Stephen Friend Genetic Alliance 25th Anniversary 2011-06-24


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Stephen Friend, Jun 24-26, 2011. Genetic Alliance 25th Anniversary Annual Conference, Washington, DC

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Stephen Friend Genetic Alliance 25th Anniversary 2011-06-24

  1. 1. it is more about how we do science than whatadvantages of an open innovation compute space for building better models of disease beyond siloed drug discovery- Arch2POCM
  2. 2. Autism Transverse Myelitis Treating Symptoms v.s. Modifying Diseases Diabetes Cancer Will it work for me?
  3. 3. Personalized Medicine 101:Capturing Single bases pair mutations = ID of responders
  4. 4. Reality: Overlapping Pathways provide complexity
  6. 6. “Data Intensive Science”- “Fourth Scientific Paradigm”For building: “Better Maps of Human Disease” Equipment capable of generating massive amounts of data IT Interoperability Open Information System Evolving Models hosted in a Compute Space- Knowledge Expert
  7. 7. It is now possible to carry out comprehensive monitoring of many traits at the population levelMonitor disease and molecular traits in populations Putative causal gene Disease trait
  8. 8. How is genomic data used to understand biology? RNA amplification Tumors Microarray hybirdization Tumors Gene Index Standard!GWAS Approaches Profiling Approaches Identifies Causative DNA Variation but Genome scale profiling provide correlates of disease provides NO mechanism   Many examples BUT what is cause and effect?   Provide unbiased view of molecular physiology as it relates to disease phenotypes trait   Insights on mechanism   Provide causal relationships and allows predictions Integrated!Genetics Approaches
  9. 9. Genomic Literature Mol. Profiles StructureThe Evolution of Systems Biology Model Evolution Disease Models Model Topology Physiologic / Pathologic Model Dynamics Phenotype Regulation
  10. 10. List of Influential Papers in Network Modeling   50 network papers 
  11. 11. (Eric Schadt)
  12. 12. 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 diseaseBuilding Disease Maps Data RepositoryCommons Pilots Discovery Platform
  13. 13. Sage Bionetworks Collaborators  Pharma Partners   Merck, Pfizer, Takeda, Astra Zeneca, Amgen  Foundations   CHDI, Gates Foundation  Government   NIH, LSDF  Academic   Levy (Framingham)   Rosengren (Lund)   Krauss (CHORI)  Federation   Ideker, Califarno, Butte, Schadt 15
  14. 14. Platform Commons Research Cancer Neurological Disease Metabolic Disease Curation/Annotation Building Data Disease Repository Maps CTCAP Public Data Pfizer Merck Data Outposts Merck TCGA/ICGC Federation Takeda CCSB Astra Zeneca CHDI Commons Pilots Gates NIH LSDF-WPP Inspire2Live Hosting Data POCHosting Tools Hosting Bayesian Models Co-expression Models Models Discovery Tools & Platform Methods KDA/GSVA LSDF
  15. 15. 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.
  16. 16. Objective Rewards vs Deeper Rewards AUTONOMY MASTERY PURPOSE
  17. 17. Bin ZhangModel of Alzheimer’s Disease Jun Zhu AD normal AD normal AD normal Cell cycle
  18. 18. THE FEDERATIONButte Califano Friend Ideker Schadt vs
  19. 19. Federated Aging Project : Combining analysis + narrative =Sweave VignetteSage Bionetworks Lab R code + PDF(plots + text + code snippets) narrative HTML Data objects Califano Lab Ideker Lab Submitted Paper Shared Data JIRA: Source code repository & wiki Repository
  20. 20. Synapse as a Github for building models of disease
  21. 21. Platform for Modeling SYNAPSE
  24. 24. Assumption that genetic alterationsin human conditions should be owned
  25. 25. We still consider much clinical research as if we were hunter gathers! not sharing soon enough - .
  27. 27. Engaging Communities of Interest 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 M and Policy Makers,  Funders...) APS FORM NEW TOOLS PLAT NEW Data Tool and Disease Map Generators- (Global coherent data sets, Cytoscape, RULES GOVERN Clinical Trialists, Industrial Trialists, CROs…) PILOTS= PROJECTS FOR COMMONS Data Sharing Commons Pilots- (Federation, CCSB, Inspire2Live....)
  28. 28.
  30. 30. … the world is becoming toofast, too complex, and too networked for any company to have all the answers inside Y. Benkler, The Wealth of Networks
  31. 31. 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
  32. 32. Are we starting with the right targets?How to help Science pay more attention to your disease- Aled Edwards
  33. 33. Largest Attrition For Pioneer Targets is at Clinical POC (Ph II) Target ID/ Hit/Probe/ Clinical Toxicology/ Phase I Phase Discovery Lead ID Candidate ID Pharmacolo IIa/IIb gyAttrition 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.
