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

Présentation au sujet: "Grilles informatiques en Europe, des sciences de la vie à la santé V. Breton Journée Génopôle IRISA."— Transcription de la présentation:

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

3 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

4 Le Concept (2/2) Une infrastructure de grille informatique permet à des communautés d’intérêt de partager de façon dynamique des ressources informatiques 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.

5 Grid technology is promising for 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)

6 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

7 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/http://www.ncbiogrid.org/  … Projets en Asie :  Japon : OBIGrid, http://www.obigrid.orghttp://www.obigrid.org Projets européens  DataGrid (FP5)  EGEE (FP6)  Embrace (soumis en Novembre 2003)  …

8 Phylojava, web portal for phylogenetics on 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

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

10 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 CenterSan 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.

11 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.ukhttp://www.mygrid.org.uk  Prototype V0 technical and user requirements  Prototype V1 Release Sept 2004, some services available now.

12 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)

13 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.

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

15 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…

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

17 Allow every physician to access a reliable grid for his daily practice New actors : hospitals, physicians, healthcare administrations, big pharmas, SMEs Technical 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 Grid technology is not ready yet to address all these challenges, but It is time to build bridges towards this vision The challenges of an healthcare grid

18 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

19 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

20 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

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

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

23 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.

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

25 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.

26 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:  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 Expérience de téléradiologie entre 1992 et 1995 entre un hôpital rural de l’Arkansas et des radiologues universitaires de Iowa City (USA)

27 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

28 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” Film Papier 230 - Radiologues “Double Lecture” 50% - Croissance examens 2,000,000 – examens chaque année 120,000 – Rappelées pour 2ème contrôle 10,000 – Cancers détéctés 1,250 – vies sauvées par an Digital Aujourd’huiDemain Le dépistage du cancer du sein au Royaume Uni

29 MetadataImages Logical View is One Resource Grille Patient Age … … Image 107258 55 … … 1.dcm 236008 62 … … 2.dcm 700266 59 … … 3.dcm 895301 58 … … 4.dcm ……… … … … … …….. ……… … … … … …….. ……… … … … … …….. ……… … … … … …….. ……… … … … … …….. ……… … … … … …….. ……… … … … … …….. ……… … … … … …….. Données DICOM Calcul Standard Mammo Format Standard Mammo Format Data Mining Data Mining CADe CADi CADe CADi 92 centres de dépistage du cancer du sein 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 Le principe

30 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

31 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

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

33 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!

34 MammoGrid Grid 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

35 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 2 missions (Ibagué & Chuxiong) with the french NPO « Chaîne de l’Espoir » used as test cases Ibagué Hand surgery Medical centre Clermont-Ferrand/Paris Chuxiong The grid impact : Improved telemedecine services Federation of patient databases Interactive e-learning (high bandwidth network required) Request for second diagnosis Patient data consultation Second diagnostic Patient follow-up Patient data Request for 2nd diagnostic Interactive e-learning Video-conferences

36 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) deployed tested on EDG under preparation

37 Simulation Monte-Carlo sur grille Credit : D. Hill L. Maigne R. Reuillot 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

38 Impact du déploiement sur le temps de calcul Credit : D. Hill L. Maigne R. Reuillot 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.

39 Simulated vascular reconstruction Goals Supports the vascular surgeon in placement of bypasses 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

40 FP6 : the opportunities of a new paradigm 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 Research infrastructures and testbeds eHealth Grids for complex Problem solving eHealth

41 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)legre@clermont.in2p3.fr  Web site : http://www.healthgrid.org eHealth

42 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

43 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). eHealth

44 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)

45 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.