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Paper to be presented at the DRUID Summer Conference on "Industrial Dynamics of the New and Old Economy - who is embracing whom?"

Copenhagen/Elsinore 6-8 June 2002

SCIENCE-BASED INNOVATION REGIMES AND INSTITUTIONAL

ARRANGEMENTS : FROM SCIENCE BASED “1” TO SCIENCE BASED “2” REGIMES

TOWARDS A NEW SCIENCE-BASED REGIME?

(Draft. Comments Welcome)

Benjamin CORIAT1(*) , Fabienne ORSI1,2, Olivier WEINSTEIN1

1 CEPN-IIDE, CNRS, Research Unit 7115, Université Paris Nord

2 INSERM, Research Unit 379, Université de la Méditerranée

Abstract

The purpose of the paper is to enter into the black box of “science based” sectors, to try to better understand the nature of the dynamics of the different types of such innovation regimes. A special attention is given to the institutional dimensions which, in the view of the authors, play a major role in the framing of innovation regimes and organizational trajectories. After a short review of the literature on “science based” sectors and technological regimes, we focus on some specificities of the new emerging biotech sector, aiming at showing how and why, it can be regarded as a new type of science based technological regime, coined in this paper as science based “type 2” model. In a short and final conclusion, we try to explore some of the consequences of the existence of this basic distinction between two types of “science based” regimes. Key Words: science based sectors, technological regimes, innovation, biotechnology, intellectual property rights (*) Corresponding authors : coriat@club-internet.fr, f_orsi@club-internet.fr , weinstein@wanadoo.fr Universtité Paris 13, Faculté des Sciences Economiques. Avenue Jean Baptiste Clément, 93430 Villetaneuse. France.

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INTRODUCTION

The notion of Science-Based technology has been developed long time ago, in the economics

of innovation (cf. the works of Pavitt or Freeman, just to mention some the most important

ones). It reflects a long trend in the transformation of capitalist production, beginning at the

end of the 19th century, mainly in the chemical and the electric industries, and which knew a

major development since second world war. As pointed out by Nelson (1996), “The rise of

chemistry, physics, and biology as strong fundamental sciences during the last decade of the

nineteenth century was accompanied by several development that changed the nature of

industrial technical innovation”. The development of the so called “new technologies” since

the seventies, and more particularly, information technology and biotechnology, pushed

towards a renewed interesting to a better understanding of the links between science,

technology and economic organization.

It is clear today, that the conditions of development of science-based sectors are of paramount

importance for the overall economic development and the competitiveness of nations. This,

because these sectors are the locus of major structural transformations. However, the literature

on technological regimes shows that the sectors usually characterized as science-based can

exhibit quite diverse configurations. It is thus useful to enter into the black box of “science

based” models, to try to better understand the nature of the dynamics of the different types of

such innovation regimes. Our purpose here, is to explore that question, by considering more

particularly the biotech sector, putting emphasis on the institutional dimensions which, in our

view, play a major role in the framing of innovation regimes and organizational trajectories.

After a short review of the literature on “science based” sectors and technological regimes

(section1) we focus on some specificities of the new emerging biotech sector, aiming at

showing how and why, it can be regarded as a new type of science based technological

regime, coined in this paper as science based “type 2” model (Section 2). In a short and final

conclusion (section 3), we try to explore some of the consequences of the existence of this

basic distinction between two types of “science based” regimes.

I. SCIENCE-BASED TECHNOLOGICAL REGIMES

Before exploring the definition and characterization of science-based sectors, it is useful to

consider briefly the general question of the relations between science and technology.

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I-1 Science and technology

The links between science and technology are nothing but simple. We know how misleading

is the linear view of innovation : technology “is not applied science” (Pavitt, 1998). Two

preliminary points here deserve attention.

The first concerns the differences between research activity (and more particularly basic

research) and innovative activity (See, for example, Pavitt, 1998): differences regarding their

purpose (produce fundamental knowledge by developing general theories, versus

development of specific useful artifacts); the types of core outputs (codified knowledge in the

form of (published or unpublished) papers, versus artifacts intended to production and – more

often – to market, but also codified knowledge in the form of patents; the types of skills and

capabilities and the modes of organization (strong specialization by research fields on one

side, combination different types of knowledge and capabilities on the other side).

