IBISBA will team up with ESFRI-landmark RIs such as ELIXIR, Mirri, BBMRI and DSMZ, innovative companies and several research groups in an ambitious 4-year work plan to encourage the adoption of advanced digital technologies in industrial biotechnology. These include innovative measurement devices for online monitoring, data management tools for data quality, open science, and AI learning to support bioprocess design.

BIOINDUSTRY 4.0 will engage with a diverse community of stakeholders, especially industry, to co-design specific services to be well-aligned with stakeholder needs and thus be fit for use by RI users. In addition, BIOINDUSTRY 4.0 will train RI staff to deploy new services and ensure that users are well-acquainted with the opportunities offered by the project’s key developments.

The project BIOINDUSTRY 4.0 is encouraging the adoption of advanced digital technologies in industrial biotechnology. These include innovative measurement devices for online monitoring, data management tools for data quality, open science, and Artificial Intelligence learning to support bioprocess design.

The project is led by IBISBA and INRAE, and MIRRI is represented in the consortium by its partner organisations CECT-UV (Spain) and WI-KNAW (Netherlands)

This project is funded by HORIZON-INFRA-2022-TECH-01 101094287.


Industrial Biotechnology (IB) is a Key Enabling Technology for the circular bio-economy, industrial renewal and European manufacturing autonomy. Its development forms a vital part of EU’s strategy to become climate neutral in 2050. For IB to become a major manufacturing technology, it must widen its use of advanced digital technologies. These will improve R&D efficiency, reducing time-to-market and costs. Moreover, for manufacturing, advanced digital technologies will drive distributed, autonomous and highly adaptable production systems. To support digitalization of IB, BIOINDUSTRY 4.0 will create new services delivered by European research infrastructures (RI). These services will address several challenges, focusing on the acceleration of bio-process development pipelines. Drawing on the complementary skills of its consortium, BIOINDUSTRY 4.0 will develop data-driven approaches, exploiting

AI to empower novel decision support systems and digital twins, the latter being to better design bio-processes and enable their real- time online control. To complete these services, BIOINDUSTRY 4.0 will also develop data and metadata standards to generate high quality, interoperable multi-scale bio-process data, the technical basis for trusted data networks and process analytical devices to provide real-time online monitoring of bio-processes.

Once deployed, these RI services will provide Users with access to cutting-edge technologies that can be used singly or in an integrated way, covering whole R&D pipelines. Integrated services will be delivered by a distributed RI, conferring Europe with a unique R&D test-bed for bio-process development and a competitive advantage with respect to global competition.

To succeed, BIOINDUSTRY 4.0 brings together 6 EU RIs, 1 global company, 2 innovative EU SMEs and several research teams around an ambitious 4-year workplan that will be implemented in consultation with IB stakeholders, using a co-design strategy to specify goals.

eScienceLab contributions

UK partners in Horizon Europe projects are funded through Innovate UK (#10048146?) from the UKRI Horizon Europe guarantee.

eScienceLab will contribute in WP7 to the maintenance and development of the IBISBAHub and a distributed computing environment using FAIR Digital Objects and computational workflows including CWL.

  • WP7: Tools for high-quality datasets, requisite for data-driven methods and services (lead: WU)
    • Objectives:
      • Empower federated data sharing and reuse of data services and datasets
      • Create virtual environment for DT computational processes
      • Provide the technology to enable federated TDNs
      • Establish educational material to enable the use of the provided resources
    • Task 7.1 A Data and Metadata Fabric to support DTs (lead: WU)
    • Task 7.2 A modular, and scalable compute environment for AI-powered DTs (lead: ARC)
    • Deliverable D7.1 The BIOINDUSTRY 4.0 Data Management Plan (M6)
    • Deliverable D7.2 Demonstrated compute, data and metadata infrastructure supporting DTs (M48)