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
2. THANK YOU Hello, and
3. INTRO WHY CLOUD COMPUTING? LIFE SCIENCES IN THE CLOUD IMPACT ON LIFE SCIENCES
4. SEVEN years young
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
11. EVERY DAY to power amazon.com in 2003 Add enough server capacity
12. UTILITY Computing delivered as a
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
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
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
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
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
91. Apps Public Genomic Databases Users EMR Support & Engineering Instruments
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
107. INTRO WHY CLOUD COMPUTING? LIFE SCIENCES IN THE CLOUD IMPACT ON LIFE SCIENCES
108. THANK YOU
109. matthew@amazon.com aws.amazon.com