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PHUSE collaborations are organised into a number of specialist Working Groups, each with a broad topic area. The Working Groups have specific projects designed to achieve a set of particular objectives. This page will highlight the latest news and information from our projects. Participation is open to anyone who wants to contribute and if you would like to get involved, please email workinggroups@phuse.global. |
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Data Transparency Autumn Event |
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Active since 2014, PHUSE’s Data Transparency Working Group has provided 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 unrestricted 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.
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2025 – Call for Speakers is Open! |
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Call for Speakers is officially open for the Data Transparency Autumn Event 2025! This is a fantastic opportunity for those passionate about data transparency to share their bold ideas, fresh perspectives and real-world experience. The event will take place virtually 16–18 September, meaning you can participate from anywhere in the world! Plus, there’s no need to block out the whole day, as sessions are delivered in short bite-sized chunks from 10:00-12:30 (EDT) / 15:00-17:30 ( |
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The full event agenda can be found here.
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| Community Forum: Regulatory Landscape of AI/ML in DHTs (Current Landscape, Knowledge Gaps, Best Practices for Regulatory Submissions, Challenges of Regulating AI) |
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The Emerging Trends & Technologies Working Group is hosting its second Community Forum of the year, Regulatory Landscape of AI/ML in DHTs (Current Landscape, Knowledge Gaps, Best Practices for Regulatory Submissions, Challenges of Regulating AI). We will be hearing from both FDA and Pfizer speakers, who will be looking at how Digital Healthcare Technologies (DHTs) show significant potential for enhancing data acquisition in clinical trials by enabling objective and accurate data collection. Examples of DHTs include wearable devices – sensors, smartwatches, fitness trackers – that continuously monitor vital signs, physical activity, sleep patterns, and medication adherence. However, the emergence of DHTs also raises regulatory-related questions. In this PHUSE Community Forum, we will discuss the development of digitally derived measures (clinical outcome assessments and biomarkers) and germane regulatory policies from the perspectives of government and industry experts. This Community Forum will be taking place over Zoom on 25 September at 13:30-14:45 (BST) / 08:30-09:45 (EDT). |
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The Open Source Technology in Clinical Data Analysis (OSTCDA) project was set up with the aim to create a manuscript on the integration of open-source software solutions for clinical data management, analysis and reporting.
A significant amount of time and energy has been invested in recent years exploring the desirability (do we want it?), feasibility (can we do it?), and viability (is it worth it?) of integrating open source solutions into our clinical data pipelines which transform source data into clinical study reports and submission data packages. In this October edition of the Open Source Open Forums, we will provide an update on the status of this initiative and continue to hear from you on what we’ve missed so far.
When this manuscript is complete, we hope to put to rest some of the burning questions that we believe we now know the answers to. This will allow industry, and all the passionate people in it, to look ahead and start tackling the next horizon of challenges related to using open source solutions for clinical data pipelines. We hope you will contribute your expertise to this effort. The OSTCDA Project will be hosting their next forum to discuss the above, titled Open Source Technologies in Clinical Data Analysis.
This Forum will be taking place over Zoom on 11 October at 15:00-16:00 (BST) / 10:00-11:00 (EDT).
The Treatment Emergent Definitions Recommendations project within the Safety Analytics Working Group has published a new White Paper, 'Recommended Definition of Treatment-Emergent Adverse Events in Clinical Trials'. This White Paper defines treatment-emergent events in Phase I to IV clinical trials and integrates summary documents across therapeutic areas. The recommendations described herein were based on the authors' collective experiences and a survey conducted by the PHUSE Treatment Emergent Definitions Recommendations project team to solicit input from respondents on various TEAE scenarios for a simple clinical study design.
The Quality and Reusability of Real World Data project within the Real World Evidence Working Group has published its third Blog Post, RWD: The FDA’s Guidance on Assessing Registry Data to Support Regulatory Decision-Making. This Blog will explore the main messages in the regulatory guidance, what challenges we foresee in applying it, and how registry data can be used in regulatory applications.
You can learn more about this project and read their previous blogs here.
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The CDISC Standard for Exchange of Nonclinical Data (SEND) data standard has created new opportunities for collaborative development of open-source software solutions to facilitate cross-study analyses of toxicology study data.
A sub team of the BioCelerate SEND Implementation for Cross Study Analysis Initiative was formed and through collaborative efforts via a public–private partnership between BioCelerate and the FDA/Center for Drug Evaluation and Research (CDER), they worked to develop and publicise novel methods to facilitate cross-study analysis of SEND datasets.
As part of this work in collaboration with the Pharmaceutical Users Software Exchange (PHUSE), an R package called sendigR has been developed to enable users to construct a relational database from a collection of SEND datasets and then query that database to perform cross-study analyses. The sendigR package also includes an integrated Python package, xptcleaner, which can be used to harmonise the terminology used in SEND datasets by mapping to CDISC controlled terminologies. This package, sendigR, will provide data scientists and toxicologists with a free, open-source tool that can be utilised to query large repositories of electronic standardised toxicology study data. sendigR was published to the Comprehensive R Archive Network (CRAN) and GitHub - phuse-org/sendigR: Enable Cross-Study Analysis of 'CDISC' 'SEND' Datasets. An R Shiny web application was included in the R package to enable toxicologists with no coding experience to perform historical control analyses. Experienced R programmers will be able to integrate the package functions into their own custom scripts/packages and potentially contribute improvements to the functionality of sendigR.
