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LIFE SCIENCES/BIOTECHNOLOGY
Centre National de la Recherche Scientifique
Sophia-Antipolis, France
Michel Quéré
Pier Paolo Saviotti
Sandrine Selosse
And
Université Libre de Bruxelles
Brussels, Belgium
Jessica Michel
Bruno van Pottelsberghe
30 June 2002
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Table of Contents
1. INTRODUCTION………………………………………………………………..6
2. HISTORICAL INHERITANCE………………………………………………...6
2.1 BACK TO THE ORIGIN OF THE MODERN ‘LIFE SCIENCE INDUSTRY’...6
2.2 THE POST-WAR ERA OF THE ‘LIFE SCIENCE INDUSTRY’: THE
RANDOM SCREENING PERIOD………………………………………………7
2.3 UNTIL THE EIGHTIES: TOWARDS AN ‘ORGANIZED’ SCREENING
PERIOD IN DRUG DISCOVERY………………………………………………9
2.3.1 The first sub-period: A new era with “Happy few” participants…………..9
2.3.2 The second sub-period: Increasing specialisation, money accessibility and
a blast of knowledge opportunities…………………………………………...11
3. BIOTECHNOLOGY INDUSTRY ANALYSIS: US v. EUROPE…………..16
3.1 BIOTECHNOLOGY INDUSTRY: STATE-OF-THE-ART…………………...16
3.1.1 US Biotechnology Industry Analysis…………………………………….17
3.1.2 European Biotechnology Industry Analysis……………………………...19
3.2 GEOGRAPHICAL DISTRIBUTION OF BIOTECHNOLOGY ACTIVITIES..21
3.3 FUNDING OF RESEARCH AND DEVELOPMENT………………………….24
3.3.1 Public funding of R&D in Europe………………………………………..24
3.3.2 Public funding of R&D in the United States……………………………..25
3.4 RELATIVE ECONOMIC PERFORMANCE OF COUNTRIES……………….25
Biotechnology and US trade……………………………………………...26
3.5 RELATIVE SCIENTIFIC PERFORMANCE OF COUNTRIES……………….28
3.5.1 World Distribution of Scientific Publications……………………………28
3.5.2 World Distribution of Scientific Publications (Life Sciences)…………...28
3.5.3 Distribution of Scientific publications by discipline (NAFTA)………….29
3.5.4 Distribution of Scientific publications by discipline (ASEAN)………….30
3.5.5 Distribution of Scientific publications by discipline (EU)……………….30
3.5.6 Scientific Publications (all disciplines) by European Countries………….31
3.6 RELATIVE TECHNOLOGICAL PERFORMANCE OF COUNTRIES………31
3.6.1 The importance of patents in the life sciences……………………………31
3.6.2 USPTO patent grants……………………………………………………..32
Biotechnology…………………………………………………………….33
Pharmaceuticals…………………………………………………………..36
4. INDUSTRIAL ORGANISATION……………………………………………..41
4.1 MAIN ACTORS………………………………………………………………...41
4.1.1 Large Diversified Firms (LDFs)………………………………………….41
The life science company………………………………………………...41
4.1.2 Dedicated Biotechnology Firms (DBFs)…………………………………43
4.1.3 Public Research Institutes (PRIs)………………………………………...46
4.2 INNOVATION NETWORKS AND STRATEGIC ALLIANCES……………..49
4.2.1 Opportunities for firms within the life science industry………………….49
Characteristics of large pharma…………………………………………..49
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Strategic options for the biotechnology firms……………………………50
4.2.2 Alliances………………………………………………………………….51
Strategic technological alliances…………………………………………51
Strategic biotechnology alliances………………………………………...53
4.3 VENTURE CAPITAL…………………………………………………………..55
5. THE ORGANISATION OF KNOWLEDGE WITHIN THE LIFE SCIENCE
INDUSTRY……………………………………………………………………...59
6. SOURCES……………………………………………………………………….63
7. APPENDICES: A—E………………………………………………………….65
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Table of Illustrations
Table 2.1 Growth evolution of Amgen, 1980-99……………………………………11
Table 2.2 Life sciences: US IPOs…………………………………………………...12
Graph 2.1 Creation of DBFs in the US……………………………………………...13
Table 3.1 Life science industry in the US…………………………………………...17
Table 3.2 Key areas for US life science companies…………………………………18
Table 3.3 FDA approvals of biotech patents, 1982-1998……………………………18
Table 3.4 Source of funding for US life science companies, 1999…………………19
Table 3.5 Summary of life science industry in US…………………………………..19
Table 3.6 Life science industry in Europe…………………………………………...20
Table 3.7 Life science industry in France, Germany and UK……………………….20
Table 3.8 Life science industry in Europe – New Medecinal Products with European
Community Marketing Authorisation………………………………………………..21
Graph 3.1 US states with the highest concentration of life science companies,
1999…………………………………………………………………………………..21
Graph 3.2 Independent European DBFs, 2000……………………………………...22
Graph 3.3 DBFs per thousand inhabitants, 2000…………………………………….23
Table 3.9 Government funding or outlays for research and development in selected
European countries, 1997…………………………………………………………….24
Table 3.10 Share of NIH funding allocated to US biotechnology centres…………..25
Table 3.11 Cumulative share in US biotechnology exports to the OEDC area,
1999…………………………………………………………………………………..26
Table 3.12 Cumulative share in US biotechnology imports from the OECD area,
1999…………………………………………………………………………………..27
Graph 3.4 Cumulative share in US biotechnology exports from the OECD area,
1999…………………………………………………………………………………..27
Graph 3.5 Cumulative share in US biotechnology imports from the OECD area,
1999…………………………………………………………………………………..27
3.5.1 World Distribution of Scientific Publications………………………………..28
3.5.2 World Distribution of Scientific Publications (Life Sciences)……………….28
3.5.3 Distribution of Scientific publications by discipline (NAFTA)……………...29
3.5.4 Distribution of Scientific publications by discipline (ASEAN)……………...30
3.5.5 Distribution of Scientific publications by discipline (EU)…………………...30
3.5.6 Scientific Publications (all disciplines) by European Countries……………..31
Table 3.13 Biotechnology patents as percent of total patents granted in each country,
1987-1989 and 1999-2001……………………………………………………………34
Graph 3.6 Biotechnology patents as percent of total patents granted in each country,
1987-2001…………………………………………………………………………….34
Table 3.14 Biotechnology patents per million inhabitants, 1999-2001……………..35
Graph 3.7 Biotechnology patents per million inhabitants, 1999-2001………………35
Table 3.15 Pharmaceutical patents as percent of total patents granted for each
country, 1987-1989 and 1999-2001………………………………………………….37
Graph 3.8 Pharmaceutical patents as percent of total patents granted for each country,
1987-2001…………………………………………………………………………….37
Table 3.16 Pharmaceutical patents: Percent patents invented at home with rights
assigned to a foreign country, 1987-89 and 1999-2001……………………………...38
Graph 3.9 Pharmaceutical patents in selected European countries: Percent patents
invented at home with rights assigned to a foreign country, 1987-2001……………..39
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Graph 3.10 Percent of pharmaceutical patents assigned to foreign entities for selected
regions, 1987-1989 and 1999-2001…………………………………………………..40
Table 3.17 World patent distribution in percentages for key technologies (Life
Sciences and Information Technologies) among a selection of countries, 19931995…………………………………………………………………………………..41
Table 4.1 The largest pharmaceutical companies: US and European Union……….42
Table 4.2 Largest US biotech companies, 2001……………………………………..44
Table 4.3 Largest biotech companies in the European Union, 2001………………...44
Graph 4.1 US life science companies per thousand inhabitants for states with the
highest concentration, 1999…………………………………………………………..45
Table 4.4 Comparison between European countries and US states for greatest
presence of life science companies…………………………………………………...46
Table 4.5 European strategic alliances: Ernst & Young v. CATI, 1996-2000……...51
Table 4.6 Share of international strategic technology alliances: 1980-89 and 19902000…………………………………………………………………………………..52
Table 4.7 International strategic technology alliances, by technology shares………52
Graph 4.2 International strategic technology alliances, 1990-2000…………………53
Graph 4.3 US and European biotechnology alliances, 1980-98……………………..54
Graph 4.4 European biotechnology alliances, 1980-98……………………………...55
Graph 4.5 VC in Europe: biotechnology, 1987-2001………………………………56
Graph 4.6 VC in US: biotechnology, 1987-2000…………………………………...56
Table 4.8 Comparison of Europe and USA venture capital invested in technologies,
2000…………………………………………………………………………………..57
Table 4.9 Early stage venture capital in European technologies compared to US seed
financing, 2000……………………………………………………………………….58
Table 4.10 Comparison of Europe and US total technology breakdown by stage of
investment in million Euro, 2000…………………………………………………….58
Table 5.1 Major sub-sets within biotechnology……………………………………..61
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1. INTRODUCTION
This report aims to provide a framework for discussing the specific characteristics of
knowledge generation, accumulation and diffusion in the context of the “Life Science
Industry”. The latter is somewhat specific to any other sector and, consequently
exhibits very particular regulation mechanisms. This is obviously due on the one
hand to the science-based character of the industry, but on the other hand, to the
specific nature of the “products” within the industry that oblige the integration of
consumers’ preferences and related ethical considerations in a very logical manner. In
order to depict the specific regulation of knowledge generation, accumulation and
diffusion that result from the original life science industry, we organised the
discussion as follows: Section 2 provides a brief historical background of the industry
leading up to an introduction of the key factors implicated in the current stage of
development. Section 3 is an analysis of the biotechnology industry, providing an
overview of both the US and European contexts as regarding geographical
distribution, research and development, and the relevant economic, scientific and
technological indicators. Section 4 addresses the mechanisms of knowledge
generation, accumulation and diffusion in the life science industry by introducing
industrial organisation through the main actors and their behaviours. Finally, Section
5 summarizes our key findings regarding the organisation of knowledge within the
life science industry while taking a traditional product and/or activity approach in
order to introduce areas of exploration for the intended case studies.
2. HISTORICAL INHERITANCE
2.1 BACK TO THE ORIGIN OF THE MODERN ‘LIFE SCIENCE INDUSTRY’
Obviously, an industry does not appear magically on the economic scene. This
largely applies to the so-called biotechnology industry or more generally, to the life
science industry. In what follows, we will consider both industries as starting from
the beginning of the 1980s. Of course, this is reducible in that the history of those
industries began long before, and have included all types of economic activities
related to the use of industrial fermentation as applied to the manufacture of alcohol,
brewing and/or agriculture, more largely. The development of ‘zymotechnology’ (see
Bud 1993 for an overview) will not be considered here, even if this application can be
thought of as a necessary condition for the accumulation of skills, knowledge,
techniques and research protocols for the transition from zymo- to bio-technology to
occur. That transition continued progressively in the 1920s and founded the sciencebased orientation of those industries, including joint concerns from disciplines such as
microbiology, bacteriology, chemistry and biochemistry.
What we will call hereafter biotechnology or, more largely, the life science industry
began with recombinant DNA techniques, that is with the discovery of the structure of
DNA by Watson in 1953 followed by the 1973 discovery by Cohen and Boyer who
opened the door to what would be identified thereafter as “genetic engineering”.
Cohen and Boyer succeeded in cutting a section of DNA from a plasmid of
Escherichia coli bacterium and transferring it into the DNA of another plasmid. They
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then allowed for the ability to change gene structures and related messages and,
consequently, impact the production of proteins in a more or less controlled way.
As a result, a new era for biotechnology occurred and the founding of that
breakthrough can be dated back to the famous Asilomar meeting (July 1975), a very
paradoxical start, as the Asilomar outcome being a call for “a pause in research until it
could be regulated in such a way that the public need not be anxious” (Bud, 1993,
p.175). As a consequence, the beginning of this new era led to a sixteen-month
moratorium while waiting for NIH guidelines that were produced mid-1976.
Nevertheless, the Asilomar convention can be identified as the starting point of the
story. It especially reveals the importance of “genetic engineering” and the
emergence of young researchers grouped in a loosely-defined profession, the
molecular biologists.
2.2 THE POST-WAR ERA OF THE ‘LIFE SCIENCE INDUSTRY’: THE
RANDOM SCREENING PERIOD
Until the availability of recombinant DNA technology, the life science industry was
mainly associated with the pharmaceutical industry. The latter was essentially driven
by a chemistry-culture where design and screening of molecules’ potentialities were
the central stages of drug discovery procedures. Secrecy was a master word and the
strategic orientation of companies was essentially devoted to the management of a
suited pipeline of new products in order to ensure a regular trend for the growth of the
company.
Drug discovery was as such the result of a random process, because empirical
evidence was the main driver of the innovation process. At that stage of the ‘life
science’ industry, knowledge accumulation was essentially internal to each company,
from research protocols to screening and test processes, including individual libraries
of compounds that ensure the originality (and the protection as well) of the molecules
under scrutiny. Such characteristics were confronting an increase in importance
exercised by regulatory authorities, mainly national-based, where approvals for new
drugs were necessary and obtained in accordance to a philosophy of a ‘proof of
efficacy requirement’. Then, the portfolio of products of a company in that industry
was also a significant barrier to entry because of the blockbuster aspect of the market:
a firm was likely to invest for a long time in order to get any approval from regulatory
authorities, but financial returns were also ensured, and this mechanism was centrally
correlated to the relative quality of a firm’s contents in the pipeline.
Consequently, innovative capabilities and related knowledge requirements were
mainly directed toward the internal efficacy of large firms, that is to the search of a
suited combination of technical and organisational capabilities in order to ensure the
successive stages of identifying, testing and securing the effects of the drugs under
development.
Here, we need to add that the risk associated with the huge development costs of any
new drug creates incentives for companies to favour vertical integration, including the
control of marketing and distribution networks. In that respect, as those large
companies were facing the international market, nations (and their underlying
institutional frameworks) were mainly thought of as biased to open competition and a
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means of ensuring “local” protection for domestic companies (see Thomas, 1994).
The life science industry belonged to the world of large international and verticallyintegrated companies.
During this period, two main (and interrelated) changes influenced importantly the
organisation and the regulation of the industry:
On the one hand, innovative capability became highly dependent on academic
research. This obliged firms to develop absorptive capacity, ticket of admission in the
scientific community and adjust their organisations and research incentives. As a
result, a dense network of collaborative relations emerged where start-ups appear as
up-stream suppliers of technology and R&D services, and where large pharma
companies provide capital and access to complementary assets. Large pharma
companies act as integrators of highly fragmented bits of complementary knowledge
where each start-up underlies avenues of developing alternative approaches to drug
discovery, being a particular instantiation of the opportunities offered by scientific
progress.
On the other hand, large pharma companies progressively became aware of the
potentialities of new techniques for their research capabilities. At least, they chose
two major (alternative) options for exploring their innovative capabilities: (1)
improving the characterisation of new molecules to biological targets or (2) improving
generic tools and search based on the law of large numbers. But, in both cases,
structural change was occurring, promoting a new learning regime within the industry
characterised by the emergence of a new set of companies, i.e., academic start-ups
(the so-called dedicated biotech firms—DBFs, see section 4.1.2) that specialise in
research tools, the latter becoming service providers for pharma companies. Strategy
one resulted in a trajectory of increasing specifications of general research
“hypotheses”. Strategy two resulted in exploring platform technologies, mixing
different types of resources, favouring multidisciplinary knowledge exchanges, and
modifying the inter-generational structure of individual knowledge. However, both
strategies expressed structural modifications in learning regimes and knowledge
accumulation at this stage in the history of the life science industry.
If we refer to a layer model to characterise the working and the organisation of the life
science industry at this stage, we could argue that large pharma companies were not
submitted to radical change. They were able to maintain their leadership, even if they
had to build organisational structures able to integrate up-stream capabilities. This is
certainly due to the strong regulatory constraints that gave the incumbents an obvious
advantage.
However, the transition from chemistry-oriented pharmacology toward recombinant
DNA technology and molecular genetics has not been an easy one for big pharma
companies. As noted by Galambos and Sturchio (1998, p.2), all the previous stages of
significant technological transitions within the twentieth century were led by large
organisations themselves that succeeded in maintaining their leadership within the
transition process: “during the 1930s, 1940s, and 1950s, for example, it was large,
vertically-integrated companies that led the industry into the golden age of medicinal
chemistry.”
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But within the 1980s, small biotech firms have progressively developed niche
technologies and related markets which oblige large companies to conduct strategic
shifts and significant changes in their collective organisation. Under the pressure of
the progress of science and the related emergence of the DBFs associated to sciencebased activities, large pharma companies had to manage the increasing need of
establishing alliances or participating in initial public offerings in order to take
advantage of the opportunities resulting from the multiple development of
recombinant DNA techniques. Technical opportunities and organisational challenges
in the respective role of large and small companies have provoked a radical shift in
the definition of this industry as well as in the characteristics of knowledge generation
and accumulation.
2.3 UNTIL THE EIGHTIES: TOWARDS AN ‘ORGANIZED’ SCREENING
PERIOD IN DRUG DISCOVERY
2.3.1 The first sub-period: A new era with “Happy few” participants
The transition from classical biotechnologies to recombinant DNA techniques occurs
in different stages. The first one came from the observation that using those
techniques to challenge the production of human proteins was economically
interesting. Three major candidates have been targeted by companies: insulin,
growth hormone and interferon. Insulin was of course on the top of the list. Until
genetic engineering, insulin was produced from animals and, consequently, was
slightly different from human insulin. As insulin was intensively used for decades to
treat diabetes disease, the market revealed huge opportunities. The same for growth
hormone which was until then extracted from cadavers and interferon which was
highly difficult to extract from the human body (a tenth of one gram of interferon
requires approximately 90.000 liters of human blood to be extracted). Thus, the
economic implications of these human proteins were obviously important and resulted
in the birth of original start-ups, due to innovative entrepreneurs. Among those
“happy few” we identify four exemplified companies: Cetus, Genentech, Biogen, and
Amgen. These companies have a few characteristics in common, representative of
this first stage in biotech development.
