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Eurogentec

Digital lab, digital twin, and modular manufacturing for mRNA scale-up

Industry
mRNA and pDNA CDMO
Headquarters
Seraing, Belgium
Public information as of
January 2026

A4BEE prepared this analysis from publicly available sources. It reflects our own reading of Eurogentec's published strategy and is not endorsed by, or produced in cooperation with, Eurogentec. Company website

Strategic priorities

Eurogentec is a Belgian biotech CDMO and subsidiary of Kaneka Corporation, specialising in mRNA and plasmid DNA (pDNA) manufacturing at GMP scale. The company is executing a 5x expansion in mRNA GMP production capability targeting June 2025 completion, alongside a 1kg pDNA batch milestone achieved in July 2024. The Seraing facility operates more than 10,000 m2 of GMP cleanroom space with fermentation suites from 80L to 2200L, using E. coli, P. pastoris, and S. cerevisiae host systems. As a Kaneka group company, Eurogentec benefits from a ¥15 billion DX investment allocation across FY2023-2025, with the therapeutic manufacturing unit operating as a 'gene to injectable' CDMO serving global biopharma clients.

The immediate digital priority is connecting that expanded capacity. The transition from research-grade to 2200L GMP mRNA production has unpredictable process outcomes at scale — high-viscosity fermentation creates oxygen transfer limitations that are difficult to characterise without a digital model. Multiple vendors across the mRNA supply chain (pDNA, IVT, purification, LNP encapsulation) create data gaps between process stages that slow technology transfer and complicate regulatory filings.

The facility expansion is the moment to establish the digital backbone. The PTD (Process Transfer and Development) lab was revamped in January 2023 and the 100% Digital Lab programme is underway. The mRNA expansion completing in mid-2025 is the integration window — equipment selected now will run for a decade, and the data architecture chosen now determines whether that equipment can be read from enterprise systems later.

Challenges we see

  • Operations Manufacturing

    Predicting bioprocess outcomes before scaling to 2200L

    The transition from research-grade to 2200L GMP production of pDNA and mRNA involves unpredictable process outcomes at scale, requiring extensive wet-lab iterations that delay time-to-market for therapeutic clients.

    Where process behaviour at production scale has to be characterised by running batches, the cost of each iteration includes the materials, time, and downstream disruption of a failed run. Digital Twin simulation allows that characterisation to happen virtually before a physical run is committed.

  • Digital Integration

    Connecting data across the mRNA production stages

    Using multiple vendors for mRNA production (pDNA, IVT, purification, LNP encapsulation) creates a relay-race dynamic with significant delays and data gaps between process stages.

    Where each production stage is run by a different organisation with its own data system, the records that describe what happened in each stage arrive in different formats at different times. A continuous digital thread across stages means the complete process record is assembled as the batch moves rather than assembled from fragments after it.

  • Digital Operations

    Integrating legacy equipment with modern MES and ERP systems

    Legacy equipment interfaces (RS-232, proprietary protocols) are not integrated with modern MES/ERP systems, creating data islands across the 10,000 m2 production area. Multiple microbial host systems (E. coli, P. pastoris, S. cerevisiae) require different software for each.

    Where equipment generations differ in their connectivity, the data they produce is held in different systems that do not speak to each other. Consistent data capture across host systems requires a common data layer that reads each equipment generation on its own terms.

  • Compliance Regulatory

    Maintaining audit-ready data integrity in GMP areas

    As an FDA/EMA-inspected CDMO, Eurogentec faces heightened scrutiny on data integrity practices, with manual data entry and paper-based processes in GMP areas increasing audit risk.

    Where data is written on paper and transcribed into electronic systems, each transcription step introduces a potential discrepancy between what happened and what the record says. Electronic capture at source, with its own audit trail, makes the record speak for itself during an inspection.

  • Digital Operations

    Securing cloud-based BLA submissions against OT network threats

    Increasing cloud-based submissions for Biologics License Applications expand the attack surface for sensitive therapeutic data and intellectual property, including proprietary mRNA sequences and manufacturing protocols.

    Where manufacturing data leaves the OT environment for cloud-based regulatory submissions, the security boundary expands beyond the physical facility. Zero-trust access architecture means that every data movement is verified rather than assumed safe on arrival.

Opportunities, by urgency and business impact

Each bubble is one opportunity, numbered to match the list below. Further right means it bites sooner; higher means a bigger effect on the business. A bigger bubble means a bigger implementation effort.

Source: A4BEE analysis of public sources

  1. Connecting lab equipment to eliminate manual data curation

    Scientists spend excessive time on manual data processing, tracking, and traceability across fragmented systems in the Research Products and Diagnostic Services business units, reducing time available for actual scientific work.

    Implement a unified Data Gateway to integrate lab equipment (bioreactors, chromatography, scales) and automate data collection, potentially reducing manual data curation time by up to 65%.

