Model Execution Environment (MEE)
An integrated solution for patient cohort analysis
Our domain organizations:
[ISW] Vaccines and therapies for COVID-19.
[ISW] ATMP for cartilage and bone tissues.
The overall aim of the EDITH project is to foster an inclusive ecosystem for Digital Twins in healthcare in Europe and to prompt the convergence of such an ecosystem towards a common strategy conducive to its further development. This is achieved by mapping and analysing the status of the fields which are crucial for the growth, uptake and use of digital twins in healthcare, including in silico medicine, health data interoperability, high performance computing, ethical and legal regulations etc. A vision for the integrated human digital twin will be developed, based on standardised (meta-)data and models, and a roadmap to realise that vision will be articulated. Additionally, a federated cloud-based repository will be established, to bring together currently available resources and best practices. The ecosystem will be leveraged to create a repository catalogue with available resources and recruit resources into the repository during the project. Conditions for integration in the repository in terms of required standards, regulations, meta-data, and others. will be identified. Finally, building on available infrastructure, a framework for a simulation platform will be put forward with pre-selected prototypes demonstrating a proof of concept. User communities (healthcare professionals, patients, industry and academia) will be actively involved in the process to ensure their needs are built into the architecture. Several activities will focus on the exploitation of parts of the repository and simulation platform. Throughout the entire EDITH action, the community, its stakeholders and relevant international partners will be consulted via advisory boards, public meetings, community challenges and other public activities in order to firmly establish a sustainable ecosystem allowing to realise the vision of the integrated digital twin for personalised healthcare.
EurValve implements, tests and validates a modelling based decision support system (DSS) for aortic and mitral valve diseases that allows simulating, comparing and understanding the effects (outcomes) and risks of different treatment strategies.
This project proposes an open platform to support decision making in the clinical management of two paediatric cancers, Neuroblastoma (NB), the most frequent solid cancer of early childhood, and the Diffuse Intrinsic Pontine Glioma (DIPG) the leading cause of brain tumour-related death in children.
Bologna Biomechanical Computed Tomography (BBCT) methodology, developed by researchers at the University of Bologna.
[ISW] In SIlico Trial and clinical decision support tool for myocardial infarction.
[ISW] In Silico Trial for multiple sclerosis drugs.
Contains demos and tutorial examples for the InSilicoWorld consortium
Improving health through personalised computation. Maximal data utility, driving optimised decision support.
[ISW] In Silico Trial for tubercolosis vaccine.
[ISW] Digital Twin for fracture risk biomarker. In Silico Trial for osteoporosis drugs.
[ISW] Flow diverters for cerebral aneurysms.
[ISW] Immunotherapies for mammary carcinoma.
Pulmonary hypertension research carried out in collaboration with the University of Sheffield