stephen friend genetic alliance 25th anniversary 2011-06-24
DESCRIPTION
Stephen Friend, Jun 24-26, 2011. Genetic Alliance 25th Anniversary Annual Conference, Washington, DCTRANSCRIPT
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it is more about how we do science than what
advantages of an open innovation compute space for building better models of disease
beyond siloed drug discovery- Arch2POCM
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Autism Transverse Myelitis
Diabetes Cancer Treating Symptoms v.s. Modifying Diseases
Will it work for me?
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Personalized Medicine 101: Capturing Single bases pair mutations = ID of responders
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Reality: Overlapping Pathways provide complexity
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WHY NOT USE “DATA INTENSIVE” SCIENCE
TO BUILD BETTER DISEASE MAPS?
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Equipment capable of generating massive amounts of data
“Data Intensive Science”- “Fourth Scientific Paradigm” For building: “Better Maps of Human Disease”
Open Information System
IT Interoperability
Evolving Models hosted in a Compute Space- Knowledge Expert
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It is now possible to carry out comprehensive monitoring of many traits at the population level
Monitor disease and molecular traits in populations
Putative causal gene
Disease trait
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trait trait trait trait trait trait trait trait trait trait trait trait trait
How is genomic data used to understand biology?
Standard! GWAS Approaches Profiling Approaches
Integrated! Genetics Approaches
Genome scale profiling provide correlates of disease Many examples BUT what is cause and effect?
Identifies Causative DNA Variation but provides NO mechanism
Provide unbiased view of molecular physiology as it
relates to disease phenotypes
Insights on mechanism
Provide causal relationships and allows predictions
RNA amplification Microarray hybirdization
Gene Index
Tum
ors
Tum
ors
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The
Evol
utio
n of
Sys
tem
s B
iolo
gy
Disease Models
Physiologic / Pathologic Phenotype Regulation
Literature
Structure Mol. Profiles
Model Evolution
Model Topology
Model Dynamics
Mol. Profiles
Genomic
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50 network papers http://sagebase.org/research/resources.php
List of Influential Papers in Network Modeling
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(Eric Schadt)
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Sage Mission
Sage Bionetworks is a non-profit organization with a vision to create a “commons” where integrative bionetworks are evolved by
contributor scientists with a shared vision to accelerate the elimination of human disease
Sagebase.org
Data Repository
Discovery Platform
Building Disease Maps
Commons Pilots
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Sage Bionetworks Collaborators
Pharma Partners Merck, Pfizer, Takeda, Astra Zeneca, Amgen
15
Foundations CHDI, Gates Foundation
Government NIH, LSDF
Academic Levy (Framingham)
Rosengren (Lund)
Krauss (CHORI)
Federation Ideker, Califarno, Butte, Schadt
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Research Platform Research Platform Commons
Data Repository
Discovery Platform
Building Disease
Maps
Tools & Methods
Repository
Discovery
Maps
Tools &
Repository
Discovery
Repository
Discovery
Repository
Discovery
Repository
Discovery
Repository
Discovery
Commons Pilots
Outposts Federation
CCSB
LSDF-WPP Inspire2Live
POC
Cancer Neurological Disease
Metabolic Disease
Pfizer Merck
Takeda Astra Zeneca
CHDI Gates NIH
Curation/Annotation
CTCAP Public Data Merck Data TCGA/ICGC
Hosting Data Hosting Tools Hosting
Models
LSDF
Bayesian Models Co-expression Models
KDA/GSVA
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Clinical Trial Comparator Arm Partnership (CTCAP)
Description: Collate, Annotate, Curate and Host Clinical Trial Data with Genomic Information from the Comparator Arms of Industry and Foundation Sponsored Clinical Trials: Building a Site for Sharing Data and Models to evolve better Disease Maps.
Public-Private Partnership of leading pharmaceutical companies, clinical trial groups and researchers.
Neutral Conveners: Sage Bionetworks and Genetic Alliance [nonprofits].
Initiative to share existing trial data (molecular and clinical) from non-proprietary comparator and placebo arms to create powerful new tool for drug development.
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Objective Rewards vs Deeper Rewards
AUTONOMY MASTERY PURPOSE
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Model of Alzheimer’s Disease Bin Zhang Jun Zhu
AD
normal
AD
normal
AD
normal
Cell cycle
http://sage.fhcrc.org/downloads/downloads.php
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THE FEDERATION Butte Califano Friend Ideker Schadt
vs
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Federated Aging Project : Combining analysis + narrative
=Sweave Vignette Sage Bionetworks Lab
Califano Lab Ideker Lab Califano Lab
Shared Data Repository
JIRA: Source code repository & wiki
R code + narrative
PDF(plots + text + code snippets) PDF(plots + text + code snippets)
Data objects
HTML
Submitted Paper
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Synapse as a Github for building models of disease
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Platform for Modeling
SYNAPSE
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IMPACT ON PATIENTS IMPACT ON PATIENTS
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ANY CITIZEN/ PATIENT
ANY FOUNDATION Or INDUSTRY PROJECT
ANY MODELER
ANY CITIZEN/ PATIENT
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Assumption that genetic alterations in human conditions should be owned
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. .
