Bioindustry4.0 Work Package 7: Tools for high-quality datasets, requisite for data-driven methods and services
OverviewBioindustry4.0 Work Package 7: Tools for high-quality datasets, requisite for data-driven methods and services
Real-time online monitoring of bioprocesses
Industrial biotechnology (IB) has the potential to create new markets while protecting the environment. With this in mind, the EU-funded BIOINDUSTRY 4.0 project will pave the way for IB to become a major manufacturing technology. Supporting the digitalisation of IB, the project will create new services delivered by European research infrastructure. These will address several challenges, focusing on the acceleration of bioprocess development pipelines. BIOINDUSTRY 4.0 will also develop data and metadata standards to generate high-quality, interoperable, multiscale bioprocess data. By developing data-driven approaches and exploiting AI to empower novel decision support systems and digital twins, the project will make it possible to control bioprocesses in real time.
Bioindustry4.0 Objective
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.
Bioindustry4.0 Work package 7
The objective of Work package 7 of Bioindustry4.0 is the following:
- Empower federated data sharing and reuse of data services and datasets
- Create a virtual environment for DT computational processes
- Provide the technology to enable federated Trusted Digital Networks (TDNs)
- Establish educational material to enable the use of the provided resources
Programme: Bioindustry 4.0
SEEK ID: https://hub.ibisba.eu/projects/90
Funding codes:- https://doi.org/10.3030/101094287
- Grant agreement ID: 101094287
Public web page: https://www.bioindustry4.eu/
Organisms: No Organisms specified
IBISBA PALs: No PALs for this Project
Project start date: 1st Jan 2023
Project end date: 31st Dec 2026
TagsRelated items
Projects: Industrial-scale penicillin simulation, Bioindustry4.0 Work Package 2: Dissemination, Communication Exploitation and capacity building, Bioindustry4.0 Public dissemination, Bioindustry4.0 Work Package 7: Tools for high-quality datasets, requisite for data-driven methods and services
Institutions: Universität Koblenz
Projects: Uncurated Protocols Library, FLOX: FLavin-containing OXidoreductases, PlanOvac, HIGHFLUX, SporeDel, Yeast Glycerol, Galambr, SULFOCEL, An inventory of the Aspergillus niger secretome by combining in silico predictions with shotgun proteomics data, Template library, Muconic Acid Production in Yeast, IBISBA 1.0 deliverables, PREP-IBISBA deliverables, Biocare, DBTL-P, Upscale of the biocatalytic transformation of Free Fatty Acids into high-value products (BIOFFA), B-PAC, BIOFFA, GLYCOMICS, KorallionBio, MAROX, PROTEIFROM, SUPI, Bioindustry4.0 Work Package 7: Tools for high-quality datasets, requisite for data-driven methods and services
Institutions: UNIMAN - The University of Manchester, Universitat Autònoma de Barcelona, CNR - Consiglio Nazionale delle Ricerche, INSAT - Institut National des Science Appliquees de Toulouse, VTT - Teknologian tutkimuskeskus VTT Oy, VITO - Vlaamse Instelling voor Technologisch Onderzoek N.V.
Projects: Industrial-scale penicillin simulation, Bioindustry4.0 Work Package 7: Tools for high-quality datasets, requisite for data-driven methods and services, Hybrid Physics-Informed Neural Networks for Efficient Computational Modeling: A Workflow Framework Applied to Schwanniomyces occidentalis, STAMM: Soft sensor moniToring and mAintenance framework for Machine learning Models
Institutions: Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement, INRAE
https://orcid.org/0000-0003-4717-3040
Projects: Bioindustry4.0 Work Package 7: Tools for high-quality datasets, requisite for data-driven methods and services, IBISBA-DIALS WP3, Bioindustry4.0 Public dissemination, Data Fabric Usage Demos, raw2ready, SCHEMA, Bioindustry4.0 Work Package 5
Institutions: Athena Research and Innovation Center In Information Communication & Knowledge Technologies
https://orcid.org/0000-0003-1160-5753
Real-time online monitoring of bioprocesses
Industrial biotechnology (IB) has the potential to create new markets while protecting the environment. With this in mind, the EU-funded BIOINDUSTRY 4.0 project will pave the way for IB to become a major manufacturing technology. Supporting the digitalisation of IB, the project will create new services delivered by European research infrastructure. These will address several challenges, focusing on the acceleration of bioprocess development pipelines. ...
