Grilles informatiques en Europe, des sciences de la vie à la santé

Grilles informatiques en Europe, des sciences de la vie à la santé V. Breton Journée Génopôle IRISA

Le concept d’infrastructure de grilles (1/2) • Internet met à disposition des informations… • L’utilisateur doit tout faire lui-même • Mettre en forme les informations à partager (site web) • Identifier, trier, analyser les données disponibles • Limites : compétence, stockage, puissance de calcul • Evolution : sites web offrant des services spécialisés • Limitations : ressources du site (compétence, CPU, stockage) • Notion d’infrastructure de grille : permettre à des communautés d’utilisateurs de partager des ressources de calcul et de stockage et des services • Mutualisation des compétences, du calcul et du stockage • Traitement de l’information, Sécurité

Le Concept (2/2) • Une infrastructure de grille informatique permet à des communautés d’intérêt de partager de façon dynamique des ressourcesinformatiques distantes et distribuées géographiquement pour le stockage de gros volumes de données et pour accroître les puissances de calcul • Une infrastructure de grille informatique comprend un ensemble hétérogène de calculateurs, de moyens de stockage, voire d ’instruments de mesure reliés entre eux par un réseau à haut débit et grâce à un middleware. Elle offre aux utilisateurs un accès aisé, transparent et sûr à l’ensemble de ces ressources hétérogènes.

Grid technology is promisingfor both computing intensive applications and knowledge discovery • To connect databases of heterogeneous content (biology and medicine) enabling new knowledge discovery (research, drug design), better guidance and information (healthcare professionals) • To increase computing power for analysis, imaging, simulation and modelling thus allowing these fields to take into account more data and therefore to provide more accurate results. • To address security (integrity, confidentiality, authentication, authorization, non-repudiation, availability)

The challenges of a life science grid • Technical challenges • data and tools integration : address data heterogeneity and legacy of tools and standards • provide the infrastructure to deploy biomedical applications in a grid environment • Human challenge : involve end users in the grid game • Grids are still very much in development and therefore user-unfriendly • Training and support to university hospitals, biology/medecine research centres

Projets de grille en bioinformatique • Projets nationaux en Europe • France : GenoGRID, GRIPPS, Rugbi • UK e-science : Mygrid • Hollande : BioASP • … • Projets américains : • Encyclopedia of Life (EOL) • North Carolina Biogrid project http://www.ncbiogrid.org/ • … • Projets en Asie : • Japon : OBIGrid, http://www.obigrid.org • Projets européens • DataGrid (FP5) • EGEE (FP6) • Embrace (soumis en Novembre 2003) • …

Phylojava, web portal for phylogeneticson DataGrid Bootstrapping : procedure to compute a consensus from a large number of independent phylogenetic tree calculations Crédit : T. Silvestre, BBE Lyon http://pbil.univ-lyon1.fr/phylojava

Exemple de prise en charge de 450 jobs sur DataGrid Nombre de jobs Temps en minutes Crédit : T. Silvestre, BBE Lyon

The Encyclopedia of Life (EOL)http://eol.sdsc.edu/ • Collaborative global project designed to catalog the complete proteome of every living species in a flexible reference system. • Open collaboration led by the San Diego Supercomputer Center • Three major development areas: • Creating protein sequence annotations using the integrated genome annotation pipeline (iGAP). • Storage of these annotations in a data warehouse where they are integrated with other data sources • A toolkit area that presents the data to users in the presence of useful annotation and visualization tools.

Mygrid • myGrid offers service based middleware components • Open source and free • Open Grid Service Architecture-compliant • Allows the scientist to be at the centre of the Grid -- Personalisation • Generic middleware that suits the creation of bioinformatics applications • Inclusion of rich semantics to facilitate the scientific process • 42 months, 20 months in. • Available from http://www.mygrid.org.uk • Prototype V0 technical and user requirements • Prototype V1 Release Sept 2004, some services available now.

Les futurs projets en Europe • EGEE : infrastructure de production pour la recherche • Suite de DataGrid • 70 partenaires autour du CERN • 32 Millions d’Euros • Démarrage en Avril 2004 • Domaines applicatifs privilégiés : Physique des particules et biomédical • Embrace : proposition de réseau d’excellence • 17 partenaires autour d’EBI • Developper les API pour intégrer les données biologiques et les outils bioinformatiques dans un environnement de grille • Soumis au 2ème appel (Nov. 2003)

Health + Grid = HealthGrid Health: All levels of data & information, from molecule to population needed to ensure better prevention, diagnosis and treatment of the citizen. Grid: An environment, created through the sharing of resources, in which heterogeneous and dispersed data as well as applications can be accessed by different partners according to their authorisation, without loss of information.