We still consider much clinical research as if we were hunter gathers!- not sharing soon enough
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TENURE FEUDAL STATES
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RULES GOVERN
Engaging Communities of Interest
PLAT
FORM
NEW
MAP
S NEW MAPS
Disease Map and Tool Users- ( Scientists, Industry, Foundations, Regulators...)
PLATFORM Sage Platform and Infrastructure Builders-
( Academic Biotech and Industry IT Partners...)
RULES AND GOVERNANCE Data Sharing Barrier Breakers-
(Patients Advocates, Governance and Policy Makers, Funders...)
NEW TOOLS Data Tool and Disease Map Generators- (Global coherent data sets, Cytoscape,
Clinical Trialists, Industrial Trialists, CROs…)
PILOTS= PROJECTS FOR COMMONS Data Sharing Commons Pilots-
(Federation, CCSB, Inspire2Live....)
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http://sagecongress.org
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!
Group A: ACTIVATING ACCESS
Group D LEGAL STACK-ENABLING PATIENTS: John Wilbanks
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“… the world is becoming too fast, too complex, and too networked for any
company to have all the answers inside”
Y. Benkler, The Wealth of Networks
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Is the Industry managing itself into irrelevance?
$130 billion of patented drug sales will face generics in the 2011-2016 decade (55% of 2009 US sales)
Sales exposed to generics will double in 2012 (to $33 billion)
98% of big pharma sales come from products 5 years and older (avg patent life = 11 years)
6 big pharmas were lost in the last 10 years
R&D spending is flattening, threatening future innovation
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How to help Science pay more attention to your disease- Aled Edwards
Are we starting with the right targets?
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Largest Attrition For Pioneer Targets is at Clinical POC (Ph II)
Target ID/ Discovery
50% 10% 30% 30% 90%
This is killing drug discovery
We can generate effective and “safe” molecules in animals, but they do not have sufficient efficacy and/or safety in the chosen patient group.
Hit/Probe/Lead ID
Clinical Candidate ID
Toxicology/ Pharmacolo
gy
Phase I Phase IIa/IIb
Attrition
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The current pharma model is redundant
50% 10% 30% 30% 90%
Negative POC information is not shared
Attrition
Target ID/ Discovery
Hit/Probe/Lead ID
Clinical Candidate ID
Toxicology/ Pharmacolo
gy
Phase I Phase IIa/IIb
Target ID/ Discovery
Hit/Probe/Lead ID
Clinical Candidate ID
Toxicology/ Pharmacolo
gy
Phase I Phase IIa/IIb
Target ID/ Discovery
Hit/Probe/Lead ID
Clinical Candidate ID
Toxicology/ Pharmacolo
gy
Phase I Phase IIa/IIb
Target ID/ Discovery
Hit/Probe/Lead ID
Clinical Candidate ID
Toxicology/ Pharmacolo
gy
Phase I Phase IIa/IIb
Target ID/ Discovery
Hit/Probe/Lead ID
Clinical Candidate ID
Toxicology/ Pharmacolo
gy
Phase I Phase IIa/IIb
Target ID/ Discovery
Hit/Probe/Lead ID
Clinical Candidate ID
Toxicology/ Pharmacolo
gy
Phase I Phase IIa/IIb
Target ID/ Discovery
Hit/Probe/Lead ID
Clinical Candidate ID
Toxicology/ Pharmacolo
gy
Phase I Phase IIa/IIb
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“Remember the two
benefits of failure. First if
you do fail, you learn
what doesn’t work and
second the failure gives
you the opportunity to try
a new approach.”
Roger van Oech
Cost of Negative Ph II POC Estimated at $12.5 Billion Annually
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• We want to improve health
• New medicines are part of this equation
• In this, we are failing, and we want to find a solution
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Innovation is the ability to see change as an opportunity – not a threat
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Let’s imagine….
• A pool of dedicated, stable funding
• A process that attracts top scientists and clinicians
• A process in which regulators can fully collaborate to solve key scientific problems
• An engaged citizenry that promotes science and acknowledges risk
• Mechanisms to avoid bureaucratic and administrative barriers
• Sharing of knowledge to more rapidly achieve understanding of human biology
• A steady stream of targets whose links to disease have been validated in humans
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A globally distributed public private partnership (PPP) committed to:
• Generate more clinically validated targets by sharing data
• Help deliver more new drugs for patients
Arch2POCM
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Arch2POCM: what’s in a name?
Arch: as in archipelago and referring to the distributed network of academic labs, pharma partners and clinical sites that will contribute to Arch2POCM programs
POCM: Proof Of Clinical Mechanism: demonstration in a Ph II setting that the mechanism of the selected disease target can be safely and usefully modulated.
