Impact of Cloud Computing: Life Sciences

39488f9d172ab92fd352f2cd7b73258d?s=47 Matt Wood
April 29, 2013

Impact of Cloud Computing: Life Sciences

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

39488f9d172ab92fd352f2cd7b73258d?s=128

Matt Wood

April 29, 2013
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Transcript

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

    WOOD
  2. THANK YOU Hello, and

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

    ON LIFE SCIENCES
  4. SEVEN years young

  5. None
  6. SERVICES to support virtually any workload Broad and deep

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

    24 9
  8. SECURITY capabilities to support virtually any workload Comprehensive

  9. None
  10. None
  11. EVERY DAY to power amazon.com in 2003 Add enough server

    capacity
  12. UTILITY Computing delivered as a

  13. None
  14. None
  15. ECONOMIES of scale to lower prices Take advantage of the

  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
  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
  18. FLEXIBILITY in using these resources Provide

  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
  20. ADOPTING cloud computing? Why are customers

  21. CAPITAL EXPENSE for variable expense Trade

  22. $0 vs TO GET STARTED

  23. VARIABLE EXPENSE than companies can do themselves Lower

  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
  25. GUESS capacity You don’t need to

  26. TIME DEMAND

  27. TIME PREDICTED DEMAND

  28. DEMAND TIME ACTUAL PREDICTED

  29. TIME WASTE ACTUAL DEMAND PREDICTED

  30. TIME WASTE OPPORTUNITY COST ACTUAL DEMAND PREDICTED

  31. TIME ACTUAL DEMAND AWS

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

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

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

    traffic to amazon.com
  35. November traffic to amazon.com

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

  37. SPEED and agility Dramatically increase

  38. WEEKS MINUTES to

  39. EXPERIMENTATION is fast and low risk Increase innovation when

  40. UNDIFFERENTIATED heavy lifting Stop spending money on

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

  42. GLOBAL in minutes Go

  43. OPEX Replace CapEx with COST Lower overall AGILITY Speed and

    CAPACITY Don’t guess FOCUS Enhance GLOBAL Go
  44. LIFE SCIENCES in the cloud? What are the drivers for

  45. DATA generation Decreasing cost of

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

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

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

    Lower costs, higher throughput Highly constrained
  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
  50. REMOVES resource constraints Utility computing

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

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

  53. Average daily number of cells that moved out from the

    communal sections. Linus Bengtsson et al. PLoS Medicine, 2011
  54. You Are What You Tweet: Analyzing Twitter for Public Health.

    M. J. Paul and M. Dredze, 2011 Tweeting about Flu
  55. Tweeting about Food

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

    Tweeting about Food
  57. None
  58. None
  59. Chromosome 11 : ACTN3 : rs1815739

  60. Chromosome X : rs6625163

  61. Chromosome 19 : FUT2 : rs601338

  62. Chromosome 2 : rs10427255

  63. TYPE II Chromosome 10 : rs7903146

  64. +0.25 Chromosome 15 : rs2472297

  65. None
  66. GENERATION COLLECTION & STORAGE ANALYTICS & COMPUTATION COLLABORATION & SHARING

  67. RATE LIMITING Data generation is no longer

  68. ANALYTICS Unconstrained and computation

  69. 12.5 3 years hours

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

  71. None
  72. $1k Less than today

  73. 1,000,000+ core hours

  74. WAREHOUSING Petabyte scale, managed with high performance

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

  76. $1000 Less than per terabyte, per year

  77. ARCHIVAL High durability

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

  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. ” “
  80. MANAGEMENT and computation challenges Beyond the data

  81. SHARING and integration Enable data

  82. None
  83. AVAILABLE at no cost Public datasets

  84. COMPLIANCE for security and privacy Regulatory

  85. SHARED responsibility An environment of

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

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

  88. RESEARCH Accelerating

  89. None
  90. None
  91. Apps Public Genomic Databases Users EMR Support & Engineering Instruments

  92. None
  93. None
  94. CLINICAL IMPACT Improving

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

    Primary uses
  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
  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
  99. WHAT’S NEXT Thinking about for cloud computing

  100. DON’T CHANGE Focus on things that

  101. LOWER PRICES Continue to

  102. EXPANSION Continued geographic

  103. BIG DATA Evolution of the landscape

  104. SECURITY Retain laser-sharp focus on and encryption

  105. MOBILE Interconnected data and devices

  106. None
  107. INTRO WHY CLOUD COMPUTING? LIFE SCIENCES IN THE CLOUD IMPACT

    ON LIFE SCIENCES
  108. THANK YOU

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