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Systems Biology for Drug Discovery

Systems Biology for Drug Discovery. www.GeneGo.com. SoCALBSI 2004. Lien Chung. Company Overview. Locations: St. Joseph, MI; San Diego, Ca; Moscow, Russia Founded: 2000 Technology: Systems Reconstruction Software: MetaCore TM , MetaDrug TM

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Systems Biology for Drug Discovery

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  1. Systems Biology for Drug Discovery www.GeneGo.com SoCALBSI 2004 Lien Chung

  2. Company Overview • Locations:St. Joseph, MI; San Diego, Ca; Moscow, Russia • Founded:2000 • Technology:Systems Reconstruction • Software:MetaCoreTM, MetaDrugTM • Partners: SDSC, Affymetrics, Pathway Diagnostics, Invitrogen, Michigan Center for Biological Information (MCBI)

  3. Management • Hwa Lim, PhD Chairman of the Board • Tatiana Nikolskaya Chief Scientific Officer (CSO) and Founder • Sean Ekins, PhD Vice President of Computational Biology • Andrei Bugrim, Ph.D. Chief Operating Officer (COO) • Julie Bryant Vice President, Development and Sales

  4. Motivations for Systems Biology Approach Road Blocks: • Advent of high-throughput technologies have led an enormous amount of disease-related HT data that need to be mined for information • Drug discovery progressing slowly because of inability to link genotypic data to phenotypic manifestations Systems Biology Solution: • Construction of networks and pathways to show interactions between genes, proteins, and metabolites involved in the diseased state • Knowledge of mechanisms and metabolic pathways helpful in identifying biomarkers, developing new therapeutic targets, and elucidating disease pathways

  5. MetaCoreTMA Database of Human Metabolism and Regulation • Unique pathway-centered structure built upon Oracle databases • Pathways generated from the incorporation of various high-throughput sources • Can integrate user’s own HT data and overlay them onto existing pathways • Ability to edit existing pathways according to user-defined parameters

  6. Types of HT sources MetaCoreTM Microarray Expression Data Protein interaction data Literature Phenotypic Data SAGE Disease Databases

  7. Types of Visualizations • Tissue-specific maps • Metabolic pathways • Cell-signaling pathways • Regulatory networks • Toxicity data and pathways • Disease data

  8. Regulatory Pathways w/ HT Data

  9. Visualization of Networks

  10. Disease Maps

  11. MetaDrugTM • Currently under development • Software tool for drug prediction and ADME/Tox in-silico testing • Will provide information about xenobiotic metabolism (fate of foreign compounds in body) • Software for predicting toxicity of potential drugs

  12. Superiority to Competitors • Tools to incorporate one’s own high-throughput data and dynamically visualize on maps and pathways • User has full control of the parameters of the data mining procedure • User can Add/Edit protein or gene interactions and add references • Non-redundancies, more than 10,000 synonyms resolved

  13. Competitors

  14. GeneGo’s Market • Biotech Companies • Pharmaceutical Companies • Private Research Institutions • Educational Institutions

  15. GeneGo’s Future • Release of MetaDrug will boost it’s financial outlook • Technology and software is unique but it needs to make partnerships in order to expand its clientele • Expanding beyond creating databases may also attract other types of investors • Possible merging with a big company may be necessary to sustain their presence

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