Dr. Siegfried Neumann-jm: SiSIS, Sept Page 1 Systems of Life - Systems Biology Network Activities on Systems Biology A.Hepato Sys B.International Initiatives Presentation by Gisela Miczka 1, Roland Eils 2 and Siegfried Neumann 3 1 Projektträger Jülich, Jülich, Germany  2 German Cancer Research Center, Heidelberg, Germany  3 MERCK KGaA, Chemical Section R+D, Darmstadt, Germany NiSIS Symposium, Portugal, October 2005

Dr. Siegfried Neumann-jm: SiSIS, Sept Page 2 Outline A.Hepato Sys – The German Initiative on Systems Biology of Human Hepatocytes The Design of the Programme Goals, Structure and Projects Coordination and Project Management, Websites B.International Initiatives in System Biology Systems Biology for Drug Research International Crosslinks Commercial Suppliers

Dr. Siegfried Neumann-jm: SiSIS, Sept Page : How to establish a BMBF funded national research network on Systems Biology Start of the „design-process“: Discussion forum with a multidisciplinary team of 9 leading scientists to develop a funding strategy. The key criteria are  medium to long term research programme  synergy with existing BMBF funded research programmes in Genomics and Proteomics  considers the international status of the art  reckognizes international standards and contributes to them

Dr. Siegfried Neumann-jm: SiSIS, Sept Page 4 Expert panelstructuring thematic priority recommendations core expert panel (9) documentation informations elicit thematic topic funding- strategies WS 1WS 2WS 3WS 4 data-screening, conferences, interviews external expert panel (>70) March 2001 December 2001 NovemberMayJulySeptember „Systems of Life - Systems Biology“ The Design-Process

Dr. Siegfried Neumann-jm: SiSIS, Sept Page 5 Goal of the Systems Biology Initiative on Hepatocytes (HepatoSys) The long-term goal of this systems biology approach is to understand the dynamic processes in a human cell and to build up mechanism-based mathematical models of these processes in order to predict the behaviour of the system under defined conditions.

Dr. Siegfried Neumann-jm: SiSIS, Sept Page 6 high complexity of mammalian cells human diffentiated cells are not easy to handle and not easy to cultivate while keeping differentiation and metabolic properties simular to in vivo living cells the mathematical tools for modelling of cellular dynamics and systems analysis basically are not developed for complex systems Aim to overcome the obstacles in order to do systems biology on a medically relevant cell type. ! Challenges

Dr. Siegfried Neumann-jm: SiSIS, Sept Page 7 The Approach Set up an interdisciplinary competence network linking bioscience with computer science, mathematics and engineering sciences Start with studies on defined biological functions Establish standardized cells, methods, and tools

Biology Systems Engineering Bioinformatics Mathematics Tools (HTS) Systemic Behaviour Algorithms Software Databases Systems Biology biological models generation of quantitative data, anlysis of functional relations; tool development modelling (study on regulation, structure, robustness, etc. of system) establishment of databases, development of in silico models and software

Dr. Siegfried Neumann-jm: SiSIS, Sept Page 9 Why Hepatocytes? Attractivity central functions in metabolism (for lipids, carbohydrates, amino acids …) central role in the uptake and conversion of drugs (transport, metabolic conversions, detoxification...) regeneration ability i. e. high impact on problems in pharmacology and pathophysiology

Dr. Siegfried Neumann-jm: SiSIS, Sept Page 10 Structure of the National Competence Network HepatoSys Platform Cell biology Platform Modeling Coordinating Committee Steering Committee Collaborative Network “Regeneration” Project Management Collaborative Network “Detox/Dediff.”

Dr. Siegfried Neumann-jm: SiSIS, Sept Page 11 Members of the Steering Committee Prof. Dr. Dieter Oesterhelt, MPI for Biochemistry Munich (chairman) Dr. Roland Eils, DKFZ Heidelberg Prof. Dr. Joseph Heijnen, Technical University of Delft, NL Prof. Dr. Karl Kuchler, Institute for Medical Biochemistry, University of Wien, AU Prof. Dr. Siegfried Neumann, Merck KGaA Darmstadt, Senior Consultant R+D Prof. Dr. Hans V. Westerhoff, Molecular Cell Physiology & Mathematical Biochemistry, BioCentrum Amsterdam, NL

