Strategic Management of Drug Discovery
New, emerging technologies are revolutionising the way drug discovery groups manage themselves. They offer a range of management options previously not available which will enable companies to meet commercial demands more effectively.
Strategic Management of Drug Discovery from Scrip Reports provides you with a complete overview of these trends and analyses how they affect you. It assesses new technologies including: combinatorial chemistry, high throughput screening, genomics and information technology.
Written by the respected drug discovery expert, Dr Wendy Warr, this report enables you to understand the processes involved in new technological approaches and evaluate strategic alliances between drug discovery and outsourcing companies.
The appendices to this report provide you with lists of global suppliers for new technologies
PUBLISHED: MAY 1998
REF: BS959E
PAGES: 150+
PRICE: £695/$1,460/¥167,000
Politicians worldwide are fighting to keep healthcare spending in control in the face of ever increasing demands from patients. Healthcare costs are soaring partly because of advances in medical technology and the problems associated with an ageing population. The pharmaceutical industry is also faced with loss of revenue as patents expire on major drugs and governments apply price cuts in an attempt to keep healthcare spending in control.
The pharmaceutical industry is thus being forced to become more innovative, productive and efficient. For the past two years, approximately 50 new chemical entities (NCEs) a year have come onto the world market but this needs to rise to 70-100 if companies are to maintain growth in annual revenue and profit levels in the region of 10%. Over the next three to four years, it has been claimed, companies are hoping to be able to move each NCE into development with 45% fewer people and 38% less in discovery spending.
Another source, however, claims that R&D budgets will grow by more than 40% and personnel by 20%, yet pharmaceutical companies want a threefold increase in productivity, ie, a 300% increase in productivity must be achieved with much less than a 100% increase in resourcing. Yet again, there are also cynics who believe that increasing R&D spending will not be a panacea and that R&D management deficiencies are at the root the problem. Details of all these opinions are discussed within this report.
Many management consultancies have benefited at the expense of the beleaguered pharmaceutical industry. A great deal of management science jargon has been written. This report is more of a factual review than an evaluation of new technologies, giving readers the means to follow up on the study themselves and draw up their own strategic plans.
The pressure to bring improved drugs to market faster affects all stages of the discovery and development process, a process which can take up to 12 years. This report looks in particular at the discovery stage: lead discovery and lead optimisation, which includes applied research, synthesis, biological testing and pharmacological screening.
The new technologies of genomics, combinatorial chemistry, computer-aided drug design (CADD) and high-throughput screening (HTS) offer promise in terms of speeding up the drug discovery process and making it more effective. Within these fields, even newer trends such as miniaturisation, microfluidics and 'lab-on-a-chip' technologies seem to offer exciting possibilities. The effective use of information technology (IT) is critical to the implementation of genomics, combinatorial chemistry and HTS in the pharmaceutical industry. IT is also of strategic importance in improving communications amongst R&D multidisciplinary teams and their managers.
Functional genomics is still considered a bottleneck in the drug discovery process. Many genes have been sequenced whose function remains unknown. Identifying genes which are abnormally expressed will enable scientists to locate targets for therapeutic intervention as well as to investigate new ways of diagnosing and monitoring disease.
By using the new science of pharmacogenomics, which involves correlating genetic variations with different responses to the same drugs, researchers can define specific populations most likely to benefit from a drug. Another new technology is that of proteomics. Both proteomics and genomics are concerned with understanding of health and disease at a molecular (genetic) level, but whereas genomics focuses on genes, proteomics focuses on proteins. There are now a few companies with bioinformatics systems that integrate clinical data, robotics and protein identification and characterisation into an automated process: systems which can characterise 300-400 disease-specific proteins a week.
Combinatorial chemistry and multiple parallel synthesis are already well established techniques for radically increasing the number of compounds that a given number of research chemists can synthesise, but there is still scope for new developments in the field. Exciting new technologies, especially in automation and miniaturisation, are set to change the way in which libraries are synthesised.
The process of lead identification has been revolutionised by HTS but ultra-high throughput screening (UHTS) could have a dramatic effect on speed and efficacy of screening. Companies are no longer contemplating screening 10,000 compounds per target per week in 10-20 simultaneous assays. The typical rate has already risen to 10,000 compounds per day per target. With UHTS technologies, it is estimated that screening capacity will be 100 million data points a year and a million compounds will be tested against a given target in a matter of weeks.
To handle data volumes of this sort, advances in IT are also needed. The effective use of IT is critical to the implementation of genomics, combinatorial chemistry and HTS. IT is also of strategic importance in improving communications amongst R&D multidisciplinary teams and their managers.
As drug discovery departments generate an increasing number of leads, the bottleneck will move further along in the R&D process and more effective ways of optimising leads and profiling development candidates will be needed. There will still be insufficient resources to develop all possible candidates and management will need sophisticated techniques to decide upon the most worthwhile projects to pursue.