HealthGRID Patient related data PublicHealth Association Modelling Computation Databases Public Health Patient Patient Tissue, organ Tissue, organ Cell Cell Molecule Molecule INDIVIDUALISED HEALTHCARE MOLECULAR MEDECINE Computational recommandation Draft Ideas, September 2002 S. Nørager Y. Paindaveine DG-INFSO

A recent example of the potential grid impact • Last summer heat wave killed more than 10000 people in France • Mortality rate in excess of 10 to 50% in retirement homes and hospitals unnoticed for 2 weeks • A monitoring system could have raised the alarm much earlier • Requirements : collect information from hospitals and/or funeral services on the number of casualties • Internet can do it through a centralized web portal • Grid added value : database federation (data left in hospitals, à la BIRN) + a grid service for mortality rate computation and monitoring • Grid technology allows to do it today…

enter Grid enter Grid enter Grid enter Grid CE UI UI WN WN WN WN WN WN Conception d’une grille Machines de stockage de données (images radiologiques) Ordinateurs du médecin SE SE - PKI X.509 certificate keys - JDL files RB/II Machines de calcul

Allow every physician to access a reliable grid for his daily practice New actors : hospitals, physicians, healthcare administrations, big pharmas, SMEsTechnical issues Networking, User interface Grid quality of services (stability, scalability, security,…) Legal/ethical issues : obey the laws of the European countries with respect to personal data ownership and data transfer The challenges of an healthcare grid Grid technology is not ready yet to address all these challenges, but It is time to build bridges towards this vision

In silico drug discovery • Goal : speed up the cycle for drug discovery • Challenge : bridge gaps in the translation of basic research through to drug development from the public to the private sector and in the feedback from the private sector of their results • The grid impact : • high performance computing and data storage for massive docking • Collaborative environment for searching new targets and sharing results while respecting privacy • Short term perspective : a grid for neglected disease • Non profit drug discovery in a grid environment • Technical issues : security, data management

Multi-site therapy monitoring • Goal : reduce time and cost to launch a drug on the market (100 million euros and 10 years) • Challenge : improve monitoring of multi-site clinical trials • The grid impact : moving away from a single centralized repository • Technical issues : security, data management

Intensity Modulated Radiation Therapy • Goal : deliver a variable fluence (number of particles per unit square) using complex geometries adapted to the tumoral volume depending on the beam incidence • Challenge : necessity to simulate treatment through inverse dosimetry for each incidence of the beam and geometry of the multi-lames collimator and validate the dose delivered to the patient • 30 beams x 2 minutes = 1 hour for each iteration of treatment validation • The grid impact : parallel execution of the different beam configurations on a cluster • Reduce time needed for treatment planning and increase number of patients • Technical issues : security, quality of service

Some health related FP5 grid projects in Europe Perform a trial for the introduction of the Grid approach in the biotechnology industry Biomolecular simulations

GEMSS:GRID-enabled Medical Simulation Services Project Duration: 30 months, Commencement: 1.9.2002 Grid Software /solutions Simulation/Imaging Software Bio-numeric modelling Medical Expertise Legal Aspects http://www.gemss.de

GEMSS - main goals Main GEMSS Goals: • Secure and lawful Grid provision of medical simulation services, • Build 6 Grid-enabled medical prototype applications, • Build suitable middleware on top of common standards, • Install and evaluate a GEMSS test-bed, • Anticipate privacy, security and other legal concerns related to providing medical services over the Internet.

GEMSS -Technical Goals & Challenges Necessary Assumption: No special purpose network infrastructure Appropriate User Interfaces & Applications Workflow • Workflow Enactor • Negotiation • Business Processes Negotiated Service Provision • Secure Transfer, Web Services Security, Logging

GEMSS - outlook Status of Work: • GEMSS has finalised its design phase: client-server arch. based on web services (OGSA-compliant). • Outlook: prototype system – Feb. 2004 final GEMSS system – Aug. 2004 • Contribution to Standardisation: GEMSS is assessing its involvement in GGF, IETF or W3C. Final Strategy has yet to be decided.

