| Overview |
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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. Registration will open 4 January!
Day 1 Day 1 of the Data Transparency Winter Event started with a presentation titled ‘A Cross-Sectional Study to Evaluate the Real-World Impact of Clinical Trial Transparency Initiatives’ by Shalini Dwivedi (Krystelis). Shalini discussed a survey they are conducting across stakeholders (trial participants, investigators, researchers, sponsors) on the impact of data transparency. The survey remains open, and the preliminary results have revealed interesting trends. Notably, findings suggest an opportunity to raise awareness around best practices. For instance, while more than half of research requests focus on meta-analyses, more than half of surveyed sponsors enable secondary-purpose research on their own platform (versus multi-sponsor environments). Such data illustrates the level of awareness (or lack of?) from the different groups on the progress of data sharing. The second presentation, ‘Improving Data Findability Through Better Clinical Metadata’ from Lukasz Kniola (Biogen), introduced a metadata repository concept developed at Biogen, incorporating summary statistics on demographics, findings, intervention and events data. This repository facilitates the search of studies while removing the need to access the data until the final set of studies is approved for reuse. The solution is both simple and efficient, and code is even provided in the slides. Roche was one of the first sponsors to embark on the data sharing path, back in 2013. In the third presentation, Nuria Mackes and Asad Preuss-Dodhy (Roche) outlined their journey and recent work on sharing genetic data. ‘Lessons Learned in Anonymizing Complex Health Data’ offered insights into the WAYFIND-R project – a global real-world evidence generation initiative – and how applying stricter controls enabled them to share data with higher data utility. The fourth and final presentation by PHUSE Good Transparency Practices (GTP) Project Leads Abby McDonell and Lauren Hepburn took us through the deliverable, which is currently in its finalisation stage. The GTP white paper has been developed with EMA and Health Canada officers as observers and touches upon governance, training and procedure matters around data sharing between data anonymisers, data controllers and data recipients. This deliverable will complement more technical deliverables from the Working Group and will soon be available for public review. Stay tuned for updates. Day 2 Day 2focused on data privacy governance in the current evolving landscape of clinical trial transparency initiatives. During the first presentation of the day, ‘De-Identification |
Beyond Borders: Global Applicability of HIPAA Safe |
Harbor’, Obaraboye Olude |
(Privacy Analytics |
) investigated the effectiveness of HIPAA Safe Harbor de-identification in other countries by applying the same methods (that inspired HIPAA Safe Harbor de-identification) to census data from other countries at different points in time. |
Obaraboye also |
compared the definition of PHI found in the HIPAA Privacy Rule with the definition of personal data in other jurisdictions |
and summarised the potential for re-identification through other means |
such as combining de-identified data with |
potentially available information, which motivated the creation of HIPAA Safe Harbor. This presentation |
highlighted the need to adopt a more globally accepted standard for de-identification |
– and what |
this means in practice. |
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 US 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.
In the second presentation, ‘The HEAL Data Ecosystem: Enabling Data Sharing within the NIH |
HEAL Initiative®’, Zixin Nie |
(RTI International |
) provided an in-depth insight into The Helping to End Addiction Long-term® Initiative, or NIH HEAL Initiative® |
– an NIH-wide effort to speed scientific solutions to stem the national opioid public health crisis, funding over 1,000 projects nationwide. |
Zixin provided an overview into the data sharing practices of the HEAL |
Initiative, the model used for the HEAL Data Ecosystem and how it helps |
enable data transparency |
. The tools available to make HEAL data FAIR |
(Findable, Accessible, Interoperable, and Reusable) were discussed, along with an emphasis on the HEAL Data Ecosystem being an important part of this effort and empowering researchers in the sharing of data. In the third presentation, ‘PSURs Public Release – Individual Patient Safety Data Disclosure Across Multiple Transparency Initiatives’, Agnieszka Glowinska and Magdalena Majewska (AstraZeneca) provided insights into their experiences of transparency of COVID-19 products, particularly on publication of PSURs and Assessment Reports of COVID-19 vaccines. This relates specifically to the cumulative and reporting period exposure from post-approval (marketing) experience (Phase IV) and cumulative exposure (Phase III) with the following key aspects in mind: 1) How to ensure the privacy of clinical study participants is protected consistently and 2) Whether a unified approach can be applied to all clinical study participants, regardless of study phase or living status. Agnieszka and Magdalena discussed how to open a dialog supporting transparent sharing of safety data without linking it to the person who has trust in both sponsors and regulators. They also detailed the importance of strategies used in their chosen privacy-enhancing data de-identification framework to ensure information security, cybersecurity and privacy protection. The fourth and final presentation of the day, ‘The Final Countdown: Preparing for the 2025 CTIS Transition Deadline’ by Francine Lane (Citeline), introduced key points on how to consolidate and harmonise disclosure both efficiently and consistently to meet the upcoming CTIS transition deadline. Using a high-energy race car theme, Francine first walked the audience through the toolbox of what is required, along with key takeaways, considerations for transitioning trials, expedited transitions, the differences between consolidation and harmonisation, and the new transparency rules. Throughout, there was a focus on maintaining collaboration and communication between each of the stakeholders involved in this highly fast-paced arena, as with all deliverables related to the field of clinical trial transparency. Day 3 The final day of the Data Transparency Winter Event started with a presentation by Woo Song (Xogene) on ‘From |
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 standardization of digital medical images and associated information. Anonymizing 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, anonymization of thousands of files, anonymization 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.
