Data Visualisation & Open Source Technology – Project Volunteer Board
Welcome! |
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Interested in joining one of the Data Visualisation & Open Source Technology Working Group Projects? The projects below welcome new volunteers. |
Project Description: The Clinical Visual Analytics for Review and Submission Project aims to support the community by addressing key questions and challenges related to data visualisation and open-source tools. These areas naturally align in the current landscape, where open-source programming languages offer powerful and flexible data visualisation capabilities. By exploring this intersection, the Working Group seeks to promote effective use of modern tools, share best practices, and improve understanding of how open-source technologies can enhance data visualisation in a regulatory and clinical context. | Regular Project Meeting Day/Time:
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Project Description: This project aims to develop or enhance a standard template (such as the Study Data Standardisation Plan [SDSP] or Analysis Data Reviewer’s Guide [ADRG]) to ensure consistent documentation of metadata related to statistical package versions and procedures. The goal is to align with health authority expectations and streamline the submission of clinical study metadata as part of the regulatory review process. Historically, with proprietary statistical programming languages, version information has typically been captured at a high level within the SAP, often as a general statement of the software and version used. However, with the increasing adoption of open-source technologies, more detailed and transparent metadata is now required. This project will address this gap by enabling structured, standardised capture of package-level metadata, supporting improved traceability, clarity and regulatory confidence. | Regular Project Meeting Day/Time:
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Comparing Analysis Method Implementations in Software (CAMIS) | |
Project Description: The CAMIS (Comparing Analysis Method Implementations in Software) project builds on the earlier Clinical Statistical Reporting in a Multilingual World initiative, addressing differences observed in statistical results across programming languages. Even within validated environments, variations in underlying computational approaches can produce results that differ but remain statistically valid. These discrepancies create uncertainty for sponsor companies when submitting to regulatory agencies, particularly regarding how such differences will be interpreted. CAMIS aims to define this challenge and provide a structured framework for assessing cross-language differences in statistical analyses. The project focuses on key analyses commonly used in submissions (e.g. summaries, models, bioequivalence testing), documents where equivalence can be achieved and evaluate known differences through practical use cases. It also provides sample code via a public repository and promotes statistically sound implementation choices over software-specific defaults, supporting greater confidence in multi-language regulatory submissions. The CAMIS repository to document known differences is now live and open for community contributions. | Regular Project Meeting Day/Time:
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Note: The project welcomes contributors, particularly those with deep expertise in specific or niche statistical methods who can research and author content for the repository. Contributors typically register as members, but anyone may raise an issue or submit a pull request without joining. |
PharmaForest: A Collaborative Repository of SAS Packages for Pharmaceutical Industry | |
Project Description: This project aims to drive adoption of reusable SAS packages and best practices across the pharmaceutical industry, addressing inefficiencies, fragmentation and limited collaboration. It focuses on establishing an open, sustainable ecosystem – PharmaForest – built on the SAS Packages Framework (SPF) to improve productivity, compliance and knowledge sharing. Key activities include developing educational materials and presentations on implementing PharmaForest packages and SPF, and sharing these through webinars, industry events (e.g. PHUSE Connect) and training sessions. The project will also create and maintain an open-source repository of high-quality SAS packages for common pharmaceutical use cases, enabling consistent installation and version control. By fostering community engagement through contributions, peer review and onboarding resources, PharmaForest will reduce duplicated coding, improve standardisation and enhance quality. This approach will accelerate development timelines, lower costs, strengthen compliance and support a more collaborative and innovative SAS programming community. | Key Skills:
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Project Description: This project aims to enhance the teal framework by increasing its flexibility for use across pharmaceutical companies. Through research, development, testing, documentation and training, it will introduce new functionality that allows users to reformat, post-process and decorate outputs from existing teal modules without changing the core code. While teal and teal.modules.clinical already provide strong support for interactive exploration of standardised clinical data, differences in company standards and analysis requirements have limited broader adoption. As a result, organisations often build custom modules from scratch, creating unnecessary effort and inefficiency. By enabling customisation of tables, graphs and listings through reusable enhancements, this project will reduce the need for bespoke development, improve scalability of existing modules, and support greater consistency across the industry. Overall, it will make teal more practical, adaptable and widely usable in pharmaceutical workflows. | Regular Project Meeting Day/Time:
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