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2. What are the drivers?Chronic disease impacts US national economy 3 February 2011 Skolkovo Vision Combined treatment and productivity costs for US in 2003 Milken Institute 2008 Total: 1.3 T US$ 3. How Big is 1.3 T$ per Year?(US Numbers, $ per year)
3 February 2011 Skolkovo Vision 4. What are the drivers?Unmet therapeutic need 3 February 2011 Skolkovo Vision Unmet Need Unrealized profit Adverse Events Cost Ineffective drugs - Waste 5. This is a big issue 3 February 2011 Skolkovo Vision Jerel Davis, McKinsey & Co http://www.dnapolicy.org/images/issuebriefpdfs/PGx%20IB.pdf Aspect Numeric 2008 Rx spend, US 292 B US$ (of 800 B US$ WW) Percent Rx not effective 20 90% (average 50%) Adverse events, US ~2,000,000 Fatal adverse events, US ~100-125,000 Cost adverse drug events, US 45-135 B US$ Percent events avoidable 20 35%
70%
3-4% 6. US Drivers:Summary 3 February 2011 Skolkovo Vision 7. Confounding issue:High failure rate/cost to discover new medicines 3 February 2011 Skolkovo Vision High risk process 1/100 ideas get to market 12-15 years Fully amortized cost US$3.9B per drug 8. Productivity of pharma industry 3 February 2011 Skolkovo Vision ~20 NMEs / yr ~ 7 NMEs / yr Bernard Munos, NATURE REVIEWS | Drug Discovery VOLUME 8 | DECEMBER 2009 | 963 9. Discovery steps largely in good shape 3 February 2011 Skolkovo Vision HP Prang: Drug Discovery and Development 10. Reason for failure:complex biology of safety and efficacy is not well understood 3 February 2011 Skolkovo Vision
I Kola, CLINICAL PHARMACOLOGY & THERAPEUTICS | VOLUME 83 NUMBER 2 | FEBRUARY 2008 11. US National Resource Committment
3 February 2011 Skolkovo Vision 12. Outline of plan 3 February 2011 Skolkovo Vision 13. Where to focus? Causes of death (US, 2005) 3 February 2011 Skolkovo Vision Jernal, et al., CA Cancer J Clin 2008;58;71-96,Feb 20, 2008 14. Breast Cancer in Russia
3 February 2011 Skolkovo Vision 15. What have we learned from cancer genomics?
3 February 2011 Skolkovo Vision Cancer genomics What necessarily follows will be the detailed functional characterization of individual candidate cancer genes, to determine whether and how they contributeto a tumorigenic phenotype. Daphne Bell National Human Genome Research Institute, NIH 16. Global, unbiased, discovery technologies to more deeply understand biology 3 February 2011 Skolkovo Vision 100s 10,000s 1000s
17. Global Unbiased Aceto-Proteomics Can Now Significantly Increase Resolution
15 January 2010 Fraunhofer Center for Molecular Biotechnology Forest White, MIT 18. ResponseNet algorithm for identifying response networks 3 February 2011 Skolkovo Vision Ernest Fraenkel,Nat Genet.2009 March,41(3) : 316323 Assay Genomic Data Proteomic Data Probabilistic interactome Computational tools 19. Chip-Seq Data for Four Transcription Factors Ernest Fraenkel MIT 15 January 2010 Fraunhofer Center for Molecular Biotechnology 20. Study hepatotoxicity using LiverChip technology 3 February 2011 Skolkovo Vision Steve Tannenbaum, Linda Griffith, MIT 21. Phenotype-driven Rx and Dx discovery Drug Targets Are Proteins 3 February 2011 Skolkovo Vision Genome T T T T T T T T Complex Biology Phenotype-driven Drug Discovery In Cancer, Genome is Altered T Primary Cancer Targets Appear Proteome Drug Resistance Resistance Targets Appear X Proteome T T T T 22. Tamoxifen and Breast Cancer Resistance 3 February 2011 