    • Eurogentec Deep Research Analysis, 2025

  2. Using Digital Twin simulation to predict 2200L fermentation outcomes

    The 2200L fermentation facility experiences unpredictable outcomes when scaling from research-grade production, leading to costly batch failures and extended development cycles for therapeutic clients.

    Deploy Digital Twin simulations to predict process outcomes at scale, enabling virtual optimisation of high-viscosity fermentation parameters before committing to expensive wet-lab iterations.

    • Eurogentec Deep Research Analysis, 2025

  3. Applying MTP standards for modular production-line configuration

    Long setup times and inflexible automation architectures prevent rapid reconfiguration between different client projects in the multi-product GMP facility.

    Implement MTP (Module Type Package) standards to enable Plug-and-Produce modularity, allowing 2200L facility transitions between recipes with minimal downtime and reduced engineering costs.

    • Eurogentec Friction Matrix analysis, 2025

  4. Monitoring ultra-cold chain with secure IoT gateways

    mRNA is inherently unstable and requires strict temperature control throughout production, storage, and logistics, with current monitoring systems lacking real-time alerting capabilities.

    Deploy secure IoT gateways to monitor ultra-cold chain storage and logistics with automated alarm management, ensuring product integrity from synthesis to delivery.

    • Eurogentec Deep Research Analysis, 2025

  5. Building sustainability measurement infrastructure for Kaneka's GHG target

    Kaneka's goal to reduce GHG by 30% by 2030 puts pressure on Eurogentec's high-energy bioprocesses, but current systems lack visibility into energy consumption patterns across fermentation and cooling systems.

    Apply ML models to optimise energy consumption of large-scale fermentation and cooling systems, providing automated reporting aligned with Kaneka's sustainability targets.

    • Kaneka Integrated Report 2024
    • Eurogentec Deep Research Analysis, 2025

What we'd propose

  • Digital Lab

    Unified lab data platform for the Seraing facility

    We deploy an integrated data acquisition platform that connects all laboratory equipment across the Seraing site, eliminating manual data curation and creating a single source of truth from instrument to enterprise system.

    • Data gateway integration

      Connecting 30+ device types to a central platform

      Connect bioreactors, chromatography systems, balances, and plate readers through a vendor-agnostic data gateway so that results are captured with instrument identity, method version, and timestamp, replacing manual transcription with a traceable digital chain.

    • Automated data pipeline

      Data flowing from instrument to platform without manual steps

      Build automated pipelines from the data gateway to Eurogentec's LIMS, MES, or ERP so that data enters downstream systems automatically, with completeness checks at each transfer point.

    • Unified scientific dashboard

      One view of all lab operations

      Deliver a consolidated dashboard giving scientists a real-time view of running experiments, completed batches, and instrument status across the Research Products, Diagnostic Services, and Therapeutic Manufacturing units.

    • Scientists spend time on science rather than on transcription and data chasing.
    • A complete data record is assembled automatically rather than reconstructed from fragments.
    • Audit questions are answered from the platform rather than from individual instrument exports.

    We've done this before

    See how we do Digital Lab
  • Digital CDMO

    Digital Twin for 2200L mRNA and pDNA fermentation scale-up

    We implement a bioprocess simulation platform that models the 2200L fermentation environment, enabling virtual optimisation of high-viscosity pDNA and mRNA production parameters before physical execution.

    • Fermentation scale-up model

      Simulating oxygen transfer and shear stress at production scale

      Build a computational fluid dynamics model of the 2200L bioreactor that predicts oxygen transfer rates, mixing behaviour, and shear stress on cells at operating scale, calibrated against Eurogentec's existing scale-down data.

    • Virtual parameter optimisation

      Finding operating windows without physical iterations

      Use the Digital Twin to run virtual experiments across operating parameter ranges, identifying the optimal window for viscosity, temperature, and pH before a physical run is committed.

    • Batch history comparison

      Current run overlaid against historical best runs

      Integrate the Digital Twin with Eurogentec's batch records so that the current run's parameters can be compared in real-time against historical high-yield batches, flagging drift before it becomes an excursion.

    • Physical iterations are reduced by running virtual experiments first.
    • The optimal operating window is known before the batch starts, not after it fails.
    • Batch history comparison surfaces drift early enough to correct during the run.

    We've done this before

    See how we do Digital CDMO
  • Digital Lab

    MTP-based modular manufacturing platform for the multi-product GMP facility

    We architect and deploy a Module Type Package (MTP) compliant software infrastructure that enables rapid reconfiguration of GMP production lines for different client projects with minimal downtime.

    • MTP-compliant equipment registration

      Equipment modules described in a standard format

      Register Eurogentec's fermentation skids, chromatography systems, and LNP encapsulation equipment in MTP format so that each module declares its process parameters, operating range, and dependencies in a standard, machine-readable form.

    • Plug-and-produce orchestration

      Recipe changes executed with minimal setup time

      Implement the orchestration layer that reads MTP declarations from registered equipment and automatically configures the process recipe when a production run switches between E. coli pDNA and P. pastoris protein campaigns.