Dr. Siegfried Neumann-jm: SiSIS, Sept Page 12  call for project proposalsDecember 2001  number of proposals40  start of the research workJanuary 2004 under this programme  first funding period15 Mio. € /3 years collaborative projects 2 platform projects: cell biology3 modeling3 number of partners 25 Facts on the Starting Phase

Dr. Siegfried Neumann-jm: SiSIS, Sept Page 13 The Project Committee on HepatoSys Dr. Jens Timmer, University Freiburg (chairman) Prof. Dr. –Ing. Matthias Reuss, University Stuttgart Prof. Dr.-Ing. Ernst-Dieter Gilles, MPI for Komplex Technical Systems, Magdeburg Prof. Dr. Augustinus Bader, Biomedizinisch- Biotechnologisches Zentrum, Leipzig

Dr. Siegfried Neumann-jm: SiSIS, Sept Page 14 Main Objectives of HepatoSys Network on detoxification and dedifferentiation in hepatocytes (Speaker: Prof. Reuss, Univ. Stuttgart-Hohenheim) Network on regeneration of hepatocytes (Speaker: Dr. Jens Timmer, Univ. Freiburg) Platform Cell biology: Development of new cells, of optimized culture conditions, of high throughput technology and supply of cells for the projects in the national network (Speaker: Prof. Bader, Univ. Leipzig) Platform Modeling: Development of bioinformatics and mathematical tools for data management, data handling etc. and service for the projects of the national network (Speaker: Prof. Gilles, MPI Magdeburg)

Dr. Siegfried Neumann-jm: SiSIS, Sept Page 15 The Network on Detoxification / Dedifferentiation Detoxification Cytochrome P 450 isoforms Molecular dynamics Kinetic experiments Polymorphisms Dedifferentiation Change of metabolic pathways during dedifferentiation

Dr. Siegfried Neumann-jm: SiSIS, Sept Page 16 The Network on Regeneration Background Liver regeneration is a highly regulated process Goal Understanding the pathways involved Method Data-based mathematical models Long term goal Support development of liver cell lines

Dr. Siegfried Neumann-jm: SiSIS, Sept Page 17 The Cell Biology Platform Distributing Standardized Cell Material Primary hepatocytes (man, mouse, rat) Isolation protocol, culturing, starving & stimulation following SOPs Developing Human Cell Lines Based on Conditionally immortalized cells Somatic stem cells Bioreactors with controlled microenvironment

Dr. Siegfried Neumann-jm: SiSIS, Sept Page 18 The Modeling Platform Work out concepts on central data management Develops algorithms and software for modeling Supply project partners of the biology networks with project-specific tools in systems theory Develop integrated systems biology research on their own concepts

Dr. Siegfried Neumann-jm: SiSIS, Sept Page 19 Geographic Distribution of the Projects

Dr. Siegfried Neumann-jm: SiSIS, Sept Page 20 Coordination of the Competence Network Systems Biologe Secretarial office for the BMBF Funding Initiative „Systems for Life – Systems Biology“ at University of Freiburg (Dr. Timmer‘s office) Flyer, Brochures, Articles, Poster... Webpages, Internet Representation... Public Relation with Journalists and Media Conference Visits and Reports Scientific Coordination of Interdisciplinary Research Groups

Dr. Siegfried Neumann-jm: SiSIS, Sept Page 21 Project Management for the Competence Network Systems Biology Workshop – Partnering, Kick-Off Workshops, Annual Status Workshops (last one on April 28 to 29, 2005, next in November 2005) Conference Organization by DECHEMA e.V.– Conference Office for the 5 th International Conference on Systems Biology, October 9 –13, 2004 in Heidelberg Coordination of due diligance, contracting and implemen- tation for a Central Data Management for the funding Initiative Systems Biology Organizing the Scientific Report Systems for PTJ, BMBF, and Steering Committee

Dr. Siegfried Neumann-jm: SiSIS, Sept Page 22 Websites Federal Ministry of Education and Research PTJ – the Project Management Organisation Jülich Competence Network Systems Biology The Database for Systems Biology Researchers

Dr. Siegfried Neumann-jm: SiSIS, Sept Page 23 Systems Biology – The Concepts Systems biology integrates the molecular parts list into quantitative models of biological functions Kitano, H. Science 295, 1662 (2002): “To understand biology at the system level, we must examine the structure and dynamics of cellular and organismal function, rather than the characteristics of isolated parts of a cell or organism.”