This presentation explores the challenges and insights gained from our experience with anonymizing complex health data. The primary focus is on the need for robust technical and organizational measures, such as a secure processing environment, to ensure controlled data access. Implementing these control measures allows us to maximize data utility while minimizing risk. We discuss specific technical challenges encountered in the data anonymization 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 anonymization process. Additionally, we emphasize the importance of providing guidance and training for anyone working with anonymized data to dispel common misconceptions surrounding anonymization.
Automated to Accountable: Building Responsible AI for Trial |
Transparency’. Woo discussed the tremendous potential to accelerate and enhance clinical trial transparency through automated plain language |
summarisation of study documents |
, using Generative AI. Woo talked about the importance of establishing proper governance and best practices (including policies and auditing mechanisms) to maximise the benefits of using AI while minimising risks of creating inconsistent or inaccurate outputs. Using a practical example and a live demo of a tool, Woo demonstrated how various considerations in prompt engineering can be taken into account when using Generative AI to automatically condense a sample protocol into a patient-friendly synopsis. |
A key aspect that was highlighted was the need for humans to remain in the loop to ensure AI is used responsibly. In the second presentation, Diwakar Angra (GENINVO) discussed ‘Challenges and Solutions to Anonymization of Imaging Data (DICOM)’. DICOM (Digital Imaging and Communications in Medicine) is a standard for the communication and management of medical imaging information and related data. Diwakar outlined the challenges faced in anonymising DICOM image data, which include editing DICOM header data, diverse identifiable information in images, file numbers and sizes involved, and anonymisation in sync with study dataset and documents. On potential solutions to these challenges, Diwakar shared insights into available open-source libraries to read DICOM files, anonymisation strategies for image data, and perspectives on preserving image quality and potential for automation. Thorough testing and validation of the DICOM anonymisation process was stressed upon, to ensure compliance to privacy regulations while preserving the clinical value of the medical images. In the third presentation of the day, Luk Arbuckle (Privacy Analytics) spoke about ‘Balancing |
The secondary use of clinical trial data can significantly increase its value beyond the original analysis and help find new insights, signals, and ultimately treatments. A major hurdle to data reuse is a lack of transparency and discoverability. SDTM and ADaM datasets have reliable, strict naming conventions and consistent structure within and across studies. These qualities make it possible to create generalized programs which stack and process datasets in an automated manner, regardless of their contents. The output is descriptive metadata that is useful, searchable, and not constrained by privacy concerns. Such metadata can be made open and searchable while access to data remains restricted. It allows to find tests, events, visits, and characteristics across datasets and studies before requesting access to relevant data assets. This paper describes the technique for leveraging CDISC standards and simple statistics to unlock the value of clinical data and increase its transparency and discoverability for researchers and data scientists. It also discusses the benefits and challenges of this approach and provides practical examples of how it can be implemented.
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.
Act: The Dynamics of Legislation, AI, and Global Health Data |
Sharing’. Luk shared his experience acting as an expert witness on Bill C-27 Consumer Privacy, Tribunal, AI and Data at a recent Canadian parliamentary committee. He recalled how his experience over the years was an important precursor to the extensive preparation required for such meetings and explained the format of the latest parliamentary committee he testified in. Drawing on insights from |
his testimony before |
the parliamentary committee, |
Luk discussed the impact of data protection laws on health research and analytics |
, emphasising the importance of privacy-enhancing technologies |
and offering a perspective to balance privacy concerns with the need for efficient and effective data sharing across borders, |
Abby McDonell, Privacy Analytics
Abby McDonell is a Senior Program and Project Manager at Privacy Analytics. Abby manages anonymisation program activities for pharmaceutical clients by providing assistance in meeting regulatory deadlines and promoting transparency of clinical trial data. Abby is a member of the PHUSE Data Transparency Work Group and is a co-lead of the Good Transparency Practice project. She holds a BSc in Health Science and an MSc in Neuroscience.
Aga Glowinska, AstraZeneca
Aga Glowinska is the Director in Clinical Trial Transparency, Anonymisation for AstraZeneca. Aga received her PhD in Medicinal Chemistry at Warsaw University and is post-graduate in Statistical Analysis and Data Mining in Business. Aga has been with AstraZeneca for 5 years. Prior to her time in AstraZeneca Aga was a Statistical Programmer and Clinical Monitoring Associate. Today, Aga is focused on clinical documents anonymisation required for regulatory submission and Vivli requests. As part of her role Aga is actively involved in E2E standardisation of data collection & display within cross-functional initiatives.
Diwakar Angra, GENINVO
Diwakar Angra has 2 years of Experience in clinical data transparency process. He handles anonymisation of clinical datasets, documents and calculation of risk assessment. He has worked on various projects which are published on Health Canada and EMA. Diwakar is currently working with GENINVO as Anonymisation Analyst.