Skolkovo Vision Based on Narmanno et al.Endocrine-Related Cancer2005 23. Experimental approaches: Quantitative phosphoproteomics 3 February 2011 Skolkovo Vision Forest White, MIT Follow time course under multiple conditions 24. Globally follow many 100s of events Quantitative time courses 3 February 2011 Skolkovo Vision Forest White, MIT 25. New RTK signaling seen with Tamoxifen resistance directly defines a new target class 3 February 2011 Skolkovo Vision Forest White, MIT Indicates an increase in tyrosine phosphorylation as a result of acquiring Tamoxifen resistance. DefinesSRCas a potential resistance target.SRC-directed therapeutics may revert Tamoxifen resistance. 26. SRC-directed therapeutics revert Tamoxifen resistance functionally definea new target and therapy class 3 February 2011 Skolkovo Vision Forest White, MIT 27. Phenotype directs target/lead, toxicity pathway and biomarker identification 3 February 2011 Skolkovo Vision 28. Lack of therapeutic efficacy affects large populations 3 February 2011 Skolkovo Vision Unmet Need Unrealized profit Adverse Events Cost Ineffective drugs - Waste 29. Solution:Diagnostics to stratify populations by drug response 3 February 2011 Skolkovo Vision Diagnostic test positive Likely to benefit from therapy Diagnostic test negative Not likely to benefit from therapy Toxicity test positive Likely to have toxic response Dx+ Dx- Tx+ 30. Genomic Dx methods have had success: Oncotype DX segregates breast cancer populations 3 February 2011 Skolkovo Vision 31. Other Commercially Available Genomic Assays 3 February 2011 Skolkovo Vision Christos Sotiriou and Lajos Pusztai, n engl j med 360, february 19, 2009 32. Quantitative immunofluorescence tools can stratify patients 3 February 2011 Skolkovo Vision Recurrence score independent of grade and stage in multivariate analysis added value to histopathology Algorithm being optimised for AQUA technology Further validation in independent cohort from another institution David Harrison and Dana Faratian 33. Quantitative PTEN protein expression is associated with Trastuzumab resistancein vivo 3 February 2011 Skolkovo Vision AQUA fluorescent analysis of PTEN expression in a TMA core, showing mainly cytoplasmic localization of PTEN (red) and masking of tumor areas for quantification by cytokeratin (green) Kaplan-Meier survival curves for patients treated with Trastuzumab for low (blue) and high (red) protein expression of PTEN.Dana Faratian,et al ., Cancer Res 2009; 69: (16). August 15, 2009 Low PTEN High PTEN PTEN is a tumor suppresser 34. Stratification using aptamer-based serum proteomic platform
3 February 2011 Skolkovo Vision SomaLogic 35. Aptamers Unlock Biomarker Discovery in The Human Proteome SomaLogic 3 February 2011 Skolkovo Vision 36. Multiplexed aptamer technology for clinical Dx discovery SomaLogic 3 February 2011 Skolkovo Vision 37. Example: Lung Cancer Diagnostic SomaLogic 3 February 2011 Skolkovo Vision 38. Aptamer-based diagnostics being developed
3 February 2011 Skolkovo Vision SomaLogic 39. Not all pathologies will be equally stratifiable 3 February 2011 Skolkovo Vision Trusheim, et al.,Nat Rev Drug Discov 6 , 287-293, 2007. Biology Economics 40. Recommend large scale longitudinal bio-banking effort
3 February 2011 Skolkovo Vision Watson, Kay and SmithNature Reviews Cancer September 2010 .10 , p646 41. Summary 3 February 2011 Skolkovo Vision 42. Summary, cont.