These firms first established themselves in the seventies and as such, they were
exceptional for the time. They reveal a generation of entrepreneurial scientists that
thought of companies as “research boutiques”. As such, they were largely interested
in pursuing academic challenges even if they were also motivated by industrial
concerns regarding an economic reality which was mainly the production of human
proteins. Secondly, they very much had a wide vision of what they could do in order
to exhibit economic profitability. This first generation of companies wanted to be “all
things to all markets”. They were developing a research strategy that was very large
and that did not result in technical specialisation. For instance, Genentech
experimentally succeeded in producing the first human protein (Somastostatin) one
year after the company had been established. However, Genentech succeeded in
producing human insulin by 1982 and a recombinant blood-clotting for hemophilians
by 1984. Genentech put Protropin (recombinant human growth hormone) on the
market in 1985, Activase (recombinant tissue plasminogen activator (TPA) to treat
heart attack) in 1987, Pulmozyme (recombinant human DNAse to treat cystic fibrosis)
in 1993, the famous Rituxan (the first monoclonal antibody approved to treat
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cancerous diseases) in 1997, and Herceptin (a second monoclonal antibody to treat
metastatic breast cancer) in 1998.
If Genentech appears very emblematic of this type of biotech company, it is primarily
because it was the first one. But the other members of this first stage of development
(Cetus, Biogen, Amgen) follow the same pathway. They all tried to become very
diversified in terms of economic applications of their skills and capabilities. Their
knowledge base was applied in many various ways. As a consequence, their
development included important partnerships with well-established companies in
related areas (notably the pharmaceuticals). To continue with the example of
Genentech, we have to emphasize that in order to put those products onto the market,
Genentech has been obliged to develop alliances and licensing strategies with the big
pharma companies: worldwide rights to recombinant human insulin have been sold to
Eli Lilly; Factor VIII (recombinant bloodclotting) has been licensed to Bayer.
Protropin rights have been sold to AB Kabi (leader on the market of cadaver-derived
growth hormone). Rights related to interferon have been bought by HoffmannLaroche, and the like . . . This kind of complementarity with big pharma companies
essentially expresses first, that the latter have not anticipated the important potentials
of the new biotech industry, and second, that those biotech companies have found an
original way to deal with the big pharma companies. They paid as they made
progress: “Genentech was the first to ask for an upfront licensing fee and benchmarks
for payments—if they don’t hit them, they don’t have to pay us” (Robbins-Roth,
2000, p.27).
That complementarity was not the specific characteristics of one company
(Genentech), but a sort of common peculiarity of that set of small biotech companies.
However, the last incumbent in that set of companies (Amgen) developed a slightly
different strategy. Even if the company was also (too) largely diversified (human
therapeutics, human diagnosis, animal health care, specialty chemicals), Amgen is the
first company to have developed independently some of its products and to go through
the different stages of development towards FDA approval and to market. Epogen (a
recombinant version of EPO in 1989), Neupogen (to prevent infection in cancer
patients in 1991), and Infergen (interferon applied to hepatitis C in 1997) are now
products on the market that allow the company to get cash returns and Amgen became
one of the leading small players of the biotech industry, and exhibits a fascinating
growth evolution as the following figure shows:
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Table 2.1 Growth evolution of Amgen, 1980-99
Employees
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
3
36
97
124
178
196
253
344
479
667
1084
1723
2335
3065
3352
4046
4646
5372
5494
6342
Revenues
Net Incomes
R&D
(Bil. US
(Mil. US dollars)
Expenditures
dollars)
(Mil. US dollars)
(Na)
(Na)
(Na)
(Na)
(Na)
(Na)
(Na)
(Na)
(Na)
(Na)
(Na)
(Na)
(Na)
(Na)
(Na)
(Na)
(Na)
(Na)
(Na)
(Na)
(Na)
(Na)
(Na)
(Na)
(Na)
(Na)
(Na)
(Na)
(Na)
(Na)
(Na)
(Na)
(Na)
(Na)
(Na)
(Na)
1,1
357,6
182,3
1,4
383,3
255,3
1,6
319,7
323,6
1,9
537,7
451,7
2,2
679,8
528,3
2,4
644,3
630,8
2,7
863,2
663,3
3,0
1100
822,8
The example of Amgen shows how the entrepreneurial stage of science-based startups evolves and consequently, biotech companies of that first generation could no
longer be thought of as research boutiques but rather as real players in those new
industrial areas.
2.3.2 The second sub-period: Increasing specialisation, money accessibility and a
blast of knowledge opportunities
A structural shift in the structuring of the biotech industry occurred at the beginning
of the nineties. It is mainly characterised by an important increase in specialisation
due to the complexity of the problems targeted: “Whereas efforts have so far been
concentrated on the generation of biologically important molecules, the next phase is
likely to lead to the engineering of pathways and cells” (ACOST, 1990, p.1). The
field became much more complex and the epoch of the first-mover advantage in
recombinant DNA techniques diseappeared. The renewal was in fact the higher
integration of biotechnology with chemical approaches because the development of
techniques, e.g., PCR, allows for a kind of industrialisation effect in the understanding
of the genes’ materials and activations. This, of course, leads companies to
specialisation and a huge set of new activities explored by science-based SMEs.
This transition phase has also been favoured by the success of the first generation of
biotech companies. At least, the four emblematic figures of successful start-ups
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mentioned above contributed to a change in the image and the vision of what the
market’s opportunities could be from the life science industry. Consequently, money
accessibility highly increased, and took on different forms. On the one hand, initial
public offerings support growth perspectives of established companies. The following
table lists the main IPOs for US companies at the beginning of the eighties and shows
how significant the role of financial ventures on that industry has been, at least in the
US context.
Table 2.2 Life sciences: US IPOs
Company
Genentech
Cetus
Genetic Systems
Ribi Immunochem
Genome Therapeutics
Centocor
Bio-Technology
General
Scios
Immunex
Amgen
Biogen
Chiron
Immunomedics
Repligen OSI
OSI
Cytogen
Xoma
Genzyme
Imclone
Genetics Institute
Total
IPO Date
Amount
Raised
(Ms #)
10/80
3/81
4/81
5/81
5/82
12/82
9/83
35
107
6
1,8
12,9
21
8,9
1/83
3/83
6/83
6/83
8/83
11/83
4/86
4/86
6/86
6/86
6/86
6/86
5/86
12
16,5
42,3
57,5
17
2,5
17,5
13,8
35,6
32
28
32
79
557,3
Then, venture capitalists progressively entered the game and provided significant
incentives to academic start-ups and DBFs. When NIH funds incorporated in research
projects’ subsidies are added to that of venture capital, the context becomes
appropriate for a huge amount of new companies. The following graph (2.1) shows
the growth effect in biotech companies in the US context and clearly shows a
favourable period for the structuring of a new industry within the 1980s.
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Graph 2.1 Creation of DBFs in the US
90
80
New DBF
70
60
50
40
30
20
10
19
98
19
96
19
94
19
92
19
90
19
88
19
86
19
84
19
82
19
80
19
78
19
76
19
74
19
72
19
70
0
Source: Dibner M., Bitoechnology Guide USA, 1999.
With this specialisation and related targeting strategy effects, the model of the biotech
company evolved importantly: “Although by 1988 over a thousand US companies
were in some way connected to biotechnology, no longer would the genre of the small
scientist-driven company define the technology . . . Increasingly, companies were led
by experienced executives rather than scientists, even if close relations between
university and industrial laboratories did endure and develop” (Bud, 1993, p.193).
The explosion of opportunities for the industry came with another crucial event: the
development of the human genome project (HGP). We use the latter as a generic term
to describe all that phase of research effort devoted to the sequencing of genomes, be
it plants, animals or human beings, i.e., the transition towards the genome era. In a
first period, the industry focused research investigation on the mapping of the DNA
which structures the cells of organisms. Planned from the joint initiative of NIH and
DOE in the US, the HGP is expected to be completed in 2003. Currently, the draft of
the human genome provides a road map of an estimated 90% of the genes included in
any chromosome. The human genome is estimated to contain 30.000 to 40.000 genes,
which is around 2% of its genetic material (3164,7 million chemical nucleotide
bases—A, C, T and G). The rest may be involved in managing the chromosomal
structure and protein regulation (where, when, and in what quantity). However,
humans have on average ten times more proteins than genes, due to mRNA transcript
alternative splicing and chemical modifications to the proteins: the same gene can
encode different proteins.
This last remark stresses the importance of the human genome project, not as such but
as a kink of impressive structural shock on the industry in terms of learning regimes,
knowledge accumulation and economic opportunities. We do not learn so much from
the identification of the human genome by itself: here we have to remind the reader
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of the image of a dictionary where not only words would not be ordered by alphabetic
ranking, but also the definitions associated to the words are not ordered. Therefore,
this amount of information is not associated to a clear-cut corresponding knowledge.
Even more, there are voices that, pursuing the image of the dictionary, are dubious
about the effect of that central allocation of research resources: “If you have a
document to read, do you put it in a shredder first?” (Hoch et al., 1996, p. xvii).
Anyway, this last point only stresses the need to seriously consider the follow-up from
the genome identification period and the entrance into the post-genomics era. Today,
we can consider that different (and more or less alternative) research orientations are
pursued expressing the increasing specialisation and diversification processes faced
by this industry:

Functional genomics (looking at changes in animal models when a gene with
an unknown function is turned on and off);

Structural genomics (looking at the 3D structure and evolution of proteins and
detecting the influence of 3D variations onto their biological functions);

Positional cloning genomics (looking at regions of chromosomes containing
genes that have shown up, according to a specific disease. Starting with the
disease, work is performed in a backwards-direction in order to identify gene
sequences that are activated in patients and not activated in healthy people);

Transcriptomics (large-scale analysis of mRNAs in order to determine where,
when and under what conditions genes are expressed);

Proteomics (identifying the constellation of all proteins in a cell and studying
their structures and activities; differences and changes in gene expression
should allow for identification of proteins which might be involved in the shift
from healthy to cancerous cells, for instance);

And Pharmacogenomics (looking at differences in gene sequences between
individuals in order to identify gene mutations that can be used to predict the
susceptibility to disease and identify appropriate individual treatments)
(currently, 1,4 million locations of SNPs1 have been detected in human DNA).
All of these research areas are promising opportunities in terms of identification of
new drug discovery, new testing protocols, and new and appropriate genetically-based
treatments of diseases. However, no single optimal path is clearly identified to deal
with those objectives, and the exploding openness of the life science industry can also
be thought of as having competing methods in order to arrive at the best ways in
which to deal with the understanding of human functioning.
SNPs – Single Nucleotide Polymorphisms – are DNA sequence variations that occur when a single
nucleotide (A, C, G or T) in the genome sequence is altered. SNPs can (or cannot) have effects on a
cell’s function but variations in DNA sequence can have important impacts on how humans react to
(potential) diseases; SNPs are relatively stable from one generation to another and influence how
individuals respond to environmental aggressions as well as to drugs and other therapies.
1
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What is very significant in this new stage of the life science industry is the need to
face very new research methods, protocols, and even scientific disciplines, i.e., to shift
the knowledge base of the industry.
Bioinformatics directly results from the requirements of the post-human genome
project. Determining the sequence of a genome is only the starting process of the
understanding of genomics, i.e., of the protein fabrication and interactions.
Bioinformatics is a generic term that expresses the need for tackling the huge amount
of scientific calculus required to understand the working of the genome. Different
orientations can be listed here. The 3D-modelling of proteins, their evolution and
variations in time and space (and milieu), the management of gene data banks are all
sources of huge amounts of numeric calculation. The introduction and the industrial
utilisation of DNA-chips in order to express RNAms and understand protein synthesis
(proteomics) requires enormous computing capabilities. If the number of human
genes is thought to be 30.000 to 40.000, the number of proteins is thought to be ten
times that number. Understanding this gap explains the importance of proteomics as
well as the strategic importance taken by bioinformatics within the last few years.
Even more than bioinformatics, the post-genome era is a source for higher
diversification processes within the life science industry, due to the introduction of
combinatory techniques and multiple technologies hybridation: “the interface
between biological and non biological substances is important for producing novel
sensors and devices” (Hoch et al., 1996, p. xiv). Among the technical devices that are
central to the life science industry, the role of electronics appears particularly critical:
“When bound to the gate regions of transistors, biological molecules can influence
and/or alter the electronic characteristics, thereby providing switching and sensing
capabilities” (Hoch et al., 1996, p. xiv). Nanofabrication and sensor research appear
as two of the most interesting areas of the penetration of electronics into biology. On
the one hand, controlling structures and suprastructures of biological molecules,
surface interactions including the fabrication of submicron pores, the orientation of
cell behaviours and/or neurons are promising areas of interfacing technologies coming
from different disciplines (physics, mathematics, informatics and automation, etc.).
On the other hand, sensibility techniques are crucial for the understanding of
biological mechanisms. For instance, when antibodies meet their antigens, mass
changes occur and sensor research is extremely important in order to identify and
understand the mechanisms at stake.
Instrumentation techniques is another example. The development of the scanning
tunnelling microscope (STM) and of the scanning force microscope (SFM) (or atomic
force microscope (AFM)) allows scientists to describe and reproduce images of
biological molecules or systems in their physiological conditions. As such, it is an
impressive support to functional studies of biological systems. Those instrumentation
techniques are improving quickly and, as they are noncontact force microscopy, they
are very promising in the analysis of molecules or in the working of biological
systems in that they allow description of the underlying phenomena without damaging
(or at least minimising the damage) due to observation.
Then, coming again to the combination of microfabrication and biology, it is really
new research areas and disciplines that are now being structured: “Such research
requires scientists who are experts in their own areas of reaserch but, at the same time,
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are able to traverse the gap between widely disparate fields. It requires an
understanding of each other’s languages and capabilities. And, it requires a genuine
cooperation between biologists and engineers and materials scientists” (Hoch et al.,
1996, p. xv).
What currently occurs in the post-genome era largely challenges the proccess of
knowledge accumulation that prevailed in the previous stages of the life science
industry. Those multiple and combinatorial aspects of scientific and technical
requirements impact importantly knowledge characteristics as well as knowledge
sources, emitters, receptors and channels of diffusion.
This remark can be generalized in order to depict the current stage being confronted
by the so-called life science industries. It especially allows one to understand why in
this stage, small and very-small companies are acting as exploratory facilities for
well-established companies. The multiplication of windows of technical opportunities
is so important that many doors can be (and are) opened by alot of companies in order
to meet the challenge of the post-human genome area. This leads to an industrial
context where knowledge accumulation and its evolution occur through
interorganisational exchanges, R&D alliances and networks of learning (see Powell et
al., 1996).
This context of exploding technical opportunities due to scientific progress goes hand
in hand with consequent changes on the market. Where new drugs were still largely
coming from the “random screening” period at the beginning of the nineties, this was
no more the case at the end of the decade. Kopp and Laurent consider the shift as
having been from 20% to 70% for new drugs within the period. In other words, drug
discovery is facing a revolution and new drugs and therapies are based on analytical
understanding of the actions of those new molecules.
Finally, referring to a layer model, this period of the life science industry is very
different from the previous one in that the well-established regulation of innovation
and knowledge accumulation centered around big international pharma companies
largely diseappeared. The structuring of innovative capabilities spread towards a
larger set of actors including academics, start-ups, health research associations, etc.
To some extent, large pharma companies are losing the control of driving innovation
and drug discovery, even if they are able to keep, for entry barrier reasons, the
marketing and distribution phases of a drug’s delivery. However, in the last decade,
they were progressively losing that control too, under the double pressure of (1) a few
small biotech companies that want to become global players (Amgen is the most
accurate example) and (2) of managed care organisations that create communities of
practices and dispute the control of human health care to large pharma companies.
3.
BIOTECHNOLOGY INDUSTRY ANALYSIS: US v. EUROPE
Please see Appendix A for background information and notes on research pertaining
to this section.
3.1 BIOTECHNOLOGY INDUSTRY: STATE-OF-THE-ART
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3.1.1 US Biotechnology Industry Analysis
Available sources for the life science industries in the US indicate the existence of a
population of around 1500 companies acting in different sectors as of 1999.
Considering only the population of companies which are still operating, one notes a
few structural characteristics that allow for better understanding the life science
industries in the US case. Basic numbers form a rough perception of what is at stake
within the life science industries in the US context and are expressed in Table 3.1:
Table 3.1 Life science industry in the US
Pharma
Corps.
Number of
companies
Number of
employees
Revenues
Bio-pharma
Cos.
Other Life
Science Cos.
Total Life
Science Cos.
Total
(overall)
51
421
828
1 249
1 300
975 215
265 710
63 081
20 671
76 692
28 302
139 773
48 973
1 114 988
314 683
The columns of the table successively consider the large US pharmaceutical
corporations, bio-pharmaceutical companies (which are a subset of life science
companies identified by a specific focus of their activities on therapeutical issues),
other life science companies (including non-therapeutical-oriented companies), and
the total of either life science companies or life science plus pharmaceutical
companies.
Life science companies represent 12,5% of employees for 15,6% of the total revenues
(respectively 87,5% and 84,4% for large pharmaceutical corporations). Within the
population of life science companies, there is a significant focus on therapeutical
issues (one-third of the population of firms whereby one-half of the total employment)
even if the relative revenues exibited by that subset of companies is weaker than those
of the other life science companies. Finally, it seems that life science companies
perform better than large corporations (14,3 % of their employees for 18,4% of their
revenues) even if the volatility of the former as well as the infatuation of venture
capitalists largely ponderate that statement.
Analysing the year of establishment for those companies (see Graph 2.1) clearly
indicates a break in the beginning of the eighties. The average of yearly-founded
companies increases at least twice, more or less from 20 to 60. The US structuring of
those industries clearly shows a change in the structural patterns in the year 1982. A
higher rate of establishment of new companies is obviously noticeable after that year.
Second, that higher rate of creating companies has more or less stabilized for more
than a decade. This impressively impacts structural patterns and progressively defines
new industrial areas or sectors, which set-up the so-called life science industry. Third,
until the mid-nineties, one can wonder about the hypothesis that the US context is
moving from a high rate of companies’ creation toward a consolidation phase
associated with an increase in specialisation. A recent evolution which is the relative
decrease in the flow of newly-created companies, seems to be sensitive but has to be
looked at more precisely, because of possible data bias. However, it makes sense to
consider that after a high range of new opportunities to be explored by the first
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generation of “research boutiques”, that industry is evolving under the pressure of a
higher specialisation that could have increased entry barriers and reduced numbers of
newly-created companies. Finally, one has to insist on the fact that Graph 2.1 only
takes into account the companies still existing. One can estimate that a set of 1000 to
1200 companies are no longer doing business but could have affected the figure in
terms of historical structuring for those industries.
