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German biopharma client

Data Model & Ontology

FAIR-ready data blueprint

Background

A contrast-media research department aiming to accelerate the transition from early research to early development, but with data scattered across spreadsheets, formats, and workflows, and no shared view of what exists, where it sits, or how it flows.

Solution

A solution-agnostic initiative to define a contrast-media-focused data model and agreed ontology: a shared end-to-end view of what data exists, how it flows across research units, and how it should be structured to be FAIR, consistent, and reusable.

Results

Shared clarity on what data exists, where it sits, and how it flows across the research workflow. Aligned definitions and KPI readiness for more reliable decisions. Clearer ownership, gaps surfaced early, and a scalable, future-proof blueprint for AI- and ML-ready data capture.

inite's role

inite led the as-is analysis of spreadsheets, formats, and workflows, identified gaps and inconsistencies, designed the to-be conceptual data model and end-to-end data-flow framework, and facilitated alignment workshops on key entities, definitions, and ontology.

“The data model and ontology gave us a shared language and a clear end-to-end view of how information flows across our research. It created a solid, FAIR-ready foundation we can now use to standardise capture, improve consistency, and enable future digitalisation and advanced analytics.”

Head of Contrast Media Research · Global Pharma Company