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Issues with Current Drug Discovery                  A Proposal                Arch2POCM        A Drug Development Approach...
Alzheimers                             Diabetes     Treating Symptoms v.s. Modifying Diseases Depression                  ...
Familiar but Incomplete
Reality: Overlapping Pathways
Extensive Publications now Substantiating Scientific Approach              Probabilistic Causal Bionetwork Models• >80 Pub...
List of Influential Papers in Network Modeling                                        50 network papers                  ...
(Eric Schadt)
Requires Data driven Science         Lots of data, tools, evolving models of diseaseRequires Scientists Clinicians & Citiz...
Sage Mission      Sage Bionetworks is a non-profit organization with a vision to   create a commons where integrative bion...
Sage Bionetworks Collaborators  Pharma Partners     Merck, Pfizer, Takeda, Astra Zeneca, Amgen  Foundations     CHDI, ...
Engaging Communities of Interest                                               NEW MAPS                                   ...
Bin ZhangModel of Breast Cancer: Integration                                                              Xudong Dai      ...
Section 1 – Project OverviewNon-Responder Cancer Project Mission                                To identify Non-Responders...
Section 1 – Project OverviewThe Non-Responder Project is an international initiative with funding for 6 initialcancers ant...
Section 1 – Project OverviewThe Non-Responder Cancer Project Leadership Team                                 Stephen Frien...
Section 1 – Project OverviewThe Non-Responder Cancer Project Leadership Team                                 Charles Sawye...
Section 2 – Research PlanFor each tumor-type, the non-responder project will follow a common workflow, with patientidentif...
Section 2 – Research PlanIdentification and EnrollmentThe number of patients and enrollment procedures will vary for each ...
Section 2 – Research PlanSample ProcessingSample processing will involve whole genome sequencing, conducted at leading TCG...
Section 2 – Research PlanData Collating and Disease ModelingThe genetic and clinical information will be combined and anal...
Arch2POCM	  A	  Fundamental	  Systems	  Change	           for	  Drug	  Discovery	     Stephen	  Friend	  Aled	  Edwards	  ...
“Absurdity”	  of	  Current	  R&D	  Ecosystem	  •    $200B	  per	  year	  in	  biomedical	  and	  drug	  discovery	  R&D	  ...
What	  is	  the	  problem?	  •     Regulatory	  hurdles	  too	  high?	  •     Low	  hanging	  fruit	  picked?	  •     Paye...
What	  is	  the	  problem?	  •  	  	  	  	  The	  current	  system	  is	  designed	  as	  if	  every	  new	     program	  ...
The current pharma model is redundant                                           	Target ID/               Hit/Probe/      ...
What	  is	  the	  problem?	  The	  real	  problem	  is	  that	  the	  current	  system	  is	  unable	  to	  provide	  the	...
The Solution: Arch2POCMA globally distributed public private partnership (PPP) committed to: 	   • Generate more clinicall...
Arch2POCM: What Will It Do?•    Arch2POCM will focus on targets that are deemed too risky for either public     or private...
Why Data Sharing Through To Phase IIb?•  Most rapid approach to reveal limitations and   opportunities associated with the...
Why No IP on “Common Stream” Compounds?•     Allows multiple groups to test compounds in diverse      indications without ...
The Benefits of the Arch2POCM Pre-competitive            Model: Crowdsourced Studies              The	  Crowd	            ...
Arch2POCM: Scale and Scope•  Proposed Goal: Initiate 2 programs. One for Epigenetic Oncology/   Immunology. One for Neuros...
Epigenetics/ Chromatin Biology:Arch2POCM s Selected Pioneer Area of Oncology/        Immunology Drug Discovery            ...
How We Define Epigenetics                                      Lysine                   DNA                           Hist...
The Case for Epigenetics/Chromatin Biology1.    There are epigenetic oncology drugs on the market (HDACs)2.    A growing n...
