HORIZON EUROPE
Europeo
Specific Challenge:The state-of-the-art approach to designing, scaling up and starting up bioprocesses is governed by ‘trial and error’ and replicating traditional manufacturing methods. These methods often cause scaling-up losses and start-up delays or failures. There are many variables that have an impact on the design and scaling-up of bioprocesses, making this a very complex exercise. Among the major causes of these variables are:
an increasingly wider range of biomass feedstock and their varied and heterogeneous composition; andrevolutionary developments in molecular biology producing more efficient microorganisms that can create a wider range of bio-products. Both developments demand reliable modelling systems to cope with many variables in simulating the full value chain, from feedstock to products, in search of the most effective combinations.
The design phase should be long enough and have sufficient tools available to test different and radical concepts. And ultimately, in the scaled-up and (semi-)commercial operating phase, there should be guidelines for continuous improvement cycles.
Today’s methods for scaling-up often take a more...
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Specific Challenge:The state-of-the-art approach to designing, scaling up and starting up bioprocesses is governed by ‘trial and error’ and replicating traditional manufacturing methods. These methods often cause scaling-up losses and start-up delays or failures. There are many variables that have an impact on the design and scaling-up of bioprocesses, making this a very complex exercise. Among the major causes of these variables are:
an increasingly wider range of biomass feedstock and their varied and heterogeneous composition; andrevolutionary developments in molecular biology producing more efficient microorganisms that can create a wider range of bio-products. Both developments demand reliable modelling systems to cope with many variables in simulating the full value chain, from feedstock to products, in search of the most effective combinations.
The design phase should be long enough and have sufficient tools available to test different and radical concepts. And ultimately, in the scaled-up and (semi-)commercial operating phase, there should be guidelines for continuous improvement cycles.
Today’s methods for scaling-up often take a more limited view and do not look at the bigger picture, so that optimisation takes place at lab level, not at plant operation level.
Industry needs reliable modelling approaches, able to predict entire pathways from feedstock and energy intake to product output. This may mean designing tailor-made paths for each specific feedstock – from its intake and preparation, through the processing steps to the end-products.
Recent developments in computation-driven frameworks can help cope with many variables in designing optimal feedstock-organisms-bioprocess configurations and simulating scaling-up. These computation approaches are already standard in fields other than microbial technology and industrial biotechnology.
The specific challenge of this topic is to design and apply reliable and robust computational modelling approaches for bioprocesses.
Scope:Develop modelling systems that contain experimental multi-omics data on microbial responses to conditions in large fermenters and that combine know-how of metabolic networks and large-scale fluid dynamics into an integral, computation-driven framework to help in the design, scale-up and start-up of bioprocesses.
The modelling approach should specify the ‘optimal’ use of the selected biomass – in terms of the environmental, economic and social sustainability of the value chain – and the resulting savings in cost and time during scaling-up and start-up. Proposals should therefore be developed in partnership with the operator of a (pre-)commercial-scale biorefinery or a pilot or demonstration plant, who should validate the results.
To achieve a fair assessment, adequate metrics will be needed to compare the results of modelling from different perspectives. The models should also make connectivity to Industry 4.0 and The Internet of Things possible for future use in a complete value chain.
Proposals should simulate a selected specific biomass feedstock and associated processing steps yielding targeted intermediary products.
Proposals may include different processing routes for the selected feedstock to show how the developed models may be replicated, scaled up and used in different value chains. This experimental validation should also include a sensitivity analysis to assess the models’ ability to cope with disruptions and non-uniform reaction mixtures. The validation should also specify all included assumptions and should yield information to quantify sensitivity and uncertainties alike.
The industry should actively participate to demonstrate the potential for integrating the developed concepts into current industrial landscapes or existing plants so that the concepts can be deployed more quickly and scaled up to apply industrial-wide.
Proposals should specifically demonstrate the benefits versus the state-of-the-art and existing technologies. This could be done by providing evidence of new processing solutions and new products obtained.
The technology readiness level (TRL)1 at the end of the project should be at least 3 for the bio-based value chain in question. Proposals should clearly state the starting TRL, which may be as low as 1 or 2.
Proposals should seek complementarity with projects funded under Horizon 2020 to avoid overlap, promote synergies and advance beyond the state-of-the-art.
Indicative funding:
It is considered that proposals requesting a BBI JU contribution of between EUR 1 million and EUR 2,5 million would allow the specific challenge to be addressed appropriately. However, this does not preclude the submission and selection of proposals requesting other amounts.
To be eligible for participation a consortium must contain at least one constituent entity of the Bio-based Industry Consortium not eligible for JU funding according to Commission Delegated Regulation (EU) No 623/2014.
1 Technology readiness levels as defined in annex G of the General Annexes to the Horizon 2020 Work Programme: http://ec.europa.eu/research/participants/data/ref/h2020/other/wp/2018-2020/annexes/h2020-wp1820-annex-ga_en.pdf
Expected Impact:help shorten the time to market for bio-based products;help realise savings in large-scale implementation of bio-based value chains in time, costs, material and energy requirements, environmental impacts, etc.;help establish more efficient bioprocesses and a higher strain performance. Expected duration: 1 to 4 years.
Type of action: Research and innovation action.
The conditions related to this topic are provided in the chapter 2.3.3. of the BBI JU AWP 2018.