La téléradiologie aujourd’hui: une solution à améliorer « Il ne suffit pas qu’un système de téléradiologie soit techniquement performant ni légalement installé pour garantir son succés pratique » Franken et coll. Les difficultés mises à nu: Expérience de téléradiologie entre 1992 et 1995 entre un hôpital rural de l’Arkansas et des radiologues universitaires de Iowa City (USA) • Délai constaté pour une interprétation d’image radiologique trop long (24 à 96h) • Les comptes rendus de téléradiologie mal adaptés • Nombreux problèmes de communication orale ou écrite, en particulier sur: • La qualité des images • Les renseignements cliniques

eDiamond Digital Mammogram National Database • Fédérer des bases de données de mammographies • Aider au programme de détection du cancer du sein au Royaume Uni • Buts: • Outil d’apprentissage pour les radiologues: e-learning • Support au télédiagnostic • Outils pour l’aide au data mining et à l’épidémiologie • Outils pour contrôle de qualité automatisé

Le dépistage du cancer du sein au Royaume Uni Aujourd’hui Demain Digital Papier Digital Film 2,000,000 – examens chaque année 120,000 – Rappelées pour 2ème contrôle 10,000 – Cancers détéctés 1,250 – vies sauvées par an 1.5M - examens en 2001-02 65,000 – Rappelées pour 2ème contrôle 8,545 – Cancers détectés 300 – vies sauvées par an 230 - Radiologues “Double Lecture” 50% - Croissance examens 230 – Radiologues “Double Lecture”

Le principe Données DICOM DICOM DICOM DICOM Calcul Standard Mammo Format CADe CADi Data Mining Patient Age … Image 107258 55 … 1.dcm 236008 62 … 2.dcm ……… ……… 700266 ……… ……… ……… ……… ……… ……… 59 … … … … … … … … … … … … … … … … … …….. …….. 3.dcm …….. …….. …….. …….. …….. …….. 895301 58 … 4.dcm Metadata Images Grille 92 centres de dépistage du cancer du sein Logical View is One Resource Challenge: La normalisation des images De nombreux paramètres influence l’apparence des images Distribution de densité des tissus, tumeurs, microcalcifications Voltage, temps d’exposition…… Solution : SMF Standard Mammogram Form

Haut gauche: Image cranio-caudale(plus contour du sein et marques Haut droit: Image médio-latérale oblique Bas: Galerie d’images disponibles Haut gauche: reconstruction 3D montrant la localisation de la tumeur Bas gauche: SMF vue des différentes densités de surface Droite :image normalisée

MammoGrid –European federated mammogram database implemented on a GRID infrastructure Main goals: • Epidemiology of breast cancer from a European perspective • Open source architecture • Use of Grid in developing quality control techniques for breast cancer screening • Development of some CADe techniques http://lotus5.vitamib.com/hnb/mammogrid/mammogrid.nsf/Web/Frame?openform

Hospital Italy University Database Local Query Local Query Local Query Local Query Healthcare Institute Local Analysis Local Analysis Local Analysis Local Analysis Hospital UK MammoGrid -Federated System Solution Query Result GRID Clinician’s Workstations Massively distributed data AND distributed analyses • Knowledge is stored alongside data • Active (meta-)objects manage various versions of data and algorithms • Small network bandwidth required Shared meta-data Analysis-specific data

MammoGrid -Grid challenges: database • Large federated databases • Images and metadata • Ontologies and metadata • Image formation parameters • Image features • Clinical information • Demographic data • Effective data mining of a rapidly growing database • Allow for complex queries involving executables • Medical image analysis clients are not Grid experts!

MammoGridGrid challenges: communications • Legal restrictions on access to data • Clinicians, researchers, developers, Govt, … • Data resides in hospitals • Firewall protected • Combining several databases • Secure file transfer • Large images to be transferred • Develop API for black box third party applications

