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Currently, analysis results are created and represented static PDF documents that may contain hundreds of tables. These tables are often difficult to navigate and there can be significant variability between sponsors. Generating these reports is expensive and they are typically only used once, offering limited reusability.

The current workflow of generating analysis results involves the end user generating the Analysis Data Model (ADaM) dataset, followed by generating the display in a static format such as RTF or PDF using the ADaM dataset. The Analysis Results Metadata (ARM) for define.xml is retrospectively generated, which provides high-level metadata documentation about analysis displays and results (Figure 1); however, there is no formal model or structures to describe analysis results metadata and analysis results data which leaves a gap in standardization.

The current process is expensive, time-consuming, and lacks automation and traceability, leading to unnecessary variation in analysis results reporting.

 

Figure 1: Current State of Display and ARM Generation (insert higher resolution picture)


Our vision for the future state of analysis results reporting is a world where analysis results are machine-readable, easily navigable, and highly reusable. We envision the following:

  • A logical model for describing analysis and results data
  • Automated generation of machine-readable results data
  • Improved navigation and reusability of analysis and results data
  • Support for the storage, access, processing, and reproducibility of results data
  • Traceability to the study protocol/SAP and to input ADaM data
  • Open-source tools for designing, specifying, building, and generating analysis results data

To achieve these goals, the ARS team has been working toward developing a logical model to fully describe analysis results metadata. This logical model will enable the implementation of an Analysis Results Metadata Technical Specification (ARM-TS) and an Analysis Results Data (ARD) framework. ARM-TS can be used to support automation, traceability, and the creation of data displays while the ARD framework will support reuse and reproducibility of results data.


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