Minnesota Partnership for Biotechnology and Medical Genomics

1. Bringing together the expertise of two Minnesota leaders to benefit all Minnesotans Minnesota Partnership for Biotechnology and Medical Genomics

2. A Partnership for Minnesota • Concept became reality in 2003 in recognition of: • Limited window of opportunity • No institution could meet the challenge alone • Health/research strengths of Mayo and the University – along with support from the State – offered great potential • The two could do more together than each individually • Strong Foundation in Minnesota • >$1billion in individual investments by the University and Mayo over past 10 years • 50 + years experience and commitment tothe industry – beginning with medical devices • Synergistic areas of expertise

3. Mayo Clinic University of Minnesota • > $500 million invested in genomics • > 4 million electronic patientmedical records • Center for Individualized Medicine • > $5 million to educate MDs in genomics • Pharmacogenomics • Heart failure research program • Neurodegenerative disease program • MRI research for cancer andcardiovascular disease • Xenotransplantation program • Strong Cancer Center, CTSA • Mayo ACT (Alliance for Clinical Trials) • Centralized tissue and serumrepository—a tradition of biobanking • > $600 million invested in genomics • Biomedical Genomics Center,Institute for Human Genetics,Proteome Analysis Facility • Computational Genomics and Bioinformatics Supercomputing Institute • Structural biochemistry • Molecular and Cellular Therapeutics Facility and Stem Cell Institute • Computer sciences/digital technology • Center for Magnetic Resonance Research (neuro-imaging) • Blood cell and solid organ transplant • Center for Drug Design • Consortium on Law and Values in Health, Environment & the Life Sciences and Center for Bioethics CP1127497-3

4. State Investment Key to Partnership Success Proof of principle (2003): Jump started with $2 million in state funds combined with $1 million each from the University and Mayo in 2004 Building the Partnership (2005-2006): $21.7 million in bonding; and $30 million total appropriated in 2005 and 2006 Commitment to long-term success (2007-2008): $25 million for biennium, $8 M each of following two years (2009-2010);$300 million expansion to University bioscience facilities

5. Critical Infrastructure in Place

6. Powerful research: Exceeding Expectations • Leveraged first $17 M in state funding with $39 M in federal, philanthropic, and private funding (including the $5 million from Medica) • More than 30 research/infrastructure projects funded, completed or currently underway – from more than 130 proposals • Recruitment of first two pairs of researchers; third search underway • Commercialized research in Minnesota; additional commercialization in progress • 6 patent applications and 1 licensing agreement • International interest

7. A Snapshot of Current Partnership Research: Advancing Science, Building Tools

8. Expanding Relationships • Mayo – University – State • Minnesota Partnership – BioBusiness Alliance of Minnesota (Industry partnerships) • Partnership – IBM collaborations • Hormel Institute/University – Mayo • Strong support from communities around MN

9. Growing International Relationships • Czech Republic • India • South Korea • Sweden

10. New Priorities for PartnershipBuilding a Life Saving Economic Engine • Alzheimer’s Disease • Diabetes and Obesity • Heart Failure

11. Future Trajectory for Minnesota • Top Level Science • World Class Potential • Momentum and Interest • Coherent statewide planning High Impact Discovery and Innovation G

12. P owerful research toimprove life and stimulateMinnesota's economy www.minnesotapartnership.info

13. Computers for CuresIBM Innovation Supporting the Biosciences • Drew Flaada • Director, Life Sciences and Emerging Technology • IBM Corporation

14. Emerging Opportunity Biosciences Information Technology The Problem = The Opportunity • Biology and Medicine • Goldmines of historic information • Explosions of new data • Genomics • Protein science • Imaging • Computing • Data federation, mining, correlation, analysis • Petaflop super computing

15. Explosion of Genomic Data • Trend in GenBank Database • Doubling in size every year • Consequence: Database size increasing faster than our ability to compute on it • What to Do? • Faster & more scalable parallel algorithms, i.e., mpiBLAST-PIO • Application of efficient, state of the art supercomputing http://www.ncbi.nlm.nih.gov/Genbank/genbankstats.html

16. Node Card (32 chips 4x4x2) 32 compute, 0-1 IO cards System IBM Blue Gene/P 72 Racks Cabled 8x8x16 Rack 32 Node Cards 1 PF/s 144 TB 14 TF/s 2 TB Compute Card 1 chip, 20 DRAMs Key Features: • 4 cores per chip • Unlimited scalability • Power/Compute efficiency • Compute density 435 GF/s 64 GB Chip 4 processors 13.6 GF/s 2.0 (or 4.0) GB DDR 13.6 GF/s 8 MB EDRAM

17. Petaflop in PracticeJuelich Supercomputing Center

18. Examining the Possible Self comparison of Microbial Gnome database (5.2 GB raw size, 16 million sequences) • Scalability tests • Achieved 93% parallel efficiency on 32768 cores (8-rack BG/P) • Complete genome-to-genome comparison • Finish searching 16 million vs. 16 million sequences within 12 hours • At a petaflop, this could be accomplished in 80 minutes! • H. Lin, P. Balaji, R. Poole, C. P. Sosa, X. Ma, and W. feng, Massively Parallel Genomic Sequence Search on the Blue Gene/P Architecture, Supercomputing 08, accepted.

19. Computers in Drug Discovery Timeline: 11 – 15 years and more than $800 million to bring a drug to market http://en.wikipedia.org/wiki/Drug_development Image source: http://en.wikibooks.org/wiki/Proteomics/Proteomics_and_Drug_Discovery

20. In Silico Screening on Blue Gene Create database of potential drug candidates For each independent node, load: DOCK binary Receptor input files Subset of potential drug candidates Store docking score results into database Amanda Peters, Marcus E. Lundberg, Carlos P Sosa, and P. Therese Lang: “In Silico Virtual Screening on a Massively Parallel System “, Midwest Symposium in Computational Biology and Bioinformatics, Northwestern University, Evanston, IL, October 2007.

21. Urgent Need for Antiviral Drugs David Katzmann, Mayo, Yiannis Kaznessis, U of MN, Jean-Pierre Kocher, Mayo, Eric Poeschla, Mayo, and Carlos Sosa, IBM-BICB Mayo Clinic, BICB, and IBM are working toward Identifying Disease Related Processes Whose Critical Pathway Can Benefit from the Use of Supercomputers Enveloped viruses, including HIV, HCV,HTLV, Influenza virus, Epstein-Barr virus, Ebola virus and others, are a significant cause of human illness and death Image source: http://home.ncifcrf.gov/hivdrp/rcas/images/

22. Clinical Practice Genomics Compute Intensive Data Intensive High Performance Computing in Medical Imaging Pathology Enterprise Data Trust Unstructured Text Analytics Molecular Simulation Center of Excellence Life Sciences System DDQB

23. MR Angiography Analysis • Eliminate manual tracing to separate vessel trees • Tedious, delays read ~10 minutes • Perform automatic aneurysm detection

24. Automated Aneurysm Detection: Points of Interest

25. Fostering Collaboration Data Knowledge High Performance Computing Healthcare, Research Research

26. Thank You! Questions?