Examples of Epigenetic Links to Cancer•    Ezh2 methyltransferase (enhancer of zeste homolog 2)      –  Somatic mutations ...
The Current Epigenetics Universe (2011)        Domain Family          Typical substrate class*             Total          ...
Some Potential Arch2POCM Epigenetic   Oncology/Immunology Targets                                      38
Open	  Access	  Test	  Compounds	  and	  Tools	  Are	  Available	  For	                             Arch2POCM	  Teams	    ...
Proposed IT Infrastructure For Arch2POCM Data                                 Sharing                                     ...
General Benefits of Arch2POCM For Drug              Development1.  Arch2POCM s use of test compounds to de-risk previously...
Arch2POCM Value Propositions For Academia  •  Funding to pursue and publish disruptive discovery research  •  Sharing of r...
Example	  6:	  Sage	  Congress	  2012	  Pa%ent	  Project                                                             	  
Stephen Friend Institute of Development, Aging and Cancer 2011-11-29
Stephen Friend Institute of Development, Aging and Cancer 2011-11-29
Stephen Friend Institute of Development, Aging and Cancer 2011-11-29
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Stephen Friend Institute of Development, Aging and Cancer 2011-11-29

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Stephen Friend Nov 28-29, 2011. Institute of Development, Aging and Cancer, Sendai, Japan

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Stephen Friend Institute of Development, Aging and Cancer 2011-11-29

  1. 1. Issues with Current Drug Discovery A Proposal Arch2POCM A Drug Development Approachfrom Disease Targets to their Clinical Validation Stephen Friend Sage Bionetworks (a non-profit foundation) Sendai November 2011
  2. 2. Alzheimers Diabetes Treating Symptoms v.s. Modifying Diseases Depression Cancer Will it work for me?
  3. 3. Familiar but Incomplete
  4. 4. Reality: Overlapping Pathways
  5. 5. Extensive Publications now Substantiating Scientific Approach Probabilistic Causal Bionetwork Models• >80 Publications from Rosetta Genetics Metabolic "Genetics of gene expression surveyed in maize, mouse and man." Nature. (2003) Disease "Variations in DNA elucidate molecular networks that cause disease." Nature. (2008) "Genetics of gene expression and its effect on disease." Nature. (2008) "Validation of candidate causal genes for obesity that affect..." Nat Genet. (2009) ….. Plus 10 additional papers in Genome Research, PLoS Genetics, PLoS Comp.Biology, etc CVD "Identification of pathways for atherosclerosis." Circ Res. (2007) "Mapping the genetic architecture of gene expression in human liver." PLoS Biol. (2008) …… Plus 5 additional papers in Genome Res., Genomics, Mamm.Genome Bone "Integrating genotypic and expression data …for bone traits…" Nat Genet. (2005) d ..approach to identify candidate genes regulating BMD…" J Bone Miner Res. (2009) Methods "An integrative genomics approach to infer causal associations ... Nat Genet. (2005) "Increasing the power to detect causal associations… PLoS Comput Biol. (2007) "Integrating large-scale functional genomic data ..." Nat Genet. (2008) …… Plus 3 additional papers in PLoS Genet., BMC Genet.