  34. 34. The current pharma model is redundant Target ID/ Hit/Probe/ Clinical Toxicology/ Phase I Phase Discovery Lead ID Candidate ID Pharmacolo IIa/IIb Phase Target ID/ Hit/Probe/ Clinical Toxicology/ gy Phase I Discovery Lead ID Candidate ID Pharmacolo IIa/IIb gy Target ID/ Hit/Probe/ Clinical Toxicology/ Phase I Phase Discovery Lead ID Candidate ID Pharmacolo IIa/IIb gy Target ID/ Hit/Probe/ Clinical Toxicology/ Phase I Phase Discovery Lead ID Candidate ID Pharmacolo IIa/IIb gy Target ID/ Hit/Probe/ Clinical Toxicology/ Phase I Phase Discovery Lead ID Candidate ID Pharmacolo IIa/IIb gy Target ID/ Hit/Probe/ Clinical Toxicology/ Phase I Phase Discovery Lead ID Candidate ID Pharmacolo IIa/IIb gy Target ID/ Hit/Probe/ Clinical Toxicology/ Phase I Phase Discovery Lead ID Candidate ID Pharmacolo IIa/IIb gyAttrition 50% 10% 30% 30% 90% Negative POC information is not shared
  35. 35. Cost of Negative Ph II POC Estimated at $12.5 Billion Annually 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
  36. 36. •  We want to improve health•  New medicines are part of this equation•  In this, we are failing, and we want to find a solution
  37. 37. Innovation is the ability to see change as an opportunity – not a threat
  38. 38. 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
  39. 39. Arch2POCMA globally distributed public private partnership (PPP) committed to: • Generate more clinically validated targets by sharing data • Help deliver more new drugs for patients
  40. 40. 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.
  41. 41. 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
  42. 42. • Is there sufficient incentive?• Will universities forego IP ownership?• Can we protect compounds that make it ?
  43. 43. PharmaPublic fundersPatient groups PPP Academics Regulators Toronto Feb-2011 meeting: consensus among 5 pillars CROs
  44. 44. Toronto Feb-2011 meeting: output on Arch2POCM FeasibilityPharma - 6 organisations supportiveAcademic Labs - access to discovery biology and test compoundsPatient 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
  45. 45. 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
  46. 46. Entry Points For Arch2POCM Programs - genomic/ genetic Pioneer target sources - disease networks - academic partners - private partners - Sage Bionetworks, SGC, Lead Lead Preclinical Phase I Phase II identification optimisation Assay in vitro probe Lead Clinical Phase I Phase II candidate asset asset Early Discovery
  47. 47. Arch2POCM and the Power of Crowdsourcing•  Crowdsourcing: the act of outsourcing taskstraditionally performed by an employee to a large groupof people or community• By making Arch2POCM s clinically characterizedprobes available to all, Arch2POCM will seedindependently funded, crowdsourced experimentalmedicine• Crowdsourced studies on Arch2POCM probes willprovide clinical information about the pioneer targets inMANY indications
  48. 48. 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
  49. 49. Arch2POCM Strategic Design Teams: Target Selection Criteria Pioneer May be “high risk” High patient valuePOCM study must provide learnings
  50. 50. ArchPOCM Oncology Disease AreaFocus: Unprecedented targets and mechanisms Novelty  MOA and clinical findingsArc2POCM 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
  51. 51. ArchPOCM Oncology: Epigenetics selected as the target area of choice Top Targets: • Discovery • Jard1 • Ezh1 • G9A • Lead • Dyrk1 • Pre-Clin • `Brd4
  52. 52. Arch2POCM: Next Steps• Oncology and CNS Arch2POCM strategic design teams togenerate project workflow plans and timelines (September)• Seed Arch2POCM strategic design team around a disease areaof high interest to private foundation(s) to generate projectworkflow and timelines (Q4, 2011)• Define critical details of Arch2POCM leadership, organizationaland 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 early2012 in at least one disease area
  53. 53. Arch2POCM Strategic Design Teams:(One of the Breakout Groups for this Afternoon ) Which disease areas? Which pathways? How will we select targets? Costs/ Timelines/ Deliverables? Strengths and Weaknesses?
  54. 54. Arch2POCM: an idea whose time has come"In a world of abundant knowledge, hoarding technology is a self-limiting strategy. Norcan any organization, even the largest, afford any longer to ignore the tremendousexternal pools of knowledge that exist. Henry Chesbrough Ideas are only as good as your ability to make them happen.
  55. 55. it is more about how we do science than whatadvantages of an open innovation compute space for building better models of disease beyond siloed drug discovery- Arch2POCM