Using Metadata for Speedy Delivery

In this R Adoption Series Webinar, the R Consortium invited two Pharmaceutical organizations to share their experience in leveraging metadata for automation pieces of the clinical delivery workflow. This session starts with Christina Fillmore using Open Source R packages {metacore} https://github.com/atorus-research/me... and {metatools} https://pharmaverse.github.io/metatools/ for creating metadata objects and enhancing columns in existing datasets. Following Christina, Yujie Zhao and Keaven Anderson discussed {metalite} https://github.com/Merck/metalite.ae which is used to define a unified data structure to save metadata information for analysis & reporting (A&R) based on ADaM datasets in clinical trial development. The last section of the event focused on answering questions about leveraging metadata in the delivery pipeline and soliciting other ways to use metadata to enhance current processes.


Main Sections

0:00 Introduction
2:35 Leveraging metadata for dataset creation using R - Christina Fillmore
2:50 Dataset metadata
3:53 {metacore}
5:15 {metatools}
20:57 metalite: ADaM - metadata - A&R - Yujie Zhao and Keaven Anderson
21:58 Introduction and background
25:14 Build metadata
29:00 metadata sample
31:15 Create A&R grid
33:33 RTF tables
37:17 Forestly - interactive AE forest plot
43:33 Advantages
48:20 Q&A session

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