Cross-cutting Priorities:Cross-cutting Key-Enabling Technologies (KETs)
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Características del consorcio
:
La ayuda es de ámbito europeo, puede aplicar a esta linea cualquier empresa que forme parte de la Comunidad Europea.
Características del Proyecto
Los costes de personal subvencionables cubren las horas de trabajo efectivo de las personas directamente dedicadas a la ejecución de la acción. Los propietarios de pequeñas y medianas empresas que no perciban salario y otras personas físicas que no perciban salario podrán imputar los costes de personal sobre la base de una escala de costes unitarios
Los otros costes directos se dividen en los siguientes apartados: Viajes, amortizaciones, equipamiento y otros bienes y servicios. Se financia la amortización de equipos, permitiendo incluir la amortización de equipos adquiridos antes del proyecto si se registra durante su ejecución. En el apartado de otros bienes y servicios se incluyen los diferentes bienes y servicios comprados por los beneficiarios a proveedores externos para poder llevar a cabo sus tareas
La subcontratación en ayudas europeas no debe tratarse del core de actividades de I+D del proyecto. El contratista debe ser seleccionado por el beneficiario de acuerdo con el principio de mejor relación calidad-precio bajo las condiciones de transparencia e igualdad (en ningún caso consistirá en solicitar menos de 3 ofertas). En el caso de entidades públicas, para la subcontratación se deberán de seguir las leyes que rijan en el país al que pertenezca el contratante
Características de la financiación
A number of non-EU/non-Associated Countries that are not automatically eligible for funding have made specific provisions for making funding available for their participants in Horizon 2020 projects. See the information in the Online Manual.
2. Eligibility and admissibility conditions: described in Annex B and Annex C of the Work Programme.
Proposal page limits and layout: Please refer to Part B of the proposal template in the submission tool below.
3. Evaluation:
Evaluation criteria, scoring and thresholds are described in Annex H of the H2020 Work Programme, with the exceptions described in part 2.3.6 of the BBI JU Work Plan.
Submission and evaluation processes are described in the Online Manual and the BBI JU Guide for applicants (RIA-IA-CSA)
4. Indicative time for evaluation and grant agreement:
Information on the outcome of evaluation: maximum 5 months from the deadline for submission.
Signature of grant agreements: maximum 8 months from the deadline for submission.
5. Proposal templates, evaluation forms and model... 1. Eligible countries: described in Annex A of the H2020 Work Programme.
A number of non-EU/non-Associated Countries that are not automatically eligible for funding have made specific provisions for making funding available for their participants in Horizon 2020 projects. See the information in the Online Manual.
2. Eligibility and admissibility conditions: described in Annex B and Annex C of the Work Programme.
Proposal page limits and layout: Please refer to Part B of the proposal template in the submission tool below.
3. Evaluation:
Evaluation criteria, scoring and thresholds are described in Annex H of the H2020 Work Programme, with the exceptions described in part 2.3.6 of the BBI JU Work Plan.
Submission and evaluation processes are described in the Online Manual and the BBI JU Guide for applicants (RIA-IA-CSA)
4. Indicative time for evaluation and grant agreement:
Information on the outcome of evaluation: maximum 5 months from the deadline for submission.
Signature of grant agreements: maximum 8 months from the deadline for submission.
5. Proposal templates, evaluation forms and model grant agreements (MGA):
Specific rules and funding rates: described in 2.3.6 of the BBI JU Work Plan.
Proposal templates are available after entering the submission tool below.
Standard evaluation form (CSA-RIA-IA)
BBI JU MGA - Multi-Beneficiary
H2020 Annotated Grant Agreement
6. Additional requirements:
Technology readiness levels (TRL)
Members of consortium are required to conclude a consortium agreement, in principle prior to the signature of the grant agreement.
7. Open access must be granted to all scientific publications resulting from Horizon 2020 actions.
Where relevant, proposals should also provide information on how the participants will manage the research data generated and/or collected during the project, such as details on what types of data the project will generate, whether and how this data will be exploited or made accessible for verification and re-use, and how it will be curated and preserved.
Open access to research data
The Open Research Data Pilot has been extended to cover all Horizon 2020 topics for which the submission is opened on 26 July 2016 or later. Projects funded under this topic will therefore by default provide open access to the research data they generate, except if they decide to opt-out under the conditions described in Annex L of the H2020 main Work Programme. Projects can opt-out at any stage, that is both before and after the grant signature.
Note that the evaluation phase proposals will not be evaluated more favourably because they plan to open or share their data, and will not be penalised for opting out.
Open research data sharing applies to the data needed to validate the results presented in scientific publications. Additionally, projects can choose to make other data available open access and need to describe their approach in a Data Management Plan.
Projects need to create a Data Management Plan (DMP), except if they opt-out of making their research data open access. A first version of the DMP must be provided as an early deliverable within six months of the project and should be updated during the project as appropriate. The Commission already provides guidance documents, including a template for DMPs. See the Online Manual.
Eligibility of costs: costs related to data management and data sharing are eligible for reimbursement during the project duration.
The legal requirements for projects participating in this pilot are in the article 29.3 of the Model Grant Agreement.
8. Additional documents
BBI JU Work Plan
BBI JU Scientific Innovation and Research Agenda (SIRA)
BBI JU Derogation to H2020 Rules for Participation
BBI JU Regulation of Establishment
H2020 Regulation of Establishment
H2020 Rules for Participation
H2020 Specific Programme
Frequently Asked Questions 2018
Información adicional de la convocatoria
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