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Corruption of Denial
Now possible to generate massive amount of human “omic’s” data
Network Modeling Approaches for Diseases are emerging
IT Infrastructure and Cloud compute capacity allows
a generative open approach to solving problems
Nascent Movement for patients to Control Sensitive information allowing sharing
Open Social Media allows citizens and experts to use gaming to solve problems
1- Now possible to generate massive amount of human “omic’s” data

2-“Top Down” Network Modeling Approaches for Diseases are
emerging

3- IT Infrastructure and Cloud compute capacity allows
a generative open approach to biomedical problem solving

4-Nascent Movement for patients to Control Sensitive information
allowing sharing

5- Open Social Media allows citizens and experts to use gaming to
solve problems


        A HUGE OPPORTUNITY -- A HUGE RESPONSIBILITY
ENVIRONMENT

                                                            Non-coding RNA network
                                        BRAIN




                                                    HEART




                                                                                         ENVIRONMENT
                                 GI TRACT
               protein network
                                                                 KIDNEY
ENVIRONMENT




                                                                    metabolite network




                                  IMMUNE SYSTEM


                                                   VASCULATURE

              transcriptional network
                                        ENVIRONMENT
.
TENURE   FEUDAL STATES
• alchemist
Iterative Networked Approaches
To Generating Analyzing and Supporting New Models



                            Data




               Biological
                System              Analysis




          Uncouple the automatic linkage between the
          data generators, analyzers, and validators
CORRUPTION OF DENIAL
“We Must Guard Against
the acquisition of unwarranted influence,
  whether sought or unsought, by the
      Military Industrial Complex”
      - Dwight D. Eisenhower 1961
BUILDING PRECISION MEDICINE


  Extensions of current Institutions

   Proprietary Short term Solutions


Open Systems of Sharing in a Commons
An Alternative




                                Biomedicine
                                Information
                                 Commons




Commons are resources that are owned in common or shared among
communities.
                                                          -David Bollier
At Sage Bionetworks we believe medical research has to change


Research needs to become more open.

Research should be transparent to other scientists and shared with the patients
it involves.
Data, tools, and methods that researchers develop should be shared in formats
that can be used time and time again.

Results should be commonly available online to all, in real-time.
And negative or neutral outcomes should be published.



Research needs to involve more relevant people in a collaborative
approach.

Patients or citizens, researchers and organizations need to work together better
to decide what questions should be answered, and how the answers should be
obtained. This would weight priorities more towards more practical benefits.
Sage Bionetworks Collaborators

 Pharma Partners
    Merck, Pfizer, Takeda, Astra Zeneca,
     Amgen,Roche, Johnson &Johnson
 Foundations
    Kauffman CHDI, Gates Foundation

 Government
    NIH, LSDF, NCI

 Academic
    Levy (Framingham)
    Rosengren (Lund)
    Krauss (CHORI)

 Federation
    Ideker, Califano, Nolan, Schadt        32
Networked Approaches

         BioMedicine Information Commons
                                                              Patients/
              Data
            Generators                                        Citizens
                                      CURATED
                                        DATA
                                                                 Data
                                                 TOOLS/         Analysts
                                                METHODS
                              RAW
                              DATA


                                         ANALYSES/
                                          MODELS


                 Clinicians


                                     SYNAPSE
                                                          Experimentalists
Technology Platform




                                           Governance
Impactful Models
                   Better Models of
                       Disease:
                   INFORMATION
                     COMMONS

                     Challenges
RAS Model using primary tumor data to predict KRAS mutation status
                            Justin Guinney

    290 CRC samples:
       • KRAS12 or KRAS13 (n=115) vs WT (n=175)
       • Penalized regression model using ElasticNet and gene expression data




                                                 1.0
                                                 0.8
     Robust External




                            True positive rate

                                                 0.6
     Validation In CRC                                                          TCGA CRC
                                                                                Khambata−Ford




                                                 0.4
                                                                                Gaedcke
     data sets


                                                 0.2
                                                 0.0   0.0   0.2     0.4       0.6       0.8    1.0

                                                                   False positive rate




                                                                                                      Model specific to CRC:
                                                                                                      does not generalized to
                                                                                                      other KRAS dependent
                                                                                                      cancers




RAS signatures derived from CRC cohort can classify mutation status in CRC
                                                                                                           35
For 11/12 compounds, the #1 predictive feature in an unbiased analysis
           corresponds to the known stratifier of sensitivity
                           Adam Margolin
                          #2 CML lineage
                              CML lineage
                                                                            #1 EGFR mut
                                                                        EGFR mut


                           #1 EGFR mut
                              EGFR mut



            #1 CML lineage
                CML linage
                                       #1 EGFR mut
                                            EGFR mut




