White paper: Smart Transformation of Disparate Biopharma Source Data to Unified Machine Readable Target Data Models
Digital data is the lifeblood of the biopharma industry as it works increasingly with study data, molecular and digital biomarkers.
Studies and assays from a variety of in-vitro, ex-vivo assays, nonclinical studies, clinical trials, and their eCRF data, bio-analytics data, molecular biomarkers from bio-samples generate data types typical of those studies.
Every laboratory or CRO that collects and publishes this data have their own format and data structures. Studies coded to CDISC data exchange standards may follow different IG versions and control terminology releases in addition to representing data according to study specific trial-designs.
This paper covers:
- Distinguishing “Exchange” standards for publishing data between organizations from “Repository” standards for ingesting and holding data in an invariant form for search, cross-study selection of cohorts or samples based on data across domains.
- Techniques, tools, and facilities in the Smart Transformation module of PointCross’ Xbiom solutions platform for converting data from one standard to another quickly, efficiently, and with automation.
- Transforming data dynamically on-demand from sources to any business purpose dictated target model for streamlined dataflow.