Dr. Siegfried Neumann-jm: SiSIS, Sept Page 24 Genome Transcriptomics Gene RegulationExpression Proteomics Proteins Metabolism Phenotype and Potential for Diseases Metabolomics Tissues and Cells Whole Organism Physiomics cit from Nicolson (2002), modified Descriptional and analytical levels in Systems Biology

Dr. Siegfried Neumann-jm: SiSIS, Sept Page 25 It is all dynamics in biological systems Measurements by the -omics technologies do not necessarily reflect real-world or endpoint observations Real world'omics world Inputs: Signals stressors etc cell Gene expression Protein profile Metabolic profile Time Outputs: Biological endpoints pathology degeneration regeneration Note: time differentials in all interaction stages Nicolson, J.K. at al. Nature Reviews Drug Discovery 1, 153 (2002)

Dr. Siegfried Neumann-jm: SiSIS, Sept Page 26 Current topics in systems biology Problems encountered when we try to understand life processes by simulation and modeling Complexity n Dimensionality Holistic versus reductionistic working modes Change, dynamics Pleiotropy and redundancy in biology Deterministic versus stochastic mathematics Bioinformatics  System Engineering Need to end in understanding physiology and disease processes

Dr. Siegfried Neumann-jm: SiSIS, Sept Page 27 Complexity and emergent properties in biology 1.Complex inputs that stimulate multiple pathways 2.Integrated networks respond to the inputs by multiple outputs 3.Interactions between multiple cell types in multi cellular organisms (like man) 4.Multiple contexts and environments for each cell type or combination of cell types To understand the effects of a target or a drug, data must be derived from cell responses in multiple environment. Butcher et al. Nature Biotechnol. 22, 1253 (2004)

Dr. Siegfried Neumann-jm: SiSIS, Sept Page 28 Deliverables and limitations of approaches by integrative biology to drug research and development OmicsCell systems Computational biology Hypothesis generation+++ Target identification/validation(+)+(+) Quantitative analysis of dynamic parameters-(+)+ Rational design of perturbance of a system-(+)+ Systems connectivities-++ Disease model properties-+- Disease indication / trial design-+/-(+) Data quantity Data quality Need for functional annotation work Limitations: Availability of all types Limited modeling of systemic effects Missing experimental data sets Availability of suitable cell material Very slow throughput Computational limitations

Dr. Siegfried Neumann-jm: SiSIS, Sept Page 29 Examples of computational models relevant to human disease biology ApproachSystemComments Disease physiologyHeart Diabetes Asthma Quantitative models of the heart from genes to physiology Approaches for modeling diabetes Math. models of chronic asthma for prediction of therapy response Integrative cell modelsCancer Cardio- myocytes Network models containing 1000 genes/proteins, 3000 components predicted effect of specific gene knock downs, Cancer pharmacogenetics-polymorphisms, pathways and beyond Linking modules (int. Metabolism, electrophysiology and mechanics) for computational modul of cardiomyocytes Pathway modelsMultiple EGFR/MAPK NF-KB Wnt Pathway Emergent properties of signaling in network models Computational models of EGFR signaling and network model Signal processing of NF-KB signaling pathway Experimental and theoretical analysis of the Wnt Pathway, roles of APC and axin. (cit. Butcher, E. C. et al., Nature Biotechnol. 22, 1253 (2004), modified)

Dr. Siegfried Neumann-jm: SiSIS, Sept Page 30 Data-based mathematical modelling of the JAK2-STAT5 Pathway (Klingmueller, pers. commun,.)

Dr. Siegfried Neumann-jm: SiSIS, Sept Page 31 Mathematical prediction: Dynamical parameters of nuclear import ( k 3 ), export ( k 4 ) and delay (  ) most sensitive to perturbation Experimental verification of mathematical prediction JAK2-STAT5 Pathway Predicting Steps Most Sensitive for Perturbation (Klingmueller, pers. commun.)