    • Engineering cost reduction framework

      Minor changes without major engineering involvement

      Show how MTP standards reduce the engineering cost of minor recipe changes by making each equipment module self-describing, so that the change is propagated automatically rather than coded by hand.

    • Campaign changeover time is reduced because the equipment configures itself from the recipe.
    • Engineering effort for minor recipe changes drops to near-zero once modules are registered.
    • New equipment added to the facility can be registered in MTP format without custom integration work.

    We've done this before

    See how we do Digital Lab
  • Enterprise AI

    IoT-enabled cold chain monitoring for mRNA stability

    We deploy a secure IoT infrastructure for comprehensive monitoring of mRNA temperature-sensitive processes across production, storage, and logistics, with real-time alerting and compliance documentation.

    • Ultra-cold sensor deployment

      Temperature monitoring from synthesis to delivery

      Deploy IoT temperature sensors across Eurogentec's production suites, cold storage, and logistics chain with sub-minute polling intervals, so that any excursion outside the required range triggers an immediate alert.

    • Automated alarm management

      Alerts routed to the right person within seconds

      Build an alarm management system that categorises alerts by severity, routes them to the responsible operator or quality team, and documents the response in the batch record, so that excursions are both caught and recorded automatically.

    • Cold chain compliance documentation

      Temperature history attached to each batch

      Generate a temperature exposure report for each batch that documents the full cold chain from synthesis to delivery, so that product integrity claims are supported by continuous measurement rather than by spot checks.

    • Product integrity is continuously verified rather than evidenced by a spot check at dispatch.
    • Temperature excursions are caught and contained within minutes rather than discovered at the next inspection.
    • Cold chain documentation is produced automatically rather than assembled from carrier records.

    We've done this before

    See how we do Enterprise AI
  • Digital CDMO

    AI-driven energy optimisation for the 2200L fermentation facility

    We implement an AI-driven energy and resource optimisation platform that monitors, analyses, and recommends efficiency improvements for Eurogentec's high-intensity bioprocessing operations while automating sustainability reporting to Kaneka's 30% GHG reduction target.

    • Fermentation energy monitoring

      Energy consumption visible at batch level

      Deploy metering on the 2200L fermentation skids and connected cooling systems so that energy consumption is tracked per batch, giving Eurogentec the resolution to identify which process conditions drive higher energy use.

    • ML-driven efficiency recommendations

      Operating conditions tuned by the model

      Train machine learning models on historical fermentation data to identify operating conditions that reduce energy per gram of product without affecting yield or quality, so the model continuously recommends better operating setpoints.

    • Automated sustainability reporting

      CSRD-compliant disclosures produced by the platform

      Build automated reporting that computes Scope 1 and 2 emissions from metered energy data and generates CSRD-compliant sustainability disclosures, so that Eurogentec's reporting to Kaneka is produced by measurement rather than estimated from activity data.

    • Energy per gram of product becomes a tracked KPI with targets and trends.
    • The ML model continuously improves operating conditions without manual analysis.
    • Sustainability reporting is produced from metering rather than assembled from estimates.

    We've done this before

    See how we do Digital CDMO

Digital maturity: today and target

Scored out of 100 across six dimensions. The target is what Eurogentec's own published ambition implies — not a perfect score.

Source: A4BEE analysis of public sources
Data Integration 35 → 85
Multiple vendors across the mRNA production chain and legacy equipment with RS-232 and proprietary protocols create data islands that prevent a continuous digital record from forming without deliberate integration work.
Process Automation 45 → 90
The 100% Digital Lab programme is underway following the PTD lab revamp in January 2023. The mRNA expansion completing in mid-2025 is the integration window before the new capacity is locked into its initial configuration.
Predictive Analytics 25 → 80
Scale-up from research to 2200L GMP production currently relies on wet-lab iterations to characterise process behaviour. Digital Twin simulation would allow that characterisation to happen virtually before a physical run is committed.
Modularity 40 → 85
Multi-product GMP suites running E. coli, P. pastoris, and S. cerevisiae require flexible reconfiguration between campaigns. MTP standards would make each equipment module self-describing and enable Plug-and-Produce orchestration.
Cybersecurity 50 → 90
Cloud-based BLA submissions and the Kaneka DX investment expanding cloud connectivity increase the attack surface for proprietary mRNA sequences and manufacturing protocols, requiring zero-trust architecture rather than perimeter-based security.
Sustainability Tech 30 → 75
Kaneka's 30% GHG reduction target by 2030 requires per-batch energy measurement and automated reporting. The 2200L fermentation skids are high-intensity consumers where the most impact is available.

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This is an independent analysis prepared by A4BEE from publicly available information as of January 2026. It reflects A4BEE's own interpretation and opinion, is not affiliated with, endorsed by, or verified with Eurogentec, and may be incomplete or inaccurate. All company names and trademarks are the property of their respective owners. To request a correction or removal, contact [email protected].