                                                                                              #1 ERBB2 expr
                                                                                          ERBB2 expr




           Can the approach make new mut
                                  #1 BRAF                                          BRAF mut


           discoveries?
           #1 HGF expr
            HGF expr
                                #2 NRAS mut                                NRAS mut

                                                                           BRAF mut
                                                                                   #1 BRAF mut
                                                                          #3 KRAS mut
                                                                    KRAS mut

                                                                          #2 NRAS mut
                                                                    NRAS mut
                                                                    BRAF mut

                                                                          #1 BRAF mut
                                                                    #3 KRAS mut
                                                             KRAS mut


                                                                    #2 NRAS mut
                                                             NRAS mut
                                                             BRAF mut



                                                                    #1 BRAF mut



                                                           #2 TP53 mut
                                                       TP53 mut

                                                        #3 CDKN2A copy
                                                       CDKN2A copy

                                                         #1 MDM2 expr
                                                       MDM2 expr
Tool: PORTABLE LEGAL CONSENT
     Control of Private information by Citizens allows sharing

                           weconsent.us
                            John Wilbanks




John Wilbanks

                    • Online educational wizard
                    • Tutorial video
                    • Legal Informed Consent Document
                    • Profile registration
                    • Data upload
two approaches to building common
                     scientific and technical knowledge




                                        Every code change versioned
                                        Every issue tracked
Text summary of the completed project   Every project the starting point for new work
Assembled after the fact                All evolving and accessible in real time
                                        Social Coding
“Synapse is a compute platform
 for transparent, reproducible, and
modular collaborative research.”
Data Analysis with Synapse


Run Any Tool



On Any Platform


Record in Synapse


Share with Anyone
Synapse is GitHub for Biomedical Data




                                                       •   Every code change versioned
                                                       •   Every issue tracked
                                                       •   Every project the starting point for new work
•   Data and code versioned                            •   Social/Interactive Coding
•   Analysis history captured in real time
•   Work anywhere, and share the results with anyone
•   Social/Interactive Science
Currently at 16K+ datasets and ~1M models
Specific Version
Pancancer collaborative subtype discovery
Download analysis and meta-analysis
Download another Cluster Result   Download Evaluation and view more stats




  • Perform Model averaging
  • Compare/contrast models
  • Find consensus clusters
Objective assessment of factors influencing model
performance (>1 million predictions evaluated)
                                               Sanger                                CCLE
Cross validation prediction accuracy (R2)

                                                            Prediction accuracy
                                                              improved by…


                                                             Not discretizing
                                                                  data




                                                                Including
                                                             expression data




                                                                Elastic net
                                                                regression



                                            130 compounds    In Sock Jang         24 compounds
Erich Huang, Brian Bot, Dave Burdick
Sage-DREAM Breast Cancer Prognosis Challenge
                     one month of building better disease models together
                                              Caldos/Aparicio




                                     breast cancer data
154 participants; 27 countries
                                                                            334 participants; >35 countries
                                                          Sep 26 Status




Challenge Launch: July 17




                                                                          >500 models posted to Leaderboard
Bob Young
         Top Hat                                  " #$$%&'!
Eric Topol
             UCSD
                                     my
Todd Park                             gene
             CTO

Michael Nielsen                      my
                                      dat a
Wadah Khanfar
        Al Jazeera

Eric Hershman
                                    m y
                                    paper
          Ushhidi

Jennifer Pahlka
   Code for America
                                         01""*) & ) &*!+,$-$. /!&
                                                (               &
                              2, % & " $) -5 " .6*& 7 7 "$*& $% **& :& <=; >?2, $&., $A4 &
                                  ) 34              0"        0" .) &     89.4 ;  & @  *A"
                                            *-.) , 7 4 &( ) & 5 5 5 C % A"$% **C .%&
                                                     $%:4 B&         *, )     .) " &
                           Keyn ot e Sp eak er s: Law r en ce Lessi g – author “The future of ideas” &“Remix”
                      Jam i e Heyw ood – patients like me Lan ce Ar m st r on g – LiveStrong Davi d Hau ssl er - UCSC
              Sage Commons Congress – San Francisco April 19-20
                      Genome Browser Jam es Boyl e – Duke Law School Ad r i en Tr eu ille –Foldit



                       ! " #$%'$( Young Investigator Awards
                             Ten ) *+% -" .*/&
                              &       ,      &
                      Ear n one of t en t r i p s t o Com m ons Cong r ess i n SF!
                             – t o ap p l y vi si t h t t p :/ / b i t .l y/ 2012YIA!
Now possible to generate massive amount of human “omic’s”
data

Network Modeling for Diseases are emerging

IT Infrastructure and Cloud compute capacity allows
a generative open approach to biomedical problem solving

Nascent Movement for patients to Control Private information
allowing sharing

Open Social Media allowing citizens and experts to use gaming
to solve problems


THESE FIVE TRENDS CAN ENABLE AN OPEN COMMUNITY OF
IMPATIENT CITIZENS-- AS PATIENTS/RESEARCHERS/FUNDERS
Upon this gifted age, in its dark hour,
Rains from the sky a meteoric shower
Of Facts…they lie unquestioned,uncombined.
Wisdom enough to leech us of our ill
Is daily spun; but there exists no loom
To weave it into fabric.