  6. 6. List of Influential Papers in Network Modeling   50 network papers   http://sagebase.org/research/resources.php
  7. 7. (Eric Schadt)
  8. 8. Requires Data driven Science Lots of data, tools, evolving models of diseaseRequires Scientists Clinicians & Citizens to link in different ways
  9. 9. 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 Sagebase.org
  10. 10. 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 10
  11. 11. 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 and Policy Makers,  Funders...) ORM APS NEW TOOLSM F PLAT Data Tool and Disease Map Generators- NEW (Global coherent data sets, Cytoscape, Clinical Trialists, Industrial Trialists, CROs…) RULES GOVERN PILOTS= PROJECTS FOR COMMONS Data Sharing Commons Pilots- (Federation, CCSB, Inspire2Live....) Arch2POCM
  12. 12. Bin ZhangModel of Breast Cancer: Integration Xudong Dai Jun Zhu Conserved Super-modules mRNA proc. = predictive Breast Cancer Bayesian Network Chromatin of survival Extract gene:gene relationships for selected super-modules from BN and define Key Drivers Pathways & Regulators (Key drivers=yellow; key drivers validated in siRNA screen=green) Cell Cycle (Blue) Chromatin Modification (Black) Pre-mRNA proc. (Brown) mRNA proc. (red) Zhang B et al., Key Driver Analysis in Gene Networks (manuscript)
  13. 13. Section 1 – Project OverviewNon-Responder Cancer Project Mission To identify Non-Responders to approved drug regimens in order to improve outcomes, spare patients unnecessary toxicities from treatments that have no benefit to them, and reduce healthcare costsSage Bionetworks • Non-Responder Project
  14. 14. Section 1 – Project OverviewThe Non-Responder Project is an international initiative with funding for 6 initialcancers anticipated from both the public and private sectors GEOGRAPHY United States China TARGET CANCER Ovarian Renal Breast AML Colon Lung FUNDING Likely to be SOURCE funded by the Pilot Funded by the Chinese private Seeking private sector funding Federal sector partners GovernmentSage Bionetworks • Non-Responder Project
  15. 15. Section 1 – Project OverviewThe Non-Responder Cancer Project Leadership Team Stephen Friend, MD, PhD Todd Golub, MD President and Co-Founder of Sage Founding Director Cancer Biology Bionetworks, Head of Merck Oncology Program Broad Institute, Charles 01-08, Founder of Rosetta Dana Investigator Dana-Farber Inpharmatics 97-01, co-Founder of the Cancer Institute, Professor of Seattle Project Pediatrics Harvard Medical School, Investigator, Howard Hughes Medical Institute “This study aims to provide both a material near term “Having focused on molecular medicine in my improvement in cancer patient outcomes and a long term decades of conducting clinical trials, I am excited by blueprint for the future of oncology trails, prognosis and the opportunity for the Non-responder project to care. I believe the team of scientific, clinical and patient change the way we select treatments for patients. My advocate partners we have assembled is unique in its passion for this project and for improving our ability to ability to execute this study. With public and private better target therapies is immeasurable and I look sector support, I know we will be able to change the forward to being an active part of this research.” future of cancer care and research around the world.”Sage Bionetworks • Non-Responder Project
  16. 16. Section 1 – Project OverviewThe Non-Responder Cancer Project Leadership Team Charles Sawyers, MD Richard Schilsky, MD Chair, Human Oncology Memorial Chief, Hematology- Oncology, Deputy Sloan-Kettering Cancer Center, Director, Comprehensive Cancer Investigator, Howard Hughes Medical Center, University of Chicago; Chair, Institute, Member, National Academy National Cancer Institute Board of of Sciences, past President American Scientific Advisors; past-President Society of Clinical Investigation, 2009 ASCO, past Chairman CALGB clinical Lasker-DeBakey Clinical Medical trials group Research Award “I have considered many opportunities to engage in “Stephen and I have worked together for many years on personalized medicine, and believe the greatest value can developing innovative network approaches to analyzing be in developing assays to better target treatments for disease. Identifying signatures of non-response is the most patients at the molecular level. I have worked with Stephen exciting project I have been involved with in recent years for 3 years and believe he is uniquely qualified to lead a and one which I believe can dramatically shift the way project of this caliber to great success.” cancer patients receive treatment.”Sage Bionetworks • Non-Responder Project
