The Challenge
Despite a modern SAS-based ecosystem, the client's statistical programming team was bogged down in manual scripting to generate Analysis Results Datasets (ARDs) using CDISC Analysis Results Standards (ARS). With each study spanning hundreds of outputs, ARD traceability to source and TFLs was a time sink, delaying timelines and QC bandwidth.
The Solution
To eliminate redundancy and bring reproducibility into focus, the client adopted siera, Clymb's automation solution built entirely in R. Within weeks, they overhauled their ARD generation process using metadata as the blueprint.
The Conclusion
By automating the generation of CDISC-compliant ARDs, siera drastically improved efficiency in statistical programming. The acceleration not only streamlines clinical reporting timelines and allowed the team to focus on strategize analysis and submission readiness with confidence. As a result, this lead to faster database lock-to-submission cycles without compromising quality or traceability.
Achieved a 60% reduction in ARD programming per study, significantly accelerating the turnaround of TFLs and statistical reports.
High-Level Process Flow
Most Biostats teams still rely on traditional, manual methods to generate Tables, Figures, and Listings (TFLs). Static shells require programmers to manually write code based on domain expertise—a time-consuming and error-prone process.
With Siera, that changes.
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Eliminated hand-coded ARDs
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Enables earlier data insights
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Full TFL Compatibility
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Ensured regulatory compliance with CDISC
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Seamless collaboration with cross-functional teams
Analysis Results
Standards Metadata
Analysis Display
Metadata
ARD - ready R scripts
Analysis Results Datasets (ARDs)
Outputs/ Displays
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The Analysis Results Standards (ARS), developed by CDISC, is designed to streamline, automate, and standardize the way clinical trial analysis results are structured. It ensures automation, reproducibility, reusability, and traceability across datasets—eliminating inefficiencies caused by inconsistent reporting methods.
At its core, ARS provides a Logical Data Model that defines analysis results and their associated metadata, creating a consistent framework for organizing and automating clinical trial outputs, such as tables and figures.
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