The SimInSitu kick-off meeting took place on 9th March 2021 with all project partners and our advisor board.Continua...
SimInSitu is aiming to develop a sophisticated in-silico method to predict the short- and long-term behavior of in-situ tissue engineered heart valves (TEHV) by combing advanced tissue remodeling algorithms with a personalized virtual heart modelling approach. The method will be specifically developed to predict the complex transformation process of biodegradable heart valves from the initially synthetic scaffold into a fully remodeled & functional valve.
Though, significant progress was made during the past years in developing TEHV based devices, it remains very challenging, costly, time-consuming, and rich with obstacles. New knowledge can only be generated through a tedious trial & error process (requiring preclinical and clinical studies), since the restorative process cannot be replicated in an in-vitro environment.
Advanced Computer Modelling & Simulation technologies have the potential to overcome this limitation by allowing to test new designs, modified scaffold compositions, or other applications in a virtual patient-specific environment – in-silico. The availability of this computer model could contribute significantly to an acceleration of especially the ETR-device development and accelerate their translation into the clinic and market.
SimInSitu aims to develop a validated in-silico method capable of predicting short- and long-term safety & performance of in-situ tissue engineered heart valve
Support the development of in-situ tissue-engineered heart valve devices by generating beyond state-of-the-art simulation capabilities:
SimInSitu will follow a traditional phase-based development plan, which will start with various initially independent work-packages and will converge towards the development of the in-silico platform. Each phase and work-package will have its own deliverables and milestones.
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101017523