Various complex and sophisticated mathematical techniques have been developed during the 1980s and 1990s to aid the decision makers in portfolio management. None of them have proved very satisfactory, for various reasons, and few companies have a formal portfolio strategy: few regularly review their research projects in the light of the company's overall plan. At the operational level, portfolio management methods should provide a rational basis for deciding between competing projects and for prioritising the resources to be allocated to individual products. New techniques for formal portfolio management now allow very dissimilar projects to be compared on a common basis and managed within a single pipeline. Some experts have considerable confidence in their ability to manage a development portfolio nowadays but portfolio management at the discovery stage is fraught with many more problems than management of a development portfolio.
Restructuring the R&D portfolio is just one of many strategies that have been adopted to increase productivity. Others include revamping the R&D organisation, perhaps by separating, or merging, 'R' and 'D', flattening the hierarchical structure, or creating centres of excellence. Fundamental changes in the traditional R&D philosophy and in corporate culture have also been recommended. Pharmaceutical companies have to seek ways to introduce more efficient processes and to organise and motivate the work force with a view to achieving greater productivity, while not stifling innovation and creativity or decreasing the opportunity for discovery by serendipity.
The traditional large pharmaceutical company contains research, development, registration, marketing, selling and other functions. Some of these activities could be outsourced to companies with expertise in niche areas. The advantages of collaboration far outweigh the disadvantages. Not only are mergers, outsourcing, contracts, alliances and other research collaborations becoming ever more commonplace, but newer types of venture are also emerging. The single-technology start-up company is finding it harder to do business and more multi-technology companies, or even companies that can handle discovery from the molecular level through to drug development, will appear in future.
Once a major pharmaceutical company has outsourced appropriate activities, concentrating on core activities in-house, and has restructured its R&D departments and adopted new technologies, how will it measure whether it has indeed improved its productivity? Companies tend to be too introspective in that they evaluate their own performance without sufficient comparison to the productivity of their competitors. Moreover, the drug development cycle is so long, and the pharmaceutical industry is changing so fast, that the commonest performance measures may relate to past performance rather than to current productivity. Much more sophisticated criteria are needed to evaluate performance if the industry is to pinpoint specific examples of inefficiencies and make plans for process improvement.
This report looks at the industry's response to the unprecedented change it has suffered over the last ten years and sees whether it can react positively to the challenge with creative new R&D strategies. Will spending more and more on R&D be a panacea for the pharmaceutical industry or will more money spent merely mean more money wasted?
CONTENTS
LIST OF TABLES
LIST OF FIGURES
EXECUTIVE SUMMARY
GLOSSARY AND ABBREVIATIONS
CHAPTER 1 THE FUTURE OF BUSINESS-DRIVEN DRUG DISCOVERY
1.1 External pressures on the industry
1.1.1 Healthcare costs
1.1.2 Risks of pharmaceutical R&D
1.1.3 The value of patents
1.1.4 Other financial problems
1.2 The cost of R&D
1.3 The pharmaceutical industry's response
1.3.1 Productivity
1.3.2 Reducing discovery timelines
1.3.3 Problems faced by the biotechnology industry
1.3.4 Genomics
1.3.5 High-throughput screening
1.3.6 Combinatorial chemistry
1.3.7 Information technology
1.4 Business strategies
1.4.1 Mergers and acquisitions
1.4.2 Strategic alliances
1.5 Summary
CHAPTER 2 TECHNOLOGY TRENDS
2.1 Introduction
2.2 Functional genomics
2.3 Pharmacogenomics
2.4 Proteomics
2.5 Transgenic proteins
2.6 Legal and regulatory issues
2.7 Combinatorial chemistry
2.7.1 Compound libraries
2.7.2 Analytical procedures
2.7.3 Mixtures and structure elucidation
2.7.4 Parallel synthesis
2.7.5 Automation
2.7.6 Commercially available samples and libraries
2.8 High-throughput screening
2.8.1 Toxicity issues
2.9 Information technology
2.9.1 Bioinformatics
2.9.2 Chemical database technology
