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Bio Base Europe Pilot Plant

Bringing online sensing to industrial-scale bioprocess scale-up

Industry
Pilot-scale bioprocess development and contract manufacturing
Headquarters
Ghent, Belgium
Public information as of
February 2026

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

Strategic priorities

Bio Base Europe Pilot Plant (BBEPP) is an independent, non-profit pilot facility in the Port of Ghent, Belgium, founded in 2008. It runs more than 900 projects for over 270 clients and manages over EUR 80 million in process infrastructure. Following the November 2023 commissioning of a 75,000-litre demonstration fermenter as part of a EUR 34 million Fermentation Park programme, the facility has tripled its fermentation capacity and is now focused on the digital layer that lets that capacity run as one connected operation.

Leadership frames the next step as a move to Industrial Biotechnology 4.0. The Bio Base NEXTGEN programme explicitly equipped the eight 30-litre fermenters with advanced sensors for online measurements, and the Head of Business Operations has described the transition as bridging the gap from manual offline monitoring to real-time process intelligence. The change sits on top of an existing EUR 45 million Bio Base FLOW investment in large-scale downstream processing and the EUR 28.3 million programme that brought the 75,000-litre vessel online.

The work takes place against a backdrop of 30 ongoing EU-funded consortium projects (including CBE-JU and Horizon Europe programmes such as WASTE2FUNC and LUCRA), hundreds of bilateral client runs each year, and a permanent workforce of more than 180 specialists. BBEPP runs food-grade, cosmetic and biopharmaceutical campaigns that must satisfy FSSC 22000, GAMP5, and FDA/EMA dossier expectations, and clients routinely take BBEPP run data into their own regulatory submissions.

Scaling at this facility is a public story: as the CEO has put it, the first kilogram of a new product can cost a million euros, and the oxygen mass transfer (kLa) and heat dissipation dynamics of a 75,000-litre tank are not the same as those of a 1-litre flask. The implication is that the data path from each NextGen 30-litre run to a future 75,000-litre decision is itself part of the deliverable, and the facility's stated Industrial Biotech 4.0 agenda is the route to making that path measurable.

Challenges we see

  • Digital Manufacturing

    Reading bioprocess signals online rather than days later

    Leadership has stated that, unlike other manufacturing sectors, industrial biotechnology still measures crucial process parameters offline, with insights often only available days after experiments through Excel reports. The Bio Base NEXTGEN investment explicitly addressed this by equipping the eight 30-litre fermenters with advanced online sensors.

    Where biological KPIs arrive in a spreadsheet days after a sampling run, the population the team can act on is small and retrospective. Streaming the same parameters as data alongside the running batch widens the loop to every unit currently in production.

  • Operations Integration

    Unifying data across pretreatment, fermentation and downstream

    BBEPP manages over 30 ongoing consortium projects and hundreds of bilateral client runs across four process halls. Data from biomass pretreatment, fermentation and downstream processing currently lives in separate systems without an integrated platform.

    When each process hall keeps its own data estate, the question a client actually asks, what the full chain from feedstock to purified product cost, has to be rebuilt for every project. A shared model turns that question into a query rather than a manual reconciliation.

  • Digital Integration

    Bridging NextGen and legacy equipment into one digital spine

    The facility runs new NextGen fermenters equipped with state-of-the-art sensors alongside air-gapped legacy equipment from multiple vendors (centrifuges from GEA, bioreactors from various suppliers, milling equipment), creating a classic IT/OT gap between shop-floor operations and enterprise systems.

    Where new and legacy equipment speak different protocols, the practical result is that the plant's data path grows one-off for each addition. A common protocol and module specification, agreed before procurement, lets every new machine join the same data path on arrival.

  • Operations Energy

    Optimising utilities and wastewater at pilot scale

    BBEPP currently produces significant wastewater volumes, sometimes five to ten truckloads per day for external processing, and manages 565 solar panels alongside steam, air and cooling systems. An on-site treatment plant is planned but not yet operational.

