Summary
EvOoC aims at developing smart mechanically active Organs-on-Chip platforms as clinically relevant in vitro setups to unravel mechanisms underlying tissue regeneration and progression of unmet diseases.
A decade ago, developmental engineering (DE) proposed to model in vitro clinically relevant tissues replica by recapitulation of embryonic developmental events. Despite physical forces have recently been suggested as main driver of developmental processes, mechanical conditioning never prevailed as key DE strategy. This is related to a lack in current in vitro mechanobiology setups, mainly based on open loop systems, which disregard the fact that native mechanical environment varies in time as function of tissue state itself.
EvOoC vision is to elevate mechanobiology as leading DE approach through a ground-breaking paradigm, named mechanical re-evolution, based on the high-risk/high-gain hypothesis that an iterative manipulation of mechanical forces is necessary to guide in vitro adult tissue development at unprecedented levels.
Towards this vision, I will deliver a new method (Evolving OoC, EvOoC), integrating three enabling functions:
“Move” - to apply native-inspired mechanical forces to tissues in vitro;
“Sense” – to monitor their comprehensive effect on tissue development;
“Adapt” – to modulate forces as a function of tissue responses through machine learning (ML)-based algorithms, towards an unsupervised tissue evolution.
I will take advantages of two paradigmatic test-cases (cartilage and heart) to showcase the power of mechanical re-evolution in guiding in vitro tissue physiological and pathological states, towards the identification of a brand-new class of mechanotherapeutics for unmet pathologies.
By combining principles of microfabrication, DE, mechanobiology and ML, EvOoC will revolutionize basic studies in tissue development and disease modeling, facilitating innovative translational strategies to tackle tissue repair in manifold applications.
A decade ago, developmental engineering (DE) proposed to model in vitro clinically relevant tissues replica by recapitulation of embryonic developmental events. Despite physical forces have recently been suggested as main driver of developmental processes, mechanical conditioning never prevailed as key DE strategy. This is related to a lack in current in vitro mechanobiology setups, mainly based on open loop systems, which disregard the fact that native mechanical environment varies in time as function of tissue state itself.
EvOoC vision is to elevate mechanobiology as leading DE approach through a ground-breaking paradigm, named mechanical re-evolution, based on the high-risk/high-gain hypothesis that an iterative manipulation of mechanical forces is necessary to guide in vitro adult tissue development at unprecedented levels.
Towards this vision, I will deliver a new method (Evolving OoC, EvOoC), integrating three enabling functions:
“Move” - to apply native-inspired mechanical forces to tissues in vitro;
“Sense” – to monitor their comprehensive effect on tissue development;
“Adapt” – to modulate forces as a function of tissue responses through machine learning (ML)-based algorithms, towards an unsupervised tissue evolution.
I will take advantages of two paradigmatic test-cases (cartilage and heart) to showcase the power of mechanical re-evolution in guiding in vitro tissue physiological and pathological states, towards the identification of a brand-new class of mechanotherapeutics for unmet pathologies.
By combining principles of microfabrication, DE, mechanobiology and ML, EvOoC will revolutionize basic studies in tissue development and disease modeling, facilitating innovative translational strategies to tackle tissue repair in manifold applications.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101077146 |
| Start date: | 01-09-2023 |
| End date: | 31-08-2028 |
| Total budget - Public funding: | 2 430 625,00 Euro - 2 430 625,00 Euro |
Cordis data
Original description
EvOoC aims at developing smart mechanically active Organs-on-Chip platforms as clinically relevant in vitro setups to unravel mechanisms underlying tissue regeneration and progression of unmet diseases.A decade ago, developmental engineering (DE) proposed to model in vitro clinically relevant tissues replica by recapitulation of embryonic developmental events. Despite physical forces have recently been suggested as main driver of developmental processes, mechanical conditioning never prevailed as key DE strategy. This is related to a lack in current in vitro mechanobiology setups, mainly based on open loop systems, which disregard the fact that native mechanical environment varies in time as function of tissue state itself.
EvOoC vision is to elevate mechanobiology as leading DE approach through a ground-breaking paradigm, named mechanical re-evolution, based on the high-risk/high-gain hypothesis that an iterative manipulation of mechanical forces is necessary to guide in vitro adult tissue development at unprecedented levels.
Towards this vision, I will deliver a new method (Evolving OoC, EvOoC), integrating three enabling functions:
“Move” - to apply native-inspired mechanical forces to tissues in vitro;
“Sense” – to monitor their comprehensive effect on tissue development;
“Adapt” – to modulate forces as a function of tissue responses through machine learning (ML)-based algorithms, towards an unsupervised tissue evolution.
I will take advantages of two paradigmatic test-cases (cartilage and heart) to showcase the power of mechanical re-evolution in guiding in vitro tissue physiological and pathological states, towards the identification of a brand-new class of mechanotherapeutics for unmet pathologies.
By combining principles of microfabrication, DE, mechanobiology and ML, EvOoC will revolutionize basic studies in tissue development and disease modeling, facilitating innovative translational strategies to tackle tissue repair in manifold applications.
Status
SIGNEDCall topic
ERC-2022-STGUpdate Date
31-07-2023
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