  17. 17. Section 2 – Research PlanFor each tumor-type, the non-responder project will follow a common workflow, with patientidentification and sample collection the most variable across studiesNon-Responder Project WorkflowIdentification and enrollment, and data and sample The remaining parts of the study will be largely similar, and collection may differ by tumor-type potentially shared, across all projects Data  and   Clinical  Iden%fica%on  and   Sample   Disease   Feedback   Sample   Data   Enrollment   Processing   Modeling   and  Results   Collec%on   Repor%ng   Payment and Reimbursement Project ManagementSage Bionetworks • Non-Responder Project
  18. 18. Section 2 – Research PlanIdentification and EnrollmentThe number of patients and enrollment procedures will vary for each study based on the biologyand stage of the disease and the size of the advocate community •  The number of patients differs according to the biology of each tumor-type being investigated Ovarian Cancer How many patients •  The sample will require enough patients to identify 100-150 patients are required? In Ovarian Cancer, the target patient population will be those who experience for each arm (responders and non-responders) that have distinct biology recurrence within 6-24 months of stopping initial treatment. This population will require enrollment of 150 patients to identify groups with distinct response/non-response biology •  Enrollment sources will vary based on the makeup of the physician Ovarian Cancer Patients Who will be and patient communities responsible for •  Each study will entail a mix of physician-driven and patient-initiated enrollment , with those with strong advocate communities trending enrolling patients? + Initial Response* Surgical removal No initial response* towards patient-initiated, and those with leverageable physician 80% and initial chemo 20% relationships involving more physician targeting No recurrence Recurrence Second series of <24mo 6-24 months Doublet Chemo •  Data will include a questionnaire to determine eligibility and to What data will need collect additional information that may inform analysis (e.g. age, to be collected at race, etc.) Responders Non-Responders •  Additionally, patient consent will need to be obtained 30-50% 50-70% enrollment? •  Genetic Alliance will own and standardize the consenting process Since most ovarian cancer patients see a Gynecologic 30% Patient- Oncologist who manages the entirety of their treatment, initiated •  Costs to identify and enroll patients will vary by channel What will be the this tumor-type is well structured to use a select group of •  Patient-driven will be predominantly marketing and shipping costs cost of (e.g. marketing through the Love/Army of women costs $1500 until physicians/AMCs to target patients for enrollment 70% Physician- identification and study is filled) driven enrollment? •  Physician-driven enrollment may require educating physicians and a grant of approximately $20,000 per patient plus some administrative expensesSage Bionetworks • Non-Responder Project