               - Edna St. Vincent Millay
Friend DREAM 2012-11-14

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Stephen Friend Haas School of Business 2012-03-05
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Stephen Friend AMIA Symposium 2012-03-21
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Friend DREAM 2012-11-14

  • 2.
  • 3. Now possible to generate massive amount of human “omic’s” data
  • 4. Network Modeling Approaches for Diseases are emerging
  • 5. IT Infrastructure and Cloud compute capacity allows a generative open approach to solving problems
  • 6. Nascent Movement for patients to Control Sensitive information allowing sharing
  • 7. Open Social Media allows citizens and experts to use gaming to solve problems
  • 8. 1- Now possible to generate massive amount of human “omic’s” data 2-“Top Down” Network Modeling Approaches for Diseases are emerging 3- IT Infrastructure and Cloud compute capacity allows a generative open approach to biomedical problem solving 4-Nascent Movement for patients to Control Sensitive information allowing sharing 5- Open Social Media allows citizens and experts to use gaming to solve problems A HUGE OPPORTUNITY -- A HUGE RESPONSIBILITY
  • 9.
  • 10.
  • 11.
  • 12.
  • 13.
  • 14. ENVIRONMENT Non-coding RNA network BRAIN HEART ENVIRONMENT GI TRACT protein network KIDNEY ENVIRONMENT metabolite network IMMUNE SYSTEM VASCULATURE transcriptional network ENVIRONMENT
  • 15.
  • 16.
  • 17.
  • 18. .
  • 19. TENURE FEUDAL STATES
  • 20.
  • 21.
  • 22.
  • 24.
  • 25. Iterative Networked Approaches To Generating Analyzing and Supporting New Models Data Biological System Analysis Uncouple the automatic linkage between the data generators, analyzers, and validators
  • 27. “We Must Guard Against the acquisition of unwarranted influence, whether sought or unsought, by the Military Industrial Complex” - Dwight D. Eisenhower 1961
  • 28.
  • 29. BUILDING PRECISION MEDICINE Extensions of current Institutions Proprietary Short term Solutions Open Systems of Sharing in a Commons
  • 30. An Alternative Biomedicine Information Commons Commons are resources that are owned in common or shared among communities. -David Bollier
  • 31. At Sage Bionetworks we believe medical research has to change Research needs to become more open. Research should be transparent to other scientists and shared with the patients it involves. Data, tools, and methods that researchers develop should be shared in formats that can be used time and time again. Results should be commonly available online to all, in real-time. And negative or neutral outcomes should be published. Research needs to involve more relevant people in a collaborative approach. Patients or citizens, researchers and organizations need to work together better to decide what questions should be answered, and how the answers should be obtained. This would weight priorities more towards more practical benefits.
  • 32. Sage Bionetworks Collaborators  Pharma Partners  Merck, Pfizer, Takeda, Astra Zeneca, Amgen,Roche, Johnson &Johnson  Foundations  Kauffman CHDI, Gates Foundation  Government  NIH, LSDF, NCI  Academic  Levy (Framingham)  Rosengren (Lund)  Krauss (CHORI)  Federation  Ideker, Califano, Nolan, Schadt 32
  • 33. Networked Approaches BioMedicine Information Commons Patients/ Data Generators Citizens CURATED DATA Data TOOLS/ Analysts METHODS RAW DATA ANALYSES/ MODELS Clinicians SYNAPSE Experimentalists
  • 34. Technology Platform Governance Impactful Models Better Models of Disease: INFORMATION COMMONS Challenges
  • 35. RAS Model using primary tumor data to predict KRAS mutation status Justin Guinney 290 CRC samples: • KRAS12 or KRAS13 (n=115) vs WT (n=175) • Penalized regression model using ElasticNet and gene expression data 1.0 0.8 Robust External True positive rate 0.6 Validation In CRC TCGA CRC Khambata−Ford 0.4 Gaedcke data sets 0.2 0.0 0.0 0.2 0.4 0.6 0.8 1.0 False positive rate Model specific to CRC: does not generalized to other KRAS dependent cancers RAS signatures derived from CRC cohort can classify mutation status in CRC 35