3 February 2011 Skolkovo Vision 43. Thanks
3 February 2011 Skolkovo Vision 44. Individual breast cancer tumors have cells with distinct lineages 3 February 2011 Skolkovo Vision Nicholas Navin, et al.,Genome Res. 201020 : 68-80 Human breast cancers display mono- and polyclonal evolution 45. Response of metastatic breast cancer to single-agent systemic therapy 3 February 2011 Skolkovo Vision Gonzalez-Angulo,et al ., Adv. Exper. Med. and Biol. 608, 1-22, 2007 Drug Response Rate, % Capecitabine 20 36 Docetaxel 18 68 Doxorubicin 25 40 Gemcitabine 14 37 Paclitaxel 17 54 Vinorelbine 25 47 Tamoxifen 21 41 Aromatase inhibitors 10 20 Trastuzumab (Herceptin) 12 - 34 46. Pathway analysis approaches 3 February 2011 Skolkovo Vision Dana Faratian,et al ., Cancer Res 2009; 69: (16). August 15, 2009 Kinetic (or dynamic) computational models offer the opportunity to cheaply and efficiently test the efficacy of targeted therapiesin silico(i.e., computationally), as part of the preclinical testing process 47. Biomarkers for immunofluorescence analysis from reverse phase protein arrays - RPPAs 3 February 2011 Skolkovo Vision RPPA protein identification HistoRx AQUA quantification Dana Faratian 48. Spectrum of Computational ToolsTo Link Observations 3 February 2011 Skolkovo Vision 49. Reason:humans are biologically heterogeneous
3 February 2011 Skolkovo Vision Lee Hood, Institute for Systems Biology Left Index Fingerprints from Identical Twins Twins 1 Twins 2 Tim Spector, Kings College London,www.TwinsUK.ac.uk 50. No measured trait correlates 100% between identical twins
3 February 2011 Skolkovo Vision Tim Spector, Kings College London,www.TwinsUK.ac.uk 51. Similarly with protein blood levels correlation is not 100%
3 February 2011 Skolkovo Vision Tim Spector, Kings College London,www.TwinsUK.ac.uk 52. Conclusions
3 February 2011 Skolkovo Vision 53. New opportunities for value creation
3 February 2011 Skolkovo Vision Trusheim, et al.,Nat Rev Drug Discov 6 , 287-293, 2007. 54. Diagnostics can take many forms
3 February 2011 Skolkovo Vision 55. General Mechanisms of Resistance to Systemic Therapy 3 February 2011 Skolkovo Vision Gonzalez-Angulo,et al ., Adv. Exper. Med. and Biol. 608, 1-22, 2007 56. ResponseNet algorithm for identifying response networks 3 February 2011 Skolkovo Vision Ernest Fraenkel,Nat Genet.2009 March,41(3) : 316323 Assay Genomic Data Proteomic Data Probabilistic interactome Computational tools 57. What does this study show?
3 February 2011 Skolkovo Vision 58. Competitive advantage, especially with multiple potential resistance mechanisms 3 February 2011 Skolkovo Vision Standard Approach Enabled Approach
Rx Rx 59. Mechanism-based Biomarker and Dx discovery 3 February 2011 Skolkovo Vision 60. Applications for biomarker technology 3 February 2011 Skolkovo Vision SomaLogic 61. Cell biology to clinic 3 February 2011 Skolkovo Vision Complex Biology Phenotype-driven Drug Discovery Continue 62. AQUA technology brings standardization and reproducibility to immunofluorescence analysis 3 February 2011 Skolkovo Vision http://www.historx.com 63. AQUA technology advantages http://www.historx.com 3 February 2011 Skolkovo Vision 64. Supporting technology: Reverse phase protein arrays 3 February 2011 Skolkovo Vision 100 unique proteins Dana Faratian 65. Protein predictor for breast cancer recurrance validated using HistoRx AQUA Technology
3 February 2011 Skolkovo Vision Dana Faratian 66. Patient stratification using pathway analysis approaches 3 February 2011 Skolkovo Vision Dana Faratian,et al ., Cancer Res 2009; 69: (16). August 15, 2009 Quantitative PTEN protein expression was found to be the key determinant of resistance to anti-HER2 therapyin silico In cancer cell lines, PTEN expression predicts sensitivity to anti-HER2 therapy Other targets also identified A similar result was found in a cohort of 122 breast cancers treated with Trastuzumab 67. Expanded tissue analysis platform: AQUA brings standardization and reproducibility 3 February 2011 Skolkovo Vision http://www.historx.com 68. Advantages
