Optimizing Genomics Asset Management for High ROI - Evaluating Strategies to Support the Bio/Pharma Value Chain

TABLE OF CONTENTS

EXECUTIVE SUMMARY

• Scope and structure
• Facta non verba: stock devaluation of innovative players is unavoidable when based on speculation
• Well diversified and specialized asset portfolios can enhance value
• Blending options-based asset valuation and unfolding asset complexity with multifactorial structural modeling offers an alternative methodology for genomics valuation

CHAPTER 1 THE EVOLUTION OF GENOMICS BUSINESS STRATEGIES

• Introduction
• A rising pipeline productivity crisis
• Transforming the 20th Centurys medicine to 21st Century Biomedicine
• The evolution of the genomics-oriented sector
• The genomics value matrix: evolving towards prosperity
• Two evolution waves: from speculation to depression, realization and diversification
• The early wave: from speculation to realization
• Key factors that formed the early evolution wave
• Strong R&D investment growth drives expansion
• Business model and supply chain structure highlights US overconfidence
• Patent portfolio formation coupled to poor evaluation drives stock overvaluation
• Initial genomics-based drug targets provide hope
• The early wave of alliance strategies
• MLNM case study: Genomics assets used to boost integration
• Genomics asset outlicensing
• Using genomics out-licensing to move towards full integration
• Bayer case study: Genomics assets not enough to boost growth
• Genomics licensing strategies
• Failure to capitalize on its genomics deals
• The early wave of M&A strategies
• Merck case study: the acquisition of Rosetta
• Costs and benefits of buying-in genomics expertise
• The new wave of genomics: investing in diversification
• Supporting supply chain integration with diversification
• Adding value through vertical integration - assessing recent deal value
• Accessing the best opportunities: key recommendations for success in accessing genomics
• Focusing on the quality of the genomics-driven targets
• Co-evolving assets and benchmarking performance against peers
• Tackling supply chain complexity with diversification
• Survival strategies for the horizontal genomics innovators
• Consolidation to diversify - increasing attractiveness
• Optimizing platform development - identifying the best competitive space
• Exit strategies for failed horizontal genomics innovators
• The case for Hyseq and Variagenics

CHAPTER 2 THE EVOLUTION OF GENOMICS PORTFOLIO VALUATION

• A novel view on the genomics business valuation landscape
• What forces the need for exploring new asset valuation methods?
• Evolving new genomics asset valuation methodologies
• Revealing the role of complexity in genomics business valuation
• Introducing a novel structural model to unfold genomics asset complexity
• Adding more depth to the proposed structural model
• Evolving the comlex dynamic asset structures
• Variation
• Selection and retention
• Evolving hybrid models: real options plus structural equation

CHAPTER 3 APPENDIX

• Key Strategy team members
• Neal Hansen, Lead Analyst-Strategic and Competitive Intelligence
• Alex Pavlou, Senior Biotechnology Analyst-Strategy
• Johannes Inama, Director of Consulting and Strategic Insight
• List of Tables
• Table 1: Early wave results of major collaborations with genomics companies
• List of Figures
• Figure 1: Datamonitors approach to analyzing the genomics sector
• Figure 2: NDAs and NMEs approved by the FDA (1996 - 2003)
• Figure 3: Datamonitors genomics perceived value matrix
• Figure 4: The evolution of the genomics index share value, January 1999- July 2004
• Figure 5: The evolution of the genomics business models according to asset and investment growth
• Figure 6: The early wave of the genomics market evolution
• Figure 7: The key elements of the genomics business model evolution
• Figure 8: R&D investment trends of the US publicly traded genomics sector, 1993-1999
• Figure 9: Geographic distribution of genomics firms
• Figure 10: Genomics patent filing volume trends, 2002
• Figure 11: Key trends from the early wave of genomics alliances
• Figure 12: Development of Millenniums strategic alliances during the early wave of alliances
• Figure 13: Bayers genomics and genomics-related agreements
• Figure 14: In 2010, Bayer is forecast to derive 71.8% of sales from mature drugs
• Figure 15: Datamonitors genomics Index for the new wave of innovation, 2002-04
• Figure 16: The new wave of genomics assets and their contribution to the bio/pharma supply chain
• Figure 17: Adding value through vertical integration: analysis of 12 recent genomics alliances by value
• Figure 18: Key trends extracted from the new wave of alliances
• Figure 19: Key trends extracted from the new wave of genomics M&A deals
• Figure 20: Key extracted trends from the new wave of chemogenomics alliances
• Figure 21: Key extracted trends from the new wave of pharmacogen-omics/enetics alliances
• Figure 22: How realization and integration moves closer to capitalization
• Figure 23: Nuvelos (merger of Hyseq and Variagenics) historical share prices 1999-2004
• Figure 24: A generalized view on the genomics business landscape
• Figure 25: Schematic representation of the main biotech asset valuation methods according to their ability to extract critical asset information for high ROI and the size of risk tolerability that they can undertake
• Figure 26: Real options decision making in genomics value chain
• Figure 27: Datamonitors multidimensional approach in revealing the key elements that govern the valuation of each genomic asset.
• Figure 28: Increasing depth in the asset valuation model using a number of sub-elements to support the basic ten-elements structural model of Datamonitors genomics success index
• Figure 29: Applying variation in genomics assets evolution to achieve high ROI
• Figure 30: Applying variation in genomics assets evolution to achieve high ROI
• Figure 31: The dynamics of biotech innovation: from a tendency towards high-ROI asset clusters within the biotech business model to the formation of biotech company clusters
• Figure 32: Evolving the "fittest" assets or identify your competitors advantages
• Figure 33: Datamonitors genomics success index linked to real option methodology
• Figure 34: Evaluation of each stage of the option decision process during a genomics-driven drug development project