Gencovery

How we work with you

01 — Diagnostic Maturity audit, arbitration and roadmap. 02 — Digitalisation Implementation, tool and process integration. 03 — Data analysis Value creation, applied AI, digital twins. 04 — Training Change management, practices and tools.

Where to start

Overview The four strands and how they follow on Our method How our engagements run, end to end Our engagements What we did with Institut Imagine, Conidia-Coniphy and Greencell Discuss an engagement Describe your situation, we reply within two working days

Platform

Platform architecture A decentralised architecture to connect data end-to-end End-to-end lab automation From raw data to clinical value, uninterrupted Constellab vs competitors The only platform that digitises life sciences with full data sovereignty

Features & benefits

Features Collaborative space, analytics, visualisation and AI Benefits Why choose Constellab — traceability, sovereignty, compliance ROI & Savings Calculate your savings by consolidating your tools Integrations Supported tools, protocols and connectors

Use cases

Patient data management Centralise and leverage medical data with AI R&D acceleration Cut your research cycles with AI Bioprocess optimisation Monitor your fermentation processes in real time Agronomy optimisation Antifungal resistance: data and AI united All use cases Browse our full solutions catalogue

Constellab Applications

Constellab Care AI-powered medical and patient data management Constellab Suite Scientific productivity: Project, Analytics, Search Constellab Digital Twin Digital twins to optimise your bioprocesses See all applications Explore the Constellab™ application ecosystem

Documentation

DLM White paper Our Digital Leadership Mastery method for data-driven strategy Regulatory compliance GxP, GDPR, HDS and quality framework navigator Interoperability standards FHIR, CDISC, DICOM, HL7, OMOP CDM and reference terminologies

Community & Events

Constellab Community The open-source Constellab user community Blog Articles, awards, events and publications
Our history and mission Why Gencovery exists and what drives us The team The people behind the project
Engagement pricing Consulting and support — on quotation Platform pricing Constellab™ subscription: plans and data labs
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Service

How we work with you

  • 01 — Diagnostic
  • 02 — Digitalisation
  • 03 — Data analysis
  • 04 — Training

Where to start

  • Overview
  • Our method
  • Our engagements
  • Discuss an engagement
Product

Platform

  • Platform architecture
  • End-to-end lab automation
  • Constellab vs competitors

Features & benefits

  • Features
  • Benefits
  • ROI & Savings
  • Integrations
Solutions

Use cases

  • Patient data management
  • R&D acceleration
  • Bioprocess optimisation
  • Agronomy optimisation
  • All use cases

Constellab Applications

  • Constellab Care
  • Constellab Suite
  • Constellab Digital Twin
  • See all applications
Resources

Documentation

  • DLM White paper
  • Regulatory compliance
  • Interoperability standards

Community & Events

  • Constellab Community
  • Blog
About
  • Our history and mission
  • The team
Pricing
  • Engagement pricing
  • Platform pricing
Blog
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FR
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Technical standards

Interoperability Standards

Technical formats, models and terminologies enabling data exchange and reuse across the biotech, pharma and health ecosystem. Complementary to compliance frameworks — often referenced or mandated by them.

9 Standards
5 Types
12 Regulatory links

Standards vs regulatory frameworks

Interoperability standards define the HOW (format, syntax, semantics). Regulatory frameworks define the WHAT and WHY (legal obligations, governance, audit). A single project may be subject to GDPR (framework) while implementing FHIR R4 (standard) to exchange patient data.

Interoperability: the prerequisite for AI in health and life sciences

Artificial intelligence is transforming biomedical research — but its promises can only materialise if data is accessible, structured and comparable. Yet in life sciences and health, data is scattered across dozens of systems with incompatible formats: EHRs, LIMS, ELNs, genomic platforms, imaging devices.

Without interoperability, every AI model is trained in a silo. With open standards (FHIR for clinical data, CDISC for trials, OMOP CDM for real-world data), data can flow, be compared and feed robust AI models — in compliance with regulatory requirements.

FHIRCDISCOMOP CDMHL7DICOM

Constellab implements these standards natively

The Constellab platform natively supports FHIR R4/R5, CDISC ODM/CDASH/SDTM, OMOP CDM, DICOM and HL7 v2/v3. Data can enter from any source format and be exported in the standard required by each partner or regulatory authority — without manual re-conversion.

FHIR R4/R5CDISC ODM/SDTMOMOP CDMHL7 v2/v3DICOM

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Showing 9 of 9 standards

Standard Type Domain Active version Regulatory link Description Organisation
Gencovery

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