Grids for medical development Preparation and follow-up of medical missions in developing countries Support to local medical centres in terms of second diagnosis, patient follow-up and e-learning Clermont-Ferrand/Paris Patient data Request for 2nd diagnostic Second diagnostic Patient follow-up Interactive e-learning Video-conferences Patient data consultation Chuxiong Request for second diagnosis • The grid impact : • Improved telemedecine services • Federation of patient databases • Interactive e-learning (high bandwidth network required) Ibagué Hand surgery Medical centre 2 missions (Ibagué & Chuxiong) with the french NPO « Chaîne de l’Espoir » used as test cases

deployed tested on EDG under preparation DataGrid : status of biomedical applications • Bio-informatics • Phylogenetics : BBE Lyon (T. Sylvestre) • Search for primers : Centrale Paris (K. Kurata) • Bio-informatics web portal : IBCP (C. Blanchet) • Parasitology : LBP Clermont, Univ B. Pascal (N. Jacq) • GRID platform for DNA microarray data analysis: Karolinska (R. Martinez) • Geometrical protein comparison : Univ. Padova (C. Ferrari) • Medical imaging • MR image simulation : CREATIS (H. Benoit-Cattin) • Medical data and metadata management : CREATIS (J. Montagnat) • Mammographies analysis ERIC/Lyon 2 (S. Miguet, T. Tweed) • Simulation platform for PET/SPECT based on Geant4 : GATE collaboration (L. Maigne)

Simulation Monte-Carlo sur grille Objectif : accélérer l’exécution de codes Monte-Carlo Méthode : étudier l’impact du déploiement sur grille de calculs Monte-Carlo Parallélisation étudiée : soumission de tâches avec des graines indépendantes GATE , plate-forme de simulation Pour l’imagerie médicale nucléaire et la curie/radiothérapie Credit : D. Hill L. Maigne R. Reuillot

Impact du déploiement sur le temps de calcul Variation du temps de calcul en fonction du nombre de tâches soumises en parallèle Variation du temps de calcul en fonction du jour du mois pour 100 tâches soumises en parallèle. Credit : D. Hill L. Maigne R. Reuillot

Simulated vascular reconstruction Goals • Supports the vascular surgeon in placement ofbypasses and stents • Predicts blood flow before operation • Geometry obtained from medical scans • Add the proposed intervention Method • Interactive Virtual Reality Environment to • View scanned data • Define proposed interventions • View simulation results • Advanced fluid code to simulate flows • Grid for data access and computational resources

eHealth FP6 : the opportunities of a new paradigm Research infrastructures and testbeds • From pilot to production grid infrastructures (EGEE,…) committed to provide to users communities • Training • User support • Access to resources • Need for collaborations with NoE and grid projects in the eHealth area to deploy large scale applications • Feedback eHealth specific requirements to middleware developers eHealth Grids for complex Problem solving

eHealth To widen the impact of the healthgrid cluster, the Healthgrid association • To disseminate information on grids for health • Summaries and links to health related grid projects • Available tools (software platforms, middleware,…) • Tutorials • Conferences • To foster exchange between projects, end users and technology developers • To avoid reinventing the wheel • To improve the take-up of grid technology • To promote standards • Involvement in GGF Life Science Research group • Open to any new member • Contact point : Y. Legrè (legre@clermont.in2p3.fr) • Web site : http://www.healthgrid.org

eHealth Healthgrid conferences • Jointly organised by CERN, CNRS and EMBnet in collaboration with the eHealth unit DG-INFSO • Meeting point for actors of grids for health • End users = healthcare professionals / providers + academic & industrial researchers and developers from bio-informatics and medical-informatics • Grid applications developers • Technology developers • First conference in Lyon (January 2003) • Next conference in Clermont-Ferrand (January 29-30 2004)

eHealth HealthGrid 2004 January 29th - 30th 2004, Clermont-Ferrand, France http://clermont2004.healthgrid.org The aims of this conference are to reinforce and promote awareness of the possibilities and advantages linked to the deployment of GRID technologies in health. In this context "Health" does not involve only clinical practice but covers the whole range of information from molecular level (genetic and proteomic information) through cells and tissues, to the individual and finally the population level (social healthcare).

Conclusion • Des grilles pilotes (FP5) aux grilles d’exploitation pour la recherche (FP6) • Grilles en bioinformatique • Premiers portails prototype utilisant des grilles pour le calcul distribué • Projets de plate-forme pour déployer des expériences • A faire : gestion des données hétérogènes distribuées (-> Embrace) • Grilles pour la santé • Projets pilotes au niveau national et européen • Initiative Healthgrid pour créer une communauté ( informaticiens, utilisateurs de grille, acteurs du monde de la santé)

goal : provide a GRID platform for DNA microarray data analysis and Gene Regulation Bioinformatics that permit predictions of involvement of genes in the pathogenesis of human diseases.

Grilles informatiques en Europe, des sciences de la vie à la santé