Summary
Biopharmaceuticals are essential for the medical treatment of diseases like immune deficiencies, cancer, and diabetes, and provide an indispensable component to the health care system worldwide, as showcased by mRNA vaccines in the recent pandemic. Despite this success, manufacturing is still based on traditional, outdated batch production technologies, and on process development procedures based on historical experience and empiricism leading to many inefficiencies, like very long values of time-to-market. There is an urgent need to introduce modern integrated, continuous, and fully digitalized production processes, to also cope with the upcoming cell and gene therapies and the emerging personalized medicine. I develop here revolutionary process development and operation methodologies to enable this.
These are based on a Digital Twin, which includes the first continuous, integrated and fully digitalized plant for producing mRNA. The “engine” are innovative hybrid models for each unit of the plant, which are updated on real time through continuous learning techniques. These provide the predictive capabilities needed for monitoring and control, knowledge transfer, scenario analysis and experimental planning.
I will develop a new generation of hybrid models and innovative machine learning algorithms and provide the experimental evaluation and validation of my methodologies. Other high precision continuous processes, like flow-chemistry for sustainable catalytic processes or microfluidics for the controlled synthesis of nanomaterials, will benefit from these results.
I am a recognised pioneer in the scientific foundations of continuous operation in biopharma. This inspired me in developing this disruptive Digital-Twin-based methodology and cope with the associated high risk. With about 110 PhD students advised in my career and now active in Academia and Industry, I know how to inspire a new generation of scientists with the novel science emerging from this project.
These are based on a Digital Twin, which includes the first continuous, integrated and fully digitalized plant for producing mRNA. The “engine” are innovative hybrid models for each unit of the plant, which are updated on real time through continuous learning techniques. These provide the predictive capabilities needed for monitoring and control, knowledge transfer, scenario analysis and experimental planning.
I will develop a new generation of hybrid models and innovative machine learning algorithms and provide the experimental evaluation and validation of my methodologies. Other high precision continuous processes, like flow-chemistry for sustainable catalytic processes or microfluidics for the controlled synthesis of nanomaterials, will benefit from these results.
I am a recognised pioneer in the scientific foundations of continuous operation in biopharma. This inspired me in developing this disruptive Digital-Twin-based methodology and cope with the associated high risk. With about 110 PhD students advised in my career and now active in Academia and Industry, I know how to inspire a new generation of scientists with the novel science emerging from this project.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101095721 |
| Start date: | 01-10-2023 |
| End date: | 30-09-2028 |
| Total budget - Public funding: | 2 500 000,00 Euro - 2 500 000,00 Euro |
Cordis data
Original description
Biopharmaceuticals are essential for the medical treatment of diseases like immune deficiencies, cancer, and diabetes, and provide an indispensable component to the health care system worldwide, as showcased by mRNA vaccines in the recent pandemic. Despite this success, manufacturing is still based on traditional, outdated batch production technologies, and on process development procedures based on historical experience and empiricism leading to many inefficiencies, like very long values of time-to-market. There is an urgent need to introduce modern integrated, continuous, and fully digitalized production processes, to also cope with the upcoming cell and gene therapies and the emerging personalized medicine. I develop here revolutionary process development and operation methodologies to enable this.These are based on a Digital Twin, which includes the first continuous, integrated and fully digitalized plant for producing mRNA. The “engine” are innovative hybrid models for each unit of the plant, which are updated on real time through continuous learning techniques. These provide the predictive capabilities needed for monitoring and control, knowledge transfer, scenario analysis and experimental planning.
I will develop a new generation of hybrid models and innovative machine learning algorithms and provide the experimental evaluation and validation of my methodologies. Other high precision continuous processes, like flow-chemistry for sustainable catalytic processes or microfluidics for the controlled synthesis of nanomaterials, will benefit from these results.
I am a recognised pioneer in the scientific foundations of continuous operation in biopharma. This inspired me in developing this disruptive Digital-Twin-based methodology and cope with the associated high risk. With about 110 PhD students advised in my career and now active in Academia and Industry, I know how to inspire a new generation of scientists with the novel science emerging from this project.
Status
SIGNEDCall topic
ERC-2022-ADGUpdate Date
12-03-2024
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