1. Vision for Skolkovo Biotech Sector – Pharma Discovery Preston Hensley Lotus Translational Medicine, LLC 3 February 2011 Skolkovo Vision

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$

4. What are the drivers? Unmet therapeutic need 3 February 2011 Skolkovo Vision Unmet Need – Unrealized profit Adverse Events – Cost Ineffective drugs - Waste

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

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

18. ResponseNet algorithm for identifying response networks 3 February 2011 Skolkovo Vision Ernest Fraenkel, Nat Genet. 2009 March, 41(3) : 316–323 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 Cancer 2005

23. Experimental approaches: Quantitative phosphoproteomics 3 February 2011 Skolkovo Vision Forest White, MIT Follow time course under multiple conditions

24. Globally follow many 100’s 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. Defines SRC as a potential resistance target. SRC-directed therapeutics may revert Tamoxifen resistance.

26. SRC-directed therapeutics revert Tamoxifen resistance – functionally define a 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 resistance in 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

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

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

41. Summary 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. 2010 20 : 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 therapies in 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 Tools To Link Observations 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) : 316–323 Assay Genomic Data Proteomic Data Probabilistic interactome Computational tools

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

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 therapy in 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

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 and analysis  Decision support  Data mining and visualization  Compound design & analysis methods  Knowledge management  New technologies and methods aligned with BBC scientific goals  Including academic collaborations  Infrastructure to enable a global community of scientists to organize, share and mine scientific findings across Skolkovo  Desktops, servers, networks, storage, communications  Email, finance, HR, portfolio, Digital Library, intranet…  Site integrations, future acquisitions  collaborations (includes monitoring portfolio & 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

78. Back up slides 3 February 2011 Skolkovo Vision

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 |

82. Mutations in KRAS abrogate EGFR inhibition by mAb colorectal cancer therapies 3 February 2011 Skolkovo Vision Arch Pathol Lab Med—Vol 133, October 2009 KRAS Testing in Metastatic Colorectal Cancer—Monzon 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 (Crohn’s 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 Crohn’s 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 the Companion 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

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)

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 Breast Cancer

94. Cancer has complex genetic origins: alterations in 24 pancreatic cancers 3 February 2011 Skolkovo Vision Siân Jones, Vogelstein, et al., Science 321, 1801 (2008)

96. Insights into the genetic basis of type 2 diabetes (T2D): GWAS 3 February 2011 Skolkovo Vision Adapted from Kelly A. Frazer, et al., NATURE REVIEWS | GENETICS 2009 | and Benjamin F. Voight et al., Nature Genetics 2010. 38 genomic intervals confer increased risk to T2D in Caucasians They explain less 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 (Crohn’s 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-R Severe congestive cardiac failure is an uncommon but recognized side effect of imatinib Imatinib (Gleevec) has passed through Phase III trials for CML, and has been shown to be more effective than the previous standard treatment of α-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

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

105. Aptamer-based serum proteomics 3 February 2011 Skolkovo Vision SomaLogic