Lauren Hepburn, Rare Disease Sponsor
Lauren Hepburn is a Senior Clinical Trial Transparency Manager at a Rare Disease Sponsor. Lauren prepares clinical trial documents for submissions related to the European Clinical Trials Regulation (EU CTR), EMA Clinical Data Publication (Policy 0070), and Health Canada Public Release of Clinical Information (PRCI). Lauren is a member of the PHUSE Data Transparency Working Group and is currently co-leading the Good Transparency Practice project. She obtained her MSc in Biology and her BSc in Ecology and Evolutionary Biology.
Lukasz Kniola, Biogen
Lukasz Kniola – Associate Director Data Transparency at Biogen UK. Data Sharing, Anonymisation, and Data Transparency Expert. PHUSE and EMA TAG Member. Clinical Programmer and Data Engineer.
Magdalena Majewska, AstraZeneca
Magdalena Majewska is the Senior Analyst in Clinical Trial Transparency, Clinical Document Anonymisation for AstraZeneca. She is responsible for leading multiple clinical documents anonymisation projects required for regulatory submission: under EMA Policy 0070 and Health Canada PRCI, but also for the requests falling outside these policies: EMA Policy 0043, FOIA.
Magdalena has a strong interest in the holistic view of patient privacy protection.
Magdalena holds a Master’s degree in Medical Analytics from Medical University of Gdansk, Poland. Before joining AZ in August, 2021, worked for the Polish Competent Authorities, the Office for Registration of Medicinal Products, Medical Devices and Biocidal Products, where she was responsible for surveillance and vigilance of medical devices and in vitro diagnostic medical devices.
Obaraboye Olude, Privacy Analytics
Obaraboye Olude MBBS, MPH is a Clinical Trial Transparency Manager at Privacy Analytics. She has over a decade of experience in clinical trials data analysis. She has a background in Medicine and Public Health and has led several anonymisation and redaction projects for both regulatory and non-regulatory submissions.
Shalini Dwivedi, Krystelis
Shalini has 17 years of pharma industry experience, and for the last 8 years she has focused on the Clinical Transparency domain. Shalini has led the delivery of Clinical Data Transparency (CDT) projects to global pharma clients from trial registry support to redaction and anonymisation of documents as per EMA Policy 0070, Health Canada PRCI and EU-CDTR. Shalini has extensive knowledge of all relevant CDT regulations and frequently provides regulatory consulting advice to customers on CDT requirements. She is active in the CDT community globally, participating in industry forums and writing publications.
Zixin Nie, RTI International
Zixin Nie is a data privacy specialist within the Center for Data Modernisation Solutions at RTI International. He has over 7 years of experience working in data privacy. His current work at RTI involves designing systems to de-identify data and enable privacy-preserving record linkage for the National Heart, Lung, and Blood Institute’s Biodata Catalyst platform, evaluating de-identification requirements for the National Institute of Health’s Helping End Addiction Long-term Initiative, and developing models using synthetic data from RTI’s Synthpop. He is also leading a project for America’s Datahub Consortium to perform an environmental scan on Privacy Preserving Technologies.
Prior to working at RTI, Zixin worked at Privacy Analytics (a subsidiary of IQVIA), where he developed customised data privacy solutions for clients within government, industry, and academia within the United States and Europe, and helped to develop techniques and methodologies for re-identification risk measurement and tools for de-identification/anonymisation of data. He has also worked at Statistics Canada as a key member within the Confidentiality group within the Household Surveys Methodology Division, where he developed the statistical disclosure control rules implemented within the Generalised Tabulation System, a tool for automated calculation of aggregate statistics for dissemination to the Canadian public. The rules he created, along with the Generalised Tabulation System, have been widely used within Statistics Canada, covering 90% of published social survey statistics and the Canadian census.
Zixin is experienced in data de-identification and anonymisation, privacy impact evaluation, privacy by design principles, and has performed expert determinations under the Health Insurance Portability and Accountability Act.
to enable development of responsible data access models that support international collaboration and research. To wrap up this year’s Data Transparency Winter Event, Aaron Mann (CRDSA) and Luk Arbuckle (Privacy Analytics) co-presented on ‘Biopharma Data Sharing Policies and Protection Methodologies’. Aaron and Luk shared the updates from CRDSA’s systematic review on biopharma sponsor data sharing policies and protection methodologies, first conducted in 2022 and updated last year. The results highlighted a 20.7% increase in number of data contributors, with increased commitment (exceeding 80%) to share across all tiers based on sponsor size. Co-presenters noted that consistency and interpretation of data protection methodologies and terminologies remains a key challenge, even for domain subject-matter experts. CRDSA hopes the systematic review will help create meaningful benchmarks to inform data contributor policy development, as well as highlight areas where continued work is needed. CRDSA is conducting a summit on Thursday 29 February 2024, to share expert insights into the latest developments in responsible reuse of patient data. Interested individuals can register at: https://crdsalliance.org/news-events/. |
| Data Transparency Winter Event Sponsors |
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Virtual Event Sponsors
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| Sponsor Flyers |
Virtual Event Sponsors
| Sponsorship |
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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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