ImmunoGrid – The Virtual Human Immune System Project

1. ImmunoGrid – The Virtual Human Immune System Project Andrew Emerson, High Performance Systems, CINECA, Italy

2. ImmunoGrid: Definition “…a 3 year project funded by the European Union which will establish an infrastructure for the simulation of the immune system that integrates processes at molecular, cellular and organ levels.” To be designed for applications that support clinical outcomes such as design of vaccines and immunotherapies and optimization of immunization protocols.” The result will be a “simulator” which will allow us to model the human immune system on the natural scale. http://www.immunogrid.org

3. The Consortium Expertise • CINECA, Bologna. • University of Queensland. • CNR, Rome. • CNRS, Montpellier. • Technical University of Denmark • Birkbeck College, University of London. • Dept of Experimental Pathology,University of Bologna. • University of Catania, Catania. http://www.immunogrid.org

4. The Human Immune System • A complex and adaptive learning system which has evolved to defend an individual against foreign invaders. • Operates at multiple levels: from molecule to cell, organ and organism • Some cells exist in many forms which differ in their specificities: • >1013 MHC class I haplotypes • 107-1015 different T-cell receptors • 1012 B-cell clonotypes in each individual • 1011 possible linear MHC-binding epitopes composed of nine amino acids • >>1011 different conformational epitopes • >109 combinatorial antibodies combinatorial complexity http://www.immunogrid.org

5. Immunomics: Successes and failures Vaccines have been instrumental in controlling many diseases • Eradication of smallpox • Near eradication of polio But many diseases are still poorly protected against • e.g. failure of the BCG vaccine against TB in some communities http://www.immunogrid.org

6. Why model the Immune System ? In particular why on the natural scale ? • Computer models complement and replace actual testing or experiments • Experimentation is expensive and has limitations: • some experiments cannot be performed • number of experiments that can be performed • time-scale (e.g. HIV infection) • ethical concerns (e.g. there are strict rules as what experiments can be performed in humans) http://www.immunogrid.org

7. Models We use agent-based models derived from the ImmSimm program of Celada-Seiden: HIV-1 infection C-ImmSimm (Castiglione et al) ImmSimm (Celada et al.) cancer immuno-prevention vaccines SimTriplex (Catania Mouse model) (Pappalardo et al.) describes the immune system entities with their different biological states and the interactions between different entities http://www.immunogrid.org

8. Self-peptides Antigens non-self Thymus Th, CTL Virus, bacteria, … Thymocytes B Th T CTL MA DC Ag Bone marrow All cells B, MA, DC, … Simulation space (secondary organ) Modelling the immune system Positive/Negative selection http://www.immunogrid.org

9. Infection site Lymph node Lymph channel Modelling the Immune System These models have proved to be very successful in reproducing the progress of AIDS or tumour progression in vivo experiments of HER2/neu transgenic mice. They have also been extended by the consortium since the start of the project, e.g. to allow chemotaxis (i.e. diffusion along a chemical gradient) or 3D simulation spaces. http://www.immunogrid.org

10. Modelling the Immune System – computational requirements Simple cases can run on a pc in mins but our project aims to go much further: • timestep from 8h → mins (for allergies) • timesteps from 103 → 108 • no. of entities from 104 → 1015 • increase simulation time from 1 yr (mouse) → many yrs (e.g. human) • more complex simulation spaces (e.g. representing real organs) • from 1 to many individuals for population analysis The aim is to reach the natural scale of the human immune system. http://www.immunogrid.org

11. Motivation for the Grid Need for high computational power to match the combinatorial complexity and natural scale of the human immune system. Comment: The programs have been parallelised, why not just use a parallel computer ? http://www.immunogrid.org

12. Motivation for the Grid • Distribute simulations • Allow exploration of parameter space • Access the consortium’s geographically distributed resources • Access to large machines for computationally expensive simulations • Not limit ourselves to one solution. e.g super computer • Cannot guarantee access to super computer • Different levels of usage, some not relevant for a supercomputer. http://www.immunogrid.org

13. Motivation for Grid We anticipate different levels of access to the simulator which will vary the computational requirements of the simulator. Small, computationally inexpensive simulations. Complex GRID solution unnecessary. Web services more appropriate. Educational Larger, computationally expensive simulations. GRID solution required to distribute simulations around available resources. Standard Large, computationally expensive simulations. GRID solution required. Access to super computer desirable. Developer http://www.immunogrid.org

14. Grid infrastructure - concepts What our grid will not do: • No attempt to distribute a single simulation over different grid nodes (too difficult) • No attempt to design new middleware • we will use existing solutions • No attempt to install the same middleware on each node • partners’ resources too diverse and may violate local policies. http://www.immunogrid.org

15. Grid infrastructure - concepts What our grid must do: • Able to integrate seamlessly the available resources, modifying as little as possible local infrastructures and policies. • Must conform to standards. • Allow the different types of usage, including access to supercomputers and other Grids. • Single point of access and easy-to-use graphical interface (essential for educational purposes) Our grid will be a kind of “virtual organisation” and user-driven http://www.immunogrid.org

16. Grid implementation We are still in the design phase but we intend to utilise and amalgamate multiple different GRID solutions GridSAM AHE This approach will provide flexibility and redundancy http://www.immunogrid.org

17. Grid Implementation - resources http://www.immunogrid.org

18. Web Interface Job launcher AHE Client UNICORE AHE Server JSDL GridSAM GridSAM GridSAM GATEWAY GATEWAY GridSAM FORK FORK RSL NJS Web Service Group Local NGS Group Cluster DEISA CINECA GLOBUS Proposed GRID Implementation CINECA e.g Birkbeck college http://www.immunogrid.org

19. Interfaces Web interface will provide access to simulations. One interface will serve each level of access. Educational General interface Standard Job Launcher Developer Job Launcher could act as a simple brokering agent http://www.immunogrid.org

20. Application Hosting Environment Web Interface Job launcher AHE Client UNICORE AHE Server JSDL GridSAM GridSAM GridSAM GATEWAY GATEWAY GridSAM FORK FORK RSL NJS Web Service Group Local NGS Group Cluster DEISA CINECA GLOBUS http://www.immunogrid.org

21. Application Hosting Environment http://www.immunogrid.org

22. UNICORE Web Interface Job launcher AHE Client UNICORE AHE Server JSDL GridSAM GridSAM GridSAM GridSAM GATEWAY GATEWAY FORK FORK FORK RSL Web Service Group Local NGS Group Local DEISA CINECA GLOBUS UNiform Interface to COmputing Resources http://www.immunogrid.org

23. UNICORE • Allows access to: • DEISA • CINECA (Linux and IBM SP clusters) • OGSA middleware (WSDL & SOAP based web services) http://www.immunogrid.org

24. Summary We are now entering a critical phase in the project as work begins on realising the principal objective, i.e. the virtual human immune system simulator. The details of the Grid implementation is still being discussed but the overall strategy is clear. Please see www.immunogrid.org for information and if you wish to try out educational versions of the simulators. Feedback is very welcome! http://www.immunogrid.org

25. Acknowledgments All partners and associate members of the ImmunoGrid consortium. The European Union for financial support. http://www.immunogrid.org