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Arch2POCM: a new drug development model?
• Pool public and private sector funding into an independent organization • Public sector provides stability and new ideas • Private sector brings focus and experience • Funding can focus explicitly on high-risk targets
• Pre-competitive model to test hypotheses from financial gain • Will attract top scientists and clinicians • Will allow regulators to participate as scientists • Will reduce perceived conflicts of interests – engages citizens/patients • Will reduce bureaucratic and administrative overhead • Will allow rapid dissemination of information without restriction - informs
public and private sectors and reduces duplication
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• Is there sufficient incentive?
• Will universities forego IP ownership?
• Can we protect compounds that “make it”?
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PPP
Pha
rma
Pub
lic fu
nder
s
Pat
ient
gro
ups
Aca
dem
ics
Reg
ulat
ors
CR
Os
Toronto Feb-2011 meeting: consensus among 5 pillars
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Toronto Feb-2011 meeting: output on Arch2POCM Feasibility
Pharma
- 6 organisations supportive
Academic Labs - access to discovery biology and test compounds
Patient groups
- access to patients more quickly and cheaply
- access to “personal data”
Regulators
- access to historical data
- want to help with new clinical endpoints and study designs
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Arch2POCM: April San Francisco Meeting
• Selected Disease Areas of Focus: Oncology,, Neuroscience and Opportunistic (Oncology, CNS-Autism/Schizophrenia and Project X, respectively)
• Defined primary entry points of Arch2POCM test compounds into overall development pipeline
• Committed academic centers identified: UCSF, Toronto, Oxford
• CROs engaged
• Evaluated Arch2POCM business model
• Two Science Translational Medicine manuscripts published
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Entry Points For Arch2POCM Programs
Lead identification Phase I Phase II Preclinical
Lead optimisation
Assay in vitro probe
Lead Clinical candidate
Phase I asset
Phase II asset
- genomic/ genetic Pioneer target sources - disease networks
- academic partners - private partners - Sage Bionetworks, SGC,
Early Discovery
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Arch2POCM and the Power of Crowdsourcing
• “Crowdsourcing:” the act of outsourcing tasks traditionally performed by an employee to a large group of people or community
• By making Arch2POCM’s clinically characterized probes available to all, Arch2POCM will seed independently funded, crowdsourced experimental medicine
• Crowdsourced studies on Arch2POCM probes will provide clinical information about the pioneer targets in MANY indications
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Arch2POCM Communities of Interest
• Arch2POCM Strategic Design Teams • Currently in place for oncology and CNS disease areas • Multiple pharmas represented in leadership • Charged to define detailed project workflow and timeline
• Private Foundations • Opportunity to seed an Arch2POCM Strategic Design Team • Opportunity to leverage the release of patient data for sponsored trials
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Arch2POCM Strategic Design Teams: Target Selection Criteria
Pioneer
May be “high risk”
High patient value
POCM study must provide learnings
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ArchPOCM Oncology Disease Area
Focus: Unprecedented targets and mechanisms
Novelty MOA and clinical findings
Arc2POCM Capacity: 5 targets/year for ~ 4 years
Gate 1: ~75% effort • New target with lead and Sage bionetworks insights on MOA (increase
likelihood of success), or • New target (enabled by Sage) with assay
Gate 2: ~25% effort • Pharma failed or deprioritized/parked compounds • Compound ID is followed by a Sage systems biology effort to define MOA and
clinical entry point
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ArchPOCM Oncology: Epigenetics selected as the target area of choice
Top Targets:
• Discovery • Jard1 • Ezh1 • G9A
• Lead • Dyrk1
• Pre-Clin • ̀Brd4
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Arch2POCM: Next Steps • Oncology and CNS Arch2POCM strategic design teams to generate project workflow plans and timelines (September)
• Seed Arch2POCM strategic design team around a disease area of high interest to private foundation(s) to generate project workflow and timelines (Q4, 2011)
• Define critical details of Arch2POCM leadership, organizational and decision-making structures (Q3-Q4, 2011)
• Develop business case to support Arch2POCM programs (Q3-Q4, 2011)
• Obtain financial backing in order to launch operations in early 2012 in at least one disease area
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Which disease areas?
Which pathways?
How will we select targets?
Costs/ Timelines/ Deliverables?
Strengths and Weaknesses?
Arch2POCM Strategic Design Teams: (One of the Breakout Groups for this Afternoon )
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Arch2POCM: an idea whose time has come
Ideas are only as good as your ability to make them happen.
"In a world of abundant knowledge, hoarding technology is a self-limiting strategy. Nor can any organization, even the largest, afford any longer to ignore the tremendous external pools of knowledge that exist.“ Henry Chesbrough
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it is more about how we do science than what
advantages of an open innovation compute space for building better models of disease
beyond siloed drug discovery- Arch2POCM