  19. 19. Section 2 – Research PlanSample ProcessingSample processing will involve whole genome sequencing, conducted at leading TCGAparticipating sequencing centers, as well as bioinformatics and pathological review Labs  &  Pathology   Gene%c  Analysis   Core  Bioinforma%cs   •  Each  cancer  type  will   •  Analysis  will  include:   •  Bioinforma%cs  will  be   have  designated  sites   Whole  Genome   conducted  by  the  most   for  conduc%ng  rou%ne   Sequencing,   cost-­‐effec%ve,  trusted   labs  and  pathological   transcriptome  gene   provider  to  ensure  the   review  to    ensure   expression  and  copy   quality  and  consistency   consistency  of  analysis   number  varia%on   of  data  for  analysis   •  Each  study  will  have  a   •  The  core   primary  processing   bioinforma%cs   site,  which  will  be   processing  will  turn  the   selected  from  among   raw  data  into  usable   leaders  in  gene%c   altera%on  component   sequencing  that  have   lists  of  muta%ons  and   par%cipated  in  similar   dele%ons   projects,  such  as  The   Cancer  Genome  Atlas  Sage Bionetworks • Non-Responder Project
  20. 20. Section 2 – Research PlanData Collating and Disease ModelingThe genetic and clinical information will be combined and analyzed by Sage Bionetworks todesign a disease model identifying the causes of non-response 1 2 3 Combines genomic and Applies sophisticated Generates a map of drivers clinical data mathematical modeling of non-response All scientific output will be publicly available and no members of the research group will own any resulting IPSage Bionetworks • Non-Responder Project
  21. 21. Arch2POCM  A  Fundamental  Systems  Change   for  Drug  Discovery   Stephen  Friend  Aled  Edwards  Chas  Bountra  Lex  vander  Ploeg,  Thea  Norman,  Keith  Yamamoto  
  22. 22. “Absurdity”  of  Current  R&D  Ecosystem  •  $200B  per  year  in  biomedical  and  drug  discovery  R&D  •  Handful  of  new  medicines  approved  each  year  •  Produc%vity  in  steady  decline  since  1950  •  90%  of  novel  drugs  entering  clinical  trials  fail  •  NIH  and  EU  just  started  spending  billions  to  duplicate  process  •  98%  of  pharma  revenues  from  compounds  approved  more   than  5  years  ago  (average  patent  life  11  years)  •  >50,000  pharma  employees  fired  in  each  of  last  three  years  •  Number  of  R&D  sites  in  Europe  down  from  29  to  16  in  2009  
  23. 23. What  is  the  problem?  •  Regulatory  hurdles  too  high?  •  Low  hanging  fruit  picked?  •  Payers  unwilling  to  pay?  •  Genome  has  not  delivered?  •  Valley  of  death?  •  Companies  not  large  enough  to  execute  on  strategy?  •  Internal  research  costs  too  high?  •  Clinical  trials  in  developed  countries  too  expensive?  •  In  fact,  all  are  true  but  none  is  the  real  problem  
  24. 24. What  is  the  problem?  •         The  current  system  is  designed  as  if  every  new   program  is  des%ned  to  deliver  an  approved  drug  •  Each  new  therapy  is  pursued  through  use  of   proprietary  compounds  moving  in  parallel  with  no   data  being  shared  (ohen  5-­‐10  companies  at  a  %me)  •  Therefore  it  makes  complete  sense  to  maintain   secrecy  •  But  we  have  no  clue  what  we’re  doing   •   Alzheimer’s,  cancer,  schizophrenia,  au%sm.….  
  25. 25. The current pharma model is redundant Target ID/ Hit/Probe/ Clinical Toxicolog Phase I PhaseDiscovery Lead ID Candidate y/ IIa/IIb PhaseTarget ID/ Hit/Probe/ Clinical ID Pharmaco Toxicolog Phase IDiscovery Lead ID Candidate logy y/ IIa/IIb ID PharmacoTarget ID/ Hit/Probe/ Clinical logy Toxicolog Phase I PhaseDiscovery Lead ID Candidate y/ IIa/IIb ID PharmacoTarget ID/ Hit/Probe/ Clinical Toxicolog logy Phase I PhaseDiscovery Lead ID Candidate y/ IIa/IIb ID Pharmaco logyTarget ID/ Hit/Probe/ Clinical Toxicolog Phase I PhaseDiscovery Lead ID Candidate y/ IIa/IIb ID PharmacoTarget ID/ Hit/Probe/ Clinical logy Toxicolog Phase I PhaseDiscovery Lead ID Candidate y/ IIa/IIb ID PharmacoTarget ID/ Hit/Probe/ Clinical Toxicolog logy Phase I PhaseDiscovery Lead ID Candidate y/ IIa/IIb ID Pharmaco logy 50% 10% 30% 30% 90% AttritionNegative POC information is not shared
  26. 26. What  is  the  problem?  The  real  problem  is  that  the  current  system  is  unable  to  provide  the  needed  insights  into  human  biology  and  disease  required  We  need  to  develop  a  mechanism  to  be8er  understand  disease  biology  before  tes:ng  compe::ve  compounds  on  sick  people  
  27. 27. The Solution: Arch2POCMA globally distributed public private partnership (PPP) committed to: • Generate more clinically validated targets by sharing data • Help deliver more new drugs for patients 27 27