    Trucking water off-site is a lagging indicator rather than a managed utility. Online measurement at each hall's effluent, and energy flows from the solar array into the same model, turns the utility stream into a dataset that can be optimised while the run is live.

  • Operations Manufacturing

    Replacing best-guess scale-up runs with simulation-based transfer

    Scaling from a 1-litre flask to a 75,000-litre fermenter is non-linear: kLa and heat dissipation dynamics differ at every order of magnitude. The CEO has publicly stated that the first kilogram of a new product can cost a million euros.

    When scale-up depends on physical best-guess runs, every change at pilot scale repeats as a new campaign. A model that links 30-litre NextGen runs to the 75,000-litre dynamics lets each pilot run inform the next, and reduces the number of campaigns a new process actually needs.

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. Streaming biological KPIs from NextGen fermenters into one model

    Critical biological KPIs such as VCD, VVD and CSPR are tracked in Excel separate from live process trends, with insights often only available days after experiments via offline reports. The NextGen sensors are in place, but the data layer above them is not.

    A real-time process intelligence layer that captures sensor data, calculates biological KPIs automatically and overlays the running batch against a historical Golden Batch profile turns each NextGen run into a continuous comparison rather than a post-mortem.

    • BBEPP press release, Following recent tripling of fermentation capacity, 27 November 2023
    • Bio Base NEXTGEN project page, bbeu.org

  2. Putting pretreatment, fermentation and downstream data on one ontology

    Data is held in physical logbooks, local instrument memory and separate hall-level systems, with no unified view across pretreatment, fermentation and downstream processing. Clients receive data that has to be reconciled by hand per project.

    An ontology-based data platform that defines batch, lot, process step, sample and result as shared entities, and loads each hall's source data against the same model, gives every project one queryable history and one source of truth.

    • BBEPP, Who We Are page, bbeu.org
    • Head of Business Operations interview, Planet B.io, 2025

  3. Linking new fermenters and legacy equipment through one protocol

    The eight NextGen fermenters arrive with state-of-the-art sensors, while centrifuges, milling equipment and older bioreactors from multiple vendors operate on closed or air-gapped protocols. The result is a growing set of one-off integrations per hall.

    An MTP- and OPC UA-based digital spine with documented equipment data contracts lets new NextGen equipment and legacy assets publish to the same model, so each new integration reuses what is already in place.

    • BBEPP, Bio Base NEXTGEN project page
    • Secomea, The IT-OT Convergence: benefits, challenges, strategic initiatives

  4. Measuring utility flows online for water and energy optimisation

    Wastewater is currently removed by truck, and 565 solar panels run alongside steam, air and cooling systems without integration. An on-site treatment plant is planned, but the data layer to operate it is not yet in place.

    Online flow, conductivity and temperature sensors in each hall's effluent, combined with energy metering across the boiler house, cooling plant and solar array, produce the dataset the future treatment plant and the EU sustainability reporting can both use.

    • BBEPP press release, Following recent tripling of fermentation capacity, 27 November 2023
    • Bio Base Advance project page, bbeu.org

  5. Producing validated digital data packages for client regulatory dossiers

    FSSC 22000 and GAMP5 compliance for food-grade and biopharmaceutical runs requires rigorous batch records and equipment sterilisation evidence. Clients use BBEPP run data in their own FDA and EMA submissions, so data packages are themselves a deliverable.

    A digital batch record system with LIMS integration, ALCOA+ data integrity principles and audit-ready reporting turns the run data into a validated package that travels directly into a client's dossier.

    • BBEPP, Who We Are page, bbeu.org
    • CEO interview, Catalisti, 2023

What we'd propose

  • Digital Lab

    Real-time bioprocess intelligence for NextGen fermenters

    We instrument the eight NextGen fermenters and the surrounding analytical sensors, stream their values into one time-series model, and run KPI calculation and Golden Batch comparison against the batch that is currently running, so biological signals arrive with the run rather than after it.

    • Sensor data acquisition

      Getting data off the fermenters

      Connect controllers, online sensors and the analytical lab through OPC UA (Open Platform Communications Unified Architecture) and MQTT so process values leave each fermenter as documented, vendor-neutral data instead of staying inside a closed controller.

