Impact of Cloud Computing: Life Sciences

A description of the impact cloud computing is having in the life sciences.

Transcript

1. IMPACT
   The
   of Cloud Computing
   a presentation by
   DR. MATT WOOD
   

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2. THANK YOU
   Hello, and
   

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3. INTRO
   WHY CLOUD
   COMPUTING?
   LIFE SCIENCES
   IN THE CLOUD
   IMPACT ON
   LIFE SCIENCES
   

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4. SEVEN
   years young
   

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6. SERVICES
   to support virtually any workload
   Broad and deep
   

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7. 2007 2008 2009 2010 2011 2012
   159
   82
   61
   48
   24
   9
   

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8. SECURITY
   capabilities to support virtually any workload
   Comprehensive
   

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11. EVERY DAY
    to power amazon.com in 2003
    Add enough server capacity
    

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12. UTILITY
    Computing delivered as a
    

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15. ECONOMIES
    of scale to lower prices
    Take advantage of the
    

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16. Q4 2006
    Q1 2007
    Q2 2007
    Q3 2007
    Q4 2007
    Q1 2008
    Q2 2008
    Q3 2008
    Q4 2008
    Q1 2009
    Q2 2009
    Q3 2009
    Q4 2009
    Q1 2010
    Q2 2010
    Q3 2010
    Q4 2010
    Q1 2011
    Q2 2011
    Q3 2011
    Q4 2011
    Q1 2012
    Q2 2012
    Q3 2012
    Q4 2012
    Q1 2013
    2 TRILLION OBJECTS
    

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17. 5/22/2010
    6/12/2010
    7/3/2010
    7/24/2010
    8/14/2010
    9/4/2010
    9/25/2010
    10/16/2010
    11/6/2010
    11/27/2010
    12/18/2010
    1/8/2011
    1/29/2011
    2/19/2011
    3/12/2011
    4/2/2011
    4/23/2011
    5/14/2011
    6/4/2011
    6/25/2011
    7/16/2011
    8/6/2011
    8/27/2011
    9/17/2011
    10/8/2011
    10/29/2011
    11/19/2011
    12/10/2011
    12/31/2011
    1/21/2012
    2/11/2012
    3/3/2012
    3/24/2012
    4/14/2012
    5/5/2012
    5/26/2012
    6/16/2012
    7/7/2012
    7/28/2012
    8/18/2012
    9/8/2012
    9/29/2012
    10/20/2012
    11/10/2012
    12/01/2012
    12/22/2012
    1/12/2013
    2/2/2013
    2/23/2013
    3/16/2013
    4/6/2013
    5.5 MILLION HADOOP CLUSTERS
    

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18. FLEXIBILITY
    in using these resources
    Provide
    

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19. Free steak campaign
    Facebook page
    Mars exploration ops
    Consumer social app
    Ticket pricing optimization
    SAP & Sharepoint Securities Trading Data Archiving
    Marketing web site Interactive TV apps Financial markets analytics
    Consumer social app Big data analytics
    Web site & media sharing
    Disaster recovery
    Media streaming Web and mobile apps
    Streaming webcasts
    Facebook app Consumer social app
    Business line of sight Mobile analytics
    IT operations Digital media Core IT and media
    Ground campaign
    

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20. ADOPTING
    cloud computing?
    Why are customers
    

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21. CAPITAL EXPENSE
    for variable expense
    Trade
    

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22. $0
    vs
    TO GET STARTED
    

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23. VARIABLE EXPENSE
    than companies can do themselves
    Lower
    

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24. On-premises AWS
    $3.01M
    $0.90M
    Source: IDC Whitepaper, sponsored by Amazon, “The Business Value of Amazon Web Services Accelerates Over Time.” July 2012
    70% LOWER 5 YEAR TCO PER APP
    

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25. GUESS
    capacity
    You don’t need to
    

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26. TIME
    DEMAND
    

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27. TIME
    PREDICTED
    DEMAND
    

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28. DEMAND
    TIME
    ACTUAL
    PREDICTED
    

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29. TIME
    WASTE ACTUAL
    DEMAND
    PREDICTED
    

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30. TIME
    WASTE
    OPPORTUNITY COST
    ACTUAL
    DEMAND
    PREDICTED
    

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31. TIME
    ACTUAL
    DEMAND
    AWS
    

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32. Sunday Monday Tuesday Wednesday Thursday Friday Saturday
    Weekly traffic to amazon.com
    

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33. Sunday Monday Tuesday Wednesday Thursday Friday Saturday
    Weekly traffic to amazon.com
    

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34. Sunday Monday Tuesday Wednesday Thursday Friday Saturday
    39%
    61%
    Weekly traffic to amazon.com
    

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35. November traffic to amazon.com
    

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36. 76%
    24%
    November traffic to amazon.com
    

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37. SPEED
    and agility
    Dramatically increase
    

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38. WEEKS MINUTES
    to
    

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39. EXPERIMENTATION
    is fast and low risk
    Increase innovation when
    

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40. UNDIFFERENTIATED
    heavy lifting
    Stop spending money on
    

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41. data centers
    power
    cooling
    cabling
    networking
    racks
    servers
    storage
    labor
    

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42. GLOBAL
    in minutes
    Go
    

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43. OPEX
    Replace CapEx with
    COST
    Lower overall
    AGILITY
    Speed and
    CAPACITY
    Don’t guess
    FOCUS
    Enhance
    GLOBAL
    Go
    

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44. LIFE SCIENCES
    in the cloud?
    What are the drivers for
    

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45. DATA
    generation
    Decreasing cost of
    

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46. GENERATION
    COLLECTION & STORAGE
    ANALYTICS & COMPUTATION
    COLLABORATION & SHARING
    

