as a critical foundation for advancing privacy-preserving data integration frameworks for RWD. If you would like to volunteer or learn more about this project, email workinggroups@phuse.global. Closing date: 7 October. The Kick-Off Meeting for this project will be held on 8 October at 9:00-10:00 (EST) / 14:00-15:00 (BST) / 15:00-16:00 (CEST) |
If you would like to get involved in a PHUSE Working Group Project, please explore the projects via the Volunteer Board and contact the PHUSE Office on workinggroups@phuse.global to express your interest. |
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