Introduction to the ImmunoGrid Simulators Grid Open Days Workshop - PowerPoint PPT Presentation

Introduction to the ImmunoGrid Simulators Grid Open Days Workshop Catania, 23rd January 2009 Adrian Shepherd Birkbeck College University of London

Innate and Adaptive Immunity

Immune System Cell Types Immune System Cell Types

Inside the Cell… Transport, cleavage, presentation, recognition Inside the Cell...

Phases of Adaptive Immunity

Maturation of B and T Cells Maturation of B and T Cells

The Challenge of Complexity • Multi-level (from molecules to organs) • Temporal (seconds to years) • Spatial (signalling and diffusion) Immune System Characteristics • Diversity (molecules, cells, individuals) Key modelling issue: Complexity versus simplification

Cellular Automata Conway’s Game of Life (1970) Cellular Automata Emergence of complex, unpredictable “behaviour” from simple rules

Characteristics of CAs • Simple, local rules • Emergent behaviour Cellular Automata Characteristics Contrast to differential equations: – Individual agents , not average behaviour (enables us to model the life-history of individual cells) – Stochastic (potentially model the distribution of behaviours within a population) – Understandable – Easily extensible

The C-IMMSIM 2D Lattice Agent based model: set of biological agents (cells and molecules) at a given location on lattice interacting probabilistically MHCII B IL-12 T DC Abs TCR MHCI +Pep Ag Tumor M ϕ cell In practice a hexagonal or triangular lattice is often used.

The ImmunoGrid Simulators Lattice-gas cellular automata of increasing complexity B Th The ImmunGrid Simulators CTL MA DC Ag

Modelling Lymph Nodes Towards Models of Lymph Nodes Lymph channel Lymph node Lymph node

Computational Requirements  To run complex single simulations (large cluster or supercomputer)  To run large sets of simulations (explore parameter space, investigate clinical scenarios for multiple individuals)  To support smaller-scale simulations (e.g. educational simulations using standard workstations)

Why Developed Our Own Grid Solution?  Long-term access to national /international production-quality Grids not guaranteed  Consortium partners can contribute own local resources (though no single partner has sufficient resources for whole project)  We believe simple “home-made” Grid now both feasible and effective solution  Provides us with the control and flexibility we desire

Our Grid Implementation Web Interface Job launcher AHE Client VM-Ware DESHL Glite Virtual UI AHE Server UNICORE JSDL JSDL JSDL JDL GridSAM GridSAM GridSAM GATEWAY GATEWAY Web Service FORK RSL NJS PI2S2 Local NGS Local DEISA CINECA Resource Cluster GLOBUS RSL - Resource Specification Language JSDL - Job Submission Description Language NJS - Network Job Supervisor JDL – Job Description Language

The Triplex Vaccine Allo-MHC (H-2 q ) IL-12 p185 neu genes IL-12 HER-2/neu transgenic mouse mammary carcinoma

Vaccination Schedules

Schedules and Tumor Progression

Schedules and Tumor Progression

Schedules and Tumour Progression Summary of experimental evidence

Simulation Reproducing results of in vivo experiments SimTriplex vaccine in virtual mice

Acknowledgements Elsewhere Birkbeck  Vladimir Brusic (scientific coordination:  David Moss formerly U of Queensland, now Dana-Farber)  Mark Halling-  Elda Rossi (CINECA) Brown  Filippo Castiglione (CNR)  Claire Sansom  Santo Motta (U of Catania)  Masters and  Pierre-Luigi Lollini (U of Bologna) PhD students  Marie-Paule Lefranc (IMGT, CNRS)  Søren Brunak, Ole Lund (DTU)