Summary
Articular cartilage (AC) is a connective tissue that is essential for smooth movement of our joints. Damage to AC leads to a debilitating joint disease called osteoarthritis (OA), which can cause severe restriction of joint movement and overall mobility. Currently, there are more than 40 million Europeans who are affected by OA. Tissue engineering approaches present promising treatment strategy through the replacement of the damaged tissues with tissue-engineered (TE) constructs. Although the current paradigm is to produce a cell-seeded biomaterial that matches the properties of the native tissue, such biomaterial may hinder growth and discourage replacement of the supportive biomaterials by newly synthesized proteins. Current TE constructs integrate poorly with the host tissue, with problems of interfacial gaps and compositional discontinuity, thus impeding their translation to the clinic. As cartilage cells are mechano-sensitive, we hypothesize that the mechanical signals conducive to cell biosynthesis can improve functional integration of TE constructs into host cartilage, and such mechanical signals can be tuned through carefully-designed TE constructs with optimal distribution of material stiffness and cell density. The aim of this research is to develop an advanced computational model that can simulate the biomechanical and growth behaviours of TE constructs and the host cartilage, and to use this model to determine optimal TE construct design that allows for functional integration into the host cartilage. The numerically-determined optimal design will be validated by state-of-the-art bioprinting technology and bioreactor testing. This computational biomechanical growth model will be the first-of-its kind as it can accelerate the design process and improve the performance of the TE constructs. This novel model can make a long-term impact on personalized design of TE constructs and have a high potential to advance the TE technique towards clinical translation.
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| Web resources: | https://cordis.europa.eu/project/id/890936 |
| Start date: | 01-03-2021 |
| End date: | 28-02-2023 |
| Total budget - Public funding: | 190 680,96 Euro - 190 680,00 Euro |
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Original description
Articular cartilage (AC) is a connective tissue that is essential for smooth movement of our joints. Damage to AC leads to a debilitating joint disease called osteoarthritis (OA), which can cause severe restriction of joint movement and overall mobility. Currently, there are more than 40 million Europeans who are affected by OA. Tissue engineering approaches present promising treatment strategy through the replacement of the damaged tissues with tissue-engineered (TE) constructs. Although the current paradigm is to produce a cell-seeded biomaterial that matches the properties of the native tissue, such biomaterial may hinder growth and discourage replacement of the supportive biomaterials by newly synthesized proteins. Current TE constructs integrate poorly with the host tissue, with problems of interfacial gaps and compositional discontinuity, thus impeding their translation to the clinic. As cartilage cells are mechano-sensitive, we hypothesize that the mechanical signals conducive to cell biosynthesis can improve functional integration of TE constructs into host cartilage, and such mechanical signals can be tuned through carefully-designed TE constructs with optimal distribution of material stiffness and cell density. The aim of this research is to develop an advanced computational model that can simulate the biomechanical and growth behaviours of TE constructs and the host cartilage, and to use this model to determine optimal TE construct design that allows for functional integration into the host cartilage. The numerically-determined optimal design will be validated by state-of-the-art bioprinting technology and bioreactor testing. This computational biomechanical growth model will be the first-of-its kind as it can accelerate the design process and improve the performance of the TE constructs. This novel model can make a long-term impact on personalized design of TE constructs and have a high potential to advance the TE technique towards clinical translation.Status
TERMINATEDCall topic
MSCA-IF-2019Update Date
28-04-2024
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