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The SEND Coding Bootcamp is a new project within the Nonclinical Topics Working Group. Which is currently calling for volunteers. The 4-day SEND Coding Bootcamp aims to help those working with SEND datasets become more productive by teaching basic coding and plotting skills. Over the course of a series of separate hands-on coding sessions, participants will learn the basics of programming and plotting using the R programming language. The course will be oriented around SEND datasets and will include reading, writing, plotting, and manipulating SEND datasets stored in .xptformat. Basic knowledge of the SEND standard is expected. No previous knowledge about programming or the R programming language is needed. If you would like to volunteer or learn more about this project, email workinggroups@phuse.global. Closing date: 1 April. The Kick-Off Meeting for this project will be held 4 April 2025 11:00 (EDT) / 16:00 (BST) / 17:00 (CEST) |
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There is interest across the pharmaceutical industry in using Git for statistical programming. Some companies have already incorporated Git, or are attempting to, and there are common challenges being faced. In these cases, the introduction of Git has increased the complexity of a statistical programmer’s tasks, which has led to challenges in uptake and to taking advantage of the benefits Git offers. This is an important challenge to overcome for increasing efficiency of operations. The purpose of this Working Group project is to provide the industry with tools and guidance for addressing and overcoming this common challenge.
If you would like to volunteer or learn more about this project, email workinggroups@phuse.global. Closing date: 3 April 2025.
The Kick-Off Meeting for this project will be held 4 April 2025 10:00 (EDT) / 15:00 (BST) / 16:00 (CEST)
The Anonymization of Imaging Data project is looking for volunteers to join our ongoing project focusing on anonymization and sharing of images in clinical trials. Our recent literature review has highlighted a gap in existing research, particularly in the context of sharing images and related metadata in parallel to clinical trial data. We will focus on DICOM images and related metadata in oncology. Our project will take our collective knowledge of clinical trial data and images to create guidance that will inform de-identification decisions in the anonymization process for the images. There will be a comprehensive review of DICOM image tags and relevant packages and methods that are used to process them. We aim to develop best practices for processing identifiers and anonymising images in oncology, ensuring both privacy and usability. If you have experience in processing and de-identifying images in clinical trials, particularly with DICOM images in oncology, we want to hear from you. If you would like to volunteer or learn more about this project, email workinggroups@phuse.global. Closing date: 25 April. The regular meeting series is currently bi-weekly on Tuesdays 9:00 (EDT) / 16:00 (BST) / 17:00 (CEST) |
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