Project

Subproject 5: «Infrastructures, Tools, and Systems for Organization, Processing, and Analysis of Biomedical Data

The project will design and develop the IT infrastructure and the software tools to collect, process and analyze biomedical data in order to support the standardization,and the effective and efficient execution of sequence analysis and diagnostic workflows performed in Precision Medicine Units (PMU)in Greece. Moreover, the project will design and develop tools to support tasks related to clinical diagnosis, as well as to support administration tasks inPMUs.
The IT infrastructure will provide the following digital services:
•Editing and management of doctors’ referrals and labs’ sample data
•Data processing, storage and integration to support all steps of NGS analysis for precision medicine (sequence data production, generation of variant calling data, variant annotation and interpretation)
•Automatic execution of NGS analysis workflows for precision medicine
•Search, exploration and analytics on NGS data and related clinical data collected from diagnostic workflows performed in PMUs
•Support diagnostic guidelines for precision medicine by harvesting data from external data sources (digital libraries and clinical databases).Specifically, the project will support the execution of NGS analysis workflows for precision medicine based on well-defined PMUs diagnostic scenarios, best practices and certified medical protocols. In the first stage, we will adopt and adapt well-established, certified commercial sample analysis and diagnostic software tailored to the management and analysis of NGS data. The focus will be on: solid tumors, blood cancer and hereditary cancer. In the second stage, we will adopt additional software developed by PMUs, which, after a maturing phase, will be included in the diagnostic workflows of the infrastructure to address the relevant diseases.Also, the project will support the analysis of biomedical data produced during NGS analysis workflows and their integration with other relevant data from external data sources. Specifically, to support variant annotation and interpretation, the platform will harvest data from digital libraries of scientific publications, clinical databases, gene-specific databases, variant databases, etc.