Dr. Siegfried Neumann-jm: SiSIS, Sept Page 32 Systems Biology: Selected commercial players CompanyCore TechnologiesApproachDeliverables AccelrysSoftware ToolsSoftware for process simulationSimulation of biological and chemical process Bayer Technology Services Software tools PK-MAP™ PK-SIM™ Prediction, interpretation and extrapolation of pharmacokinetics / pharmacodynamics High quality estimates of ADME and PK BG MedicineBioselective Targets ™ Biosystems Markers ™ Application of SB for target discovery, biomarkers and predictive toxicology Targets, biomarker identification Predictive toxicology EntelosMath. models (diff. equations) for simulation and analysis Dynamic models for disease processes on molecular, cellular and physiological levels (Physio Labs) Target ID, Evaln. Leads, Biomarkers, Clinical trial design Gene GOMETA core analysisNetwork analysis of HAT expression data Gene profile analysis in breast cancer

Dr. Siegfried Neumann-jm: SiSIS, Sept Page 33 Systems Biology: Selected commercial players ctd. CompanyCore TechnologiesApproachDeliverables IconixHTP molecular biology Data-mining Integration of chemistry and genomics to profile drug candidates to predict toxicity Predictive toxicology IngenuityOntology Pathway database Computing on DB Identification of altered pathways from diff. expression date Target ID based on pathway analysis Icoria Inc. (former Paradigm Genetics) Biochemical Profiling Platform Metabolic ProfilingBiomarkers for DD and diagnosis Physiomics plc In silico simulationsComputer models for human diseases Pathway simulation, multiple cell systems In silico tests for interpretation of PK and PD SurromedHTP molecular biology Data-mining Profile immune cell populations, proteins and small molecules for biomarkers. Fingerprint pathways involved in disease and therapeutic response Biomarker ID Clinical trial design

Dr. Siegfried Neumann-jm: SiSIS, Sept Page 34 Systems Biology at Work in Drug Discovery of Big Companies Drug CompanyResearch ActivitySpecialist Partner Eli Lily / Lilly Systems Biology in Singapore Explore network pathways, use dynamic models to simulate cellular responses to drugs, 140 Mio. $ over 5 years commitment NovartisFocus on pathway studiesCellzome AG Novo Nordisk ASSB approach to the combinatorial nature of signal transduction Johnson + Johnson's Pharmaceutical R+D Using PhysioLabs mathematical models for analysis of dynamic relationships within human biological networks (Diabetes II, hematology, clin. development, phase IV clinical trials) Entelos OrganonUsing PhysioLabs on Rheumatoid Arthritis drug targets Entelos Astra ZenecaSB in predictive toxicologyBeyond Genomics Glaxo Smith KlineSB in metabolic disease pathways, drug mechanism of action, identify new biomarkers Beyond Genomics Lit. zit.: Littlehales, C.: Bio News Dec January 2005, p. 9, modified

Dr. Siegfried Neumann-jm: SiSIS, Sept Page 35 The Multiple Input of Systems Biology into Molecular Medicine Drug Discovery Clinical Development Therapy Markers Safety, Toxicity EfficacyResponse/ Non response Safety/ Efficacy Diagnosis/ Prognosis Disease Progression Target - Identification, - Characterization, - Prioritization Pathway Elucidation, Network Analysis Animal Model Validation Targets Mode of Action Trial Design Product Decision Combination with Other Drugs Disease Indications

Dr. Siegfried Neumann-jm: SiSIS, Sept Page 36 Research centers on systems biology in the USA (1) Institute for Systems BiologyIntegration of the different levels of biological information, (Hood et al.; Seattle)modeling of integral systems -microorganism models and yeast -immune system, cancer, hematopoeitic development The Molecular Science InstituteDevelopment of prediction biology (Brenner, Brent; Berkeley)-genomic, evolutionary studies on E. coli -protein/protein interactions -computational biology, instrumentation Dept. on Bioengineering Systematic analysis of genetic circuits (Palsson, UCSD)-coordinated activities of multiple gene products in metabolism and cell motility -in silico metabolic routing in E. coli CaltechModeling of nonlinear systems in E. coli (Simon, Doyle, Kitano, et al.)-Simulation systems for gene regulation and metabolism -Modeling and simulation of the cell cycle Biomolecular Systems Initiative (BSI)Studies on cellular networks (within cells and between cells) at Pacific Northwest Natl. Laboratory -in microbiological systems by (Wiley et al.) -quantitative and integrative cell biology

