My domain relates to data science in the large health sector. I have a strong interests and background in medical data warehouses, semantics, data quality and interoperability in healthcare generated data reuse for public health (epidemiology and surveillance systems).

I am associated to the Inserm LIMICS (Medical Informatics and Knowledge Engineering Lab) lab for my research in the e-health domain.

My main area of expertise deals with semantic interoperability healthcare data, which covers a wide area and includes particularly the problems associated with the exchange of medical information (in the broad sense) between the medical computer systems. Technical themes typically associated with these areas are ontologies, semantic mediation architectures, clinical data warehouses, data quality in the web of data.

French expert for medical coding and rare diseases, I have been appointed several times as a consultant, such as in the european project ASSESS-CT.

I am a member of the french temporary scientific committee of the SNOMED-CT national project.

I am co-editor of the clinical research informatics section of the IMIA yearbook of medical informatics. I participate to various expertise for ANR and as a reviewer for various journals and conferences.

I have participated in the working groups of various national initiatives in France such as the new France Genomic 2025 plan as well as the Big Data consultation group.

I participated into a FP7-IP project named DebugIT as co-leader of the interoperability platform work package during my Ph.D. degree defining innovative solutions for healthcare data interoperability that were then valorized by Agfa Healthcare.


    • e-health strategy
    • Public health
    • Semantic interoperability and big data
    • Rare diseases and genetic data
    • Health data privacy

    Expertise and Review

    • 2016
      The 2025 Genomic Medicin French Plan
      Expert group member
    • 2016
      French Big Data for Healthcare Initiative
      Expert group member
    • 2015
      Orphanet Journal of Rare Diseases
    • 2013-2017
      IMIA yearbook of medical informatics
      Section editor of Clinical Research Informatics
    • 2015
      IEEE Transactions on Industrial Informatics
    • 2013-2015
      Agence Nationale pour la Recherche (ANR)
      Expert pour appels blancs et défis pour la santé
    • 2015
      Computer in Biology and Medicine

    Main projects



      Rare disease EU joint action

      RD-ACTION it a 3 year (2015-2018) joint action for rare diseases. In this project, I am involved with the Germany and Italy for the codification WP5 package for rare diseases.

    • BNDMR


      A national pubic health infrastructure for rare diseases

      The National Bank for Rare Diseases project is a priority project of the 2nd Plan for Rare Diseases. It is built as part of the CEMARA experience that started in 2007 in Necker Hospital for Children (AP-HP) in a Paris 5 University research unit (SBIM). The working program undertaken as part of the 2nd national plan was dedicated to reinforce the current infrastructure and implement a nationwide framework incorporating other existing rare diseases (RD) registries and patient files in order to reduce data collection burden for rare disease centers of expertise. In this perspective, CEMARA is being be replaced by BaMaRa in 2015 in order to facilitate the integration with other existing databases (registries) and applications (Electronic Health Records, genetic centered applications). Meanwhile, the overall model for RD data collection at national level has proven to be successful as a useful infrastructure to support research activities for RD centers of expertise (using the infrastructure to manage local or national cohorts). Research on this infrastructure itself also benefited from information technology (IT) developments dedicated to link care planning, public health and research.



      ASSESS CT - Assessing SNOMED CT for Large Scale eHealth Deployments in the EU

      ASSESS CT will contribute to better semantic interoperability of eHealth services in Europe, in order to optimise care and to minimise harm in delivery of care. The ASSESS CT project, integrating a broad range of stakeholders, will investigate the fitness of the international clinical terminology SNOMED CT as a potential standard for EU-wide eHealth deployments. In a joint one-year effort, the ASSESS CT consortium will

      • will address this challenge by investigating a number of issues related to the current use of SNOMED CT such as concrete reasons for adoption/non adoption of SNOMED CT, lessons learned, success factors, type and purpose of use, multilingualism, cultural differences, strengths and weaknesses
      • review – using literature review, survey, interviews; focus groups and workshops – the current state of use of SNOMED CT and the fulfilment of semantic interoperability use cases, known technical and organisational drawbacks, and the way the terminology is improved and maintained.
      • employ established evaluation approaches from social science. It will scrutinise adoption against two alternative scenarios: to abstain from actions at the EU level, or to devise an EU-wide semantic interoperability framework alternative without SNOMED CT.
      • analyse the impact of SNOMED CT adoption from a socio-economic viewpoint, encompassing management, business, organisational, and governance aspects.

      Validation of all working tasks, both political and domain-specific, will be secured through four large workshops with a list of distinguished experts assembled in an Expert Panel, Committee of MS Representatives, and national focus groups.

    • BaMaRa


      An integrated application to hospital information systems for rare disease centres

      A web based application for rare disease patients diagnosis and activity follow up. It is based on semantic technology standards, on a home made eCRF engine developed in Ruby on Rails / MongoDB.

      It is a highly secure application where data is encrypted and stored separately from an hospital to the other.

      The application embeds new generation web paradigms, helping users with data management tasks. It offers a set of data exploitation dashboards for local use.

    • LORD


      Linking open rare diseases data for coding

      Characterizing a rare disease diagnosis for a given patient is often made through expert’s networks. It is a complex task that could evolve over time depending on the natural history of the disease and the evolution of the scientific knowledge. Most rare diseases have genetic causes and recent improvements of sequencing techniques contribute to the discovery of many new diseases every year. Diagnosis coding in the rare disease field requires data from multiple knowledge bases to be aggregated in order to offer the clinician a global information space from possible diagnosis to clinical signs (phenotypes) and known genetic mutations (genotype). Nowadays, the major barrier to the coding activity is the lack of consolidation of such information scattered in different classifications such as Orphanet, OMIM or HPO. The Linking Open data for Rare Diseases (LORD) Web portal we developed stands as the first attempt to fill this gap by offering an integrated view of 8.400 rare diseases linked to more than 14.500 signs and 3.270 genes. The application provides a browsing feature to navigate through the relationships between diseases, signs and genes, and some Application Programming Interfaces to help its integration in health information systems in routine.

    • DebugIT


      Detecting and Eliminating Bacteria Using Information Technology Large-scale integrating project

      In half a century of antibiotics use, new challenges have surfaced: the fast emergence of resistances among pathogens and the overuse of antibiotics. Antimicrobial resistance results in escalating healthcare costs, increased morbidity and mortality and the (re-)emergence of potentially untreatable pathogens. For infectious diseases DebugIT

      • detects patient safety related patterns and trends
      • acquires knowledge, and
      • invests this knowledge to upgrade quality healthcare.

      The DebugIT project uses clinical and operational information from Clinical Information Systems (CIS) across the European Union through the view of a virtualized, fully integrated Clinical Data Repository.