Research Project
SHE: cloud platform for advanced diagnostics based on clinical-omic data
Electronic Medical Records (EMRs) for precision medicine, integrating phenotypic data and clinical history of the patient with the data from omics analysis.
Where: italy
Where: italy
Financing Framework
Challenge
The precision medicine, especially in the context of rare diseases, requires the causes of the disease to be postulated (or confirmed) by genotyping, CNV (Copy Number Variation), whole genome screening, transcriptome or proteome analysis.
Approach
The information that needs to be shared within multidisciplinary teams is heterogeneous, complex, expensive and difficult to interpret. In addition, the possibility to access external database to identify similiar cases is crucial in the identification of both possibile diagnosis and therapy.
SHE overcomes these complexities by providing tools that integrate the heterogeneous data, making them easly accessible to both the physicians and geneticists, facilitating the decision-making processes of both parties.
Solution
SHE defines and implements the structure of a new generation holistic EMR (Electronic Medical Record). It is a robust, interoperable, modular, secure and easy-to-use system capable of maintaining in a structured way data and analytical results generated by bioinformatics pipelines and primary analysis of omics data, relevant from a diagnostic and therapeutic point of view. It also offers Machine Learning based clinical decision support and info-visualization features to help the diagnostic and drug treatment identification processes. Engineering is the project coordinator and it is also responsible for the design and prototyping of the new generation clinical-omics EMR.
Project implemented thanks to co-financing from the PON 'Enterprises and Competitiveness' 2014-2020 ERDF-AXIS 1 - OT1 Investment Priority 1b - Action 1.1.3 LDR.
Results
Care personalization with outocmes optimization
Cost Reduction for Hospital
Quality life improved for patient’s family
Reuse of structured dataset for further research
Impacts
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