Project description
Tissue regeneration through mechanobiology
Many diseases remain untreatable because scientists lack reliable models to study how tissues develop and regenerate. Traditional lab methods fail to replicate the complex mechanical forces that influence tissue formation, limiting progress in regenerative medicine. Although developmental engineering has made advances by mimicking embryonic development, it largely overlooks mechanical forces as a key factor. Current in vitro setups operate in a fixed manner, disregarding how tissues naturally respond to and modify their mechanical environment. The ERC-funded EvOoC project aims to transform this approach by developing intelligent Organs-on-Chip platforms that actively apply, monitor, and adjust mechanical forces. By integrating microfabrication, mechanobiology, and machine learning, EvOoC could pave the way for breakthrough therapies in tissue repair.
Objective
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.
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Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
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HORIZON.1.1 - European Research Council (ERC)
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(opens in new window) ERC-2022-STG
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20133 Milano
Italy
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