3 February 2011 Skolkovo Vision 69. SOMAmers Detected by Hybridization to Probes Printed on a Highly Multiplexed Array 3 February 2011 Skolkovo Vision SomaLogic 70. Fluorescent aptamers may bring increased resolution to immunofluorescence/IHC analyses 3 February 2011 Skolkovo Vision Bryan P. Schneider, et al., Clin Cancer Res 2008;14(24) 71. Data sharing 3 February 2011 Skolkovo Vision 72. Data Analysis, Visualization and Sharing Capabilities Giles Day 3 February 2011 Skolkovo Vision Infrastructure and Business Systems Scientific Systems and Methods Collaboration 1 2 3 Value, Complexity & Resources 3 2 1 Lab automation, sample logistics Experimental data capture, processing andanalysis Decision support Data mining and visualization Compound design & analysis methods Knowledge management New technologies and methods aligned withBBC scientific goals Including academic collaborations Infrastructure to enable a globalcommunity of scientists to organize, shareand mine scientific findings across Skolkovo Desktops, servers, networks,storage, communications Email, finance, HR, portfolio, DigitalLibrary, intranet Site integrations, future acquisitions collaborations (includes monitoringportfolio & progress against goals) 73. Commercial progression 3 February 2011 Skolkovo Vision This Project RVC Seed Investments Fund RVC venture funds (Maxwell, Bioprocess) ROSNANO RVC Russian Venture Company New Targets Rx, Dx Discovery External Biotech Drug Develop-ment Market 74. Russian scientists involvement
3 February 2011 Skolkovo Vision 75. Impact for Russia
3 February 2011 Skolkovo Vision 76. Impact to economy in different industries
3 February 2011 Skolkovo Vision 77. Establish Skolkovo Enterprise Center
3 February 2011 Skolkovo Vision 78. Back up slides 3 February 2011 Skolkovo Vision 79. Genetic approaches - GWAS Impact not fully realized
3 February 2011 Skolkovo Vision www.genome.gov/gwastudies . 80. Overlap of genetic risk factor loci for common diseases 3 February 2011 Skolkovo Vision Complex diseases are complex Kelly A. Frazer, et al.,NATURE REVIEWS | GENETICS 2009 | 81. Multi-gene Oncotype DX expression panel prognostic tool for breast cancer recurrence
3 February 2011 Skolkovo Vision genomic health www.oncotypedx.com 82. Mutations in KRAS abrogate EGFR inhibition by mAb colorectal cancer therapies 3 February 2011 Skolkovo Vision Arch Pathol Lab MedVol 133, October 2009 KRASTesting in Metastatic Colorectal CancerMonzon et al 83. Only a fraction of the genetic components of common diseases and traits have been identified 3 February 2011 Skolkovo Vision *AMD Age related macular degeneration Wei Chen, et al. PNAS 2010 (AMD); Andre Franke, et al., Nature Genetics 2010 (Crohns disease); Benjamin F. Voight et al., Nature Genetics 2010 (type 2 diabetes); Hana Lango Allen et al., Nature Genetics 1020 (height) Disease/ Trait Overall Heritability, % Overall Heritability Explained, % Gene Locations Identified AMD* 45 - 70 50 12 Crohns Disease 50 - 60 23 71 Type 2 Diabetes 30 - 70 10 38 Height 60 - 80 15 180 84. A proteomics approach looks at phenotype - Move directly to Rx and Dx 3 February 2011 Skolkovo Vision Rx cRx 1 cDx 1 Phospho- pattern Pattern is theCompanion Diagnostic Companion Rx, Restores Sensitivity Resistance Mechanisms POC demonstrated in breast cancer Forest White, MIT Resistant phenotype Tumor cell - Sensitive phenotype 85. Drug response is heterogeneous because the disease is heterogeneous 3 February 2011 Skolkovo Vision Bryan P. Schneider, et al., Clin Cancer Res 2008;14(24) 86. The disease is heterogeneous 3 February 2011 Skolkovo Vision Bryan P. Schneider, et al., Clin Cancer Res 2008;14(24) Genetic heterogeneity Phenotypic heterogeneity 87. Reverse phase protein arrays 3 February 2011 Skolkovo Vision 88. Global Unbiased Discovery Biology Global Biomarker Discovery Global Unbiased Discovery Toxicology Academic Pharma Partner
