1. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands. Health-grid essentials Peter Sloot University of Amsterdam

2. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands. From Molecule to Man DNAProteinsCellularPharma- ceutical Treatment GenomicsProteomicsImmunology Medical MutationsProtease Reverse Transcriptase CD-4 Experssion # RNA particles Vivo- Vitro- Experimentation Silico- Molecule Time Space 10 -14 sec 10 -10 m Years 10 -1 m Man

3. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands. From Molecule to Man… Molecule Time Space 10 -14 sec 10 -10 m Years 10 -1 m Man First Principle Modeling Genetic Regulatory Networks Metabolic Networks Immunological Networks … Silicon Cell Hierarchical data Modeling G-P-M & Patient Dbases Analytic Molecular Dynamics Monte Carlo Mesoscopic AI – GA’s, NN’s, Fuzzy L.

4. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands. Time Space 10 -14 sec 10 -10 m Years 10 -1 m From Molecule to Man…GRID High Performance Computing => Mesoscopic Simulation High Throughput Computing => Parameter Space Exploration Data Disclosure =>Dbase Federation and Integration Data Fusion => Parameter Transfer Access => Visualization/VR && Roaming and Remote &&PDA

5. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands.

7. What DRIVeS the X# ? Distributed Real-time Interactive Visualization (E) Simulation

8. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands. Goal of WP 1 Applications in health and environment –Data gathering, processing and interpretation in geographically distributed locations –Fast, interactive decision making Interactive access to distributed –Databases –Super computers and High Performance Clusters –Visualisation engines –Medical scanners –Environmental data input devices

9. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands. CrossGrid structure General grid services (a.o. Globus) New grid services (WP 3) Application programming environment (WP 2) Distinct Applications (WP 1) The applications are rooted in the underlying common environment. The more they share, the firmer the stand.

10. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands. A new IST Grid project space (Kyriakos Baxevanidis) GRIDLAB GRIA EGSO DATATAG CROSSGRID DATAGRID Applications GRIP EUROGRID DAMIEN Middleware & Tools Underlying Infrastructures Science Industry / business - Links with European National efforts - Links with US projects (GriPhyN, PPDG, iVDGL, … )

11. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands. Three central functionalities Data gathering –Data generators and data bases geographically distributed –Selected on demand Processing –Needs large processing capacity on demand –Interactive Presentation –Complex data require versatile 3D visualisation –Support interaction and feedback to other components

12. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands. WP 1 structure Task 1.0 Co-ordination & management Task 1.1 Surgery planning & visualisation Task 1.2 Flooding control MIS Task 1.3 HEP data analysis Task 1.4 weather & pollution modelling

13. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands. A Case study from biomedicine...

14. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands. Changing the Paradigm In Vivo In Vitro In Silico

15. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands. Changing the Paradigm In Vivo In Vitro In Silico

16. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands. Changing the Paradigm In Vivo In Vitro In Silico

17. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands. Current Situation Observation Diagnosis & Planning Treatment

18. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands. WP 1.1 Nature March 2002

19. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands. Some Key Data for WP 1.1 New Scanners 1024 x 1024 128 slices of 2 byte depth ==> 256 MByte 10 images per systole = 1 per second

20. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands. Design Considerations High Quality presentation High Frame rate Intuitive interaction Real-time response Interactive Algorithms High performance computing and networking… Distributed Resources and Data

21. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands. Runtime Support Need generic framework to support modalities Need interoperability High Level Architecture (HLA): –data distribution across heterogeneous platforms –flexible attribute and ownership mechanisms –advanced time management

22. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands. Provoking a bit…

23. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands. Experimental set-up MRI, PET Monolith, Cluster Cave, Wall, PC, PDA

24. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands. Immersive Environments

25. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands. 3D Information and Interaction

26. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands. Architecture GRIDWARE

27. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands. Simulation Based Planning and Treatment Diagnostic Findings –Occluded right iliac artery –75% stenosis in left iliac artery –Occluded left SFA –Diffuse disease in right SFA

28. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands. Methods - MR Imaging MR Scan of AbdomenMR Scan of Legs

29. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands. Methods - Geometric Models

30. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands. VR-Interaction

31. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands. Alternate Treatments Angio w/ Fem-Fem & Fem-Pop AFB w/ E-S Prox. Anast. Angio w/ Fem-Fem AFB w/ E-E Prox. Anast. Preop Courtesy Prof. C. Taylor

32. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands. Flow through complex geometry After determining the vascular structure simulate the blood-flow and pressure drop… Conventional CFD methods might fail: –Complex geometry –Numerical instability wrt interaction –Inefficient shear-stress calculation

33. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands.

34. Velocity Magnitude 10 cm/sec 0 cm/sec

35. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands. Peak Systolic Pressures – Rest 150 mmHg 50 mmHg Angio w/ Fem-Fem & Fem-Pop AFB w/ E-S Prox. Anast. Angio w/ Fem-Fem AFB w/ E-E Prox. Anast. Preop

36. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands.

38. T.S. Elliot ‘How much wisdom has been lost in knowledge and how much knowledge has been lost in information...’ How much Information has been lost in Data!!

39. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands. New Possibilities Fast, High-throughput Low Latency Internet High Performance Super Computing Time and Space Independence 3D Information Simulation based planning Surgeon ‘in the loop’

40. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands.

42. The silicon cell: towards computing living cells

43. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands. From cells to molecules

44. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands. Mesoscopic modelling of living cells Models of genetic regulatory networks and spatio-temporal gene expression Models of biochemical pathways and reactivity at complex-shaped membranes models of spatial structures: membranes, cytoskeleton, chromatin, aggregates of cells,.....

45. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands. Development of morphogen gradients in time (left) and regulatory network for segment specification in Drosophila (Carroll,2001)

46. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands. Model for a genetic network and the formation of patterns of morphogens in linear row of cells (Salazar-Ciudad, 2001)

47. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands. The glucose phospho transferase system (PTS) in E. coli

48. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands. Example: modelling uptake and metabolism of glucose by PTS at the membrane

49. Peter Sloot: Computational Science, University of Amsterdam, The Netherlands. Towards computing living cells Van Kampen, Amsterdam Medical Centre Westerhoff, Free University of Amsterdam Blom & Peletier, Centre for Mathematics and Computer Science, Amsterdam