The Platform and expert system for genomic studies, MEDIGENOMICS, pursues the design, construction and development of a unique, integrated and expert service that combines the entire process of genomic studies of an individual (DNA/RNA extraction, nucleic acid sequence analysis, file generation, analysis and interpretation of results, and real-time information) on a single platform.

The service simplifies and automates the analysis of mass genome, exome, or gene panel sequencing done automatically on a centralised device.

Combining the entire sequencing analysis process on a single platform would improve diagnostic efficiency and effectiveness, cutting down on time and sample handling.

An innovative computerised platform could analyse, compile and store genomic information of healthy/ill individuals, with the unprecedented possibility of being kept up to date in a database as knowledge and information emerge in the medical literature.

Watch the video of the technical workshop of the PMC

millons euros for Phase 1

The project has a total budget for Phase I of €2.5 million (R&D&I Phase), under the collaboration agreement signed by the Ministry of Health of the Community of Madrid and the Ministry of Science and Innovation in December 2020, within the framework of the Line of Promotion of Demand-Side Innovation (FID) of the third call for proposals) to promote the Public Procurement of Innovation (PPI) in health services.

MEDIGENOMICSis 50% co-financed by the European Regional Development Fund (ERDF),through a grant awarded by the Ministry of Science and Innovation,which is part of the Pluri-Regional Operational Programme of Spain (POPE) 2014-2020. It reinforces the Community of Madrid’s commitment to this instrument to continue modernising the Administration and It also favours business competitiveness and strengthens public-private collaboration.

This project will run from 25 September 2019 through 30 June 2023.

General objectives

To design, build and develop an integrated genetic service that combines in a single platform the whole process of genomic study of an individual, in a simple and automated way, with continuous real-time updating, to optimise the overall process of genetic diagnosis for the patient/citizen, improving the diagnostic tools for genetic diseases and improving the information available to the administrations.

Specific objectives

Develop more effective genomic diagnostic tools that are integrated into clinical management processes.
To obtain more efficient genomic diagnostic tools that have a direct impact on the adequacy of treatments.
To develop a high-performance computerised genomic analysis system capable of integrating and standardising patient genomic information in a centralised expert system, and with future interaction with patients/individuals.

Expected results

The added value of this project can be summarised as follows

  1. It would allow the integration of patients’ genomic information into a centralised expert system, within the National Health System (regional, national, supranational, etc.)
  2. It would facilitate the standardisation of genomic information (health/disease) of patients or individuals within the National Health System, and the possibility of sharing it with other health systems, through computerisation with identical standards (FASTQ, BAM and VCF files) of genomic information
  3. It would enable interaction, updating and decision making between patients/individuals and health professionals
  4. It would optimise health information systems, electronic medical records, and patient management systems, improving the efficiency of healthcare big data and international coding languages in EHRs, such as SNOMED-CT, HPO, etc.

Health impact:

  • Improvement in the early diagnosis of genetically based diseases. When faced with a genomic variant, and because the opinions of individual experts vary considerably from one to another, there is a compelling need for these findings to be evaluated in an objective, up-to-date manner and with data from multiple, self-updating databases.
  • Better response time to genetic tests and improved handling of biological samples (safety).
  • Treatment optimisation, including the possibility of avoiding lethal toxicities and lack of therapeutic response to commonly used drugs. Thus, by means of an intelligent system (machine learning or similar) and by means of a transparent, reproducible, evidence-based method, it can determine whether an identified variant is clinically relevant, and what health actions, if any, should be implemented.

Public health impact:

  • Improvement in public health coordination in the autonomous communities involved in the development of the tool, with the possibility of data integration, integration of automated diagnostic support tools, and implementation of records in electronic clinical histories.

Organisational impact:

  • Refined standardisation and integration of genomic information into a centralised system within a health system (regional, national, or supranational).
  • Improved interaction, updating and responsible decision making by patients and healthcare professionals through the empowerment of patients and healthcare professionals themselves.
  • Improved interaction, updating and responsible decision making by patients and healthcare professionals through the empowerment of patients and healthcare professionals themselves.
  • Optimisation of information systems, electronic medical records, and patient management systems by improving the efficiency of healthcare big data management.