clearScienceStrataRx2012

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The impetus behind Sage Bionetworks' clearScience project and how it effaces the boundary between doing science and communicating science.

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clearScienceStrataRx2012

  1. 1. clear Sciencedragging scientific communication intothe information ageerich s. huang, md/phddirector, cancer researchsage bionetworkserich.huang@sagebase.org@erichhuang
  2. 2. http://www.viahealthcaredesign.com/LMCH%20Universal%20Exam%20Rm.jpg
  3. 3. Betty Jones “I have a lump near my mastectomy scar”
  4. 4. Betty Jones menopause ~50 years “high risk” breast cancer “normal risk” breast cancer
  5. 5. Betty Jones menopause 36 years ~50 years “high risk” breast cancer “normal risk” breast cancer
  6. 6. Betty Jones African American Population Non-African American Population 16% 39% 61% 84% Triple Negative Breast Cancer Triple Negative Breast Cancer All Other Types All Other Types http://jama.jamanetwork.com/article.aspx?articleid=202952
  7. 7. her2 receptor progesterone receptorestrogenreceptor breast cancer cell depends on receptor-driven growth signals
  8. 8. her2 receptor progesterone receptorestrogenreceptor breast cancer cell depends on receptor-driven growth signals
  9. 9. her2 receptor progesterone receptor LSestrogen NAreceptor S IG T H OW G R breast cancer cell depends on receptor-driven growth signals
  10. 10. breast cancer cellgrowth signals becomeindependent of receptors
  11. 11. “triple negative” breast cancer breast cancer cell growth signals become independent of receptors
  12. 12. “triple negative” breast cancerthe receptors are no longer present on thecell surface... breast cancer cell growth signals become independent of receptors
  13. 13. “triple negative” breast cancerthe receptors are no longer present on thecell surface...but the intracellular signals persist breast cancer cell growth signals become independent of receptors
  14. 14. “triple negative” breast cancerthe receptors are no longer present on thecell surface...but the intracellular signals persist T N S E L D A N N E IG EP S D H IN T OW G R breast cancer cell growth signals become independent of receptors
  15. 15. http://www.cancer.gov/images/cdr/live/CDR415523-750.jpg
  16. 16. http://www.cancer.gov/images/cdr/live/CDR415523-750.jpg
  17. 17. http://www.cancer.gov/images/cdr/live/CDR415523-750.jpg
  18. 18. Betty Jones minus plus lymph node young negative african-american triple negative multifocal cancer
  19. 19. Betty Jones minus plus lymph node young negative african-american = Aggressive therapeutic strategy triple negative multifocal cancer
  20. 20. http://www.flickr.com/photos/kbrookes/7497906298/sizes/h/in/photostream/
  21. 21. radiotherapy 3d planning http://radonc.ucsf.edu/patient_information/breast/images/Radiation_Oncology_breast_img_2.jpg
  22. 22. Betty Jones “I have a lump near my mastectomy scar”
  23. 23. Betty Jones Triple negative breast cancer. What are the options?
  24. 24. Betty Jones Triple negative breast cancer. What are the options? Standard Stuff (Old Fashioned Targets) Anthracyclines Taxanes Anti-Metabolites
  25. 25. Betty Jones Triple negative breast cancer. What are the options? Standard Stuff (Old Fashioned Targets) Anthracyclines Taxanes Anti-Metabolites Platinum Agents
  26. 26. Betty Jones Triple negative breast cancer. What are the options? { Standard Stuff (Old Fashioned Targets) Anthracyclines conventional Taxanes chemotherapy Anti-Metabolites Platinum Agents
  27. 27. Betty Jones Triple negative breast cancer. What are the options? { Standard Stuff (Old Fashioned Targets) Anthracyclines conventional Taxanes chemotherapy Anti-Metabolites Platinum Agents Targeted Agents Cetuximab + Platinum (BALI-1) Bevacizumab (GeparQuinto) PARP Inhibitors SRC Inhibitors HDAC Inhibitors (ER-alpha)
  28. 28. Betty Jones Triple negative breast cancer. What are the options? { Standard Stuff (Old Fashioned Targets) Anthracyclines conventional Taxanes chemotherapy Anti-Metabolites Platinum Agents { Targeted Agents Cetuximab + Platinum (BALI-1) Bevacizumab (GeparQuinto) new therapies PARP Inhibitors SRC Inhibitors HDAC Inhibitors (ER-alpha)