    • Live KPI calculation

      Biological metrics as they run

      Automate the calculation of biological KPIs such as VCD (viable cell density), VVD (volumetric oxygen demand) and CSPR (cell-specific perfusion rate) from the live sensor stream, replacing the current Excel compilation with values that update through the run.

    • Golden Batch overlay

      Comparison against the best prior run

      Overlay the current batch against the best-matching historical profile at each time point, flag deviation against a documented envelope, and present the comparison in a P&ID-aligned view so engineers and operators see the same picture.

    • Biological KPIs are read during the run, not days after the sampling visit.
    • Operators and engineers see the same deviation against the same Golden Batch profile.
    • Each NextGen run leaves behind a comparable dataset that informs the next scale-up.

    We've done this before

    See how we do Digital Lab
  • Enterprise AI

    Ontology-based industrial data platform across process halls

    An ontology-based data platform that defines batch, lot, process step, sample and result as shared entities once, then loads pretreatment, fermentation and downstream data from each hall against the same model, so one query returns the full chain.

    • Shared bioprocess ontology

      One agreed set of entities

      Define batch, lot, process step, sample, result, instrument and operator as explicit entities with documented relationships, so a query written once returns comparable answers across pretreatment, fermentation and downstream instead of three dialects of the same table.

    • Hall-level pipelines

      Loading each process hall

      Build ingestion for biomass pretreatment, the NextGen and 1,500-litre fermenters, the 75,000-litre demonstration fermenter and downstream processing, with schema validation at each boundary so bad records fail loudly rather than silently.

    • Client-facing data products

      Run history on demand

      Expose the platform through dashboards and a retrieval layer so client project teams can see their own run history, the LCA (Life Cycle Analysis) and TEA (Techno-Economic Analysis) inputs it feeds, and the validated package that goes into their regulatory dossier.

    • One query covers the full chain from feedstock to purified product.
    • LCA and TEA reporting pulls from the same model that produced the run.
    • Validated digital data packages are produced automatically, not compiled by hand.

    We've done this before

    See how we do Enterprise AI
  • Digital CDMO

    MTP and OPC UA spine across NextGen and legacy equipment

    An MTP (Module Type Package) and OPC UA-based digital spine with documented equipment data contracts, so new NextGen equipment and legacy assets from multiple vendors publish to the same data path without bespoke integration each time.

    • MTP module library

      Plug-and-produce process modules

      Build an MTP-compliant module library for the NextGen fermenters and for representative legacy unit operations, so each new process module integrates into the orchestration system through a documented interface rather than a custom one.

    • OPC UA backbone

      One protocol across the plant

      Implement OPC UA as the secure communication backbone between shop-floor equipment and the enterprise IT layer, so process data and equipment status leave the plant in a documented form rather than via screen scraping or file exports.

    • Legacy equipment bridge

      Older equipment on the same path

      Add a documented bridge for air-gapped legacy assets so their data reaches the same model without exposing them to the open network, preserving vendor independence while closing the IT/OT gap that currently fragments reporting.

    • Each new integration reuses what is already in place.
    • Vendor lock-in is replaced by an open, documented interface.
    • Engineering cost for reconfiguration follows physical changes, not a separate project.

    We've done this before

    See how we do Digital CDMO
  • Digital CDMO

    Predictive maintenance for the 75,000-litre demonstration fermenter

    An IoT-based condition monitoring and predictive maintenance layer for the 75,000-litre demonstration fermenter and the 1,500-litre lines, using vibration, temperature gradient and motor load data to flag mechanical drift ahead of failure.

    • Vibration and motor load monitoring

      Mechanical health, continuously

      Fit vibration sensors and motor load monitoring on the agitator, gearbox and bearing assemblies of the 75,000-litre vessel and the 1,500-litre lines, so mechanical health is read continuously rather than inferred from a maintenance schedule.

    • Drift and anomaly detection

      Alerts before the run is at risk

      Build the normal operating envelope from historical run data, flag drift against that envelope while a batch is still progressing, and route alerts to the operations team with a documented rationale.