To learn more, read the sendigR accompanying manuscript here: Frontiers | sendigR: an R package to leverage the value of CDSIC SEND datasets for cross-study analysis (frontiersin.org)
sendigR reference manual: Enable Cross-Study Analysis of CDISC SEND Datasets • sendigR (phuse-org.github.io)
sendigR R Shiny demo app: phuse-org.shinyapps.io/sendigR/
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BST) / 16:00-18:30 (CEST) Submit your 150-word abstract by 12 June for the chance to take part in one of the most focused, forward-looking events in the transparency space.
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Real World Evidence Webinar Series | ||
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Webinar 2: Estimands in Real-World Evidence Studies This webinar will explore the pivotal role of estimands in real-world evidence (RWE) studies, bridging the gap between regulatory guidance and practical implementation. The session will address challenges unique to RWE settings, such as heterogeneous patient populations, complex treatment regimens, and the impact of intercurrent events on study outcomes with a focus on generating RWE that can inform regulatory decision-making. Through practical examples, case studies, and an engaging panel discussion featuring domain experts, this session will highlight best practices for defining estimands that enhance the interpretability and reliability of RWE findings. Participants will leave with a systematic approach to estimand definition, empowered to conduct RWE studies that are robust, actionable, and aligned with evolving regulatory standards. This webinar will held virtually on 5 June 2025 at 11:00 (EDT) / 16:00 (BST) / 17:00 (CEST)
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Community Forum: AI and SaMD in Healthcare: From Compliance to Patient-Centred Innovation | ||
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Digital health technologies (DHTs), such as wearable accelerometers, are increasingly being adopted in clinical trials, as they enable objective and continuous evaluations of health parameters, functions and behaviours in the participant’s naturalistic environment. The continuous data stream provided by DHTs combined with artificial intelligence/machine learning (AI/ML) tools can lead to the identification of novel digital endpoints (NDEs) and measuring objective outcomes that are meaningful to patients. These NDEs can support clinicians with early diagnosis, prognosis, and personalised treatments of a wide range of diseases. To address the need to develop and validate NDEs before their large-scale deployment in clinical trials and gather evidence supporting their regulatory adoption, at Pfizer we have collected in-clinic and at-home data from hundreds of healthy volunteers across age ranges, spanning paediatrics to geriatrics, and device locations. In the first part of this presentation, considerations about the selection of fit-for-purpose DHTs and the validation of AI-driven algorithms for NDEs of gait and physical activity will be discussed as compared to standard measurements. Since understanding individual perception towards using new technologies is crucial for clinical adoption of NDEs, the evaluation of self-reported measures of usability, acceptability, and level of continued usage will also be addressed. Results suggest high reliability and accuracy of DHT-derived gait and physical activity endpoints, for example by effectively tracking walking at different speeds, while ensuring participants’ comfort in wearing DHTs. Finally, the deployment of the validated AI-driven digital biomarkers in clinical studies will be presented, with particular focus on older individuals at risk of frailty and malnutrition. This Community Forum will take place virtually on 18 June at 11:00 (EDT) / 16:00 (BST) / 17:00 (CEST)
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End-to-End RBQM Webinar: Value-Driven Clinical Data Review, Together | ||
Clinical data review is no longer just a technical checkbox – it’s a strategic, cross-functional effort that can make or break the success of a clinical trial. When teams collaborate across functions, align on risk, and focus on value-driven review, the result is more reliable, coherent and compliant trial data. In this session, we’ll explore how to move beyond traditional data cleaning by embracing a collaborative, risk-based approach. Learn how functional interdependencies – when properly understood and leveraged – can drive smarter, more efficient reviews. We’ll also host a dynamic roundtable featuring voices from big pharma, tech and CROs, who will share real-world insights, challenges, and best practices for building effective, cross-functional data review strategies. Whether you’re in data management, clinical operations, biostatistics, or a supporting function, this session will offer actionable strategies to foster collaboration and value-driven data review processes. This webinar will be held virtually on 26 June at 10:00 (EDT)/ 15:00 (BST) / 16:00 (CEST)
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The Implementation of Estimands (ICH E9 (R1)) using Data Standards project within the Optimizing the Use of Data Standards Working Group, have published a new White Paper and Example Document! This white paper provides recommendations and examples to illustrate the implementation of the estimands framework introduced by the ICH E9(R1) Addendum on Estimands and Sensitivity Analysis in Clinical Trials to the Guideline on Statistical Principles for Clinical Trials [ICH E9(R1), 2019] using data standards (as part of the clinical data flow). |
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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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Working Group Report: Includes project updates, recent and upcoming deliverables and future plans for each Working Group. | |
Monthly Mailings: The monthly newsletter. Here you will find a full update from each month of the year, easily accessible and divided into key areas of PHUSE. | |
PHUSE Blogs: Fancy a quick read? A blog is a perfect way to catch up on all things Working Groups. Get the lowdown on the latest events from across the globe and stay updated on industry topics brought to you by industry professionals. |
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Initiate and lead a new project under the PHUSE Working Groups umbrella. The new project must address problems of significant relevance to computational science related to drug, biological and device development and must meet all of the guidelines for projects within the collaboration, including the following mandatory requirements:
New projects can be submitted anytime during the year, click here to submit. |