  28. 28. Arch2POCM: What Will It Do?•  Arch2POCM will focus on targets that are deemed too risky for either public or private sectors in the disease areas of cancer/immunology and shizophrenia/autism•  Arch2POCM will devleop and use test compounds to de-risk these targets and determine if the targets play a role in the biology of human disease•  Arch2POCM will share the risk by pooling public and private resources•  Arch2POCM will file no patents and place all data into the public domain: •  Enables the pharmaceutical sector to use this information to start, refine or shut down their own proprietary efforts •  Crowdsourcing expands our understanding of human biology and the number of ideas that can be pursued without additional funds•  Arch2POCM will make the test compounds available to academic groups and foundations so they can use them to explore a multitude of additional indications 28
  29. 29. Why Data Sharing Through To Phase IIb?•  Most rapid approach to reveal limitations and opportunities associated with the target•  Increases probability of success for internal proprietary programs•  Scientific decisions are not influenced by market considerations or biased internal thinking•  Target mechanism is only properly tested at Phase IIb 29
  30. 30. Why No IP on “Common Stream” Compounds?•  Allows multiple groups to test compounds in diverse indications without funds from Arch2POCM- crowdsourcing drug discovery•  Broader and faster data dissemination•  Far fewer legal agreements to negotiate•  Generates “freedom to operate” on target because there are no patent thickets to wade through•  Efficient way to access world’s top scientists and doctors without hassle 30
  31. 31. The Benefits of the Arch2POCM Pre-competitive Model: Crowdsourced Studies The  Crowd   Arch2POCM Compounds And Data Crowdsourced data on Arch2POCM test compound • SAR  med  chem   • Best  indica%on   Clin   • Clinical  data  Crowdsourced  studies  on  Arch2POCM  test  compounds  will  provide  clinical  informa:on  about  the  pioneer  targets  in  MANY  indica:ons   31
  32. 32. Arch2POCM: Scale and Scope•  Proposed Goal: Initiate 2 programs. One for Epigenetic Oncology/ Immunology. One for Neuroscience/Schizophrenia/Autism. Both programs will have 8 drug discovery projects (targets) - ramped up over a period of 2 years•  These will be executed over a period of 5 years making a total of 16 drug discovery projects•  We project a five-year budget of $200-250M in order to advance up to 8 drug discovery projects within each of the two therapeutic programs.•  Arch2POCM funding will come from a combination of public funding from governments (50%) and private sector funding from pharmaceutical and biotechnology companies (25%) and from private philanthropists (25%) 32
  33. 33. Epigenetics/ Chromatin Biology:Arch2POCM s Selected Pioneer Area of Oncology/ Immunology Drug Discovery 33
  34. 34. How We Define Epigenetics Lysine DNA Histone Modification Write Read Erase Acetyl HAT Bromo HDAC Methyl HMT MBT DeMethyl 34
  35. 35. The Case for Epigenetics/Chromatin Biology1.  There are epigenetic oncology drugs on the market (HDACs)2.  A growing number of links to oncology, notably many genetic links (i.e. fusion proteins, somatic mutations)3.  A pioneer area: More than 400 targets amenable to small molecule intervention - most of which are only recently shown to be “druggable”, and only a few of which are under active investigation4.  Open access, early-stage science is developing quickly – significant collaborative efforts (e.g. SGC, NIH) to generate proteins, structures, assays and chemical starting points 35