The other characteristic is the mapping of the specialisation process followed by those
companies. The following table (3.2) expresses the different research areas explored
by those life science companies. Major concerns are:
Table 3.2 Key areas for US life science companies
Key areas
Number of
companies
Cancer
Combinatorial Chemistry
Cardiovascular
HIV/AIDS
Osteoporosis
Gene therapy
Genomics
Bioinformatics
Breast cancer
Hepatitis
Cell therapy
Cytokines/Lymphokines
Lung Cancer
Neurological Disorders
Alzheimer’s disease
Multiple Sclerosis
352
175
172
158
143
137
125
108
105
100
96
78
72
62
52
31
This larger spectrum of domains is complemented by the increasing number of
biotechnology-derived products having received FDA approval and been put on the
market. The following table is simply indicative and compiles different sources of
information to identify the progressive increase in the FDA approval of biotechproducts:
Table 3.3 FDA approvals of biotech patents, 1982-1998
Year
1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998
Number of 1
0
0
1
4
2
0
2
4
4
2
5
2
14
13
13
25
FDA
approvals
From these few sketchy characteristics, it clearly becomes evident how recombinant
DNA techniques have opened a huge window of opportunity that also put into
question the identification and the characterisation of the life science industry.
Until the mid-nineties, the industry appeared to be facing a consolidation phase.
Significant increases in acquisitions, mergers and IPOs highlight the argument that a
new phase has started for those newly-created companies. On the one hand, mergers
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are very few relative to acquisitions; on the other hand, a strong recent increase in
IPOs (320 in 1997, 408 in 1999) is evident. Both are indices of a redefinition of the
relationships between large and small (including very small) companies and,
consequently, of the entry towards a consolidation phase for those industrial activities.
1999 is for instance the first year where the majority of life science companies were
no longer privately-funded. Table 3.4 describes the firm-funded structure. It shows
what can be interpreted as a re-organisation process for those companies by noticing
the increase in the participation of large corporations in those businesses, mainly
through acquisitions (more or less 25% of that population of firms are now in the
direct surrounding of large corporations).
Table 3.4 Source of funding for US life science companies, 1999
Private-funded
Public-funded (IPOs)
Subsidiary of large corporations
Divisions of large corporations
Joint ventures
Total
48%
27%
17%
6%
2%
100%
This consolidation process also makes sense with regard to the average increase in
revenues reached by that population of companies:
Table 3.5 Summary of life science industry in US
Employees
Revenues (millions)
R&D expenditures (millions)
Number of life
sciences companies
1995
1997
1999
96.000 116.000 116.000
12,1
23,3
39,7
10
9,62
12,9
1 050
1 070
1 239
Those numbers make explicit the progressive emergence of new products explored by
those companies on the market; this stage of their development allows for the
consolidation of sales and revenues as well as R&D expenditures. Basically, those
activities are taking their place in the industrial system and desire to become active
players in the areas of drug discovery and delivery. Interestingly, that consolidation
process is not only a result of the life science companies but also that of the large
pharmaceutical corporations. For instance, in 1991, less than 20.000 employees were
attached to large companies. Those numbers had gone up 3,5 fold by 1999, but only
doubled in the case of life science companies (cf. IBI, 1999, p.7).
3.1.2
European Biotechnology Industry Analysis
The comparison between the US and European contexts, with regard to the
development of the life science industries is generally misleading. There are more
and more voices stressing the apparent catching-up of Europe in terms of the
structural patterns in these industries. However, this is a very controversial
perspective to adhere to and part of the arguments we are developing are emphasising
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that structural differences as well as qualitative differences very much prevail between
the situations in the US and Europe.
The following table (3.6), taken from the Ernst & Young 2000 report on
biotechnology, lists, as in the case of the US, a few sketchy structural characteristics
for the European life science companies. It clearly appears that the organisation of the
life science industry exhibits highly different patterns. More notably, the average
number of employees by company is three times less than the similar population (of
life science companies) in the US and their revenues are around ten times less.
Table 3.6 Life science industry in Europe
Number of firms
Number of
employees
Sales (M EUR)
R&D expenditures (M EUR)
1994
485
1995
584
1996
716
1997
1 036
1997
1 178
1998
1 351
16 100
(na)
17 200
1 471
27 500
1 721
39 045
2 725
45 823
3 709
53 511
5 368
(na)
1 252
1 508
1 910
2 334
3 164
Interestingly, those structural differences concerning US and European patterns in the
life science industry do not seem to decrease, despite the initial perception of a more
or less similar number of companies. Looking at public R&D expenditures, that is of
course not clearly indicative of future innovative capabilities as well as product
opportunities. Kopp and Laurent (2001) also show that the relative effort in public
R&D is significantly in the advantage of the US context throughout the last decade.
Public support to the life science industry is importantly influent, especially because
of the highly science-based character of knowledge production, diffusion and
accumulation. Kopp and Laurent (2001) argue that public R&D expenditures across
Europe are facing dramatic differences. For instance, French R&D expenditure in the
cumulative life sciences is seven times less than that of Germany and eight times less
than the UK. This situation seems to be not very useful in disputing US domination
regarding the expected economic benefits from those activities.
Within the European context, quantitative disparities are sensitive, with regard to
national patterns (Table 3.7). Germany is more structured in terms of the density of
created companies, and established networks of knowledge production and
accumulation with universities and academics. The UK is higher performing in terms
of economic indicators; the life science companies in UK benefit from US
connections and seem to be more effective in their contact to business opportunities.
The French life science industry is less developed and appears to be lesser performing
with regard to the recent report provided by Kopp and Laurent (2001).
Table 3.7 Life science industry in France, Germany and UK (*)
France
Number of firms
Number of
employees
Germany
250
340
United Kingdom
280
4 500
10 700
18 400
Source: Kopp & Laurent, 2001
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(*) Significant differences in numbers between this data and the OECD data are mainly due to
definitional issues related to the “biotechnology” industry.
The number of newly authorised medicinal products in Europe did not stop growth
throughout the period 1996-2001, as the increase is nearly 50 % (Table 3.8). The
licenses associated to these new products are indeed a very important aspect of world
competition; these new molecules which result from high levels of research
investments, partially allow for the capturing of the capabilities exhibited by various
countries in the biotechnological and pharmaceutical domains. These approvals of
launching molecules onto the markets reflect not only the performances of a country
in terms of production of new molecules, but it also shows the importance of
environmental variables such as the legal and regulatory contexts that can benefit
from domestic resources and enhance a country’s international competitiveness.
Table 3.8 Life science industry in Europe – New Medecinal Products with European
Community Marketing Authorisation (*)
1996
24
Number of European
Approvals
1997
20
1998
29
1999
30
2000
33
2001
37
Source: European Agency for the Evaluation of Medecinal Products (EMEA)
(*) The differences between the above numbers and the numbers in Table 3.3 (FDA approvals) are due
to the fact that this data are including all new agreements whereas the previous only include new
agreements related to the use of recombinant-DNA techniques.
3.2 GEOGRAPHICAL DISTRIBUTION OF BIOTECHNOLOGY ACTIVITIES
In order to make the picture of the US life science companies more complete, we must
consider further elements. One is the highly concentrated localisation of those
companies within the US. The following graph (3.1) expresses the main geographic
areas where those companies are located. It clearly depicts high disparities within the
US states.
Graph 3.1 US states with the highest concentration of life science companies, 1999
1273
TOTAL US
TOTAL
EUROPE
1570
0
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1000
1500
2000
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176
Oregon
23
25
27
29
30
31
35
36
37
42
Colorado
Minnesota
Michigan
Washington
Wisconsin
53
55
64
New York
74
75
Pennsylvania
98
106
North Carolina
152
332
California
0
50
100
150
200
250
300
350
No. of life science companies
Source: Dibner M., Biotechnology Guide USA, 1999.
Four states concentrate more or less half of the companies concerned with life science
activities. Obviously, this has to do with the disposal of highly skilled scientific
resources and the prestige of a few universities concerned within those research areas.
A twin intersect between companies and academics is still a major characteristic for
those industries. Thus, they consider it beneficial to be located in the surroundings of
those academic actors.
Graph 3.2 Independent European DBFs, 2000
60
32
37
39
51
53
55
64
79
93
Spain
Ireland
Finland
Italy
Switzerland
235
342
France
448
504
Germany
0
100
200
300
400
500
600
No. of independent DBFs
Source : EC, No. 7-2002, based on BID data, p. 33.
Graph 3.2 shows the number of DBFs in major European countries as of December
2000. The data excludes public research organisations, companies whose main
activities are not in biotechnology, and biotech divisions, and therefore represents
firms active in “core” biotechnologies. Here too, a few countries concentrate the main
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European companies, even if the essential explanation is less immediately related to
the academic resources as in the US previous concentration.
In the year 2000, Germany and the UK together accounted for approximately one-half
of the 2092 DBFs present in Europe. Of the 504 DBFs in Germany, only 279 are
dedicated to biotechnology, uniquely including “therapeutics” activity which is
primarily pharmaceutical development. Concerning the corresponding employment
data, 73% of Germany’s 16.382 biotech employees (1999) were engaged either by
large companies (greater than 500 employees) or by firms engaged in “extended”
biotech activities. By breaking down the available German DBF data in such a
manner, we begin to understand how the presence of DBFs alone can be a misleading
indicator of entrepreneurial activity. Consequently, approximately 4.400 German
employees in 1999 were employed by “dedicated” SMEs (fewer than 500
employees), recalling that “dedicated” in the German case refers to both biotech and
pharmaceutical development, ignoring differentiation between the two sectors which
are most often regarded separately. Similarly, the biotech companies in the UK
employed 10.590 workers in 1999, of which 46% were involved in
“biopharmaceutical” activity (OECD, 3-4 May 2001).
With precautions concerning the variations between measurement criteria in mind, it
may be possible to gain a more clear indication of each countries’ respective
entrepreneurial landscape by calibrating the number of DBFs using population figures
(Graph 3.3). In doing so, it becomes apparent that Sweden is far ahead of other
European countries with twice as many DBFs per inhabitant as Switzerland, the
country ranked second in this analysis. In fact, the first six countries having the
greatest number of DBFs per capita all have a population of less than 10 million
inhabitants. One consequence of this fact may be that the small (nothern) European
countries may exhibit more specialisation in the biotechnologies; these countries show
a large number of small DBFs relative to population. Sweden, Finland, Denmark and
Norway occupy 4 of the six top performing positions.
Graph 3.3 DBFs per thousand inhabitants, 2000
0,0300
DBF per 1000
0,0250
0,0200
0,0150
0,0100
0,0050
Sp
ai
n
Ita
ly
Ire
la
nd
Fi
nl
an
d
D
en
m
ar
k
N
or
U
ni
w
te
ay
d
Ki
ng
do
m
Fr
an
ce
G
er
m
an
y
Be
lg
iu
N
et
m
he
rl a
nd
s
Au
st
ria
Sw
Sw
ed
en
i tz
er
la
nd
0,0000
Source: BID, University of Siena in EC, No.7-2002, p.34.
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3.3 FUNDING OF RESEARCH AND DEVELOPMENT
3.3.1 Public funding of R&D in Europe
R&D expenditures can be used as one indicator of a country’s potential for future
growth and productivity. The trend over the past decade across OECD countries has
been a decline in the amount of all government provided R&D funding, and an
increase in the share of industrial R&D funding (NSF, 2000, Ch.2). While it is
difficult to compare R&D funding for specific sectors across countries, the OECD has
published data on public funding of biotechnology, 1997 being the most recent year
available. The following conclusions can be drawn from the data:



The median contribution of government budgets dedicated to biotechnology in
1997 was 3,5%, while the spread was between 0,4% to 13,8%.
Belgium (13,8%) spent the largest percentage of its government R&D budget
on biotechnology, followed by Canada, Finland and the UK at 10,1%, 8,1%
and 7,8% respectively.
In absolute figures, the greatest biotechnology R&D budgets (publicly-funded)
were found in Germany, the UK and France (OECD, 3-4 May 2001, p.36).
Table 3.9 Government funding or outlays for research and development in selected
European countries, 1997
Country
Biotechnology
R&D
Total Government Budget
Appropriations or
R&D biotech/R&D
overall
Outlays** for R&D
Million PPP$
Belgium
Canada
Denmark
Finland*
France
Germany
Ireland
Italy
Netherlands
Norway*
Sweden*
Switzerland*
UK
181.7
261.4
45.2
94.5
560.0
1,048.2
15.0
32.1
78.0
26.8-32.2
65.6
16.4
705.1
Million PPP$
1,314.0
2,581.0
945.6
1,165.0
12,683.1
15,595.7
229.9
7,329.6
3,069.9
880.3
1,795.2
1,379.7
9,055.7
Percent
13.8%
10.1%
4.8%
8.1%
4.4%
6.7%
6.5%
0.4%
2.5%
3.0-3.7%
3.7%
1.2%
7.8%
Exchange rate based on ECB annual average for 2000.
*National estimates.
**Federal outlays represent the amounts of checks issued and cash payments made during a given period,
regardless fo when funds where appropriated.
Source: OECD, based on data from the European Commission (Inventory of Public Biotechnology R&D
Programmes in Europe, 2000), Eurostat, Statistics Canada, and national sources, OECD compendium, 3-4 May
2001, p.37.
Considering the EU as a unit, the European Union Framework Programmes for
Research & Technological Development include research funds allocated to the
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Programme Quality of Life, the latter programme including money dedicated to
research in “life sciences, genomics, biotechnology and health”. The 5th EU
Framework Programme (1998-2002) was equal to about 15 billion EUR, of which 2,4
billion EUR was applied to the Programme Quality of Life, again emphasising the
point that the latter programme is not exlusively dedicated to biotechnology. The
overall budget for the 6th Framework Programme (2002-2006) is 17,5 billion EUR, of
which 2,255 billion EUR or nearly 13% will be applied toward the life sciences,
biotechnology and genomics for health. However, the primary focus of the above
Programme is on increasing the cooperational nature of research across European
countries, and these funds only account for 4-5% of the total research budgets for the
European nations combined (European Commission, 2001).
3.3.2 Public funding of R&D in the United States
The National Institutes of Health (NIH) is the largest federal agency in the US
funding research and training in medicine, health, biotechnology and related fields
such as agriculture. The NIH budget for 2002 was approved by Congress at $23,4
billion dollars, a 14,7% increase over fiscal-year 2001. Clearly enormous disparities
exist between the US and EU with regard to government funding allocations for
biotechnology and health-related research: US $23,4 billion for 2002 v. EU 2,3
billion EUR for the four-year period 2002-2006.
A recent study released by the Brookings Institution in Washington, D.C. shows that
NIH funding is disbursed to research programmes throughout the US, but goes
disproportionately to areas with well-established research infrastructures; the largest
proportion of the funding going specifically to medical colleges and universities. It is
generally understood that biomedical research is the primary practice area leading to
breakthroughs in biotechnology. Often, it is from these publicly-funded research
environments where a scientist gains knowledge and training that later leads to the
founding of a private biotech firm. Table 3.10 lists the nine US metropolitan areas,
labelled “Biotechnology Centres”, which received the largest share of NIH funding in
2000. The Boston metropolitan area received the largest portion of funding at 12,2%
followed closely by New York at 11,8%:
Table 3.10 Share of NIH funding allocated to US biotechnology centres
Metropolitan Area
Boston-Worcester-Lawrence, MA
New York-Long Island, NY-Northern New Jersey
Washington, DC-Baltimore, MD
San Francisco-Oakland-San Jose, CA
San Diego, CA
Philadelphia, PA-Wilmington, DE-Atlantic City, NJ
Los Angeles-Riverside-Orange County, CA
Seattle-Tacoma-Bremerton, WA
Raleigh-Durham-Chapel Hill, NC
NIH Funding ($)
1 422 875 474
1 382 530 715
952 835 848
703 529 044
680 954 889
596 195 344
594 666 368
504 375 867
469 119 754
Share (%)
12,2
11,8
8,1
6,0
5,8
5,1
5,1
4,3
4,0
Source: Brookings Institution, Table 7, p.16, 2002.
3.4 RELATIVE ECONOMIC PERFORMANCE OF COUNTRIES
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Biotechnology and US trade2
The US trade data was extracted from the US International Trade Commission
website and compiled by the OECD. Historically, US trade shows a debit balance in
all areas except for technology-related products, and it is therefore logical that the US
would be the leading supplier of biotechnology products and the benchmark for
measurement in terms of biotechnology trade.
However, the definition of
biotechnology used for compilation of the data is more closely related to “biologics”
which exludes all of the advanced biotechnologies and several other important
applications whose inclusion could significantly alter the landscape. Additionally, the
data represents trade for 1999, in which biotechnology-related products only
accounted for 1% of US advanced technology exports and less than 0,9% of imports
within the same category. With these factors being taken into consideration, certain
conlusions can be drawn from the trade data (see Tables 3.11 & 3.12):



US biotechnology trade is concentrated among a small number of countries.
In 1999, both US biotechnology 76% of imports and 80% of exports were
distributed among seven OECD countires.
The main trade partners of the US for biotechnology are not their traditional
technology trade partners. Belgium, Ireland and Switzerland emerge among
the leading trade partners, with Belgium accounting for approximately onequarter of all US biotechnology imports and exports. (Interestingly, Belgium
is acitve only in biotechnology among all technology trade.) When comparing
the data for the other three leading countries for US exports, Japan, Germany
and Canada, one remarks that Japan and Germany are absent among the
biotech imports, while Canada’s share is only 7,2%.
Most US biotechnology partners import or export but rarely do both.
Belgium, and to a lesser extent the UK, are the only countries which are
equally represented with US exports and imports. Closer examination of the
trade data may reveal national specializations within biotechnology and weak
intra-industry trade patterns.
Table 3.11 Cumulative share in US biotechnology exports to the OEDC area, 1999
Belgium
Japan
Canada
Germany
UK
Netherlands
France
Other OECD
Biotechnology Technology All products
24,0%
*
2,4%
20,0%
14,7%
11,2%
15,2%
16,8%
32,0%
9,1%
8,6%
5,2%
5,6%
12,2%
7,5%
5,5%
5,9%
3,8%
3,2%
6,6%
3,7%
17,2%
33,9%
34,2%
Source: www.usitc.gov, December 2000 in OECD; 3-4 May 2001.
*Less than 2%
2
All data represented in this section was taken from the OECD compedium on biotech statistics, 3-4
May 2001. Please refer to this document for a complete discussion.
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Table 3.12 Cumulative share in US biotechnology imports from the OECD area,
1999
Biotechnology Technology All products
26,4%
*
*
13,0%
7,0%
3,7%
11,7%
*
*
10,5%
*
*
7,7%
8,6%
5,7%
7,2%
14,0%
28,4%
6,9%
4,8%
*
16,4%
62,4%
56,7%
Belgium
France
Switzerland
Netherlands
UK
Canada
Ireland
Other OECD
Source: www.usitc.gov, December 2000 in OECD, 3-4 May 2001.
