Biomarker Strategy talk presented at the PRISM forum Special Interest Group: "Information Challenges in the Age of Biomarkers”, October 2009

1. It’s the Narrative… Informatics Strategies to Maximize Biomarker Impact Part of the Special Interest Group: Information Challenges in the Age of Biomarkers Thomas Plasterer, PhD October 13, 2009

4. Proteomics Metabolomics Genomics Blood, Urine, Tissues Clinical, Preclinical High Resolution Measurements BG Medicine Technology Platform IP-Protected Technology Suite to Maximize Novel Biomarker Discovery Data Analysis / Integration / Interpretation / Visualization

6. BG Medicine: Enabling Biomarker-Guided Medicine We discover and develop novel diagnostics in cardiovascular disease and cancer Address unmet need for diagnostics that match patients and treatments to provide more effective, less costly and safer therapies Exceptional portfolio of cardiovascular product candidates to address important unmet medical needs Flexible and highly scalable discovery platform enables us to align with multiple constituencies

8. Molecular Systems Analysis – BGM Workflows Fully Integrated Operations, QA/QC, IT Data Mgmt, LIMS & Oracle Pipeline Clear, measurable objective Protein Analysis Transcript Analysis Statistical Modeling Qualified Biomarker Additional Analyses Master Dataset Metabolite Analysis Correlation Analysis Biomarkers -Predictive -Prognostic -Diagnostic Population-based Biochemical Similarity Biomarker Context Biological Data Mining Exploratory Analysis Sufficiently powered study design

9. BGM’s Systems Biology Information System (SBIS) LIMS Metabolomics database Proteomics database Statistics database CORRNET BTE SEER Omics database Bioanalytical Data Generation Statistical Analysis Bioinformatics Transcriptomics database Corporate database Pipeline database Report database workflow and processes security and management reporting and data mining LIMS API AIMS API MXSUITE API PXSUITE API STATDB API CORPDB API Oracle PL/SQL API (packages, procedures) Java Domain Objects / Data Access Objects SEER API Resource Tier Oracle 10G on NAS Integration Tier Oracle PL/SQL Business Tier Java, PL/SQL, Open source framework Presentation Tier JSP / Servlet, Java, RMI, DHTML Open source frameworks Client Tier HTML BGM SYSTEM BIOLOGY INFORMATION SYSTEM (SBIS) LIMS AIMS MXSUITE PXSUITE STATS SEER REPORT BGM Central Authentication Service (BGM CAS) Pipeline Client server

10. Experimental Design Sidney Harris, New Yorker

12. Fully Integrated Operations, QA/QC, IT Data Mgmt, LIMS & Oracle Pipeline Clear, measurable objective Protein Analysis Transcript Analysis Statistical Modeling Qualified Biomarker Additional Analyses Master Dataset Metabolite Analysis Correlation Analysis Biomarkers -Predictive -Prognostic -Diagnostic Population-based Biochemical Similarity Biomarker Context Biological Data Mining Exploratory Analysis Molecular Systems Analysis – BGM Workflows Sufficiently powered study design

14. Resent CVD Study Example

20. Molecular Systems Analysis – BGM Workflows Fully Integrated Operations, QA/QC, IT Data Mgmt, LIMS & Oracle Pipeline Clear, measurable objective Protein Analysis Transcript Analysis Statistical Modeling Qualified Biomarker Sufficiently powered study design Additional Analyses Master Dataset Metabolite Analysis Correlation Analysis Biomarkers -Predictive -Prognostic -Diagnostic Population-based Biochemical Similarity Biomarker Context Biological Data Mining Molecular Systems Analysis – BGM Workflows Exploratory Analysis

25. Recursive Feature Reduction in Classifiers reduce number of analytes at each step

27. Molecular Systems Analysis – BGM Workflows Fully Integrated Operations, QA/QC, IT Data Mgmt, LIMS & Oracle Pipeline Clear, measurable objective Protein Analysis Transcript Analysis Statistical Modeling Qualified Biomarker Sufficiently powered study design Additional Analyses Master Dataset Metabolite Analysis Correlation Analysis Biomarkers -Predictive -Prognostic -Diagnostic Population-based Biochemical Similarity Biomarker Context Biological Data Mining Molecular Systems Analysis – BGM Workflows Exploratory Analysis

29. Molecular Systems Analysis – BGM Workflows Fully Integrated Operations, QA/QC, IT Data Mgmt, LIMS & Oracle Pipeline Clear, measurable objective Protein Analysis Transcript Analysis Statistical Modeling Qualified Biomarker Sufficiently powered study design Additional Analyses Master Dataset Metabolite Analysis Correlation Analysis Biomarkers -Predictive -Prognostic -Diagnostic Population-based Biochemical Similarity Biomarker Context Biological Data Mining Molecular Systems Analysis – BGM Workflows Exploratory Analysis

35. Analyte Correlations Example of Negative Correlation r = -0.93 2 4 6 8 30 40 50 60 70 Animal Number 1 2 3 4 5 6 7 8 9 9.42 9.58 9.73 9.89 10.04 Serum HDL Lipid LCMS 554-1221 30 40 50 60 70 9.5 9.6 9.7 9.8 9.9 10.0 Serum HDL 554-1221 30 35 40 45 50 55 60 65 70

36. Analyte Correlations r = 0.15 Example of Correlation near zero 2 4 6 8 10 14 15 16 17 18 19 20 Animal Number 1 2 3 4 5 6 7 8 9 10 5.01 5.14 5.26 5.38 5.51 5.63 5.75 Serum HDL mRNA 1417384_at 14 15 16 17 18 19 20 5.0 5.2 5.4 5.6 Serum HDL 1417384_at

37. “ Known ” Networks vs. Observed Correlations A schematic view of the simplified Calvin cycle with subsequent sucrose phosphate synthase in the cytoplasm. Pair-wise metabolite correlations obtained numerically from the model depicted to the left. All concentrations are given in arbitrary units. K. Morgenthal, W. Weckwerth, R. Steuer, BioSystems 83 (2006) 108-117

41. Correlation Networks™: Liver - Plasma Sub-Network Plasma Liver

45. BioImage Semantic Web (BISW)