But the key point, in order to appreciate the ongoing transformations in the relations between

science and industry (and the evolution of scientific institutions themselves) is to consider

science and technology – and their relationships - as institutionalized activities. The

separation between (fundamental) science and technology is not a “natural” fact, it is the

result of an historical process resulting in a particular mode of division of labor, and a

particular institutional arrangement. This arrangement is now well known, it is based first on

the existence of non-firm and non-for-profit organizations specialized in the production of

basic knowledge (the “academic institutions”, composed mainly of Universities and other

non-commercial research institutions dedicated to basic research) on one side, and on

industrial R&D on the other side, which function is to “routinize” innovative activity, but also

to create an internal capacity of the firms as regards the absorption of external knowledge and

discoveries produced particularly by non-firm organizations, (which imply some internal

investments in “basic research”).

Furthermore, this institutional arrangement is based on a critical differentiation as regards the

“rules of the game” governing those different institutions. It concerns first of all the property

regime of diverse levels of scientific and technological knowledge. The knowledge produced

by academic institutions, or at least a large part of it, have the status of a “free good”1, a

1 « Free good » does not mean that everybody can effectively use it, but just that the knowledge is freely available for those, individuals or organizations, who have the capabilities, and the complementary assets needed

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property which is a central dimension of the “Economic of Open Science” (cf. David 1994 ).

The world of open science is thus governed by a set of rules on publicity and the precedence

of discoveries (ensuring the discoverers’ reputation and fame), and also on availability : a

discovery is a “free good”; its circulation cannot be hindered (under the only restriction that

what belongs to Caesar ought to be rendered to him). (Merton , Dasgupta and David 1994).

The knowledge and other outputs produced by the innovative activity of firms (and in

particular produced by their R&D units) is intended for a private appropriation by different

ways, including intellectual property systems (See Levin and al., 1987). In particular,

inventors (i.e. innovators using scientific discoveries), under the condition that they establish

the “novelty”, “utility” and “non-obviouness” of their discoveries can thus enjoy an

exclusive but time-limited monopoly for the commercial exploitation of their inventions, via

complex patenting rules. As a compensation, they have to “disclose” the basic content of their

inventions, and present some “written descriptions” of their inventions. Thus, the patent

system is, in itself, designed to make, available for the public, whatever technological

progress derived from those inventions.

On one side, the usual justification of the status of scientific knowledge refer to the specific

nature of the good “knowledge” as a “public” or “non-rival” good, and the difficulties of its

appropriation (Arrow 1962, Nelson 1959). But, clearly, the same is true for the more applied

knowledge produced in industrial R&D laboratories (even if that type of activity gives a

greater importance to tacit capabilities, and results in knowledge which is in great part

embedded in people and artefacts). On the other side, the appropriation of innovation and

invention, and more particularly the patent system, is justified as an incentive system, but we

have to notice that the production of novelty in the “republic of science” has been based on a

completely different incentive system, with great success! Thus, rather than considering

science and technology simply as given activities, with objective characteristics, we have to

consider them as the result of fundamental institutional choices, defining – in a more or less

strict way - the boundaries between the two domains and the rules governing their

organization, and their relations. In particular, the « discovery/invention » distinction seems to

be the cornerstone of a system coordinating through very subtle and complex ways firms and

non-firm organizations, encompassing at the same time institutions as well as labor

to exploit it. On this point and for a discussion on the distinction between “public” and “free” good see Pavitt, 1988.

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organization and social division between bodies giving birth to a science-based model of

innovation.

The mode of financing is also a key dimension of the science/innovation system. The

characteristics of the open science institutions imply a non-market funding; in practice is

realized mainly through public funding. But, a permanent and important public financing of

industrial R&D and innovation is also one of the central dimension of innovation systems in

industrial countries since the second world war (and particularly in the US). It can be partly

explained, and justified, by the peculiar characteristics of information and knowledge as

economic commodities, and the resulting problems of market failures (Arrow, 1962). But,

whatever the justification given to that fact – in that respect crucial political and social

choices, and for example, the reference to “national security” requirements, are probably more

important that questions of externalities and appropriation difficulties - the combination of

private and public funding, and the way it is organized has been one of the key factor of

innovation dynamics since fifteen years.

