Transcript MetaCore TM - D`Trends, Inc.

Systems Biology for Drug Discovery
www.GeneGo.com
SoCALBSI 2004
Lien Chung
Company Overview
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Locations: St. Joseph, MI;
San Diego, Ca; Moscow, Russia
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Founded: 2000
Technology: Systems Reconstruction
Software: MetaCoreTM, MetaDrugTM
Partners: SDSC, Affymetrics, Pathway
Diagnostics, Invitrogen, Michigan Center
for Biological Information (MCBI)
Management
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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
Motivations for Systems Biology Approach
Road Blocks:
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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:
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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
MetaCoreTM
A Database of Human Metabolism and Regulation
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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
Types of HT sources
Literature
Microarray
Expression Data
Protein
interaction data
MetaCoreTM
Phenotypic
Data
SAGE
Disease
Databases
Types of Visualizations
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Tissue-specific maps
Metabolic pathways
Cell-signaling pathways
Regulatory networks
Toxicity data and pathways
Disease data
Regulatory Pathways w/ HT Data
Visualization of Networks
Disease Maps
MetaDrugTM
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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
Superiority to Competitors
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Tools to incorporate one’s own highthroughput 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
Competitors
GeneGo’s Market
Biotech Companies
 Pharmaceutical Companies
 Private Research Institutions
 Educational Institutions
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GeneGo’s Future
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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