  36. 36. Examples of Epigenetic Links to Cancer•  Ezh2 methyltransferase (enhancer of zeste homolog 2) –  Somatic mutations in B-cell lymphoma•  JARID1B demethylase (jumonji, AT rich interactive domain 2 ) –  Linked to malignant transformation: expressed at high levels in breast and prostate cancers; Knock-down inhibits proliferation of breast cancer lines and tumor growth•  G9A methyltransferase (euchromatic histone-lysine N-methyltransferase 2) –  Expressed in aggressive lung cancer cells: high expression correlates to poor prognosis; G9a knockdown inhibits metastasis in vivo•  MLL: myeloid/lymphoid or mixed-lineage leukemia –  Multiple chromosomal translocations involving this gene are the cause of certain acute lymphoid leukemias and acute myeloid leukemias•  Brd4: (Bromodomain-containing protein 4) –  Implicated in t(15; 19) aggressive carcinoma: Chromosome 19 translocation breakpoint interrupts the coding sequence of a bromodomain gene, BRD4•  CBP bromodomain –  Oncogeneic fusions –  Mutated in relapsing AML 36
  37. 37. The Current Epigenetics Universe (2011) Domain Family Typical substrate class* Total Targets Histone Lysine Histone/Protein K/R(me)n/ (meCpG) 30   demethylase Bromodomain Histone/Protein K(ac) 57   R Tudor domain Histone Kme2/3 - Rme2s 59   O Chromodomain Histone/Protein K(me)3 34   Y A MBT repeat Histone K(me)3 9   L PHD finger Histone K(me)n 97   Acetyltransferase Histone/Protein K 17   Methyltransferase Histone/Protein K&R 60   PARP/ADPRT Histone/Protein R&E 17   MACRO Histone/Protein (p)-ADPribose 15   Histone deacetylases Histone/Protein KAc 11   395  Now known to be amenable to small molecule inhibition 37
  38. 38. Some Potential Arch2POCM Epigenetic Oncology/Immunology Targets 38
  39. 39. Open  Access  Test  Compounds  and  Tools  Are  Available  For   Arch2POCM  Teams   Probe Kd < 100 nM G9a/GLP Selectivity > 30x Criteria Cell IC50 < 1 µM BET SETD7 JMJD2 Kd < 500 nM PHF8 FBXL11 Selectivity > 30x BET 2nd Screening / Chemistry SUV39H2 Active L3MBTL3 GCN5L2 EP300 Kd < 5 µM L3MBTL1 JMJD3 WDR5 HAT1 PRMT3 BRD Weak CREBBP BAZ2B PB1 KDM FALZ SETD8 HAT MYST3 EZH2 JARID1C Me Lys Binders None DOT1L JMJD2A Tu SMYD3 UHRF1 HMT In vitro assay
 Cell assay
 available available Assay Development 39
  40. 40. Proposed IT Infrastructure For Arch2POCM Data Sharing Arch2POCM  funded  Research Crowdsourced Research                                                                                                                                                        Academic  Basic            Clinical  Research          Research    ac%vi%es   CRO  or   and  internal  use  requires  significant   CRO     CRO     Data  base  design  for  crowdsourced   Independent   Independent   funded   investment  in  data  base  structure   preclinical   Clinical   Basic  Res   Clin  Res   Basic   IT  structure   Data  management   Good  QC   and   control  and   Harmonize  data  management   compliance   IT  data   with   base   reduced   structure     control   1.  Arch2POCM  QC  data  and  IT  structure   2.  Database  from  crowdsourcing  with  volunteer  contr.       3.  Published  data   40
  41. 41. General Benefits of Arch2POCM For Drug Development1.  Arch2POCM s use of test compounds to de-risk previously unexplored biology enables drug developers to initiate proprietary drug development with an array of unbiased, clinically validated targets   Arch2POCM operates without patents and advances pairs of test compounds through Ph II   Test compounds are used by Arch2POCM and the crowd to define clinical mechanisms for epigenetic targets impacting oncology2.  Arch2POCM crowdsourced research and trials provides parallel shots on goal: by aligning test compounds to most promising unmet medical need3.  Negative clinical trial information generated by Arch2POCM and the crowd will increase clinical success rates (as one can pick targets and indications more smartly)4.  Build methods to track and visualize crowd sourced data, clinical safety profiles and reporting of potential adverse event 41
  42. 42. Arch2POCM Value Propositions For Academia •  Funding to pursue and publish disruptive discovery research •  Sharing of resources and data among private and academic partners •  Development of basic discoveries toward therapies and cures •  Collaboration with private sector and regulatory scientists •  Education of students and public about nature and process of discovery, and understanding disease •  Exit options: extend/branch studies beyond arch2POCM 42
  43. 43. Example  6:  Sage  Congress  2012  Pa%ent  Project  

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