(ii) Given the global structure of science/innovations systems, the links between scientific

knowledge (and academic research) and industrial technology can take different forms. Many

empirical studies have explored the ways through which scientific research can contribute to

technological innovation. Let’s just consider here two facets of that question.

First, its seems possible to identify two mains forms of influence of advances in scientific

knowledge on industrial R&D and innovation (Klevoric and al., 1995). In the first one,

scientific research “provides an expanding pool of theory, data, technique, and general-

problem-solving capability that is re-used in industrial R&D” (op. cit. p. 193). In the second

one, new advances in scientific knowledge contribute directly to the emergence of new

technological possibilities and are directly used in applied research for the development of

new products or processes. This mode of influence, which is, in a way, in accordance with the

“linear” model innovation is certainly not the more common, but it can play a key role in

some fields, and precisely in sectors usually considered as “science-based”. Another point

advanced by Klevoric and al., (1995) deserve attention: this direct contribution of scientific

research can involve basic science (like for example molecular biology or nuclear physics),

but also, and more often, applied science en engineering research, which means quite different

ways of interactions between academic institutions and firms.

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This observation opens to a second point : the diversity of channels through witch scientific

knowledge and more generally the divers outputs of basic research can spread into industry

and contribute to innovation. In some cases the academic research can lead directly to

applicable discoveries (Pavitt, 1998). It can take the form of a direct relationship between

discovery, invention and innovation, (in that case the distinction between discovery and

invention appears as quite fuzzy), or of transfer of research techniques and instrumentation

(ibid.). Others links are indirect, more particularly through the training of researchers and

engineers, and by the diffusion of information and knowledge through formal and informal

relations between academic and industrial researchers and engineers, inside scientific and

professional networks.

This various form of interactions between science and technological innovation can combine

according to complex and diverse configurations, depending of the specificities of innovation

process in different activities and sectors. It means that the notion of “science-base”

technology can cover different organizational realities, as we will see later on. Here again, it

is essential to realize that institutional factors will greatly contribute to the shaping of this

configurations: the legal status of different forms of knowledge, the formal and informal rules

governing the relation between individual researchers and organizations, the conditions of

mobility of people between divers institutions and organizations, and thus the functioning of

internal and external labor markets, the precise conditions of funding of the divers types of

institutions…

If increasing links between science and technology can be seen as a general tendency, the

importance and the modalities of that links are quite different between technological fields

and sectors. That observation leads to the identification of the particular features of the so

called “science-based technological regimes” specific to some industries.

I-2 General characteristics of science-based sectors

The key characteristics of Science-Based technological regimes have been well documented

since the seminal paper by Pavitt (1984). The basic point, in order to understand the

specificities of science-based sectors, is the opposition between two main forms of industrial

innovation process, as regard the conditions of production and diffusion of the basic

knowledge and capabilities (See Coriat and Weinstein, 2001; Marsili, 2001).

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In the “Scale intensive” and “Specialized suppliers” sectors (In the typology of Pavitt, 1984)

or in the “Complex systems” and “Product engineering” regimes (in the typology of Marsili,

2001):

- innovation is mainly the result of development (as opposed to research) or engineering

activities

- the innovation capacities of firms are based mainly on specific, and in great part tacit,

collective capabilities, formed by internal collective learning process. It does not mean

that relations with academic research is unimportant, but it concern mainly

engineering disciplines. (mechanical and electrical engineering, computer science…)

or general scientific knowledge (Mathematics).

- One of the key problem for firms is the capacity to have access and to combine

various technical knowledge and capabilities.

In the science-based innovation regimes, :

- Innovation is critically based on Research, which is in great part realized outside

firms. Innovation is thus directly dependant on strong and direct links between firms

and academic research. The new “external” scientific knowledge produced by the

academy has to be quickly transferred into industrial applied research and

development. Therefore the access to external knowledge from universities and public

research institutions is a critical factor of innovation. Innovation thus means the

commercial use (and appropriation?) of a type of knowledge that often is at the edge

of state-of-the-art, and which comes from non-firms organizations.