  29. 29. Betty Jones Triple negative breast cancer. What are the options? { Standard Stuff (Old Fashioned Targets) Anthracyclines conventional Taxanes chemotherapy Anti-Metabolites CURRENT KNOWLEDGE: Platinum Agents ALL THESE THERAPIES { Targeted Agents ARE A Platinum (BALI-1) Cetuximab + WASH Bevacizumab (GeparQuinto) new therapies PARP Inhibitors SRC Inhibitors HDAC Inhibitors (ER-alpha)
  30. 30. Betty Jones
  31. 31. Betty Jones
  32. 32. http://www.viahealthcaredesign.com/LMCH%20Universal%20Exam%20Rm.jpg
  33. 33. molecularly-customized~4 million datapoints cancer treatment plan
  34. 34. E S TIM 4 6 3 EDC IT
  35. 35. E S TIM 6 3 4 CS- ED MI LS ITC EN O RIA G ED T 3 ID GU
  36. 36. E S TIM 6 3 4 CS- ED MI LS ITC EN O RIA G ED T 3 ID GU
  37. 37. molecularly-customized~4 million datapoints cancer treatment plan
  38. 38. molecularly-customized~4 million datapoints cancer treatment plan
  39. 39. Magic molecularly-customized~4 million datapoints cancer treatment plan
  40. 40. Open
  41. 41. Open
  42. 42. Open
  43. 43. Open Source
  44. 44. Open
  45. 45. Open Data
  46. 46. Open
  47. 47. Open Access
  48. 48. Access
  49. 49. Access = Accessible?
  50. 50. OpenSourceOpenDataOpenAccess } Clear ?
  51. 51. Nature 483, 509 (29 March 2012) | doi:10.1038/483509a
  52. 52. Nature 483, 509 (29 March 2012) | doi:10.1038/483509a
  53. 53. the status quotolerates poorcommunicationof findings
  54. 54. the status quo can reproducetolerates poor partiallycommunicationof findings 6% can reproduce from processed data w/ 21% discrepancies 54% can reproduce w/ 8% cannot discrepancies reproduce 11% can reproduce in principle
  55. 55. so what’s inprinciplereproducible, is notpracticallyreproducible
  56. 56. so what’s in principle 208,294,724 reproducible, is not datapoints practically reproducible 124 pages supplemental material ? lines unobtainable source code ? version or architecture of R? R packages key R package “ClaNC” no longer available 442 citations
  57. 57. THE SCIENTIFIC PROCESS:it’s not one and done... define a question
  58. 58. THE SCIENTIFIC PROCESS:it’s not one and done... define a question gather information
  59. 59. THE SCIENTIFIC PROCESS:it’s not one and done... define a question form a hypothesis gather information
  60. 60. THE SCIENTIFIC PROCESS:it’s not one and done... define a question form a hypothesis gather information experimentally test your hypothesis
  61. 61. THE SCIENTIFIC PROCESS:it’s not one and done... analyze define a question form a hypothesis experimental data gather information experimentally test your hypothesis
  62. 62. THE SCIENTIFIC PROCESS:it’s not one and done... analyze define a question form a hypothesis experimental data gather information experimentally test draw conclusions your hypothesis
  63. 63. THE SCIENTIFIC PROCESS:it’s not one and done... analyze define a question form a hypothesis experimental data report, i.e. “publish” gather information experimentally test draw conclusions your hypothesis
  64. 64. THE SCIENTIFIC PROCESS:it’s not one and done... analyze define a question form a hypothesis experimental data report, i.e. “publish” gather information experimentally test draw conclusions your hypothesis validation by the scientific community validation by clinical trials
  65. 65. generate data@ the bench orfrom a clinical cohort
  66. 66. generate data@ the bench orfrom a clinical cohort
  67. 67. store on localgenerate data server@ the bench orfrom a clinical cohort
  68. 68. store on localgenerate data server@ the bench orfrom a clinical cohort
  69. 69. store on localgenerate data server@ the bench orfrom a clinical cohort analyze on local machine
  70. 70. store on localgenerate data server@ the bench orfrom a clinical cohort analyze on local machine
  71. 71. store on localgenerate data server@ the bench orfrom a clinical cohort analyze on local machine write a document
  72. 72. store on localgenerate data server@ the bench orfrom a clinical cohort analyze on local machine write a document al to journ su bmit
  73. 73. store on localgenerate data server@ the bench orfrom a clinical cohort analyze on local machine sent to write a reviewers document as pdf al to journ su bmit
  74. 74. store on localgenerate data server@ the bench orfrom a clinical cohort analyze on local machine sent to write a reviewers document as pdf al to journ su bmit
  75. 75. store on localgenerate data server@ the bench orfrom a clinical cohort accepted & digitally typeset analyze on local machine sent to write a reviewers document as pdf al to journ su bmit
