• PDF: Delivered by email within 2 to 24 hours during UK Business hours (Mon-Fri)
  • PRINT/CD-ROM: Despatched from the US by normal mail to US & Canada within 3 to 5 days and within 3 to 7 days to Any other country

Systems Biology
A Disruptive Technology

Systems Biology A Disruptive Technology

This report focuses on the current and future applications of Systems Biology in drug discovery, specifically in pinpointing optimal individual targets, and combinations of targets, to overcome metabolic pathway redundancies, leading to efficacious and safe products. Topics covered include:

  • Application successes at AstraZeneca, Pfizer, and J&J
  • Landscape of the Systems Biology marketplace and its future
  • Implications of innovative predictive modeling and global transcription epigenetics analysis
  • Review of 18 Systems Biology company business models
  • How SB will enable pharmacological progress in biologically complex ""money"" diseases
  • Projections on the future for Systems Biology in leukemia, Alzheimer's, and Huntington's diseases.

Systems biology (SB) is challenging the existing dominant drug discovery approaches and on track to becoming a classic disruptive technology. This report describes examples of SB successes in big pharma and current SB applications as well as the radically new concepts emerging from basic SB research.

The report provides a survey on the origins of SB and the varying definitions in common use and then moves to a review of the current bioanalytical- and bioinformatics-based technologies for making sense of omic's data through enabling pathway and network analysis. Pathway analysis, cell modeling, and disease modeling technologies today dominate the bioinformatics branch of systems biology. Database-mediated pathway analysis studies, which are particularly popular today, help to discover meaning in global biological data for drug discovery and diagnostics. As examples, systems biology approaches played a key role in understanding AstraZeneca's Iressa (gefitinib), liver abnormalities were identified by Pfizer, and Johnson & Johnson identified a kinase inhibitor mechanism. Next, the report provides an overview of the recent explosion of academic SB activity and implications for highly novel approaches to drug discovery and diagnostics not envisioned today. Examples include nanosystems studies to construct a predictive model for transcription control, ChIP-on-chip technology for global transcription factor identification, and methylation-specific polymerase chain reaction (PCR) for global DNA methylation detection as an entry point to epigenetics.

Systems Biology: A Disruptive Technology provides an analysis of the commercial activities of 18 small systems biology companies reviewed in the context of the nature and dynamics of the systems biology market: the business models, deals, scope, and prospects. As examples, commercial databases and software programs from companies such as Ingenuity Systems (Redwood City, CA), GeneGo (St. Joseph, MI), and Ariadne Genomics (Rockville, MD) provide enhanced usability and comprehensiveness. Gen-struct's Knowledge Assembly platform enables ""knowledge-driven systems biology;"" Gene Network Sciences' (Cambridge, MA) REFS (Reverse Engineering and Forward Simulation) systems permit reverse engineering and hypothesis generation from omic data; and Entelos' (Foster City, CA) PhysioLab biosimulation models, which incorporate both molecular and higher-order disease data, permit construction of ""virtual patients.""

Systems Biology: A Disruptive Technology concludes with a discussion and speculation as to the future for SB, supported by interviews with scientists and managers deeply engaged in this space. This analysis explains how and why pharma and diagnostics industries will benefit from advances in SB by leading to highly novel approaches for application to drug discovery and diagnostics discovery and development.