- It supposes an internal capacity of the firms as regards the absorption of external

knowledge and discoveries produced by that organizations, as well as some internal

investments in basic research (cf. Rosenberg, 1990).

- Technological opportunities are particularly high and persistent. The scientific

advances are creating a large spectrum of potential new products (Marsili, 2001).

- Product (and process) design is thus based on the commercial exploitation of a cluster

of scientific results belonging to related but often distinct disciplines; but the

differentiation of the knowledge base is relatively low, as compared to “complex

systems” (Like Aeropace or Motor vehicle) or “Product engineering” sectors (ibid.).

Following Marsilli (2001), the science-based sectors belongs to two main categories: the “Life

science-based” sectors (drugs and bioengineering) and the “Physical-science-based” sectors

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(computers, electrical telecommunications instruments). The key point, on which we want

now to insist, is the possible diversity of “science-based” regimes, according to different types

of technological regimes, but also to the diverse and changing institutional patterns inside

which innovation is rooted. To be more accurate: what is important is the “co-determination”

and “co-evolution” of technological and institutional regimes.

I-3 Diversity of science-based innovation regimes.

Lest first consider more precisely the characteristics of science-based innovation regimes.

When considering diverse industries, some important must be exhibited, concerning in

particular the characteristics of the knowledge base, the type of R&D activities, and the

conditions of appropriation.

A) Links between science and production, and between academic institutions and

firms

The literature on technological regimes gives a lot of information about various characteristics

of these regimes, in particular as regards the sectors considered as science-based. Some key

differences appear, more particularly between drugs (and biotech) on one side, and computers

or semi-conductors technology on the other side.

(1) Some sectors appear as “strongly science-based” (Grupp, 1996), insofar as the

contribution of academic research to innovation is particularly high. According to the

treatment of the data from the Pace report by Marsili (2001), it concern

Pharmaceutical in first rank, Computers and Aerospace, (a sector witch is at the same

time, classified in “complex systems”). But, the structure of the internal R&D is quite

different : in the pharmaceutical industry research, and even basic research is

strongly dominant, while in the computer industry, or in Telecom and electronics

development activities are important (ibid.). The data on patents applications (Narin et

al., 1997) are also revealing : the situation of Drugs and Medicine appears very

specific: (i) the average number of references to science is exceptionally high (Table

1), and (ii) the importance of references to papers published by public institutions (as

opposed to industry) is also high, (as well as for Chemical patents, as compared to

Electrical component Patents: 79,1% and 72,7% versus 49,2%; ).

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Table 1

Average number of science references – in US – per US patents (1995)

Chemical

patents

Drugs and

medicine patents

Electrical

components

patents

Prof. and sci.

instruments

patents

4.63 11.61 1.28 1.72

Source : Narin et al. (1997)

(2) A second important difference concern the type of academic research which is the

more relevant as regard industrial innovation: basic science vs. engineering. That

dimension is clearly analyzed by Marsili (2001). If the contribution of academic basic

and applied science is important for Pharmaceuticals and Computers, academic

research in engineering is also very important for Computers (while relatively

unimportant for Pharmaceutical).

(3) In Pharmaceutical, and in chemistry-based industries the links to science are

concentrated in few fields, while in semi-conductor and in physics-mathematics based

industries they are more diversified (Klevorick et al. 1995)

(4) A last important point concern the divers channels trough which firms derives

knowledge from academic research. The links between academic research and

science-based industry are of various type (“scientific” links through publications and

conferences, contractual relations, informal contacts and exchange of personnel). Here

again there seems to be, according to the Pace report, some differences between

pharmaceuticals and computers (Marsili 2001: 196). In pharmaceuticals the scientific

links, corresponding to more codified knowledge transfer, are particularly important,

while in the computer industry, publications seems to be negligible, temporary

exchange, conferences and hiring of personnel being the most important sources of

assimilation of academic knowledge. This observation can be connected to what has

been said previously about the importance of scientific citations in drugs patents.