*Less than 2%
Graph 3.4 Cumulative share in US biotechnology exports from the OECD area, 1999
17.2%
33.9%
34.2%
Other OECD
3.2% 6.6% 3.7%
France
5.5%
3.8%
5.9%
Netherlands
Biotechnology
5.6%
12.2%
7.5%
8.6%
5.2%
Technology
UK
9.1%
All Products
Germany
15.2%
32.0%
16.8%
Canada
14.7%
20.0%
11.2%
Japan
24.0%
*
2.4%
Belgium
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
Source : OECD compendium, 3-4 May 2001.
Graph 3.5 Cumulative share in US biotechnology imports from the OECD area, 1999
16.4%
56.7%
62.4%
Other OECD
6.9%
4.8%
Ireland
*
7.2%
14.0%
28.4%
Canada
7.7%
8.6%
5.7%
Biotechnology
UK
Technology
10.5%
Netherlands
* *
All products
11.7%
Switzerland
* *
13.0%
7.0%
3.7%
France
26.4%
Belgium
**
0%
20%
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60%
80%
100%
120%
140%
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Source : OECD compendium, 3-4 May 2001.
3.5 RELATIVE SCIENTIFIC PERFORMANCE OF COUNTRIES
3.5.1 World Distribution of Scientific Publications
The number of scientific publications within the set of the three major regions of
scientific activity (European Union, Japan and United States) continued to grow
throughout the 1980's, leaving the US in a dominant position, followed by the EU and
Japan (see graph below).
500,000
Japan
450,000
U.S.A
European Union
400,000
350,000
300,000
250,000
200,000
150,000
100,000
50,000
0
1980
1985
1990
1991
1992
1993
1994
1995
Source : Rasci Data : Science Citation Index, from EU report on S&T indicators, 1997.
Since the beginning of the 1990's, contrary to the American dominance, the growth in
the number of scientific publications by the EU seemed to be more steady than that of
the US. One can thus expect a relative catching-up of the EU with regard to the US.
But, this is not the same for Japan. Indeed, since the 1980's, even if a similar growth
pattern in the number of scientific publications is observed, a slower increase in the
growth rate since the beginning of the 1990's is equally present (note that the number
of publications practically doubled in 15 years), Japanese publications increase but
from a sharply lower initial level with regard to the US and the EU. This is of course
due to the much lesser importance of Japanese public research infrastructure
compared to the United States and Europe.
3.5.2 World Distribution of Scientific Publications (Life Sciences)
Publications in the field of the life sciences have also experienced an increase in
numbers since the 1980s. The dominance of the United States (actually, the NAFTA)
remains. But, the European Union experiences higher growth and is beginning to
catch up the US. With regard to the relative parts of total patenting, however, the EU
is positioned worse than the US. Asean countries in the life science fields are again
rankede third, and their growth rate is sharply stronger than those of both other sets of
countries for the reasons already indicated (level effect). Besides, the number of
publications have more than doubled in the field of the life sciences for the period
1980-1995.
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350,000
ASEAN
NAFTA
300,000
EU
250,000
200,000
150,000
100,000
50,000
0
1980
1985
1990
1991
1992
1993
1994
1995
Source : Rasci Data : Science Citation Index, from EU report on S&T indicators, 1997.
3.5.3. Distribution of Scientific publications by discipline (NAFTA)
Scientific publications of the NAFTA countries increase globally but this is mainly
due to the domain of life sciences, followed by engineering, physics, chemistry, earth
and space sciences and finally mathematics. Life sciences represent an important part
of scientific publications; in fact, they represent more than 50%. Intra-discipline
growth does not modify significantly over the period 1980-1995, and does not
engender significant change in the composition effect.
On the other hand, the growth rates in publication numbers vary according to
scientific disciplines. Indeed, publications in the life sciences and engineering
demonstrate more or less the same growth, which is relatively more important than
that of any other discipline. The relative part of publications in the life sciences, with
regard to the total, is still significantly higher.
300000
Earth and space sciences
Engineering
Mathematics
Physics
Chemistry
250000
Life sciences
200000
150000
100000
50000
0
1980
1985
1990
1991
1992
1993
1994
1995
Source : Rasci Data : Science Citation Index, from EU report on S&T indicators, 1997.
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3.5.4
Distribution of Scientific publications by discipline (ASEAN)
80000
Earth and space sciences
Engineering
70000
Mathematics
Physics
Chemistry
60000
Life sciences
50000
40000
30000
20000
10000
0
1980
1985
1990
1991
1992
1993
1994
1995
Source : Rasci Data : Science Citation Index, from EU report on S&T indicators, 1997.
In the Asean countries, publications in the life sciences are always the most important
with regard to any other discipline. In that case, the discipline following life sciences
is physics, followed by engineering and chemistry which have more or less
comparable proportions of publication numbers. Publications in mathematics and in
earth and space sciences appear in a marginal way. The strongest progress returns to
the life sciences, followed, again, by physics and engineering for which the number of
publications has also more than doubled in 15 years. On the other hand, if one
compares with the results obtained in the US, it is noticed that the scales are in no way
the same. Indeed, the American publications are on the order of 75-120.000, while
the Japanese publications are on the order of 10-30.000.
3.5.5 Distribution of Scientific publications by discipline (EU)
300,000
Earth and space Sciences
Engineering
Mathematics
250,000
Physics
Chemistry
life sciences
200,000
150,000
100,000
50,000
0
1980
1985
1990
1991
1992
1993
1994
1995
Source : Rasci Data : Science Citation Index, from EU report on S&T indicators,1997.
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The scientific publications of the European Union are the most numerous in the field
of the life sciences. Following then are physics, engineering and chemistry.
Publications in mathematics and in earth and space sciences are the least important. If
one compares the European results with those of Japan, one remarks that the EU
records the same order of scale as the US, and thus exhibits sharply more important
results than those of Japan. In term of the growth rate, the discipline which showed
the strongest progress for the period 1980-1995 is engineering, followed by physics,
earth and space sciences, mathematics, life sciences and, to finish, chemistry. The
publications in the field of life sciences exhibited, in value, the strongest increase and
still represent the main discipline. However, the other disciplines showed strong
growth in publications; some have even more than doubled. Nevertheless, in relative
terms, one can notice that the publications in the field of life sciences in Europe
experienced decline.
3.5.6 Scientific Publications (all disciplines) by European Countries
250,000
UK
200,000
S
FIN
P
A
150,000
NL
L
I
IRL
100,000
F
E
EL
D
50,000
DK
B
0
1980
1985
1990
1991
1992
1993
1994
1995
Source: Rasci Data : Science Citation Index, from EU report on S&T indicators, 1997.
Here, the three major dominant countries are again, and respectively, the United
Kingdom, Germany and France. They are trailed by Italy, the Netherlands, Sweden
and Spain. With regard to the effects of the citations among the European countries,
the numbers are practically the same as those exhibited in the analysis for scientific
publications. The growth of the first three countries is rather important and similar for
each, even if France exhibits the highest increase in the rate of growth, as France has
doubled its number of scientific citations over the 15-year period.
3.6 RELATIVE TECHNOLOGICAL PERFORMANCE OF COUNTRIES
3.6.1 The importance of patents in the life sciences
Consistent with the “Information Revolution” that heralded the boom in information
technology, economic value in biotechnology is also knowledge-based. The major
cost associated with innovation is associated with original research and development,
while the costs of production and distribution are relatively low. Patenting of
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biotechnology is the same as for other patents: product information is published along
with the right to exclusivity for a limited amount of time, meaning others are
prohibited from capitalising on the invention or innovative idea. Patent protection is
of particular importance for life science companies, because most of the development
costs are incurred to prove one, that a drug or technology works, and two, that it is
safe to be placed on the market. It has been widely regarded that in the absence of
patent protection, both explicit and tacit knowledge would be readily transferred
through numerous channels due to the dynamism of the life science industry and the
highly-skilled characteristics of the work force. In theory, a competitive company
would be able to copy an original discovery and reproduce it with very little
investment once the safety criteria concerning the discovery had been satisfied.3
A European directive is currently in place identifying the criteria that must be fulfilled
in order to obtain a biotechnology patent within a European Union member state
(OJ213, 30.7.1998, Directive 98/44/E, p.13). However, most companies active in the
life sciences will opt to patent in the US regardless of their origin or market focus.
The reason for this is two-fold:
First, patenting in Europe is currently a complex and expensive matter in which
patents are awarded either on a national basis or through the European Patent Office
(EPO) in Munich. Filing with the EPO means that the inventor does not need to file
with each individual member state, yet the patent must still be translated into several
languages. Currently, a typical European patent (applied for approval in eight
member states) costs approximately 49.900 EUR, of which 25% (12.600 EUR) is
attributed to translation, while the same patent applied for in the US would cost just
10.330 EUR (Europa, 5 July 2000). The proposed Community Patent regulation
intending to slash costs and encourage European patenting may be adopted by the end
of 2002
Secondly, and especially pertinent to pharmaceutical companies, Europe’s health care
market is highly fragmented while the US market remains the largest and most
homogenous. Thus, for companies with global intent, a USPTO patent grant and
FDA approval provides the most growth opportunities.
In conclusion, the most accurate measurement of innovation in the life science
industry is obtained by using the USPTO patent database.
3.6.2 USPTO patent grants
This report includes a USPTO search on biotechnology patents granted between 19872001. The search was performed first using USPTO Class 435 as the definition of
biotechnology; this is the same definition most commonly employed by OECD to
3
However, it is worth mentioning that as biotechnology evolves, new discussions are emerging which
illuminate the complexity actually involved in replicating many biotechnology-related manufacturing
processes. Many of the new drugs, intended to replicate proteins found naturally in the human body,
must be administered through methods other than pills, increasing the difficulty in manufacturing. The
increased complexity of the manufacturing processes increases the risk of a safety hasard occuring in
production and is also a common cause of FDA drug rejection. One result of these manufacturing risks,
has been the rise of the contract industries, some of which specialise in manufacturing, thereby working
to reduce the hasards of vertical integration. Discussed in BWOnline, 25.3.02.
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gather biotechnology statistics. For illustrative purposes, a second search was
performed which defined biotechnology more strictly, in which each patent must
include the terms “sequence” and “DNA” or “sequence” and “nucleic acid” in the
contents of its abstract. The two searches based on the different definitions of
biotechnology allow one to compare the number of USPTO patents granted in the
“extended + core” biotechnologies with the “core-only” definition of biotechnology
whose activities must involve the use of recombinant DNA. As with biotechnology in
its broadest definition, the pharmaceutical industry data was obtained by performing a
search limited to USPTO Class 424 concerning drugs (method applied is that of
Dernis et al., 2001). As mentioned previously, the patent search is intended to be
primarily illustrative, thus the selection of certain countries within the report was done
in a subjective manner and based on limited presuppositions.
Please refer to Appendix B. USPTO patent grants, 1987-90 for the complete data set.
Biotechnology
For the US, the “core” biotech definition reduces the number of patents issued for the
broader biotech definition to approximately 10%. Although the actual percentages
vary widely across countries, the following holds true for all countries employed in
the search: The number of patents granted within the core, recombinant DNA
definition is a small fraction of all patents granted to the given country within Class
435.
The number of biotechnology patents granted to the US between 1987-2001 far
surpassed the number of patents granted to any other country in the search (Table
3.13). However, when comparing the number of biotech patents granted as a
percentage of total patents granted to a country within each three-year time period, a
different picture emerges. Denmark only obtained 306 biotech patents during 19992001, compared to 11.920 biotech patents granted to the US. However, Denmark’s
biotech patents for this period represent over 16% of all patents granted, compared to
just 6,4% in the US. Concerning biotech as a percentage of all patents granted, the
US is second with the Netherlands falling into third with biotech patent production at
5,7%. It is interesting to recall that in a previous section, Germany exhibited a
markedly high number of DBFs. In terms of biotech patent production however, only
2% (700 patents) of all patents granted in Germany were attributed to biotech during
1999-2001. Europe, as a total of the countries selected for this analysis, showed
biotech patent production at 3,3% or 89.740 patents.
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Table 3.13 Biotechnology patents as percent of total patents granted in each country,
1987-1989 and 1999-2001
COUNTRY
BIOTECH PATENTS
1987-1989 1999-2001
United States
Canada
Japan
Europe, selected
Belgium
Denmark
Finland
France
Germany
Italy
Netherlands
Norway
Sweden
Switzerland
United Kingdom
2 394
58
512
467
21
23
15
80
205
19
41
4
37
28
13
15 476
528
1261
2 973
114
306
108
520
700
76
287
38
111
209
650
TOTAL PATENTS
1987-1989 1999-2001
115 265
5 765
55 664
52 523
1170
747
800
9 323
24 688
3 991
3 254
477
2 994
4 495
1861
PERCENT
1987-1989 1999-2001
2,1%
1,0%
0,9%
0,9%
1,8%
3,1%
1,9%
0,9%
0,8%
0,5%
1,3%
0,8%
1,2%
0,6%
0,7%
240 547
12 775
101 792
89 740
2 935
1891
2 306
14 035
34 969
6 104
5 039
904
5 663
5 422
13 682
6,4%
4,1%
1,2%
3,3%
3,9%
16,2%
4,7%
3,7%
2,0%
1,2%
5,7%
4,2%
2,0%
3,9%
4,8%
Source: USPTO patent database.
Graph 3.6 Biotechnology patents as percent of total patents granted in each country,
1987-2001
Source: USPTO patent database.
US
18.0%
16.0%
Japan
14.0%
Europe
Percent
12.0%
10.0%
Belgium
8.0%
Denmark
6.0%
4.0%
France
2.0%
Germany
0.0%
1987-1989
1990-1992
1993-1995
Three-year period
1996-1998
1999-2001
Netherlands
A surprisingly similar picture emerges when the number of biotechnology patents
granted per country is calibrated by population figures. Denmark still exceeds the US
under the population criteria. However, the US produced more than 50 times the
number of biotech patents than Denmark; we cannot ignore the importance of sheer
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volume when comparing the resultant figures but rather interpret the numbers as an
attempt to illustrate the presence of a “biotech culture”. It is still clear that the smaller
European countries, along with Switzerland and the Netherlands, rise to the top as the
top performers within this criteria. Four of the major European economies, UK,
France, Germany and Italy, along with Japan, show the smallest number of biotech
patents per inhabitant, which may be an indication of the ability for relative
specialisation within the smaller economies.
Table 3.14 Biotechnology patents per million inhabitants, 1999-2001
Country
Denmark
United States
Switzerland
Finland
Netherlands
Canada
Sweden
Belgium
United Kingdom
Japan
France
Germany
Norway
Italy
Population
2001
(millions)
5,4
281,8
7,3
5,2
16,0
31,6
8,9
10,3
59,6
126,8
59,6
83,0
4,5
57,7
Biotech
patents,
Period
1999-2001
No. of biotech
patents/million
inhabitants
57
55
29
21
18
17
12
11
11
10
9
8
8
1
306
15 476
209
108
287
528
111
114
650
1261
520
700
38
76
Source: USPTO patent database.
Graph 3.7 Biotechnology patents per million inhabitants, 1999-2001
60
No. of patents
50
40
30
20
10
Fr
an
ce
G
er
m
an
y
N
or
w
ay
Ja
pa
n
D
en
m
U
ar
ni
k
te
d
St
at
es
Sw
it z
er
la
nd
Fi
nl
an
N
d
et
he
rla
nd
s
C
an
ad
a
Sw
ed
en
Be
U
lg
ni
iu
te
m
d
Ki
ng
do
m
0
Source: USPTO patent database.
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Appendix C measures the percent growth in biotechnology patents from one threeyear period to the next. No clear patterns emerge, other than in Italy where the
percent growth has consistently declined over the 15 year period, resulting in an
average growth per period of 47,7%. Most countries exhibited their highest percent
increase in growth over the periods 1993-95 to 1996-98. The increase is logically
correlated to a burst of innovative activity resulting from the mapping of the human
genome during this time frame.
Pharmaceuticals4
In terms of drug-related patent activity, France shows that an impressive 7,2%
(14.035 patents) of all patent activity in 1999-2001 was attributed to pharmaceuticals.
Taking only patent data into account, France is shown to be particularly strong in this
sector relative to the other countries included in this analysis. Not only is the
percentage of drug-related patents invented in France high, but during this same
period only 17% of these patents (all of which were invented within the country) were
assigned to another country for use. The only other country that guarded more
pharmaceutical patents domestically during the same period was Japan, who assigned
a mere 13% of pharma patents abroad (Table 3.16). In absolute terms, the number of
patents did not vary greatly: France, inventing 1009 drugs and assigning 168 of these
patents abroad, compared to Japan inventing 955 and assigning 128.
Denmark, Belgium and Canada experienced the greatest increase in pharmaceutical
patent growth as a percentage of total patents granted over the most recent periods.
Italy and Sweden both experienced a decline of less than one percent, while the UK
remained relatively constant at 4,9% in 1996-98 and 4,8% in 1999-2001. The UK led
the pack with the highest percentage of pharma patents between 1993-95 but was
overtaken the following period by France, and most recently by France, Denmark and
Norway. Again, one must take into consideration that the number of pharma patents
invented both in Denmark and Norway is very small compared to the amount of
patents invented in the UK (107, 49 and 653 respectively). 3,9% of Europe’s patents,
as a total of the selected countries, were pharmaceuticals in 1999-2001, comparable to
4,2% of patents in the US. In absolute numbers however the US invented 10.188
pharmaceuticals, while Europe invented 3.558.
4
Due to the search mechanisms, the US was only included in this analysis for the years 1999-2001.
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Table 3.15 Pharmaceutical patents as percent of total patents granted for each
country, 1987-1989 and 1999-2001
COUNTRY
PHARMA PATENTS
1987-1989 1999-2001
United States
Canada
Japan
Europe, selected
Belgium
Denmark
Finland
France
Germany
Italy
Netherlands
Norway
Sweden
Switzerland
United Kingdom
2 335
60
404
669
16
7
6
191
220
48
34
8
34
79
40
TOTAL PATENTS
1987-1989 1999-2001
10 188
453
955
3 538
126
107
46
1009
903
177
183
49
157
223
653
115 265
5 765
55 664
52 523
1170
747
800
9 323
24 688
3 991
3 254
477
2 994
4 495
1861
240 547
12 775
101 792
89 740
2 935
1891
2 306
14 035
34 969
6 104
5 039
904
5 663
5 422
13 682
PERCENT
1987-1989 1999-2001
2,0%
1,0%
0,7%
1,3%
1,4%
0,9%
0,8%
2,0%
0,9%
1,2%
1,0%
1,7%
1,1%
1,8%
2,1%
4,2%
3,5%
0,9%
3,9%
4,3%
5,7%
2,0%
7,2%
2,6%
2,9%
3,6%
5,4%
2,8%
4,1%
4,8%
Source: USPTO patent database.
