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

HEART

VASCULATURE

KIDNEY

IMMUNE SYSTEM

transcriptional network

protein network

metabolite network

Non-coding RNA network

GI TRACT

BRAIN

ENVIRONMENT E

NV

IRO

NM

EN

T

ENVIRONMENT

EN

VIR

ON

ME

NT

.

TENURE FEUDAL STATES

• alchemist

Biological

System

Data

Analysis

Iterative Networked Approaches

To Generating Analyzing and Supporting New Models

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

Commons are resources that are owned in common or shared among

communities.

-David Bollier

Biomedicine

Information

Commons

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

32

Foundations

Kauffman CHDI, Gates Foundation

Government

NIH, LSDF, NCI

Academic

Levy (Framingham)

Rosengren (Lund)

Krauss (CHORI)

Federation

Ideker, Califano, Nolan, Schadt

SYNAPSE

CURATED

DATA

TOOLS/

METHODS

ANALYSES/

MODELS

RAW

DATA

BioMedicine Information Commons

Data

Generators

Data

Analysts

Experimentalists

Clinicians

Patients/

Citizens

Networked Approaches

Better Models of

Disease:

INFORMATION

COMMONS

Technology Platform

Challenges

Imp

actf

ul M

od

els

Go

vernan

ce

RAS Model using primary tumor data to predict KRAS mutation status

Justin Guinney

35

290 CRC samples:

• KRAS12 or KRAS13 (n=115) vs WT (n=175)

• Penalized regression model using ElasticNet and gene expression data

Robust External Validation In CRC data sets

RAS signatures derived from CRC cohort can classify mutation status in CRC

False positive rate

Tru

e p

ositiv

e r

ate

0.0 0.2 0.4 0.6 0.8 1.00.0

0.2

0.4

0.6

0.8

1.0

TCGA CRC

Khambata−Ford

Gaedcke

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

TP53 mut

CDKN2A copy

MDM2 expr

HGF expr

CML linage

EGFR mut

EGFR mut

EGFR mut

CML lineage

ERBB2 expr

BRAF mut

BRAF mut

NRAS mut

BRAF mut

NRAS mut

KRAS mut

BRAF mut

NRAS mut

KRAS mut

#1 BRAF mut

#2 NRAS mut #1 BRAF mut

#3 KRAS mut #2 NRAS mut #1 BRAF mut

#3 KRAS mut #2 NRAS mut #1 BRAF mut

#1 EGFR mut

#1 ERBB2 expr

#1 EGFR mut

#2 CML lineage #1 EGFR mut

#1 CML lineage

#1 HGF expr

#2 TP53 mut #3 CDKN2A copy #1 MDM2 expr

Can the approach make new discoveries?

For 11/12 compounds, the #1 predictive feature in an unbiased analysis corresponds to the known stratifier of sensitivity

Adam Margolin

Tool: PORTABLE LEGAL CONSENT Control of Private information by Citizens allows sharing

weconsent.us

John Wilbanks

• Online educational wizard • Tutorial video • Legal Informed Consent Document • Profile registration • Data upload

John Wilbanks

two approaches to building common

scientific and technical knowledge

Text summary of the completed project

Assembled after the fact

Every code change versioned

Every issue tracked

Every project the starting point for new work

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

• Data and code versioned

• Analysis history captured in real time

• Work anywhere, and share the results with anyone

• Social/Interactive Science

• Every code change versioned

• Every issue tracked

• Every project the starting point for new work

• Social/Interactive Coding

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 Prediction accuracy

improved by…

Not discretizing data

Including expression data

Elastic net regression

130 compounds 24 compounds

Cro

ss v

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red

icti

on

acc

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R2)

In Sock Jang

Erich Huang, Brian Bot, Dave Burdick

Sage-DREAM Breast Cancer Prognosis Challenge one month of building better disease models together

154 participants; 27 countries

334 participants; >35 countries

>500 models posted to Leaderboard

breast cancer data

Challenge Launch: July 17

Sep 26 Status

Caldos/Aparicio

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Keynote Speakers: Lawrence Lessig – author “The future of ideas” &“Remix”

Jam ie Heyw ood – patients like me Lance Armst rong – LiveStrong David Haussler - UCSC

Genome Browser James Boyle – Duke Law School Adr ien Treui l le –Foldit

! "#$%&'$( ) *+%, -" .*/&&Earn one of ten t r ips to Commons Congress in SF!

– t o apply visi t ht tp :/ / b i t .ly/ 2012YIA!

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Sage Commons Congress – San Francisco April 19-20 Ten Young Investigator Awards

Bob Young Top Hat Eric Topol UCSD Todd Park CTO Michael Nielsen Wadah Khanfar Al Jazeera Eric Hershman Ushhidi Jennifer Pahlka Code for America

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