2.9.3 Managing screening data
2.9.4 Qualitative structure-activity relationships
2.9.5 Molecular diversity
2.9.6 Communication technology
2.10 Summary
CHAPTER 3 PORTFOLIO MANAGEMENT
3.1 Introduction
3.2 Costs and risks
3.3 Strategic decisions about research areas
3.3.1 Patterns of disease
3.3.2 Natural products
3.3.3 Biopharmaceuticals
3.4 R&D functions
3.5 Attrition and clinical success rate
3.6 Development candidate profiling
3.6.1 Pharmacology and toxicology
3.6.2 Metabolic data
3.6.3 Pre-formulation and pharmaceutics
3.6.4 Chemistry scale-up
3.6.5 Analytical methods
3.6.6 Impact of new technologies
3.7 Newer techniques for predicting toxicity
3.7.1 Artificial intelligence techniques
3.8 Financial and risk analysis models introduction
3.8.1 Introduction
3.8.2 Example one
3.8.3 Example two
3.8.4 Example three
3.8.5 Example four
3.9 Summary
CHAPTER 4 STRATEGIC MANAGEMENT ISSUES
4.1 Introduction
4.2 R&D resources
4.3 Innovation and serendipity
4.4 Changes in organisational structure
4.4.1 Organisational strategies
4.4.2 Network and cluster organisations
4.4.3 Organisation by discipline
4.4.4 Organisation by therapeutic area
4.4.5 Organisation by research function
4.4.6 Multidisciplinary teams
4.5 Motivation
4.6 Communication
4.6.1 Electronic notebooks
4.6.2 Competitive intelligence databases
4.6.3 Virtual communities
4.7 Management of change
4.7.1 Theory of constraints
4.7.2 Cultural change
4.7.3 Mergers impose change
4.7.4 Business process re-engineering
4.8 Decision-making
4.9 Summary
CHAPTER 5 STRATEGIC ALLIANCES
5.1 Outsourcing
5.2 Examples of collaborations
5.3 Collaborators
5.4 Reasons for collaborating
5.5 Finding the right partner
5.6 Funding research in a university
5.7 Features of collaborations
5.7.1 Costs
5.7.2 Spreading risk
5.7.3 Other advantages
5.8 Problems associated with collaborations
5.8.1 Managing intellectual property
5.8.2 Information management and IT issues
5.8.3 Miscellaneous issues
5.9 Newer types of collaboration
5.9.1 Consortia
5.9.2 The virtual, networked company
5.9.3 Biotechnology company deals
5.9.4 Alliances in computational chemistry
5.10 Summary
CHAPTER 6 MEASURING PRODUCTIVITY AND PERFORMANCE
6.1 Costs and return
6.2 Performance indicators
6.3 Competitive intelligence
6.3.1 Benchmarking
6.3.2 Drug databases
6.4 Citation analysis
6.4.1 Patent citation analysis
6.5 Summary
REFERENCES
APPENDIX I DIRECTORY OF SELECTED COMPANIES
A1.1 New technologies
A1.2 Information and information technology
A1.3 Databases and chemical sample collections
A1.4 Automation
APPENDIX II
A2.1 Abbott Pharmaceuticals
A2.1.1 Joint ventures
A2.1.2 Agreements with (1995-1998)
A2.2 American Home Products
A2.2.1 Joint ventures
A2.2.2 Agreements with (1995-1998)
A2.3 Bristol-Myers Squibb
A2.3.1 Joint ventures
A2.3.2 Agreements with (1995-1998)
A2.4 Eli Lilly
A2.4.1 Joint ventures
A2.4.2 Agreements with (1995-1998)
A2.5 Glaxo Wellcome
A2.5.1 Joint ventures
A2.5.2 Agreements with (1995-1998)
A2.6 Hoechst Marion Roussel
A2.6.1 Joint ventures
A2.6.2 Agreements with (1995-1998)
A2.7 F Hoffmann-La Roche
A2.7.1 Joint ventures
A2.7.2 Agreements with (1995-1998)
A2.8 Johnson & Johnson
A2.8.1 Joint ventures
A2.8.2 Agreements with (1995-1998)
A2.9 Merck & Co
A2.9.1 Joint ventures
A2.9.2 Agreements with (1995-1998)
A2.10 Novartis
A2.10.1 Joint ventures
A2.10.2 Agreements with (1995-1998)
A2.11 Pfizer
A2.11.1 Joint ventures
A2.11.2 Agreements with (1995-1998)
A2.12 SmithKline Beecham
A2.12.1 Joint ventures
A2.12.2 Agreements with (1995-1998)
List of tables
Table 3.1 The top therapeutic classes as of December 1997
Table 3.2 US R&D costs (%) by function, ethical pharmaceuticals
Table 4.1 R&D personnel in research-based companies in the US
List of figures
Figure 1.1 Stages of R&D
Figure 1.2 Real and target discovery timelines by process in 1996 and 2000
Figure 2.1 Split synthesis
Figure 2.2 The components of a knowledge management system
Figure 2.3 The drug design cycle
Figure 3.1 Approaches used for portfolio management in decision to start preclinical development to support administration to humans and late development
Figure 3.2 Information used in decision to start preclinical development to support administration to humans and full-scale development for launch
Figure 3.3 Portfolio grid for balancing projects
Figure 4.1 Pharmaceutical R&D Employees (1993-1995)
Figure 4.2 Factors necessary for fast development - perceptions of the current situation and the ideal situation
Figure 4.3 The most important factors necessary for fast development
Figure 6.1 Measures of productivity used by leading companies