Graph 3.8 Pharmaceutical patents as percent of total patents granted for each country,
1987-2001
8.0%
US
7.0%
Canada
6.0%
Japan
Percent
5.0%
4.0%
Belgium
3.0%
Denmark
2.0%
France
1.0%
UK
0.0%
1987-1989
1990-1992
1993-1995
Three-year period
1996-1998
1999-2001
Europe
Source: USPTO patent database.
Table 3.16 and the corresponding Graph 3.9 both aim to provide deeper insight into
each country’s activity within the pharmaceutical industry. Part of the patenting
process is to indicate the “inventor country” in which the patent was actually
developed. The inventor then indicates an “assignee country”, which is not forcibly
the same country as the inventor country. By looking at the percentages of pharma
patents invented in one country and assigned to another, descriptions of a country’s
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pharma activities arises. A reason for this may be that one country may be
particularly strong in pharma R&D and yet have a poor representation of large pharma
companies within the population. Therefore, many of the patents could be assigned to
big pharma located in another country. Likewise, an R&D centre may be located in
one country while the proprietary headquarters are located elsewhere. An example of
this could be Switzerland: A few large pharmaceutical companies are located in
Switzerland, yet on average 60% of pharma patents invented in this country were
assigned to a foreign country between 1987-2001. This may be interpreted as an
indication of Switzerland’s strength in pharmaceutical R&D.
Table 3.16 Pharmaceutical patents: Percent patents invented at home with rights
assigned to a foreign country, 1987-89 and 1999-2001
COUNTRY
INVENTED
1987-1989 1999-2001
United States
Canada
Japan
Europe, selected
Belgium
Denmark
Finland
France
Germany
Italy
Netherlands
Norway
Sweden
Switzerland
United Kingdom
2 335
60
404
683
16
7
6
191
220
48
34
8
34
79
40
10 188
453
955
3 633
126
107
46
1009
903
177
183
49
157
223
653
ASSIGNED ABROAD
1987-1989 1999-2001
*
31
34
163
5
3
0
33
35
12
8
5
18
50
34
1279
145
128
809
72
49
22
168
241
80
88
11
77
134
325
PERCENT
1987-1989 1999-2001
*
52%
8%
24%
31%
43%
0%
17%
16%
25%
24%
63%
53%
63%
85%
13%
32%
13%
22%
57%
46%
48%
17%
27%
45%
48%
22%
49%
60%
50%
Source: USPTO patent database.
*Search not performed
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Graph 3.9 Pharmaceutical patents in selected European countries: Percent patents
invented at home with rights assigned to a foreign country, 1987-2001
90%
Belgium
80%
Denmark
70%
France
Percent
60%
50%
Germany
40%
Italy
30%
Netherlands
20%
Sweden
10%
Switzerland
0%
1987-1989
1990-1992
1993-1995
1996-1998
1999-2001
UK
Three-year period
Source : USPTO patent database.
As shown above, over the 15-year period, the UK and Canada have both consistently
decreased the amount of pharmaceutical patents that were invented domestically and
later assigned to foreign countries. This is significant in that it may indicate the
growing strength of domestically-located pharmaceutical companies. On the other
hand, Italy and the Netherlands have both increased the number of foreign-assigned
pharmaceutical patents. This is likely attributed to cross-border strategic alliances
which have placed R&D centres in these countries.
It should also be noted that both France and Japan, and to a lesser extent Germany,
have carefully guarded the rights to the majority of the pharmaceutical patents
invented in the home country. Japan assigned rights to a foreign country for only
13% of its pharmaceutical inventions in the past three years. France assigned 17% of
its pharmaceutical patents, and Germany assigned 30%. This may be viewed as an
indication of the relative strength of the vertical-integration of the pharmaceutical
industry in these countries; pharmaceutical firms are large and profitable enough to
encompass both upstream R&D activities and downstream production and marketing
and sales.
Graph 3.9 shows the percentage of pharmaceutical patents that were invented in one
of our selected European countries and assigned for use in a non-European country.
As a whole, the European countries have not dramatically changed their patterns of
invention and corresponding assignment, increasing non-European assignment of
pharma patents over the 15-year period by only 2 percentage points, from 22% to
24%. No clear comparisons can be made concerning European activity with regard to
the other countries in the sample.
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Graph 3.10 also shows the foreign pharmaceutical assingments for Cananda, Japan
and the US over the periods 1987-89 and 1999-2001. Canada experienced a 20%
decline in the number of pharma patents that were invented in Canada and then
assigned to a foreign entity. Canada is the only country in this sample to experience a
decline; although the assignment percentages appear to be very high, one must recall
that the numbers referred to are relatively small: 31 and 145 pharma patents in the
respective periods, as Canada does not appear to be particularly strong in
pharmaceutical development according to this criteria. Again referring to the absolute
numbers of pharma patents assigned abroad by Canada, 31 and 145, it is worth noting
that these numbers are comparable to the amount of pharma patents assigned abroad
by Japanese inventors/firms (34 in 1987-89 and 128 in 1999-2001). However, the
percentages for Japan with respect to the number of pharma patents invented in the
country are much lower (8% and 13%). Rights to use of the Japanese invented
patents have largely remained within the country. The US also assigned only 13% of
pharmaceutical patents abroad during the most recent period. A further study would
need to be conducted to understand what differences exist between the knowledge
governance mechanisms in the US and Japan, other than the difference in sheer patent
volume. As discussed, the homogeneity of the US market provides multiple
opportunities for alliances and collaborations at home. It is possible that the Japanese
pharma patents originate almost exclusively with the pharmaceutical companies that
have a need for them, unlike in the US where universities play a large role in the
invention process.
Graph 3.10 Percent of pharmaceutical patents assigned to foreign entities for selected
regions, 1987-1989 and 1999-2001
60%
52%
50%
Percent
40%
32%
1987-1989
30%
1999-2001
22% 24%
20%
13%
13%
8%
10%
0%
Europe,
selected
countries
Canada
Japan
US
Source: USPTO patent database.
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Information
Tech
Life Sciences
Table 3.17 World patent distribution in percentages for key technologies (Life
Sciences and Information Technologies) among a selection of countries, 1993-1995
Technology
Medical imaging techniques
Recombinant vaccines
Recombinant drugs
Monoclonal antibodies
DNA sequencing
Genetically modified organisms (GMOs)
Recombinant proteins
Membrane separation processes.
Low-energy components
Flat screens
Broadband communication
Intelligent networks’ technologies
Optical fibers
EU *CH
24,8 0,9
30,0 0,4
21,0 1,0
30,4 1,7
25,6 0,6
41,3 0,3
25,8 0,9
36,9 1,6
16,5 0,0
21,7 0,7
48,7 0,9
35,7 0,3
37,4 2,7
JP
8,9
3,2
6,1
9,3
4,2
8,5
5,8
9,6
28,0
51,3
10,4
5,3
17,3
US Others World
64,5
0,9 100,0
55,4
11,1 100,0
65,2
6,7 100,0
51,8
6,7 100,0
62,4
7,2 100,0
42,5
7,4 100,0
60,4
7,1 100,0
46,1
5,7 100,0
51,7
3,8 100,0
23,5
2,9 100,0
35,4
4,6 100,0
56,8
1,9 100,0
39,8
2,9 100,0
Source: OST Data from the European Patent Office. *CH indicating Switzerland.
The above table (3.17) tends to show how the US is dominating what is identified as
the key technologies. However, the contrasted aspects between life sciences and
information technologies is very significant. Regarding the genetic modification of
plants, the EU is very close to the US in that it occupies the second ranked place in the
world for all of the listed disciplines combined. One can also note that on average,
the European positioning is quite similar in relative terms and that the dominance of
the US context is more or less affected by the role played by Japan. If the latter
appears effective in information technologies, this is not the case for life science
technology. Resultingly, the US occupies a relatively stronger postion.
4. INDUSTRIAL ORGANISATION
4.1 MAIN ACTORS
4.1.1 Large Diversified Firms (LDFs)
The life science company
As it was previously pointed out, the transition from the so-called random screening
period to the one characterized by the adoption of new biotechnology techniques was
essentially determined by a radical change in the knowledge base of firms in a number
of industrial sectors. The sectors that could benefit from biotechnology were the
pharmaceutical, agro-chemical, food, environment, etc.
Early investment
concentrated on pharmaceuticals due to a combination of profitability and ease of
application of the technology. The potential of the new biotechnology was
considerable also in other sectors, although greater hurdles had to be overcome there
in order to make biotechnology operational. During the 1990s firms active in
chemicals and pharmaceuticals realised that important synergisms could be obtained
by using a common knowledge base in order to supply the different and sometimes
highly heterogeneous markets of the different sectors mentioned above. In other
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words, companies started focusing on the economies of variety that could be obtained
by exploiting a common knowledge base (Lemarie, Julien, 2002). This concept of the
firm, defined essentially by its knowledge base rather than by its outputs, was called
the life science company.
It has to be observed that even in the random screening period knowledge based
synergisms occurred, and that they were based on the knowledge of chemistry, mostly
organic chemistry. The switch to biotechnology as the core of the new knowledge
base of firms was on the one hand responsible for the increased accuracy of the
screening process and, on the other hand, for the redefinition of the boundaries
between firms and sectors. For example, in the random screening period the types of
knowledge required to produce pharmaceuticals and pesticides were similar, both
based on organic chemistry, but very different from the type of knowledge required to
produce seeds. The transition to biotechnology increased the similarity between the
knowledge required to produce on the one hand pharmaceuticals and pesticides and,
on the other hand, seeds. This change helped to redefine the boundaries of firms and
sectors by bringing seeds within the pursuit of the life science company. It is to be
noticed that the definition of the life science company corresponds also to the growing
emphasis placed in general on knowledge as opposed to physical capital and to
material goods as the basis of firms' and economies' performance. Thus an important
trend in firm strategy in the 1990s was the evolution from their previous structure
towards the life science company.
Table 4.1 The largest pharmaceutical companies: US and European Union
United States
Merck Pfizer
& co
European Union
BMS
Pharmacia Corp
Eli
Lilly
Bayer
Glaxo
Astra Aventis Sanofi
Zeneca
CA (1)
47,7
32,26
19,42
13,84
11,54
30,27
(€)
29,5
16,5
R&D
(2)
2,46
4,8
2,26
2,26
2,23
2,5 (€)
3,68
2,69
78100
NA
NA
59000
Employ
ees
41.134 116900 100000 54000
17,67
(€)
6,5 (€)
2,98 (€) 1,03 (€)
NA
30000
(1)&(2) Million US$
For all its apparent attractiveness, the concept of the life science company seems to
have been already superseded by new organisational forms. At the end of the 1990s
several large firms, most notable amongst them those that had initiated the transition
towards the life science company (e.g., Novartis), backtracked and separated their
agrochemical from their pharmaceutical subsidiaries. This type of behaviour is now
common as to be considered the norm amongst large firms in these sectors. The
reasons for this extremely rapid change of strategy have not yet been analysed in great
detail, even if some potential determinants seem to be clear. First, although the
knowledge base required to supply the pharmaceutical, agrochemical, etc., markets
could be considered similar, the markets in which these products could be sold were
very strongly heterogeneous. For example, the regulations to be complied with, and
especially their geographical and inter-temporal distribution, differed considerably
amongst the sectors. This seemed to be of limited relevance during the life science
company (brief) period, but acquired a renewed importance recently. Thus, the
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barriers to the acceptance of the new biotechnology are very different in the
pharmaceuticals and in the agrochemicals and food sector. Genetic engineering is
welcome when it promises to cure previously incurable diseases but it is strongly
opposed as a source of food of new plant varieties including genetically modified
organisms (GMOs). We could say that the heterogeneity of the selection environment
for the outputs of the life science company increased recently to such an extent as to
deny the potential benefits due to the exploitation of a common knowledge base. In
general we could say that whether the firm is defined predominantly on the basis of its
outputs or of the knowledge it uses depends on the relative heterogeneity of the
outputs produced and of the knowledge used for their production. This of course
implies that the dominant criterion for the definition of the firm may shift in the
course of time depending on the evolution of markets and of knowledge.
The result of abandoning the life science company strategy has so far been the
separation of pharmaceutical from agrochemical activities. Pharmaceuticals continue
to be highly profitable and to absorb the majority of the investment. Agrochemicals
face much more substantial barriers to the acceptance of their products embodying the
new biotechnology. Whether these barriers are temporary or permanent will certainly
affect the future development of firm strategy in this sector. Clearly, the presence of
these barriers is very specific to the life science industries. For example, similar
barriers do not exist in electronics or in IT. This shows how important are the
selection environment and its variations in the course of time as determinants of
sectoral and firm boundaries and of firm strategy. A further factor affecting the
development of the biotechnology based firms is the maturation of their knowledge
base. The extent to which the commonality of the knowledge base of firms can be a
determinant of their behaviour and performance is likely to be greater in the early
phases of development of a new technology. In these phases the knowledge base of
the new technology is not yet highly differentiated and firms are mainly worried about
internalising it. When the technology matures the knowledge base is likely to become
more specialised by application, and the synergisms based on knowledge are likely to
be outweighed by the need for specialisation. The recent behaviour of both
pharmaceutical and agrochemical firms cold also be influenced by trends of this type,
in addition to the growing heterogeneity of their selection environments.
4.1.2 Dedicated Biotechnology Firms (DBFs)
“Dedicated biotechnology firms (DBFs) are primarily university spin-offs that mobilize scientific and
technological knowledge and transform it into potentially commercially useful techniques and
products. These firms are usually formed through collaboration between scientists and professional
managers, backed by venture capital. Their specific skills reside in the knowledge of new techniques
and in research capabilities” (EC, No.7-2002, p.1).
Life sciences encompass a wide range of scientific disciplines; biotechnology is one
part of the life science industry, but it too is not limited to one industrial sector, but
rather encompasses a set of technologies and activities ranging from agriculture to
health care. Most biotech firms begin as small, research-intensive companies, or
DBFs. It is important to regard DBF activity for the following reasons:

DBFs are efficient organisational solutions for navigating an increasingly
complex space of scientific discovery and technological innovation in which
no single firm can lead in all areas;
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

DBFs intermediate in knowledge transfer from research-oriented universities
to private firms with downstream capabilities;
DBFs “promote and are crucial agents in markets for technology and division
of innovative labor, in the context of a system in which control rights can be
allocated to maximise innovative output in conditions of incomplete learning”5
(EC, No.7-2002).
Table 4.2 Largest US biotech companies, 2001
CA (1)
R&D (2)
Employees
Amgen
Genentech
3510
2212
865
526,2
7000
5000
Genzyme
1220
244
5200
Chiron
1141
344
3736
Biogen
immunex
1043
959
314
204,6
2000
1550
(1)&(2) Million US$
Source: Annual reports 2001.
Table 4.3 Largest biotech companies in the European Union, 2001
Qiagen
CA (1)
R&D(2)
Employee
s
294,39
29,88
1557
Shire Pharma ceuticals
979,43
18,97
NA
Innogenetics
Powder
Ject
59
176,85
23,8
49,68
580
1000
Genset
29
41,7
487
Celltech
216,40
67,04
NA
(1) & (2) Million EUR
Source: Annual reports 2001.
Two different pictures emerge from an immediate comparison between the largest
biotechnology companies in the US and EU (Tables 4.2 & 4.3). Large differences
exist between the American and European companies. Turnovers exhibited by US
firms are sharply higher than those of the European firms, more than 10 times on
average. With regard to R&D spending, the same remark can be addressed, even if
this can be thought of as a consequence of the previous point.
High differences also appear when the number of employees is considered. These
data put into light that the largest European biotechnology firms are sharply less
important than the largest American ones. Even if the range of differences is less
significant than for turnovers, it impacts quite considerably private research
capabilities that are thus weaker in Europe.
This has important consequences in terms of industrial organisation for the life
science industries. The situation faced by the US context is one of consolidation of
those industries, implying a significant process of mergers and acquisitions whereas
the European situation is one of emerging capabilities mainly through the setting up of
academic start-ups. Therefore, both contexts are sharply constrasted.
5
Arora A., Gambardella A., Pammolli F., Riccaboni M., 2001, The Nature and the Extent of the
Market for Technology in Biopharmaceuticals, NBER Summer Institute, Cambridge, MA; and Lerner
J. and Merges R., 1998, The Control of Technology Alliances: An Empirical Analysis of the
Biotechnology Industry, Journal of Industrial Economics, vol.46, pp.125-156, in EC, No.7-2002, p.28.
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A common argument for the relatively slow birth of enterprise in Europe has been the
social and legal frameworks in place across European countries which:
“tend to discourage risk-taking and business creation. Obstacles include bankruptcy
rules that may preclude further ventures, regulatory uncertainty, lack of liquidity in
the risk capital markets as well as more mundane problems such as stigmatisation of
failed entrepreneurs and barriers to the reintegration of entrepreneurial scientists into
academic careers” (EC, 9 April 2001, p.10).
Consequently, by analyzing the social and legal environment fostering the
development of DBFs in the Scandinavian countries certain insights may arise which
will allow the development of more general policy and practices to be applied at the
European level.
As discussed, the European country rankings for the presence of DBFs changes
dramatically when measured as DBFs per thousand inhabitants (refer back to Graph
3.3). In the US however, the state rankings are surpisingly similar when calibrated by
population figures. California, the leader in terms of the number of life science
companies present (332) falls to sixth place with population as a consideration (Graph
4.4). Massachusetts, previously second with 152 firms rises to first place with regard
to population; Maryland (74) rises to second; and North Carolina (106) and New
Jersey (98) remain at third and fourth places respectively. Rather than being an
indication of specialisation as may be the case for the small nothern European
countries, it is more likely that these states represent the presence of true “centres of
excellence” with developed mechanisms for knowledge transfer between multiple
actors, namely public research organisations, academia, and private enterprises.