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47. GENERATION
    COLLECTION & STORAGE
    ANALYTICS & COMPUTATION
    COLLABORATION & SHARING
    Lower costs,
    higher throughput
    

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48. GENERATION
    COLLECTION & STORAGE
    ANALYTICS & COMPUTATION
    COLLABORATION & SHARING
    Lower costs,
    higher throughput
    Highly constrained
    

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49. 1990 2000 2010 2020
    The Data Analysis Gap
    Enterprise Data Data in Warehouse
    Generated data
    Available for analysis
    Data volume
    Gartner: User Survey Analysis: Key Trends Shaping the Future of Data Center Infrastructure Through 2011
    IDC: Worldwide Business Analytics Software 2012–2016 Forecast and 2011 Vendor Shares
    

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50. REMOVES
    resource constraints
    Utility computing
    

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51. GENERATION
    COLLECTION & STORAGE
    ANALYTICS & COMPUTATION
    COLLABORATION & SHARING
    Lower costs,
    higher throughput
    Highly constrained
    

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52. GENERATION
    COLLECTION & STORAGE
    ANALYTICS & COMPUTATION
    COLLABORATION & SHARING
    

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53. Average daily number of cells that moved out from the communal sections.
    Linus Bengtsson et al. PLoS Medicine, 2011
    

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54. You Are What You Tweet: Analyzing Twitter for Public Health. M. J. Paul and M. Dredze, 2011
    Tweeting about Flu
    

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55. Tweeting about Food
    

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56. Tweets about
    the price of rice
    Official food
    price inflation
    Tweeting about Food
    

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59. Chromosome 11 : ACTN3 : rs1815739
    

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60. Chromosome X : rs6625163
    

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61. Chromosome 19 : FUT2 : rs601338
    

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62. Chromosome 2 : rs10427255
    

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63. TYPE II
    Chromosome 10 : rs7903146
    

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64. +0.25
    Chromosome 15 : rs2472297
    

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66. GENERATION
    COLLECTION & STORAGE
    ANALYTICS & COMPUTATION
    COLLABORATION & SHARING
    

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67. RATE LIMITING
    Data generation is no longer
    

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68. ANALYTICS
    Unconstrained
    and computation
    

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69. 12.5 3
    years hours
    

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70. 12.5 3
    $20M $4k
    years hours
    

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72. $1k
    Less than
    today
    

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73. 1,000,000+
    core hours
    

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74. WAREHOUSING
    Petabyte scale, managed
    with high performance
    

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75. WAREHOUSING
    Petabyte scale, managed
    with high performance
    aws.amazon.com/redshift
    

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76. $1000
    Less than
    per terabyte, per year
    

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77. ARCHIVAL
    High durability
    

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78. 99.999999999%
    $0.01
    durability
    per gigabyte, per month
    

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79. As our company moves into the clinical space, we face a
    legal requirement to archive patient data for years that
    would drastically raise the cost of storage.
    Thanks to Amazon Glacier’s secure and scalable solution,
    we will be able to provide cost-effective, long-term
    storage and thereby eliminate a barrier to providing
    whole genome sequencing for medical treatment of
    cancer and other genetic diseases. ”
    “
    

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80. MANAGEMENT
    and computation challenges
    Beyond the data
    

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81. SHARING
    and integration
    Enable data
    

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83. AVAILABLE
    at no cost
    Public datasets
    

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84. COMPLIANCE
    for security and privacy
    Regulatory
    

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85. SHARED
    responsibility
    An environment of
    

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86. HIPAA
    21 CFR Part 11
    CLIA, GxP and others...
    

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87. CLOUD COMPUTING
    on life sciences?
    What is the impact of
    

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88. RESEARCH
    Accelerating
    

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91. Apps
    Public Genomic Databases
    Users
    EMR
    Support & Engineering
    Instruments
    

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94. CLINICAL IMPACT
    Improving
    

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95. Speeding server provisioning for R&D apps
    Extending capacity for internal grid environments
    Slowing internally hosted compute infrastructure growth
    On-boarding security, validation services and compliance
    Hosting research data
    Reducing cost while extending capabilities
    Challenges
    

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96. Clinical pharmacology and pharmacometrics
    Molecular dynamics
    Computational genomics
    Research portfolio
    Primary uses
    

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97. 98% time saved for clinical trial simulations
    Internal System AWS
    Individual Clinical Trial Simulation Run Time (Min) 56 56
    Total Number of Clinical Trial Simulations 2000 2000
    No. Servers 2 256
    No. CPU’s 32 2048
    Total Analysis Run Time (hr) 60 1.2
    Cost ?? $336
    

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98. Reduced burden on pediatric subjects
    Traditional Design
    Design Optimized Using Clinical Trial
    Simulation
    # of subjects 60 40
    # of blood samples per subject 12 5
    Length of stay per subject 72 hours 26 hours
    Length of study 2.5 years 1.7 years
    Total study cost $700K $250K
    Length and cost projected based on historical data in pediatric subjects
    

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99. WHAT’S NEXT
    Thinking about
    for cloud computing
    

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100. DON’T CHANGE
     Focus on things that
     

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101. LOWER PRICES
     Continue to
     

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102. EXPANSION
     Continued geographic
     

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103. BIG DATA
     Evolution of the
     landscape
     

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104. SECURITY
     Retain laser-sharp focus on
     and encryption
     

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105. MOBILE
     Interconnected
     data and devices
     

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107. INTRO
     WHY CLOUD
     COMPUTING?
     LIFE SCIENCES
     IN THE CLOUD
     IMPACT ON
     LIFE SCIENCES
     

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108. THANK YOU
     

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109. matthew@amazon.com
     aws.amazon.com
     

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