  • Chapter 1
  • Introduction
    • 1.1. Scope and Content of This Report
    • 1.2. Historical Perspective
    • 1.3. Defining Systems Biology
  • Chapter 2
  • Technological Aspects of Systems Biology
    • 2.1. Bioanalytical Technologies
    • Academic Perspective: Institute for Systems Biology
    • Commercial Perspective: Bg Medicine
    • 2.2. Regulatory Mechanisms and Organization
    • DNA-Protein Binding: Chip-on-Chip Analysis
    • DNA Methylation
    • Micrornas
    • 2.3. Bioinformatics Technologies
    • Pathway Analysis
    • Databases
    • Commercial Software Systems
    • Cell and Disease Modeling
    • Genstruct
    • Entelos
    • Gene Network Sciences
    • 2.4. Summary
  • Chapter 3
  • Basic Research in Systems Biology
    • 3.1. Network-Based Models and Simulations
    • Types of Biological Networks
    • Transcriptomic/Genetic Variation Approach
    • Combination Drug Therapy
    • 3.2. Protein Networks
    • Yeast Two-Hybrid and Related Technologies
    • Metabolic Interaction Networks
    • Databases
    • Systems Biology Research Approaches
    • 3.3. An Emerging Paradigm for Viewing Health and Disease
    • Diseaseome
    • Genotyping/Gene Expression Combinations in Biological Network Construction
    • Implications of Systems Biology for Clinical Medicine
    • Systems Biology Approach for Cancer Research
  • Chapter 4
  • Applied Research in Systems Biology
    • 4.1. Impacts of Systems Biology on Specific Disease Areas
    • Cancer
    • Acceptance of Systems Biology by Big Pharma
    • Network-Based Cancer Research
    • Neurological Diseases
    • Cardiovascular Diseases
    • Metabolic Disorders
  • Chapter 5
  • Market Dynamics
    • 5.1. Approaches of Small-Company Players X
    • Ariadne Genomics
    • Bg Medicine
    • Bioseek
    • Connexios
    • Entelos
    • Gene Network Sciences
    • Genego
    • Genetics Squared
    • Genomatica
    • Genstruct
    • Ingenuity Systems
    • Optimata
    • Physiomics
    • Protein Lounge
    • 5.2. Approaches of Selected Drug Discovery and Development Organizations
    • Cellicon Biotechnologies
    • Combinatorx
    • E-Therapeutics
    • Merck
    • Merrimack Pharmaceuticals
    • Pfizer
    • Su Biomedicine
    • 5.3. Systems Biology Deals
    • 5.4. Insight Pharma Reports Systems Biology Survey: Results and Comments
  • Chapter 6
  • Conclusions and Future Prospects
    • 6.1. Challenges for Systems Biology in Drug Discovery
    • 6.2. Possible Solutions to Advancing Medical and Pharmacological Knowledge via Systems Biology
    • 6.3. Systems Biology as A Disruptive Technology
    • 6.4. Future Prospects
  • Chapter 7
  • Expert Interviews
    • David De Graaf, Phd
    • Director of Systems Biology, Pfizer, Research Technology Center, Cambridge, Ma
    • Brian Edmonds, Phd
    • Research Advisor, Integrative Biology and Global External Research, Lilly Research Laboratories, Indianapolis, in
    • Colin Hill
    • Ceo, President, Chairman, and Co-Founder, Gene Network Sciences, Cambridge, Ma
    • David Lester, Phd
    • President and Founder, Ithw, Inc., Morristown, Nj
    • Stephen Naylor, Phd
    • Chairman, Ceo, and Co-Founder, Predictive Physiology and Medicine (Ppm), Bloomington, in
    • References
    • Company Index with Web Addresses
  • Figures
    • Figure 1.1. Causation in Living Systems Is A Two-Way Street
    • Figure 1.2. Experimentally Accessible Levels of Systems Biology
    • Figure 2.1. The Bg Medicine Approach to Commercial Systems Biology
    • Figure 2.2. Graphic Representation of A Bg Medicine Correlation Network Using Proteomic and Metabolomic Data
    • Figure 2.3. Multicomponent Protein and Metabolite Biomarkers for Distinguishing among Normal Controls, Alzheimer's Disease, and Mild Cognitive Impairment
    • Figure 2.4. Chip-on-Chip Workflow
    • Figure 2.5. Cytoscape Graphical User Interface
    • Figure 2.6. Ariadne Genomics' Pathway Studio Graphical User Interface
    • Figure 2.7. Tumor Angiogenesis Network Generated by The Ingenuity Pathways Analysis System
    • Figure 2.8. Genstruct's Forward and Reverse Causal Analysis Schema
    • Figure 3.1. Modeling of Biological Systems at Multiple Levels
    • Figure 3.2. Important Cellular Networks
    • Figure 3.3. Human Disease Network/Disease Gene Network
    • Figure 5.1. Respondents by Sector
    • Figure 5.2. Respondents by Position
    • Figure 5.3. Respondents by Stage of Work
    • Figure 5.4. Use of Systems Biology in R&d Projects
    • Figure 5.5. Areas of Systems Biology Involvement
    • Figure 5.6. Companies' Views toward Systems Biology
    • Figure 5.7. Means by Which Systems Biology Effort Is Conducted
    • Figure 5.8. Vendor Emphasis in Outsourced Systems Biology Efforts
    • Figure 5.9. Expectations for Fiscal 2008 Systems Biology Budget
    • Figure 5.10. Expectations for Systems Biology Budget over The next 3 Years
    • Figure 5.11. Estimation of 2008 Systems Biology Budget
    • Tables
    • Table 1.1. Growth in Literature Citations Relevant to Systems Biology during The Period 1998 to 2007
    • Table 5.1. Business Models of Small Systems Biology Companies
    • Table 5.2. Selected Recent Deals in The Systems Biology Space
+44 20 8816 8548

Ask a question about Systems Biology

Enter the characters you see in the picture below
Captcha