Open-Source Analytics Tools for Clinical Data Management

Session chaired by Pekka Tiikkainen

Description:

The use of open-source analytics tools is becoming increasingly prevalent in the management of clinical data. Initiatives such as the IMPALA consortium and the PHUSE RBQM Working Group have published tools with code that is freely shared and available to everyone. Examples include CTAS for time series anomaly detection (IMPALA consortium, originally developed in-house at Bayer), simaerep for detecting adverse event underreporting (IMPALA consortium, originally developed at Roche), and the Good Statistical Monitoring R package for Key Risk Indicators (originally developed in-house at Gilead Sciences). Unlike proprietary software, these open-source tools offer the advantage of transparency, as the functionality of the program is fully visible to all users. This transparency allows users to trust the results more, as the calculation logic can be examined line-by-line if needed. Additional benefits include savings on licensing fees and the continuous development of the tools by the user community which ensures that the future of the tool does not rely solely on a single actor such as a software vendor. Participants in this session will learn about recent advanced open-source tools available for clinical data management and will have the opportunity to join discussions on the future of open-source development in the field. This session is aimed not only at programmers and data scientists who develop these tools but also at data managers interested in learning more about the available possibilities.

Learning Objectives:

• Gain an understanding of various advanced open-source tools currently available for clinical data management.
• Learn about the advantages of open-source software vs. proprietary solutions.
• Learn how they and their organization can actively contribute to the growth and adoption of open-source tools.