Academic Commercial Large Scale Longitudinal Bio-banking Commercial Academic Computational Infrastructure Commercial Academic 89. Drug response is heterogeneous because the disease is heterogeneous 3 February 2011 Skolkovo Vision Bryan P. Schneider, et al., Clin Cancer Res 2008;14(24) David Botstein, et al., Molecular Interventions 2(2) 101-109 (2002) 90. Use biomarkers to relate tumor phenotype to clinical outcome
3 February 2011 Skolkovo Vision 91. Skolkovo Technopolis 3 February 2011 Skolkovo Vision 92. Classification of breast cancer subtypes using to IHC stratification tools 3 February 2011 Skolkovo Vision David Huntsman,et al ., PLoS Medicine May 2010 | Volume 7 | Issue 5 | 78% 92% 8% 22% 6% 16% 58% 42% 93. This project: Two pronged focus 3 February 2011 Skolkovo Vision Short Term Goal Long Term Goal BreastCancer 94. Cancer has complex genetic origins: alterations in 24 pancreatic cancers 3 February 2011 Skolkovo Vision Sin Jones, Vogelstein,et al., Science321, 1801 (2008) 95.
Gene alterations map to 12 pathways and processes 3 February 2011 Skolkovo Vision Sin Jones, Vogelstein,et al., Science321, 1801 (2008) 96. Insights into the genetic basis of type 2 diabetes (T2D): GWAS 3 February 2011 Skolkovo Vision Adapted fromKelly A. Frazer, et al.,NATURE REVIEWS | GENETICS 2009 | and Benjamin F. Voight et al., Nature Genetics 2010. 38 genomic intervalsconfer increased risk to T2D in Caucasians They explainless than 10% of the total variance Predicted that >85 associations are required to fully explain variance 97. Genetic components of common diseases identified so far 3 February 2011 Skolkovo Vision *AMD Age related macular degeneration Wei Chen, et al. PNAS 2010 (AMD); Andre Franke, et al., Nature Genetics 2010 (Crohns disease); Benjamin F. Voight et al., Nature Genetics 2010 (type 2 diabetes); Hana Lango Allen et al., Nature Genetics 1020 (height) 98. Genomic Dx Success: KRAS Dx stratifies EGFR mAb responders 3 February 2011 Skolkovo Vision KRAS mutant Wt KRAS No response to panitumab Response to panitumab Salvatore Siena , et al., Review | JNCI Vol. 101, Issue 19 | October 7, 2009 99. Genomic Dx Success: Cancer stratification using BCR-ABL gene fusion 3 February 2011 Skolkovo Vision Nicholas Lydon , volume 15 | number 10 | october 2009 nature medicine Gleevec The BCR-ABL gene fusion is causative for CML and ALL. Imatinib (Gleevec)is specific for the TK domain in abl, c-kit and PDGF-RSevere congestive cardiac failure is an uncommon but recognized side effect of imatinibImatinib (Gleevec) has passed through Phase III trials for CML, and has been shown to be more effective than the previous standard treatment of -interferon and cytarabine. 100. Proteomic tools:Cell biology to clinic 3 February 2011 Skolkovo Vision 101. Proteomic tools:Cell biology to clinic 3 February 2011 Skolkovo Vision Targets and leads Biomarkers Patient stratification 102. Breast cancer: A multi-stage stratification process 3 February 2011 Skolkovo Vision From www.oncotypedx.com
Oncotype DX testing 21 Gene expression signature
103. The disease is genetically and phenotypically heterogeneous 3 February 2011 Skolkovo Vision Joel Gray, January, 2007 Science@Berkeley Lab http://www.medble.com/breast-cancer-information.htm 104. New phosphorylation pattern seen with Tamoxifen resistance in breast cancer
3 February 2011 Skolkovo Vision Forest White, MIT MCF7HER2is a Tamoxifen resistant cell line, 4-OHT is a Tamoxifen analog 105. Aptamer-based serum proteomics 3 February 2011 Skolkovo Vision SomaLogic
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