See what a validation package looks like when it builds itself
A short walkthrough of how GxPForge keeps traceability current as your team works, instead of reconstructing it before a release.
Book a demoGenomics and precision medicine labs validate more than software behavior, they also have to account for reference databases and bioinformatics pipelines that change as science advances. A pipeline that was accurate against last year's reference data needs revalidation when that reference data updates.
A genomic interpretation pipeline depends on reference databases that get updated as new research emerges. Unlike a typical business system, where the underlying logic stays fixed until someone deploys new code, a genomics pipeline's output can shift purely because the reference data behind it changed, even with zero code changes.
Validation evidence for these labs needs to capture which version of a pipeline, and which version of the reference data it ran against, produced a given result. Losing track of that pairing makes it very hard to explain, months later, why two runs of what looks like the same pipeline produced different outputs.
Beyond standard functional testing, a defensible package for this space documents the change history of reference data sources, the criteria for deciding a pipeline update needs revalidation, and a clear link between a specific report and the exact pipeline and reference version that generated it.
A short walkthrough of how GxPForge keeps traceability current as your team works, instead of reconstructing it before a release.
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