0,030
0,025
0,020
0,015
0,010
0,005
so
ta
a
in
ne
M
va
ni
ra
do
ol
o
nn
sy
l
Pe
to
n
C
hi
ng
go
n
W
as
O
re
ni
a
n
al
ifo
r
C
co
ns
i
ey
rs
Je
ew
W
is
a
ol
in
Ca
r
or
th
N
N
yla
M
ar
sa
ch
u
M
as
nd
0,000
se
t ts
Life science companies per 1000
Graph 4.1 US life science companies per thousand inhabitants for states with the
highest concentration, 1999
Source: Dibner M., Biotechnology Guide USA, 1999.
A direct comparison between the top-ranking European countries and the US states
shows that Sweden, with 2,6 million more inhabitants than the state of Massachusetts,
is similar to Massachusetts with regard to the number of DFBs per 1000 inhabitants at
0,0260 and 0,0239 respectively (Table 4.4). Germany and the state of California
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represent the greatest number of life science firms for Europe and the US. There is a
very large difference between the two in terms of both population and DBFs per 1000:
Germany exceeds California in poluation by 52 million inhabitants, yet has fewer
DBFs per 1000 (0,0059 v. 0,0098).
Table 4.4 Comparison between European countries and US states for greatest
presence of life science companies
No. of DBFs
Population (Mil.)
DBF per 1000
No. of DBFs
Population (Mil.)
DBF per 1000
Europe
US
Sweden
Massachusetts
235
152
8,9
6,3
0,0260
0,0239
Germany
California
504
332
85,9
33,9
0,0059
0,0098
4.1.3 Public Research Institutes (PRIs)
Even if highlighting the importance of science-based industries is not new in
economics (Pavitt, 1984), there is an obvious shift in the analysis of the importance of
science in the working of economic systems for the last two decades. The so-called
transition towards a knowledge-based economy is the final stage of this evolution that
results in a significant increase in scientific influence on technology-based industries.
Among the scientific disciplines, the case of the life sciences is certainly one of the
most emblematic for such a qualitative change in the importance of scientific
resources for industrial applications. With the info-com industries, life sciences
represent one of the thematic areas which has been the most influenced by
development in basic research and scientific resources.
There are many reasons for the increasing importance of basic research in those
sectors. First, life sciences are facing quite a recent revolution as we already noted
through the blast of opportunities associated with the so-called third generation of
biotechnology. Second, scientific progress evolves quickly and creates an insecure
environment for firms in that the innovation process becomes very risky as
investments can rapidly become obsolete, with regard to radical change in
technologies. Third, downstream activities in production processes related to life
sciences (be it for discovering new medicine products or new GMOs) imply high sunk
costs in terms of development and clinical testing, legal agreements, and distribution
networks. The life cycle of producing a new product in those areas is still very long
and the timing of scientific progress conflicts with the importance of irreversible
investments associated to related economic activities. Fourth, life sciences have been
confronting a real breakthrough since the 1990s that questions the ability of large
diversified firms to identify suited strategies in order to survive. In that respect, the
importance of DBFs as integrators of new knowledge that we already mentioned is
highly important to secure their innovative behaviours.
Consequently, the
hybridization between public research institutions and large diversified companies
through the mediation of small academic-based companies has became very
significant. Fifth, this same scientific and technological breakthrough importantly
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modifies the nature (the aim and the modalities) of interaction between public
research and large companies active in life sciences. Whereas the pre-existing
situation was one where large companies were using public research as a main
provider of new compounds to be screened and as a punctual problem-solving
resource through standard contractual agreements, the renewed technological context
obliges large companies to be much more aware of the deep consequences that
opportunities from those techniques explored by small companies can have on their
own research organisation and, consequently on their economic viability. The new
economic context results in the need to consider public research institutions as an
actual economic actor that influence significantly knowledge dynamics within the life
science industries. Consequently, this emphasizes the importance of connections
between those institutions and traditional economic actors, be it LDFs or DBFs in this
case.
Collaborations between scientific institutions and industry can take on several forms.
In fact, science-industry relationships can cover at least three major types of
connections. First of all, contractual agreements are still a major type of relationship
that links public researchers to private ones. The most significant inflection here lies
in the fact that private scientists are now really competing with public ones in that
they both benefit from research contexts (money and physical equipment especially)
that, by and large, are as favourable as those of the public scientists. As large
companies progressively considered the need to be aware of the technological
breakthrough, they invested considerably in in-house research in order to absorb these
new capabilities and become attractive also to the public research scientists. As a
result, private research is quite impressive and the increase in joint-results (not only
patents but also publications and citations) has been quite enormous in the last decade.
Indeed, contractual agreements between public and private science have evolved not
only in quantitative numbers but also in qualitative contents, as private research in
large companies became much more accurate within the last decade.
Interactions among scientific and industrial actors also include mobility of individual
researchers who leave (temporarily or definitively) the academic environment to take
positions in firms. Of course, it is the case of temporary individual mobility which
strengthens the interactions between public and private research because individuals
are alternatively facing both types of research environments and are more attuned to
identifying the opportunity which can explore at best joint interests for both.
Associated with that debate on the importance of scientists’ mobility is the role played
by doctoral and post-doctoral students (Quéré, Ravix, 1997). The latter appear as a
crucial population to influence and structure the pursuit of joint opportunities between
public and private research. They really perform in bridging both types of
environments and promoting the diffusion of knowledge in both directions
(emergence of basic research knowledge from industrial problems vs. emergence of
private opportunities from basic research resources).
Finally, the third type of interaction lies in the creation of new companies from
academic resources. There has been a significant increase in the number of
companies created by scientists within the last decades. This is a general trend for
many European and non-European countries. Of course, that phenomenon differs
from one discipline to the other, and the life science industry, again, appears among
the few disciplines that are on the top of the list for exploring new entrepreneurial
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potentials from scientific opportunities. There is interesting debate around the
characteristics of researchers who wish to exploit their knowledge and want to create
a company, an academic start-up. High-ranked researchers are not neccessarily the
best candidates. To succeed in academic entrepreneurship requires complementary
skills to scientific ones (social and marketing interactions, finance and economic
capabilities, etc.) (Quéré, Ravix, 1997). Therefore, the individual profiles of the
academic entrepreneur is not linearly correlated to his (her) scientific capabilities.
The way in which academic entrepreneurs are inserted in industrial networks,
including SMEs’ incumbents as well as large diversified companies, directly impacts
its economic viability.
This variety of collaborations has important consequences on knowledge dynamics in
the life science industry. First, modern biotechnology requires change in the
organisation of R&D in large companies. Consequently, the availability of academic
scientists remains an important cause of success in the adaptive behaviours of large
diversified firms. Darby and Zucker (1996) show how the local availability of good
scientists increases the speed of adaptability of large companies. In other words, the
importance of localised knowledge in facing the adaptation of large companies to the
third generation of biotechnology is obvious and they highlight the influence of
physical proximity for speeding the knowledge dynamics and diffusion as well. More,
Darby and Zucker (1998) also stressed differences in institutional arrangements, laws
and regulation mechanisms as explanatory variables for the density of connections
between public and private science. They conclude to a higher local effect in the case
of the US, as compared to the Japanese context. What appears extremely helpful from
those works is the need to identify public researchers (and public research institutions)
as key actors in the process of knowledge generation that conduct the innovative
patterns for the life science industry. Indeed, what is needed is a better understanding
of the mechanisms that govern localised innovation systems (Antonelli, Quéré, 2002).
That observation leads to a sort of paradoxical argument: whereas the importance of
star scientists and consequently of local contexts through the existence of specific
localised interactive learning is obvious in the case of the life science industry, star
scientists are nevertheless concentrating in a few prestigious universities which render
the evolution of science-industry relationships very exclusive for a few spatial areas.
That concentration phenomenon has previously been pointed out for both the US and
the European contexts. However, what is extremely curious and influential for
policy-making is that paradoxical aspect of the importance of localised knowledge
coupled with the concentration of key academic resources in a few locations. From
that observation, one can derive two implications: either the life science industry will
increase its geographical concentration by an increase in the location of companies in
the surroundings of star scientists because academic resources will remain one of the
main drivers of the knowledge dynamics, or the location of (large) companies can
continue to be spread geographically but this will imply some particular knowledge
transmitters and/or specific knowledge channels that will compensate for the
concentration of academics on a few prestigious universities or research institutions.
By and large, the current role played by DBFs can be more or less discussed in the
line of that remark.
The importance of public research institutions on the dynamics of the life science
industry induces significant differences in the organisation of that industry, as
compared to other sectoral patterns. One cannot understand firms’ innovative
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behaviours without considering the location of key scientists in those related activities
as well as the interaction mechanisms that firms can establish with them. Public
research institutions have became central actors actually embedded in the innovative
dynamics for those areas.
4.2 INNOVATION NETWORKS AND STRATEGIC ALLIANCES
4.2.1 Opportunities for firms within the life science industry
As presented in its historical context (for the full discussion, please see section 2.2),
the strategic needs of the pharmaceutical and biotechnology industries foster a codependency, generally with the big pharma companies occupying the dominant
position. Forms of collaborations between the two may include but are not limited to:
joint research activities, licensing of technology and product patents, co-marketing
and co-promotion, and mergers and acquisitions.
Characteristics of large pharma
The large pharmaceutical companies have traditionally been vertically integrated,
channelling millions of dollars into R&D in order to identify a few prospective drugs
that then must survive clinical development and trials. Those drugs that do gain
approval are marketed and sold through extremely efficient channels that include
large forces of sales representatives present in local markets. Very few prospective
drugs ever become the “blockbusters” that will drive top line sales growth, making the
drug development process extremely risky. Yet, the return on investment for a
successful drug is high enough to sustain several enormous global players.
Consequently, it is important for the large pharmaceutical companies to ensure a
plentiful product pipeline in order to ensure the continuous development of
marketable drugs, as well as compensation for patent expiry.
The pharmaceutical drug industry in 2000 was characterised by a number of large
consolidations, primarily undertaken in order to increase R&D capabilities, increase
efficiency, and cut costs through the realisation of synergies so that short-term savings
can be funnelled back into the R&D budgets (E&Y, 2001, p.2). Apart from
organisational cultural clashes (of particular importance in cross-border mergers), one
large risk associated with consolodition is that of a heavy “corporate” culture that
quells innovation. One way large pharmaceutical companies like Pfizer and
GlaxoSmithKline have dealt with this issue is to spin-off independent research entities
that essentially became fully-owned biotech companies. The independent entities are
managed as DBFs, yet knowledge is transferred directly towards product development
within the large pharma company.
Apart from the outright acquisition of DBFs and their proprietary knowledge, another
way for pharmaceutical companies to fill their product pipelines is to strategically ally
with a biotechnology firm. The “core” biotech firms are positioned up-stream in the
value chain, meaning they are most often much smaller and much more specialised
than the pharma companies, and are primarily engaged in the early phases of research
and discovery. With the completion of the sequencing of the human genome, an
enormous amount of data was made available to manage, process and exploit;
consequently, there has been an explosion in the number of firms in niche areas
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related to proteomics activities (moving beyond gene identification to protein
identification) and the “platform technologies” (tools enabling research and
discovery). (See the full discussion in section 2.3.2). In an interview Ernst & Young
(2001) conducted for their annual life sciences report, industry expert and former
CEO of SmithKline Beecham Jan Leschly identified the four main drivers for today’s
successful drug development as:




New technologies such as genomics, proteomics, high throughput screening,
chiral and combinatorial chemistry and electronic data transfer;
Molecular diagnostics, which roughly equates to “personalized”
drugs/vaccines;
Bioinformatics technology that translates the enormous data available into
useful information; and
The growing impact of consumers on healthcare systems (p.3).
Strategic options for the biotechnology firms
Biotech companies must employ strategic decision-making in order to survive in the
globally competitive environment of the life sciences, where each firm is in a race for
discovery or innovation. The up-stream biotech firms can roughly be grouped into
two categories: “discovery-making” or “technology-making”. Both groups rely
heavily on companies further down the value chain as customers; these companies
being of course the pharma giants. Many of these biotech firms identify as an endgoal their own acquisition by a big pharma company; acquisition provides cash in
exchange for innovation and minimizes the biotech firms exposure to the risk
associated with struggling to survive as an independent entity.
As the biotech industry matures, one also witnesses the emergence of related “contract
industries”; these “extended” biotech companies provide the core biotech firms with
an option for growth and development beyond large pharma. The goal of contract
industries is to provide horizontal services, e.g., clinical testing, manufacturing,
marketing and distribution, that will allow a core biotech firm to move further down
the value chain without creating fixed costs (E&Y, 2001, p.3).
Another strategic option for the biotech firm is to attempt to achieve critical mass in
order to attract the attention of potential investors and become a vertically-integrated
firm. This strategic approach continues to be difficult to achieve and uncommon.
However, with the maturation of the industry, many biotech firms have managed to
grow considerably in size. Since 1995, American biotech companies with market
capitalisations greater than 1 billion EUR have increased in number from 7 companies
to 50, while Europe experienced an increase from no firms to the presence of 10 in
2000 (E&Y, 2001, p.48).
In sum, biotech firms in 2002 face a much larger number of strategic options than
anytime in the past decade. Currently, the trend is for biotech firms to ally themselves
less frequently with the big pharma, in order to enter alternatively into strategic
alliances with biotech firms involved in complementary activities. In 1998, 86% of
biotech alliances were with pharma companies, while in 2000 this number decreased
to 64% (E&Y, 2001, p.48).
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4.2.2 Alliances
Strategic technological alliances
Databases exist which track the development of these biotechnology-based
collaborations. Strategic research partnerships may be contract-based or informal in
nature. The Cooperative Agreements and Technology Indicators database (CATI) is
compiled by the Maastricht Economic Research Institute on Innovation and
Technology (MERIT) and covers international collaborations announced in
newspapers and journals. While the CATI data is useful in capturing the essence of
trends in technological transfer activity, extreme caution must be exercised with
regard to the data. As most biotech-related newspapers and journals are published in
English, CATI’s bias is toward American companies and undertakings, with 80% of
all CATI technology alliances involving the US (OECD, 3-4 May 2001, p.23).
Furthermore, many biotech-biotech alliances involve small firms whose size may not
have attracted enough attention to merit publication. The CATI data contrasts sharply
with the figures obtained by Ernst & Young on strategic alliances. E&Y data shows a
54% increase in the number of strategic biotech alliances in Europe from 1996 to
2000, while CATI data demonstrates a slight decrease in the number of alliances for
the same period.
Table 4.5 European strategic alliances: Ernst & Young v. CATI, 1996-2000
Year
1996
1997
1998
1999
2000
Strategic alliances
(E&Y)
Total biotech alliances
(CATI)
123
179
160
261
403
102
71
79
70
87
Source: E&Y, 2001; CATI database maintained by MERIT and made available by NSF
According to CATI data, in 2000, 574 new alliances were formed worldwide in the
major technological sectors: information technology (IT), biotechnology, advanced
materials, aerospace and defense, automotive, and (nonbiotech) chemicals (NSF,
2002). In total, 6477 technology alliances were formed during the 1990s, compared
to 3826 between 1980-89, a growth in the number of technological alliances of 69%
from one decade to the next. Between 1990-2000, the US participated in 80% of
these alliances, while Europe and Japan were much more active at the interregional
level (Table 4.6).
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Table 4.6 Share of international strategic technology alliances: 1980-89 and 19902000
Percent
Interregional Intraregional Total alliances
1980–89
United States
62.9
37.1
Europe
Japan
64.8
78.3
35.2
21.7
2,445
1,904
1,073
1990–2000
United States
Europe
48.8
76.4
Japan
88.6
51.2
23.6
5,187
2,784
910
Source: NSF, 2002.
With regard to the specific technologies, the number of international strategic
alliances in biotechnology obtained its highest level yet in 2000, with 35% of all
technological alliances. This increasing partnership activity may again demonstrate a
global maturation of the biotech sector. It is interesting to note that the number of IT
alliances peaked in 1995, and 2000 represents the first time that biotech alliances
outnumber the number of alliances in the IT sector (See Table 4.7 and Graph 4.2).
Table 4.7 International strategic technology alliances, by technology shares
Percent
Year Information technology Biotechnology All others
11,4
1990
50,1
38,4
10,8
1991
54,6
34,7
19,9
1992
46,7
33,3
24,1
1993
39,7
36,3
27,0
1994
41,4
31,6
20,2
1995
41,6
38,2
24,8
1996
41,8
33,4
28,6
1997
36,0
35,4
22,2
1998
41,8
36,0
32,6
1999
38,4
29,0
34,7
2000
32,1
33,3
Source: NSF, 2002, Figure 4-24.
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Graph 4.2 International strategic technology alliances, 1990-2000
60,0
Percent
50,0
40,0
Information Technology
30,0
Biotechnology
20,0
All other technologies
10,0
19
90
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
0,0
Source: NSF, 2002, from text table 4-12.
A close examination of the CATI data shows that technological strategic alliances
tend to be cyclical in nature for both the US and Europe. US and Europe peaked in
the number of such alliances in 1995, most likely as a result of activity in the IT sector
(Appendix D).
Strategic biotechnology alliances
Please refer to Appendix D. International strategic biotechnology alliances, 1980-98
for the following discussion.
US biotech alliances peaked at 162 in 1997, dropped sharply in 1998, and then
reached 170 and 168 alliances in 1999 and 2000 respectively (Graph 4.3). Europe, on
the other hand, peaked at 102 biotech alliances in 1996, and the alliance activity
remained somewhat consisent throughout the remainder of the decade, increasing
again in 2000, but not reaching the peak in alliances experienced four years prior.
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Graph 4.3 US and European biotechnology alliances, 1980-98
180
Total biotech alliances US
160
Total biotech alliances Europe
Number of alliances
140
120
US-Europe biotech alliances
100
80
60
40
20
19
80
19
81
19
82
19
83
19
84
19
85
19
86
19
87
19
88
19
89
19
90
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
0
Source : NSF, 2002, from text table 4-12.
It is also worth noting that the vast majority of European strategic alliances in the
biotech sector occur between a European firm and an American one (Graph 4.4).
During the past decade, the peak in intra-European alliances occured in 1994 and
1995 when the number of intra-European alliances approached 30 and 37%,
respectively, of the number of alliances that took place between US and European
firms. One reason for this may be that the US firms were in more advanced stages of
development during the 1990s, and have been thus actively seeking out
complementary partners, many of which were in Europe. However, as a whole the
majority of European firms may have been in growth phases in which strategic
alliances or partnerships would have been premature. The beginning of this decade
heralds a new growth period for European biotech, in which the firms have entered
into expansion stages of development that make them much more attractive as
strategic collaboration partners. Furthermore, the advancement of new platform
technologies opens up new niches for which biotech firms enter with the idea of
becoming a supplier for another biotech firm engaged in complementary activities.