  76. 76. printed on paper store on localgenerate data server@ the bench orfrom a clinical cohort accepted & digitally typeset analyze on local machine sent to write a reviewers document as pdf al to journ su bmit
  77. 77. printed on paper store on localgenerate data server@ the bench orfrom a clinical cohort static html representation accepted & digitally typeset analyze on local machine sent to write a reviewers document as pdf al to journ su bmit
  78. 78. printed on paper store on localgenerate data server@ the bench orfrom a clinical cohort static html representation accepted & digitally typeset static pdf representation analyze on local machine sent to write a reviewers document as pdf al to journ su bmit
  79. 79. printed on paper store on localgenerate data server@ the bench orfrom a clinical cohort static html representation accepted & digitally typeset static pdf representation analyze on local machine sent to write a reviewers document as pdf al to journ su bmit
  80. 80. printed on paper store on local generate data server @ the bench or from a clinical cohort static html representationTHE ACTUAL SCIENCE accepted & digitally typeset static pdf representation analyze on local machine sent to write a reviewers document as pdf al to journ su bmit
  81. 81. printed on paper store on local generate data server @ the bench or from a clinical cohort static html representationTHE ACTUAL SCIENCE accepted & digitally typeset static pdf representation analyze on local machine SCIENTIFIC CLAIMS sent to write a reviewers document as pdf al to journ su bmit
  82. 82. store on local generate data server @ the bench or from a clinical cohortTHE ACTUAL SCIENCE analyze on local machine
  83. 83. store on local generate data server @ the bench or from a clinical cohortTHE ACTUAL SCIENCE analyze on local machine
  84. 84. clear Science
  85. 85. clear Science
  86. 86. clear Science
  87. 87. clear Science1. re-imagine scientific communication
  88. 88. clear Science1. re-imagine scientific communication2. make every component of a data-intensive project (e.g. genomic analysis) web accessible
  89. 89. clear Science1. re-imagine scientific communication2. make every component of a data-intensive project (e.g. genomic analysis) web accessible3. allow consumption of content at a variety of levels of complexity and abstraction4. leverage open, RESTful APIs
  90. 90. leverage open, RESTful APIs
  91. 91. leverage open, RESTful APIs to let users reconstitute an entire analytical environment
  92. 92. leverage open, RESTful APIs to let users reconstitute an entire analytical environment hardware
  93. 93. leverage open, RESTful APIs to let users reconstitute an entire analytical environment software hardware
  94. 94. leverage open, RESTful APIs to let users reconstitute an entire analytical environment data software hardware
  95. 95. leverage open, RESTful APIs to let users reconstitute an entire analytical environment code data software hardware
  96. 96. code datasoftwarehardware
  97. 97. code data software hardwareclear Science
  98. 98. code data software hardwareclear Science a narrative that coherently interweaves scientific assertions with the executable data, code, software & hardware that support them
  99. 99. “ my computer’s the cloud, let me hand it to you ”
  100. 100. “ If I have seen further it is by standing on the shoulders of giants. ”
  101. 101. Betty Jones “I have a lump near my mastectomy scar”
  102. 102. brian bot stephen friend josh greenberg david burdick mike kellen external partnersmyles axton ian mulvaney kelly lamarcoeditor head of technology senior editornature genetics • science trans. medicine mark patterson managing exec. editorphil bourne eLife sciences eric schadtfounding editor-in-chief dir. inst. for genomics &plos comp. biology multiscale biology mt. sinai school of med.
  103. 103. brian bot stephen friend josh greenberg david burdick mike kellenour patients external partnersmyles axton ian mulvaney kelly lamarcoeditor head of technology senior editornature genetics • science trans. medicine mark patterson managing exec. editorphil bourne eLife sciences eric schadtfounding editor-in-chief dir. inst. for genomics &plos comp. biology multiscale biology mt. sinai school of med.

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