    • Maintenance planning interface

      From time-based to condition-based

      Present the maintenance team with a condition-based schedule for the critical fermentation assets, so a planned intervention is triggered by the equipment rather than by the calendar.

    • Multi-week fermentation runs are protected from mid-batch mechanical failure.
    • Maintenance is triggered by equipment condition, not by the calendar.
    • The same data layer can support a future Digital Twin of the 75,000-litre dynamics.

    We've done this before

    See how we do Digital CDMO
  • Digital Lab

    Validated digital data packages for client regulatory dossiers

    A digital batch record and LIMS integration layer that captures FSSC 22000 and GAMP5 evidence at the instrument, applies ALCOA+ data integrity principles, and produces the validated data package that travels into a client's FDA or EMA submission.

    • Instrument-to-batch-record data flow

      Evidence captured at source

      Connect balances, HPLC (High-Performance Liquid Chromatography), GC (Gas Chromatography) and the bioreactor sensors so results are captured with instrument identity, method version and timestamp, and written into the batch record as data with their own audit trail.

    • ALCOA+ integrity layer

      Attributable, legible, contemporaneous, original, accurate

      Apply ALCOA+ data integrity principles (Attributable, Legible, Contemporaneous, Original, Accurate, plus Complete, Consistent, Enduring and Available) across the batch record, so the evidence chain stands on its own during an FSSC 22000 or GAMP5 audit.

    • Client dossier package

      Validated package per project

      Generate a validated digital data package per client project, with the data lineage, methodology and integrity evidence the client's regulatory team needs for an FDA or EMA submission, instead of a reconstructed set of spreadsheets.

    • Audit questions are answered from the record itself, not from a reconstruction.
    • Validated data packages reach clients in days rather than weeks.
    • The same integrity layer underpins BBEPP's own FSSC 22000 and GAMP5 evidence base.

    We've done this before

    See how we do Digital Lab

Where QB Systems fits

Alongside our services we build QB Systems, hardware and software for bioprocess control. QB Systems is a product brand of A4BEE Sp. z o.o.

Scale
Pilot (50–300 L)

Stainless steel, where QB supplies the control software and integration and a certified partner builds the installation.

Digital maturity: today and target

Scored out of 100 across six dimensions. The target is what Bio Base Europe Pilot Plant's own published ambition implies — not a perfect score.

Source: A4BEE analysis of public sources
Real-time process monitoring 30 → 85
BBEPP has equipped its eight NextGen 30-litre fermenters with advanced online sensors under the Bio Base NEXTGEN programme, but the data layer above the sensors is not yet integrated. The shift from offline Excel reporting to streaming KPI calculation is the current gap.
Data integration 25 → 80
Pretreatment, fermentation and downstream processing each keep their own data estate, and 30 consortium projects plus hundreds of bilateral runs each add their own reporting view. An ontology-based platform is the explicit industry direction.
IT/OT convergence 35 → 85
New NextGen fermenters arrive with modern sensors while legacy assets from multiple vendors run on closed or air-gapped protocols. MTP and OPC UA are the documented route to closing this gap.
Predictive analytics 20 → 75
Public statements describe a reliance on best-guess scale-up runs and note that the first kilogram of a new product can cost a million euros. Digital Twin and predictive maintenance capabilities are the named next step.
Compliance automation 40 → 90
FSSC 22000 and GAMP5 compliance currently relies on paper or manual records, and clients use BBEPP runs in their own FDA or EMA dossiers. A digital batch record with ALCOA+ integrity is the route to validated client packages.
Utility optimisation 30 → 80
Wastewater is currently removed by truck and 565 solar panels run alongside steam, air and cooling without integration. An on-site treatment plant is planned but the data layer to operate it is not yet in place.

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This is an independent analysis prepared by A4BEE from publicly available information as of February 2026. It reflects A4BEE's own interpretation and opinion, is not affiliated with, endorsed by, or verified with Bio Base Europe Pilot Plant, 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].