Model Execution Environment (MEE)
An integrated solution for patient cohort analysis
Domain organizations:
The GEMINI project aims to provide validated multi-organ and multi-scale computational models to support therapeutic decisions and improve fundamental understanding of ischemic and hemorrhagic acute strokes. Precisely, GEMINI will deliver validated, integrated, multi-scale, multi-organ Digital Twin in Healthcare (DTH) models for cerebral blood and cerebrospinal fluid flow, brain perfusion and metabolism, blood flow and thrombosis along the heart-brain axis by integrating available and newly developed dynamic, interoperable and modular computational models.
[ISW] Vaccines and therapies for COVID-19.
[ISW] ATMP for cartilage and bone tissues.
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.
Improving health through personalised computation. Maximal data utility, driving optimised decision support.
Contains demos and tutorial examples for the InSilicoWorld consortium
[ISW] In SIlico Trial and clinical decision support tool for myocardial infarction.
Bologna Biomechanical Computed Tomography (BBCT) methodology, developed by researchers at the University of Bologna.
[ISW] In Silico Trial for multiple sclerosis drugs.
[ISW] In Silico Trial for tubercolosis vaccine.
[ISW] Flow diverters for cerebral aneurysms.
[ISW] Digital Twin for fracture risk biomarker. In Silico Trial for osteoporosis drugs.
[ISW] Immunotherapies for mammary carcinoma.
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.
Pulmonary hypertension research carried out in collaboration with the University of Sheffield