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Graph 4.4 European biotechnology alliances, 1980-98
120
Europe-US biotech
Europe-Japan biotech
100
Number of alliances
Europe-other biotech
Intra-European biotech
80
Total European biotech alliances
60
40
20
19
98
19
97
19
96
19
95
19
94
19
93
19
92
19
91
19
90
19
89
19
88
19
87
19
86
19
85
19
84
19
83
19
82
19
81
19
80
0
Source : NSF, 2002, from text table 4-12.
4.3 VENTURE CAPITAL
Venture capital plays two critical roles in the support and development of
biotechnological innovation. First, venture capitalists provide financing, primarily to
small and promising companies that may not have been able to obtain funding
elsewhere because of the high-risk nature of entrepreneurial activity. Second, venture
capital firms provide managerial advice that is essential to the development of a
young firm. The VC firms often employ industry experts such as doctorates in the life
science disciplines to participate in management teams, providing well-informed
directives on both research and commercialisation.
The amount of venture captital that was channelled into the development of European
biotechnology in 2000 was in excess of 1 billion EUR, a 58% increase in the amount
of VC money applied toward biotech in 1999. The average investment deal size also
increased from 1,1 million EUR in 1999 to 1,4 million EUR in 2000 (compared to the
average deal size of 1,8 million EUR across all technologies in 2000). There are
essentially three reasons behind this growth:



Biotech investment as an alternative to the devaluation of companies in the
high-tech sector (namely, internet technology);
the improved performance of biotech share price and the public capital
market’s positive response to biotech IPOs;
and the increase of corporate venture activities by the large pharmaceutical
companies themselves.
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Graph 4.5 VC in Europe: biotechnology, 1987-2001
1200
1017
1000
Million EUR
844
800
644
600
346
400
200
57
70
182
118
145
95
88
62
58
250
73
19
87
19
88
19
89
19
90
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
20
01
0
Source: EVCA.
Graph 4.6 VC in US: biotechnology, 1987-2000
3,000.0
2,458.6
2,000.0
1,500.0
1,102.7
515.8
675.6
1,229.5
1,031.8
20
00
19
99
19
98
19
97
454.9
19
96
500.0
19
93
278.9
19
92
19
91
309.6
19
90
19
87
0.0
395.5
19
94
67.0
19
89
500.0
586.4
355.5
19
95
1,000.0
19
88
Million Dollars
2,500.0
Source: Venture Economics in NSF, 2002.
The amount of VC money invested in European biotechnology in 2000 was 9% of the
total amount of 11,5 billion EUR invested in all technologies while in the US,
biotechnology consumed approximately 3% of the 98 billion EUR of the total
technology-oriented investment (Table 4.8). In both Europe and the US, biotech was
ranked 5th in importance among the major categories. However in Europe, software
and related services placed first in importance accounting for 37% of the total, while
communications drew 17% of the total in the US making it the most important sector.
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Table 4.8 Comparison of Europe and USA venture capital invested in technologies,
2000
EUROPE
European Sector Mil. EUR Percent of VC American Sector
US
Mil. EUR
Percent of VC
$1=1.082 EUR
Software & Services
Communications
Internet technology
Semiconductors &
other electronics
Biotechnology
Computer Hardware
Medical
Total
4 219
2 175
1 843
1 356
1 017
441
413
11 464
37%Software & Services
19%Communications
16%Internet specific
Semiconductors &
12%other electronics
9%Biotechnology
4%Computer Hardware
4%Medical & Health
0%Consumer-related
0%Industrial & Energy
Other products &
0%services
100%
14 080
16 026
44 257
14%
17%
6%
6 127
2 661
2 263
3 601
2 105
890
6%
3%
2%
4%
2%
1%
5 990
97 999
6%
100%
Exchange rate based on ECB annual average for 2000.
Source: PwC, 2000 and NSF, 2002.
Measuring the percentages of VC money in its various stages of investment gives a
fairly good indication of the stage of development for the technology as a whole.
Investment can be roughly divided into the early and later stages of investment, and
then further separated by the intended use of the VC funding. Early stage investments
occur in a sequential manner and include: seed, start-up and first-stage financing.
Most venture capital investments are targeted at the more secure later stage
investments6: expansion financing, acquistion financing and management/leveraged
buy-outs.
The table below (4.9) indicates 10% of all early stage VC money in Europe was
invested in biotechnology. Software and services was the dominant consumer of early
stage financing at 39%, followed by internet technology and communications at 25%
and 17% respectively. The data given for the US includes seed capital only, money
that is usually used by the entrepreneur to prove a concept, thus ommitting financing
used in the start-up and first-stages. Only 1%, or approximately 12 million EUR was
used for seed money in biotechnology in 2000, whereas 44%, or 561 million EUR in
seed money was used towards internet specific technology.
6
Since 1982, 59 to 79% of venture capital disbursements were targeted at these later stage investments
(NSF, 2002).
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Table 4.9 Early stage venture capital in European technologies compared to US seed
financing, 2000
EUROPE
European Sector
Mil. EUR
Software & Services
Communications
Internet technology
256
468
57
Medical/Instruments/Devices
114
4 560
% of VC
as Seed
$1=1.082
Money
EUR
146
11%
363
26%
607
44%
Mil. EUR
% of Early
Stage VC
1 769
39%Software & Services
755
17%Communications
1 141
25%Internet specific
Semiconductors & other
electronics
Biotechnology
Computer Hardware
Total
US
American Sector
Semiconductors &
5%other electronics
10%Biotechnology
1%Computer Hardware
73
13
30
5%
1%
2%
3%Medical & Health
Consumer-related
Industrial & Energy
41
11
NA
3%
1%
NA
Other products &
services
106
7%
1 388
100%
100%
Exchange rate based on ECB annual average for 2000.
Source: PwC, 2000 and NSF, 2002.
The 468 million EUR directed at early stage financing of biotechnology comprised
46% of all VC money directed at the biotech sector in 2000. The European
technological sectors whose predominant amount of VC investment came in at the
early stages were: Internet technology at 62%, biotechnology, and computer software
and computer services both at 42%, an indication of the strong growth potential in
these sectors (E&Y, 2001, p.8).
The following table (4.10) compares the amount of money in the early and expansion
stages for Europe and the US for all technologies combined. In terms of proportion,
the amount of money in the early and later stages in Europe is approximately equal
(4.561 v. 4.612 million EUR), while the US has almost three times as much VC
money directed at the expansion stages. Venture capital investment clearly occupies a
much larger role in the US business culture, as VC money for technologies in Europe
was just 11% of the amount raised in the US.
Table 4.10 Comparison of Europe and US total technology breakdown by stage of
investment in million Euro, 2000
Investment Stage
Early Stage
Expansion
VC Subtotal
Management buy-outs
Other
Total
European
Biotech
468
288
756
175
86
1 017
Europe
Total Tech
4 561
4 612
9 173
1 824
367
11 464
US
Total Tech
22 452
61 202
83 654
2 986
13 709
22 452
Exchange rate based on ECB annual average for 2000 ($1=1.082 EUR).
Source: PwC, 2000 and NSF, 2002.
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While data on strategic biotech alliances (see section 4.2.2) indicates a considerable
maturation of the biotech industry throughout the 1990s, analyzing the destination of
venture capital within the industry reveals the relativity of this statement. As noted,
46% of all venture capital in 2000 was invested in early stage financing, and another
28% in the expansion stage, meaning that just over three-fourths of VC money was
invested in “young” firms. Thus, we can conclude that the industry as a whole is
maturing with regard to its importance relative to all technologies and the VC culture
is gaining in importance in Europe, while the explosion of knowledge related to the
sequencing of the human genome and new related niche activities may be aimed at
promoting a higher degree of specialisation at the beginning of this century.
5. THE ORGANISATION OF KNOWLEDGE WITHIN THE LIFE SCIENCE
INDUSTRY
This report has worked towards the creation of a sketch of the life science industry,
resulting in a descriptive framework from which a few concluding remarks can be
drawn.
First, it has been shown that the life science industry is one of the most fascinating
science-based industries. It is perhaps one of the most impressive examples of the
difficulty of depicting innovation dynamics, as the set of characteristics influencing
the dynamics in this particular industry is enormous. We list more or less its
complexity by identifying the key actors in the innovation dynamics: namely the
large diversified firms (LDFs), dedicated biotechnology firms (DBFs), public research
institutions (PRIs), public authorities and consumers’ associations.
The various ways in which these actors intersect underly the large complexity of
industrial organisation in this industry. That complexity results from the important
dependence between factors internal to firms and factors related to their environment
(mainly science, public authorities and consumers).
This complexity induces a few characteristics that seem to be specific to the life
science industry. On the one hand, instead of spreading homogeneously, the location
of the actors within this industry is very much concentrated around science-based
resources. This stresses the role of localised knowledge in that local interactions
appear to be influencing significantly innovation dynamics.
However, the relevance of localised patterns for this industry has to be
counterbalanced by the increasingly obvious importance of international strategies.
Here, for instance, the trends exhibited towards an internationalisation of patenting
strategy for companies are also obvious and shows how localised patterns must be
considered with regard to the globalisation of related or expected markets. If the
sources of innovation have to be anchored because of the previous complexity, this
industry is also one of the few ones in which knowledge dynamics are rapidly
diffusing globally, due to its science-based character. Finally, concerning these
characteristics, one must also insist on the contrasting patterns exhibited by the
European countries with regard to the US context in facing these same sets of
constraints.
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From those observations then, the report concludes in two major hypotheses that must
be further addressed:
The one is that the current working of innnovation dynamics in the life science
industry proves a relative weakness of the LDFs which have historically been the
major drivers of knowledge dynamics in this industry. This is not to say that they are
no longer innovative, but only to insist on the difficulty they are currently facing in
order to insure the continuity of their oligopolistic control on the life science industry.
They largely failed to integrate scientific opportunities in the 1990s, due to a kind of
blindness regarding the evolution of scientific opportunities. They are now trying to
compensate for the difficulty of integrating new knowledge by connecting more or
less formally (see the evolution of alliances in section 4.2) with DBFs. In any case,
they are finally trying to control innovation dynamics (and knowledge discontinuities)
by maintaining oligopolistic powership through size and reputation effects.
The other is the importance of the DBFs which prove to be the main drivers of
knowledge dynamics during the 1990s. They express to some extent a kind of shift
from an economics of research where LDFs were quite effective, toward an
economics of knowledge where it is not only a matter of R&D budgets, but also a
matter of exploring, combining, and adapting science opportunities with the
understanding of life mechanisms in a larger sense. For certain, not all of the DBFs
yet have all the capabilities in hand to compete seriously with the LDFs. However, in
some areas, one can wonder if what has appeared in other industries (like the “Bill
Gates success” in information technology) is reproducible in the life science industry.
However, to be more precise, one can insist on the fact that the exploding
opportunities induced by the post-genome era mainly benefit DBFs, even if DBFs
have not yet supplanted the incumbents due to the complexity of the set of actors that
has to be necessarily taken into account.
Let us summarise the basic arguments leading to now: The life science industry
offers a curious example of a science-based industry because of the huge number of
constraints that must be faced in order to manage innovation dynamics properly. Not
only are scientific resources and basic research centrally at stake, but demand concern
is also very active: patients want to have an increasingly important role and
increasing control; product definition is under the scrutiny of ethical issues; public
authorities want to control experimental phases, clinical testing protocols, as well as
more largely offer legal guidance for innovation dynamics. From that complexity of
constraints results the complexity of industrial organisation which attests to the
difficulty of managing knowledge and innovation dynamics in those fields. LDFs are
confronting integration problems with absorption of required knowledge, whereas
DBFs are facing co-ordination problems to articulate complementary resources and
shift from specialised to globalized opportunities.
Going further with the understanding of knowledge and innovation dynamics in this
industry requires some analytical clarifications in order to face the complexity of
industrial organisation in those areas.
A few methodological considerations have to be addressed at this stage. We have first
to insist on the fact that the life science industry is no longer competing on well-
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established markets and related products. Competition is about knowledge advances
and firms’ capabilities. Therefore, there is a need to look at the industry by
considering the type of competencies and capabilities developed by its companies.
This is why we must try considering economic issues in those areas by referring to an
activity framework (Richardson, 1972) which reveal themselves to be more
appropriate to deal with knowledge dynamics. Exploring the specific characteristics
of activities developed in the life science industry allows for a better understanding of
the rate and direction of innovation process in those areas.
At least, at the end of this first investigation into the industry, one can wonder about
the existence of different sub-sets in the life science industry that are confronting
similar economics problems. Regarding the current dynamics in those fields, we can
identify at least three major sub-sets that are more or less diverging in terms of
purposes, targets and economic applications (Table 5.1). Those major sub-sets are
nevertheless intersected by common features with regard to technological progress
and development.
Table 5.1 Major sub-sets within biotechnology
Health Care
Diagnostics
Gene Therapy
Genomics
- Structural
- Functional
Medicines
Monoclonal Antibodies
Proteomics
Stem Cell Research
Agriculture/Aquaculture/
Animal Health
Environment/Marine Biotechnology/
Industrial Applications
Agriculture
Environment
Genetic Modification
Bioremediation
- Bioaugmentation
Biocides
- Biopesticides
- Bioenrichment
- Herbicide tolerance
Marine Biotechnologies
Aquaculture
Marine Biotechnology Products
Animal Health
- Creation of new pharmaceuticals
and diagnostic products
Domestic Animals
- Development of new medicines
- Cleaner industrial and environmental
and treatments
products and processes
DNA Typing
Bioremediation
Industrial Applications
Food & Beverage
-Chiral and combinatorial chemistry
Biomass-Derived Energy
Bioprocessing
-Biological polymers
-Bioreactors
Bioconversion, uses Biocatalysts for
-Fermentation
-Genetic modification
-Bioprospecting
Interestingly, these three major sub-sets are inter-connected by a fourth dimension of
the industry which can be labelled as Key Technologies. The latter is transverse to
each of the three sub-sets of applications, and include common basic technological
requirements in the understanding of fundamental mechanisms (like cell culture,
cloning techniques, protein engineering, or hybrid technologies, for instance) (see
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Appendix E for an illustrative diagram). From that ‘key technologies viewpoint’,
there are economies of scale to be obtained by keeping common parts of the
knowledge dynamics in each of the three initial sub-sets. However, there are other
considerations that favour a divide (not to say an increasing divergence) among those
fields of applications (IPR systems, ethical issues, demand concern, and legal
frameworks, for instance).
This ordering of the life science industry through an activity framework is something
to be further explored because it helps to qualify the characteristics of knowledge
dynamics as well as the rate and direction of innovation. The case studies that are
planned for the next workpackages of the TELL project will explore some specific
aspects in the workings of some of these sub-sets.
LIFE SCI/BIOTECH
62
Project TELL
SOURCES
Boston Consulting Group (July 2001), “A Revolution in R&D-Part II, The Impact of
Genetics”, BCG Focus.
Biotechnology Industry Organization (3 June 2001), Editors’ and Reporters’ Guide to
Biotechnology, 5th Ed., http://www.bio.org/aboutbio/guide2001/letter.pdf.
Bud R. (1993), The uses of life, an history of biotechnology, Cambridge, Cambridge
University Press
Brookings Institution Center on Urban and Metropolitan Policy (2002), Signs of Life:
The Growth of Biotechnology Centers in the U.S.,Washington, D.C.
Bureau van Dijk (September 2000), Amadeus: pan-European financial database,
Update 71.
BusinessWeek Online (25 March 2002), “Biotech: The challenges facing this young
industry don’t end with drug discovery and FDA approval” by Catherine Arnst
and Arlene Weintraube.
De la Mothe J., Niosi J. (2000), The Economic and Social Dynamics of
Biotechnology, Boston, Kluwer Academic Press.
Dernis H., Guellec D., van Pottelsberghe B. (2001), “Using patent counts for crosscountry comparisons of technology output”, STI Review, 27, OECD.
European Commission (2002), Innovation and competitiveness in European
biotechnology, Enterprise Papers No 7-2002, Enterprise Directorate-General.
European Commission (9 April 2001), Towards a strategic vision of life sciences and
biotechnology: consultation document, COM(2001) 454 final.
European Commission (2001), European Competitiveness Report 2001: Chapter V:
The competitiveness of Eruopean Biotechnology: a case study of innovation, pp.
97-136.
EUs Europa: The European Union On-line http://europe.eu.int/, including Official
Journal 213 of 30.7.1998, Directive 98/44/E; and Commission proposes the
creation
of
a
Community
Patent,
http://europa/eu.int/comm/internal_market/en/indprop/2k-714.htm, 5 July 2000.
Ernst & Young, Integration: Ernst & Young’s Eighth Annual Life Sciences Report
2001 (March). http://www.ey.com/GLOBAL/gcr.nsf/UK/hs_-_Integration.
Galambos L., Sturchio J. (1998), “Pharmaceutical Firms and the Transition to
Biotechnology: A Study in Innovation”, Business History Review, vol. 72, issue
2, pp. 250-278.
LIFE SCI/BIOTECH
63
Project TELL
Hoch H.C., Jelinsky L.W., Caighead H.G., (1996), Nanofabrication and biosystems,
Integrating materials science, engineering, and biology, Cambridge, Cambridge
University Press.
ISIC industry codes were obtained from Amadeus, a pan-European financial database
published on CD-ROM by Bureau van Dijk. US version of SIC codes is
available via the Occupational Safety & Health Administration (OSHA) of the
US Department of Labor: http://155.103.6.10/cgi-bin/sic/sicser4?28.
Kopp P., Laurent T. (2001), Biotechnologies et hautes techniques: le retard français,
France Biotech Objectif 2010, http://France-biotech.org/precedentes.htm.
McKelvey M. (1996), Evolutionary Innovations: The Business of Biotechnology,
Oxford, Oxford University Press.
National Science Foundation,
http://www.nsf.gov.
Science
&
Engineering
Indicators
2002.
Oliver R.W. (1999), The coming Biotech-age, New-York, McGraw-Hill.
PriceWaterhouseCoopers, Money for Growth: The European Technology Investment
Report
2000.
http://www.pwcglobal.com/images/technology/MoneyforGrowth_2000.pdf/Mon
eyforGrowth_2000.pdf.
Robbins-Roth C. (2000), From alchemy to IPO: the business of biotechnology,
Cambridge, Mass, Perseus Publishing.
Senker J., van Vliet R. (1998), Biotechnology and competitive advantage, Europe’s
firms and the US Challenge, Cheltenham, Edward Edgar.
