DCI for Clinical Translational Research

1. DCI for Clinical Translational Research Shantenu Jha, LSU & UC-London Peter Coveney, UC-London Slide acknowledgement Barbara Alving, NIH

2. Applying high throughput technologies • Translating basic science discoveries into new and better treatments • Benefiting health care reform • Comparative effectiveness research • Prevention and personalized medicine • Health disparities research • Pharmacogenomics • Health research economics • Focusing on global health • Reinvigorating and empowering the biomedical research community Opportunities for Research and NIH Francis Collins 1 January 2010 Vol 327 Science, Issue 5961, Pages 36-37

3. The Translation Gap National Health Expenditures as a Percent of GDP Source: Butler D. Translational research: Crossing the valley of death. Nature. 2008;453:840–2.

4. Imaging • Technology • MRI • Image-guided therapy • PET • CAT • Ultrasound Informatics Resources • Genetics • Modeling of complex systems • Molecular dynamics • Visualization • Imaging informatics Optics & Laser Technology • Microscopy • Fluorescence spectroscopy • In Vivo diagnosis Biomedical Technology Research • Scope: from basic discovery to clinical research • Scale: from molecule to organism Technology for Structural Biology • Synchrotron x-ray technologies • Electron microscopy • Magnetic resonance Technology for Systems Biology • Mass spectrometry • Proteomics • Glycomics & glycotechnology • Flow cytometry

5. The key to successful computational physiology is the capture of structure-function relationships in a computationally efficient manner. [Crampin et al., 2003] VPH: Ambitious Way Forward What is the Physiome? The Physiome is the quantitative and integrated description of the functional behaviour of the physiological state of an individual or species “We need adaptable tools able to cope with multi-physics and multi-scale problems ranging from molecular to physiological levels. In-house tools must be developed, maintained and updated, or the scientists must rely on available software, adapting it to their specific needs“ “The predictive paradigm in the treatment of disease” In order to obtain patient-specific simulations, simulations must be performed on a routine basis in the clinical setting. … high performance computing required for transient CFD simulation must be accessible, possibly using Grid technology

6. VPH/Physiome History -- Consilience Human Genome Project 1st meeting standards working group Systems Biology ICT Bio: need for standards working group Grid Computing Finite Elements VPH NoE starts White paper completed Microcomputers/home computers FP7 call 2 Objective ICT-2007.5.3: Virtual Physiological Human EC/ICT Health Start discussing Physiome research Molecular Biology Physiome at IUPS Conference Physiome Project VPH Roadmap for (STEP) Roadmap for Physiome FP6: STEP 1993 1997 2005 2006 2007 2008 2009

7. VPH- I FP7 projects Industry Parallel VPH projects Grid access CA CV/ Atheroschlerosis IP Liver surgery STREP Breast cancer/ diagnosis STREP Heart/ LVD surgery STREP Osteoporosis IP Oral cancer/ BM D&T STREP Cancer STREP Networking NoE Heart /CV disease STREP Vascular/ AVF & haemodialysis STREP Liver cancer/RFA therapy STREP Alzheimer's/ BM & diagnosis STREP Heart /CV disease STREP Other Clinics Security and Privacy in VPH CA

8. Monomer B 101 - 199 Monomer A 1 - 99 Flaps Glycine - 48, 148 Saquinavir P2 Subsite Catalytic Aspartic Acids - 25, 125 C-terminal N-terminal Leucine - 90, 190 Patient-specific HIV drug therapy HIV-1 Protease is a common target for HIV drug therapy • Enzyme of HIV responsible for protein maturation • Target for Anti-retroviral Inhibitors • 9 FDA inhibitors of HIV-1 protease • So what’s the problem? • Emergence of drug resistant mutations in protease • Render drug ineffective • Drug resistant mutants have emerged for all FDA • One part of “HIV Cycle” • Need for speedy calculation

9. VPH: LONI-TeraGrid-DEISA Project Simulation and calculation workflow • Aim: To enhance the understanding of HIV-1 enzymes using replica-based methods across federated TG-DEISA-LONI • Do so using general-purpose, extensible, scalable approach • Test limits of Distributed Scale-Out – both algorithmic and infrastructure limits • As part of the VPH project, to ultimately help build the CI for quick, efficient (patient-specific) decision-tools using predictive MD of drugs and enzymatic targets (HIV-1 protease) • Integration of SAGA into Binding Affinity Calculator (BAC) tools to facilitate distributed Scale-Out • Protonation study of Ritonavir bound to HIV-1 Protease wild type • Study of binding affinity between 6 HIV-1 Protease mutants and the drug Ritonavir using SAGA-BAC Tools

11. JA.NET (UK) 40Gb network Transatlantic 10Gb link TeraGrid 40Gb backbone DEISA 10Gb network

12. .. And You Asked • # What problem was your project designed to solve? • True Grand Challenge – scientific and research infrastructure • Many elements to VPH/Translational Research. Focus on lowering TTC • # How did the community come together? • Collectively Seduced by Money… • # What were the challenges? • Trade off between General purpose vsCustomised solutions/approaches • “Novel” Usage Modes of Research Infrastructure – viewed as disruptive • # What did you learn? • [Ongoing project] Difficult to interoperate across infrastructure • Establish Application-level Interoperability not just Service-level Interoperabilty • # What have you achieved • Utilized multiple resources in a given grid infrastructure, but still struggling to do routine concurrent simulations across distinct DCI (Grid projects) • # What is left to be done? • Software, policies, interoperability … all in all: A lot!