  • 36. For 11/12 compounds, the #1 predictive feature in an unbiased analysis corresponds to the known stratifier of sensitivity Adam Margolin #2 CML lineage CML lineage #1 EGFR mut EGFR mut #1 EGFR mut EGFR mut #1 CML lineage CML linage #1 EGFR mut EGFR mut #1 ERBB2 expr ERBB2 expr Can the approach make new mut #1 BRAF BRAF mut discoveries? #1 HGF expr HGF expr #2 NRAS mut NRAS mut BRAF mut #1 BRAF mut #3 KRAS mut KRAS mut #2 NRAS mut NRAS mut BRAF mut #1 BRAF mut #3 KRAS mut KRAS mut #2 NRAS mut NRAS mut BRAF mut #1 BRAF mut #2 TP53 mut TP53 mut #3 CDKN2A copy CDKN2A copy #1 MDM2 expr MDM2 expr
  • 37. Tool: PORTABLE LEGAL CONSENT Control of Private information by Citizens allows sharing weconsent.us John Wilbanks John Wilbanks • Online educational wizard • Tutorial video • Legal Informed Consent Document • Profile registration • Data upload
  • 38. two approaches to building common scientific and technical knowledge Every code change versioned Every issue tracked Text summary of the completed project Every project the starting point for new work Assembled after the fact All evolving and accessible in real time Social Coding
  • 39. “Synapse is a compute platform for transparent, reproducible, and modular collaborative research.”
  • 40. Data Analysis with Synapse Run Any Tool On Any Platform Record in Synapse Share with Anyone
  • 41. Synapse is GitHub for Biomedical Data • Every code change versioned • Every issue tracked • Every project the starting point for new work • Data and code versioned • Social/Interactive Coding • Analysis history captured in real time • Work anywhere, and share the results with anyone • Social/Interactive Science
  • 42. Currently at 16K+ datasets and ~1M models
  • 45. Download analysis and meta-analysis Download another Cluster Result Download Evaluation and view more stats • Perform Model averaging • Compare/contrast models • Find consensus clusters
  • 46. Objective assessment of factors influencing model performance (>1 million predictions evaluated) Sanger CCLE Cross validation prediction accuracy (R2) Prediction accuracy improved by… Not discretizing data Including expression data Elastic net regression 130 compounds In Sock Jang 24 compounds
  • 47.
  • 48. Erich Huang, Brian Bot, Dave Burdick
  • 49.
  • 50. Sage-DREAM Breast Cancer Prognosis Challenge one month of building better disease models together Caldos/Aparicio breast cancer data 154 participants; 27 countries 334 participants; >35 countries Sep 26 Status Challenge Launch: July 17 >500 models posted to Leaderboard
  • 51.
  • 52.
  • 53. Bob Young Top Hat " #$$%&'! Eric Topol UCSD my Todd Park gene CTO Michael Nielsen my dat a Wadah Khanfar Al Jazeera Eric Hershman m y paper Ushhidi Jennifer Pahlka Code for America 01""*) & ) &*!+,$-$. /!& ( & 2, % & " $) -5 " .6*& 7 7 "$*& $% **& :& <=; >?2, $&., $A4 & ) 34 0" 0" .) & 89.4 ; & @ *A" *-.) , 7 4 &( ) & 5 5 5 C % A"$% **C .%& $%:4 B& *, ) .) " & Keyn ot e Sp eak er s: Law r en ce Lessi g – author “The future of ideas” &“Remix” Jam i e Heyw ood – patients like me Lan ce Ar m st r on g – LiveStrong Davi d Hau ssl er - UCSC Sage Commons Congress – San Francisco April 19-20 Genome Browser Jam es Boyl e – Duke Law School Ad r i en Tr eu ille –Foldit ! " #$%'$( Young Investigator Awards Ten ) *+% -" .*/& & , & Ear n one of t en t r i p s t o Com m ons Cong r ess i n SF! – t o ap p l y vi si t h t t p :/ / b i t .l y/ 2012YIA!
  • 54. Now possible to generate massive amount of human “omic’s” data Network Modeling for Diseases are emerging IT Infrastructure and Cloud compute capacity allows a generative open approach to biomedical problem solving Nascent Movement for patients to Control Private information allowing sharing Open Social Media allowing citizens and experts to use gaming to solve problems THESE FIVE TRENDS CAN ENABLE AN OPEN COMMUNITY OF IMPATIENT CITIZENS-- AS PATIENTS/RESEARCHERS/FUNDERS
  • 55.
  • 56. Upon this gifted age, in its dark hour, Rains from the sky a meteoric shower Of Facts…they lie unquestioned,uncombined. Wisdom enough to leech us of our ill Is daily spun; but there exists no loom To weave it into fabric. - Edna St. Vincent Millay