Thackray A. (1998), Private Science, Philadelphia, University of Pennsylvania Press.
United States Patent and Trademark
http://www.uspto.gov/patft/index.html.
Office
patent
search
database.
US CIA. http://www.cia.gov.
US Department of Labor, Occupational Safety & Health Administration (OSHA).
http://155.103.6.10/cgi-bin/sic/sicser4?28.
Van Beuzekom B. (2001), Biotechnology Statistics in OECD Member Countries:
Compendium of Existing National Statistics, Ad Hoc Meeting on Biotechnology
Statistics,
OECD,
Paris,
3-4
May.
http://www.olis.oecd.org/olis/2001doc.nsf/LinkTo/DSTI-DOC(2001)6.
LIFE SCI/BIOTECH
64
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APPENDICES
LIFE SCI/BIOTECH
65
Project TELL
APPENDIX A
Background and notes on research
The aim of this report is to provide an overview of the global life sciences industries,
emphasizing Europe’s performance in the biotechnology sector. The intent of the
report is to provide a basic understanding from which an in-depth analysis will be
performed later at the country level (to include Belgium and France). Where named,
“Europe” includes the following OECD countries: Austria, Belgium, Czech Republic,
Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, the
Netherlands, Norway, Poland, Portugal, Spain, Sweden, Switzerland and the United
Kingdom.
The report presents information gathered from several sources, but relies heavily on
data obtained from OECD, the US National Science Foundation (NSF) and Ernst &
Young’s European Life Sciences Report 2001. Due to the globally dynamic nature of
the life sciences industries, and the rapid growth phases of the European sectors in
particular, much of the data does not allow for international comparison. Most
countries exhibit wide variations in biotechnology definitions and criteria for
measurement; this diversity merits precaution in sections of the report where crosscountry comparisions were attempted.
Of primary importance is the international adoption of a uniform set of definitions for
biotechnology. Many countries classify biotechnology companies as either “core” or
“expanded”, but the definition of a “core” biotechnology company varies widely
between countries. A “core” biotech company is generally involved in the active use
of recombinant DNA. However, a key characteristic of the current biotech industry is
the emerging importance of the non-core companies that develop “platform
technologies”, i.e., the companies that develop tools to manage the massive amounts
of data resulting from the sequencing of the human genome. Thus, a set of
definitions for biotechnology is required to address both the core and advanced forms
of biotechnology. OECD currently employs US Patent and Trademark Office
(USPTO) “class 435: molecular biology and microbiology” as a working definition
for
biotechnology
(the
complete
definition
is
available
at
http://www.uspto.gov/web/offices/ac/ido/oeip/taf/moc/435.htm).
The life sciences include a wide range of scientific disciplines whose aim is to study
living organisms. For the purposes of this report, we have limited “life sciences”
primarily to include biotechnology (including the genetic modification of agricultural
products) and medicines. Agriculture minus core biotech activities has been
ommitted.
LIFE SCI/BIOTECH
66
Project TELL
APPENDIX B. USPTO PATENT DATABASE SEARCH
Country
United States
Population
(millions)
281.8
USPTO Patents Granted
Total patents granted
Biotechnology patents
Biotech patents as % of total patents granted
Biotech patents ("sequence", "DNA", "nucleic acid")
Pharmaceutical patents
Inventor country
Invented, but assigned to a foreign country*
% of patents invented at home-assigned abroad
Pharma. patents invented as % of total patents granted
*Due to complexity of this search, data are only presented for the most recent period.
Canada
Total patents granted
31.6
Biotechnology patents
Biotech patents as % of total patents granted
Biotech patents ("sequence", "DNA", "nucleic acid")
Pharmaceutical patents
Inventor country
Invented here, but assigned to foreign country
% of patents invented at home-assigned abroad
Pharma. patents invented as % of total patents granted
Japan
126.8
LIFE SCI/BIOTECH
Total patents granted
Biotechnology patents
Biotech patents as % of total patents granted
THREE-YEAR PERIODS
1987-1989 1990-1992 1993-1995 1996-1998 1999-2001
115265
2394
2.1%
130711
3325
2.5%
148403
4705
3.2%
185198
10381
5.6%
240547
15476
6.4%
119
207
341
939
1128
2335
3232
3812
6998
2.0%
2.5%
2.6%
3.8%
10188
1279
13%
4.2%
5765
58
1.0%
6997
76
1.1%
7049
113
1.6%
9733
273
2.8%
12775
528
4.1%
2
5
6
35
82
60
31
52%
1.0%
98
44
45%
1.4%
139
59
42%
2.0%
287
110
38%
2.9%
453
145
32%
3.5%
55664
512
0.9%
66703
783
1.2%
70479
945
1.3%
81410
1174
1.4%
101792
1261
1.2%
67
Project TELL
Japan
(Contd.)
USPTO Patents Granted
Biotech patents ("sequence", "DNA", "nucleic acid")
Pharmaceutical patents
Inventor country
Invented, but assigned to foreign country
% of patents invented at home-assigned abroad
Pharma. patents invented as % of total patents granted
Europe, selected countries
317.5
404
34
8%
0.7%
574
44
8%
0.9%
604
61
10%
0.9%
781
89
11%
1.0%
955
128
13%
0.9%
53800
486
0.9%
54854
678
1.2%
52343
943
1.8%
63751
1860
2.9%
92950
3119
3.4%
16
41
76
242
368
Pharmaceutical patents
Inventor country
Invented, but assigned to a non-European country
% of patents invented in Europe, assigned outside
Pharma. patents invented as % of total patents granted
683
163
24%
1.3%
846
200
24%
1.5%
1053
249
24%
2.0%
2314
551
24%
3.6%
3633
809
22%
3.9%
Total patents granted
Biotechnology patents
Biotech patents as % of total patents granted
1170
21
1.8%
1318
12
0.9%
1474
26
1.8%
2252
51
2.3%
2935
114
3.9%
2
2
6
18
20
16
5
31%
1.4%
29
16
55%
2.2%
38
21
55%
2.6%
78
48
62%
3.5%
126
72
57%
4.3%
Total patents granted
Biotechnology patents
Biotech patents as % of total patents granted
Biotech patents ("sequence", "DNA", "nucleic acid")
Belgium
10.3
Biotech patents ("sequence", "DNA", "nucleic acid")
Pharmaceutical patents
Inventor country
Invented, but assigned to foreign country
% of patents invented at home-assigned abroad
Pharma. patents invented as % of total patents granted
LIFE SCI/BIOTECH
1987-1989 1990-1992 1993-1995 1996-1998 1999-2001
38
48
47
114
151
68
Project TELL
Denmark
5.4
USPTO Patents Granted
Total patents granted
Biotechnology patents
Biotech patents as % of total patents granted
Biotech patents ("sequence", "DNA", "nucleic acid")
Finland
5.2
3
3
7
35
50
Pharmaceutical patents
Inventor country
Invented, but assigned to foreign country
% of patents invented at home-assigned abroad
Pharma. patents invented as % of total patents granted
7
3
43%
0.9%
18
7
39%
2.2%
18
8
44%
1.9%
59
33
56%
4.1%
107
49
46%
5.7%
Total patents granted
Biotechnology patents
Biotech patents as % of total patents granted
800
15
1.9%
1063
27
2.5%
1086
33
3.0%
1649
77
4.7%
2306
108
4.7%
1
3
3
12
8
Pharmaceutical patents
Inventor country
Invented, but assigned to foreign country
% of patents invented at home-assigned abroad
Pharma. patents invented as % of total patents granted
6
0
0%
0.8%
6
0
0%
0.6%
9
0
0%
0.8%
33
10
30%
2.0%
46
22
48%
2.0%
Total patents granted
Biotechnology patents
Biotech patents as % of total patents granted
9323
80
0.9%
9993
131
1.3%
9657
157
1.6%
11037
375
3.4%
14035
520
3.7%
6
11
15
60
73
Biotech patents ("sequence", "DNA", "nucleic acid")
France
59.6
1987-1989 1990-1992 1993-1995 1996-1998 1999-2001
747
807
952
1436
1891
23
25
63
181
306
3.1%
3.1%
6.6%
12.6%
16.2%
Biotech patents ("sequence", "DNA", "nucleic acid")
Pharmaceutical patents
LIFE SCI/BIOTECH
69
Project TELL
France
Germany
(Contd.)
83.0
Inventor country
191
226
259
685
1009
Invented, but assigned to foreign country
33
36
49
129
168
% of patents invented at home-assigned abroad
17%
16%
19%
19%
17%
Pharma. patents invented as % of total patents granted
2.0%
2.3%
2.7%
6.2%
7.2%
USPTO Patents Granted
1987-1989 1990-1992 1993-1995 1996-1998 1999-2001
Total patents granted
24688
24128
21978
25491
34969
Biotechnology patents
205
258
334
531
700
Biotech patents as % of total patents granted
0.8%
1.1%
1.5%
2.1%
2.0%
Biotech patents ("sequence", "DNA", "nucleic acid")
Italy
57.7
4
10
22
34
67
Pharmaceutical patents
Inventor country
Invented, but assigned to foreign country
% of patents invented at home-assigned abroad
Pharma. patents invented as % of total patents granted
220
35
16%
0.9%
262
58
22%
1.1%
311
62
20%
1.4%
572
161
28%
2.2%
903
241
27%
2.6%
Total patents granted
Biotechnology patents
Biotech patents as % of total patents granted
3991
19
0.5%
4474
42
0.9%
4297
62
1.4%
4949
75
1.5%
6104
76
1.2%
0
3
6
6
2
Pharmaceutical patents
Inventor country
Invented, but assigned to foreign country
% of patents invented at home-assigned abroad
Pharma. patents invented as % of total patents granted
48
12
25%
1.2%
78
24
31%
1.7%
116
33
28%
2.7%
184
67
36%
3.7%
177
80
45%
2.9%
Total patents granted
Biotechnology patents
Biotech patents as % of total patents granted
3254
41
1.3%
3360
88
2.6%
3113
110
3.5%
3647
222
6.1%
5039
287
5.7%
Biotech patents ("sequence", "DNA", "nucleic acid")
Netherlands
16.0
LIFE SCI/BIOTECH
70
Project TELL
Netherlands
(Contd.)
Norway
4.5
USPTO Patents Granted
Biotech patents ("sequence", "DNA", "nucleic acid")
Pharmaceutical patents
Inventor country
Invented, but assigned to foreign country
% of patents invented at home-assigned abroad
Pharma. patents invented as % of total patents granted
34
8
24%
1.0%
40
12
30%
1.2%
53
20
38%
1.7%
128
37
29%
3.5%
183
88
48%
3.6%
Total patents granted
Biotechnology patents
Biotech patents as % of total patents granted
477
4
0.8%
390
13
3.3%
433
9
2.1%
601
24
4.0%
904
38
4.2%
0
0
1
2
3
Pharmaceutical patents
Inventor country
Invented, but assigned to foreign country
% of patents invented at home-assigned abroad
Pharma. patents invented as % of total patents granted
8
5
63%
1.7%
12
4
33%
3.1%
22
7
32%
5.1%
46
9
20%
7.7%
49
11
22%
5.4%
Total patents granted
Biotechnology patents
Biotech patents as % of total patents granted
2994
37
1.2%
2561
24
0.9%
2599
41
1.6%
3539
70
2.0%
5663
111
2.0%
0
5
4
16
23
34
18
53%
1.1%
38
11
29%
1.5%
54
25
46%
2.1%
123
54
44%
3.5%
157
77
49%
2.8%
Biotech patents ("sequence", "DNA", "nucleic acid")
Sweden
8.9
Biotech patents ("sequence", "DNA", "nucleic acid")
Pharmaceutical patents
Inventor country
Invented, but assigned to foreign country
% of patents invented at home-assigned abroad
Pharma. patents invented as % of total patents granted
LIFE SCI/BIOTECH
1987-1989 1990-1992 1993-1995 1996-1998 1999-2001
0
4
5
30
41
71
Project TELL
Switzerland
7.3
USPTO Patents Granted
Total patents granted
Biotechnology patents
Biotech patents as % of total patents granted
Biotech patents ("sequence", "DNA", "nucleic acid")
United Kingdom
59.6
0
0
2
9
19
Pharmaceutical patents
Inventor country
Invented, but assigned to foreign country
% of patents invented at home-assigned abroad
Pharma. patents invented as % of total patents granted
79
50
63%
1.8%
82
50
61%
1.8%
75
41
55%
1.8%
173
106
61%
3.9%
223
134
60%
4.1%
Total patents granted
Biotechnology patents
Biotech patents as % of total patents granted
1861
13
0.7%
2231
19
0.9%
2698
30
1.1%
4723
173
3.7%
13682
650
4.8%
0
0
5
20
62
40
34
85%
2.1%
55
45
82%
2.5%
98
74
76%
3.6%
233
170
73%
4.9%
653
325
50%
4.8%
Biotech patents ("sequence", "DNA", "nucleic acid")
Pharmaceutical patents
Inventor country
Invented, but assigned to foreign country
% of patents invented at home-assigned abroad
Pharma. patents invented as % of total patents granted
LIFE SCI/BIOTECH
1987-1989 1990-1992 1993-1995 1996-1998 1999-2001
4495
4529
4056
4427
5422
28
39
78
81
209
0.6%
0.9%
1.9%
1.8%
3.9%
72
Project TELL
APPENDIX C. AVERAGE PERIOD GROWTH RATE FOR BIOTECHNOLOGY PATENTS IN SELECT COUNTRIES, 1987-2001
COUNTRY
THREE-YEAR PERIODS
1987-1989 1990-1992 1993-1995 1996-1998 1999-2001
A
B
C
D
E
United States
2394
3325
4705
10381
15476
Canada
58
76
113
273
528
Japan
512
783
945
1174
1261
Europe, selected
486
678
943
1860
3119
Belgium
21
12
26
51
114
Denmark
23
25
63
181
306
Finland
15
27
33
77
108
France
80
131
157
375
520
Germany
205
258
334
531
700
Italy
19
42
62
75
76
Netherlands
41
88
110
222
287
Norway
4
13
9
24
38
Sweden
37
24
41
70
111
Switzerland
28
39
78
81
209
United Kingdom
13
19
30
173
650
Source: USPTO Patent Database.
LIFE SCI/BIOTECH
PERCENT GROWTH
A->B
B->C
39
31
53
40
-43
9
80
64
26
121
115
225
-35
39
46
C->D
42
49
21
39
117
152
22
20
29
48
25
-31
71
100
58
AVE. 3-YR
GROWTH RATE
D->E
121
142
24
97
96
187
133
139
59
21
102
167
71
4
477
49
93
7
68
124
69
40
39
32
1
29
58
59
158
276
62.5%
78.7%
26.3%
60.9%
73.4%
104.3%
69.0%
65.3%
36.5%
47.7%
67.7%
104.8%
41.3%
75.3%
214.1%
73
Project TELL
APPENDIX D. INTERNATIONAL STRATEGIC BIOTECHNOLOGY TECHNOLOGY ALLIANCES, 1980-98
Total US alliances
Biotech alliances:
US-Europe
US-Japan
US-other
Intra US
Total biotech alliances
of which international
1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000
139 126 200 177 234 235 292 318 367 357 312 287 394 444 497 639 578 497 477
5
6
3
10
6
8
2
12
9
12
1
23
7
7
0
13
14
7
2
28
22
16
3
27
24
14
0
39
28
11
3
36
21
6
4
36
16
6
5
23
11
4
4
13
18
1
1
16
40
5
5
33
42
10
7
57
62
7
6
58
59
6
6
60
75
13
7
53
49
14
6
93
47
6
2
53
24
14
28
16
45
22
27
14
51
23
68
41
77
38
78
42
67
31
50
27
32
19
36
20
83 116 135 131 148 162 108
50 59 75
71
95 69
55
170 168
1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998
Total biotech alliances
as % of total alliances
with US, 1980-98
17
22
23
15
22
29
26
25
18
14
10
13
21
26
27
21
26
33
23
Share of foreign biotech
alliances out of all US
alliances, 1980-98
58
57
49
52
45
60
49
54
46
54
59
56
60
51
56
54
64
43
51
Share of European "
Share of Japanese "
Share of Other "
21
25
13
21
29
7
20
27
2
26
26
0
27
14
4
32
24
4
31
18
36
14
4
31
9
6
32
12
10
34
13
3
50
3
3
48
6
6
36
9
6
47
5
5
45
5
5
51
9
5
30
9
4
44
11
2
LIFE SCI/BIOTECH
74
Project TELL
Total European alliances
Biotech alliances:
Europe-US
Europe-Japan
Europe-other
Intra Europe
Total biotech alliances
of which extra-European
1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000
102 94 127 111 166 240 242 236 266 320 203 166 233 235 257 330 261 224 245
5
0
0
6
6
1
2
5
9
2
1
3
7
2
0
11
14
0
0
10
22
7
3
27
24
1
1
9
28
4
1
18
21
1
4
24
16
6
3
12
11
4
5
8
18
0
1
2
40
3
5
10
42
4
3
10
62
6
6
19
59
6
2
22
75
6
7
14
49
1
3
6
47
2
1
9
11
5
14
9
15
12
20
9
24
14
59
32
35
26
51
33
50
26
37
25
28
20
21
19
58
48
59
49
93
74
89 102
67
88
71
65
79
70
70
87
1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998
Total biotech alliances as
% of total alliances
with Europe, 1980-98
11
15
12
18
14
25
14
22
19
12
14
13
25
25
36
27
39
26
24
Share of extra-European
biotech alliances out of all
European alliances
45
64
80
45
58
54
74
65
52
68
71
90
83
83
80
75
86
90
85
Share of US "
45 43 60 35 58 37 69 55 42 43 39 86 69 71
Share of Japanese "
0
7 13 10
0 12
3
8
2 16 14
0
5
7
Share of Other "
0 14
7
0
0
5
3
2
8
8 18
5
9
5
Source: CATI-MERIT database supported in part by the NSF, Science & Engineering Indicators 2002, text table 4-12.
67
6
6
66
7
2
74
6
7
83
2
5
80
3
2
LIFE SCI/BIOTECH
75
Project TELL
APPENDIX E
KEY TECHNOLOGIES
Cell
Culture
Molecular
Cloning
Cellular
Genetic
Modification
Protein
Engineering
Hybrid
Technologies
Animal
Microelectronics
+ Biology
Biosensor
Technology
Materials Science
+ Cell Biology
Tissue
Engineering
Semi-conductor
Manufactuing +
Molecular Genetics
DNA Chip
Technology
Information
Technology
Bioinformatics
Technology
76