Dr. Siegfried Neumann-jm: SiSIS, Sept Page 37 Research centers on systems biology in the USA (2) Alliance for Cellular Analysis of G protein coupled or related signal Signaling (AfCS)transduction in mammalian cells (Gilman, Univ. Texas -identification of all involved proteins South Western)-analysis of kinetics of information fluxes -modeling cellular signaling MIT Computational and Systems Quantitative biology of cellular functions by Biology Initiative (CSBI) experimentation, modeling and simulation in mammalian (Sorger, Tidor, Lauffenburger) cells and tissues -regulation of proliferation, adhesion, migration and transport Education in SB Systems Biology Department Bioinformatics, structural genomics, Quantitative Structure Harvard Medical School Activity Relationships in multicomponent complexes (Kirschner, Mitchison, Harvard)-Synthetic biological systems -Molecular understanding of physiological centre Education in SB Princeton Integrative Genomics Interdisciplinary research programmes on quantitative biology (Botstein et al.), University of Education in SB Michigan Life Sciences Institute (Saltiel et al.), Stanford University Biosciences Initiative (Bio-X, Scott et al.), Duke’s Institute for Genome Sciences and Policy (Willard et al.)

Dr. Siegfried Neumann-jm: SiSIS, Sept Page 38 Recent Highlights in SB International Crosslinking  EU-Initiatives EU SYSBIO, SYMBIONIC EUREKA InSysBio Project SYSMO (AU, DE, NL, GB, NO, SP)  WTEC/USA: Reports on US, EU and Japan activities  WTEC/USA:Workshop on setting up a repository for systems biology software, February 17-18, 2005, Washington, USA  5. International Conference on Systems Biology October 9-13, 2004, Heidelberg, Germany  6. International Conference on Systems Biology October 2005, Cambridge, USA, Org: Marc Kirschner, Harvard  Start of PanAsian electronic International Molecular Biology Laboratory (e IMBL) Seoul, July 12-13, 2005

Dr. Siegfried Neumann-jm: SiSIS, Sept Page 39 This is a website of SYSMO: SYSMO is a transnational funding program for the Systems Biology of MicroOrganisms, of The German BMBF, the Dutch NWO-ALW, and the Austrian bm:bmk. Additional countries have been invited to join soon.BMBFNWO-ALWAustrian bm:bmk At present SYSMO is already active in supporting the training of scientists and students in Systems Biology. Its first activity is the strong support(in terms of travel fellowships) of the FEBS advanced course (see below). A second, much larger activity is a transnational research program for Systems Biology of Microorganisms. Countries are now asked to express their interest in participating in and supporting this program. On SYSMO

Dr. Siegfried Neumann-jm: SiSIS, Sept Page 40 See also: First FEBS Advanced Course on Systems Biology: From Molecules & Modeling To Cells March , 2005, Gosau, Austria, EU Organized by: Roland Eils (Heidelberg), Karl Kuchler (Vienna), Anneke Koster (Amsterdam), and Hans V. Westerhoff (Amsterdam) Program and all informationFlyer (pdf) RegistrationRegistration Pre-registrationPre-registration

Dr. Siegfried Neumann-jm: SiSIS, Sept Page 42 Systems Biology – How to implement into pharmaceutical research and development? (1) Interdisciplinary approach needed, develop common conceptual understanding of biologists, mathematicians and bioinformatics experts Define cellular models and experiments with reproducable properties - sampling - culture conditions - validated analytical technologies - exp. schedules Iterative approaches needed between model builders and biological experimentators Provide sufficient IT hardware resources and software tools

Dr. Siegfried Neumann-jm: SiSIS, Sept Page 43 Drug researchers should join accademic initiatives for strategic cooperative projects Drug R+D should form precompetitive R+D platforms for developing SB tools and informatics standards - Speak a common research language - Share IT resources - Train researchers on an integrative approach Drug R+D should contribute views on strategic research priorities to academic research directors and share strategic concepts with national and cross-border research planning panels on precompetitive level The potential of systems biology for drug discovery and development needs a major success story in industry (Ideker, 2004) Systems Biology – How to implement into pharmaceutical research and development? (2)