Projects: Industrial-scale penicillin simulation, Scorpion antivenom nanobody production in Escherichia coli (Recombinant bispecific VHH), Production of the monoclonal antibody Trastuzumab in Komagataella phaffii (Pichia pastoris) for breast cancer treatment, Bioindustry4.0 Work Package 7: Tools for high-quality datasets, requisite for data-driven methods and services, Hybrid Physics-Informed Neural Networks for Efficient Computational Modeling: A Workflow Framework Applied to Schwanniomyces occidentalis, Saccharomyces cerevisiae, Pseudomonas putida use case, STAMM: Soft sensor moniToring and mAintenance framework for Machine learning Models, Pichia pastoris fermentation, Bioindustry4.0 Public dissemination, Bioindustry4.0 Work Package 2: Dissemination, Communication Exploitation and capacity building, Data Fabric Usage Demos, raw2ready, SCHEMA, Joint Action Research - INRAE-UAB in Pichia pastoris, Joint xylitol fermentations monitored by Kaiser and Timegate Raman devices, UAB - Komagataella phaffii Use Case, Bioindustry4.0 Work Package 5
Web page: https://www.bioindustry4.eu
ROR ID: https://ror.org/0576by029
Department: Not specified
Country: 
Greece
City: Marousi
Web page: https://www.athenarc.gr/
ROR ID: Not specified
Department: Not specified
Country: 
France
City: Paris
Web page: https://www.inrae.fr/en
ROR ID: https://ror.org/003vg9w96
Department: Not specified
Country: France
City: Paris
Web page: https://www.inrae.fr/
ROR ID: Not specified
Department: Not specified
Country: 
United Kingdom
City: Manchester
Web page: http://www.manchester.ac.uk/
ROR ID: Not specified
Department: Not specified
Country: 
Germany
City: Koblenz
Web page: https://www.uni-koblenz.de/de
Abstract (Expand)
Authors: Georgios K Georgakilas, Brett Metcalfe, Ariane Bize, Matthew Crowther, Emilie Fernandez, Susana Maria Alonso Villela, Stuart Owen, Rudolf Wittner, David Camilo Corrales, Anselm von Gladiss, Peter Blomberg, Munazah Andrabi, Cesar Arturo Aceves Lara, Hans Mattila, Marily Wiebe, Theodore Dalamagas, Jasper J Koehorst
Date Published: 2026
Publication Type: Journal
Abstract (Expand)
Authors: Brett Metcalfe, Juan Camilo Acosta-Pavas, Carlos Eduardo Robles-Rodriguez, George K. Georgakilas, Theodore Dalamagas, Cesar Arturo Aceves-Lara, Fayza Daboussi, Jasper J Koehorst, David Camilo Corrales
Date Published: 1st Mar 2025
Publication Type: Journal
Abstract (Expand)
Authors: Juan Camilo Acosta-Pavas, Carlos Eduardo Robles-Rodriguez, David Griol, Fayza Daboussi, Cesar Arturo Aceves-Lara, David Camilo Corrales
Date Published: 1st Aug 2024
Publication Type: Journal
Abstract (Expand)
Editor:
Date Published: 2024
Publication Type: Journal
The IBISBA Knowledge Hub (IBISBAKHub) is a data management platform designed to help researchers enhance the management of their research data. It offers an improved way to share, register, and organize the data and assets generated from research projects. The IBISBAKHub’s primary objective is to promote the adoption and implementation of FAIR Data principles.
IBISBA DIALS - Funded by the European Union (Grant agreement N°101131085). Views and opinions expressed are however those of the author(s) ...
Creator: Munazah Andrabi
Submitter: Brett Metcalfe
The IBISBA Knowledge Hub (IBISBAKHub) is a data management platform designed to help researchers enhance the management of their research data. It offers an improved way to share, register, and organize the data and assets generated from research projects. The IBISBAKHub’s primary objective is to promote the adoption and implementation of FAIR Data principles.
IBISBA DIALS - Funded by the European Union (Grant agreement N°101131085). Views and opinions expressed are however those of the author(s) ...
Creator: Jasper Koehorst
Submitter: Brett Metcalfe
The stakeholder workshop on IoT: Data integration from the lab took place on October 23rd, 2025 from 10:00-12:00 (CET). This two-hour workshop brought together experts and stakeholders to explore how laboratory data can be better integrated, managed, and applied using Internet of Things (IoT) technologies. The purpose of this event was to foster dialogue on the opportunities but also the challenges of IoT data acquisition within laboratory environments, exploring how connected equipment and sensors ...
Start Date: 23rd Oct 2025 (23rd Oct 2025 (Europe/Amsterdam))
End Date: 23rd Oct 2025 (23rd Oct 2025 (Europe/Amsterdam))
Event Website: https://www.bioindustry4.eu/
Country: Not specified
City: Not specified
Poster entitled 'The Lightweight Equipment Adapter Framework (LEAF) for real-time data acquisition' presented in the 'Computational challenges in the Life Sciences' track of NWO ICT.OPEN2026.
Creators: Brett Metcalfe, Jasper Koehorst
Submitter: Brett Metcalfe
Download
Data Management Plan of BIOINDUSTRY 4.0
As part of Task 7.1 “A Data and Metadata Fabric to support DTs” of Work Package (WP) 7 a Data Management Plan (DMP) is to be generated (Deliverable 7.1). This deliverable is intended to address the request by the European Commission to establish a plan regarding ‘data’ generated during the BIOINDUSTRY 4.0 programme. More explicitly, how data will be described (metadata, standards, etc.), shared, utilised, stored, and archived. This living document ...
Creators: Brett Metcalfe, Jasper Koehorst
Submitter: Brett Metcalfe
Title (String) *, Description (String) , biosafety level (String) , geographic location (country and/or sea) (String) , phase (String) , phase duration (String) , phase purpose (String) , recipe url (String) , replicate (String) , sample collection device or method (String) , sample dry mass (String) , sample material (String) , sample material processing (String) , sample storage buffer (String) , sample storage conditions (String) , sample storage container (String) , sample wet mass (String) , sampling time point (String) *, volume (String) , scientific name (String) *, ncbi taxonomy id (String) *, collection date (String) *, sample storage temperature (String) , sample storage duration (String) , sample storage location (String)
Not specified