These observations are converging to suggest that some sectors or industrial activities are

“strongly science-based”, in the sense of direct and crucial links between basic and applied

research, realized mainly in academic institutions belonging to the sphere of open science, and

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industrial invention and innovation; while in others activities (probably, until now, the most

numerous), the strictly science-based traits are combined with important engineering and

development dimensions.

B) Appropriability conditions : “discrete” versus “cumulative” technologies

Appropriability conditions are recognized as a central dimension of sectoral innovation

regimes, as well as the differences across industries regarding the prevailing modes of

appropriability (Levin et al. 1987; Cohen et al. 2000). Amongst this various modes, patents

and other intellectual property protections occupy a central position, in spite of the fact that

many studies have been suggesting that patent protection really matters only in a few sectors

(and notably in pharmaceuticals). Yet, the strengthening of patent protection since about

twenty years is one of the major institutional transformation in the US (Jaffe 2000, Coriat and

Orsi, 2002). An evolution which, in our view, cannot be without relations with more general

transformations in innovation regimes.

In that perspective, let us remind first some results about the sectoral appropriability

conditions. Following Cohen et al. (2000), firms can resort to three basic “strategies” to

protect their inventions: (1) secrecy, (2) lead time and the exploitation of complementary

capabilities, (3) patents and other legal means. The two first strategies appear to be the

favored ones in virtually all industries, but the role of patents has been probably

underestimated in this survey, according to the authors themselves. In any case, patents and

other legal means are of particular importance in science-based sectors, drugs and computers

(see Table 2), and more specifically of course, in drugs. But the most important point concern

the difference in the functions, and the economic effects of patenting across (science-based)

industries, and more fundamentally according to some central characteristics of technological

regimes.

Table 2

Effectiveness of Appropriability Mechanism for product innovation :

Mean Percentage of product innovation for which Mechanism Considered Effective

Industry Secrecy Patents Other

Legal Lead time

Complementa

ry capabilities

Sales/Services

Complementa

ry capabilities

manufacturing

Drugs 53.57 50.20 20.82 50.10 33.37 49.39

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Computers 44.2 41 27.20 61.4 40.2 38

Semiconducto

rs and related

Equipment

60 26.67 22.50 53.33 42.22 47.50

All 51 34.83 20.71 52.76 42.74 45.61

Source: Cohen, Nelson and Walsh (2000)

The observations collected by Cohen and al. highlight a key difference between drugs and

computers (See table 3).

-In drugs, if all reasons to patent are important (compared to the others industries) three goals

are of specific importance; namely “to get licensing revenues”, “blocking”, (that is creating

patent fences to prevent the development of competing products), and “enhance reputation”,

an objective which is specifically important in biotech, as we will see later on, in connection

with the specificity of biotech firms and their modes of financing.

-In computers, patenting has two particularly important purposes: the use in “negotiation”,

(which is essential as a result of the fact that in that sector, products are usually composed of a

large number of patentable components), and to “prevent suits”.

Table 3

Reasons to Patent Product Innovations: Percent of Respondents by Reasons

Industry

Mesure

performan

ce

Licensing

Revenue

For Use in

Negociatio

n

Prevent

Suits

Prevent

Copying

Blocking Enhance

Reputatio

n

Drugs 13.39 44.44 61.11 66.67 100 97.22 69.44

Computers 0 30 80 90 85 65 40

Semiconducto 0 41.67 66.67 66.67 91.67 75 33.33

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rs and related

Equipment

All 5.75 28.27 47.38 58.77 95.81 81.81 47.91

Source: Cohen, Nelson and Walsh (2000)

The questions relative to the impact of patents on innovation and firm’s strategies are often

connected with a basic distinction between two types of technologies (See, for example, Levin

et al. 1987, Levin 1988, Klevorick et al. 1995, Cohen et al. 2000): “discrete technologies… in

which innovation more or less stand alone as isolated discoveries” (Levin, 1988); and

“cumulative technologies” or “complex technologies” in which one generation of inventions

and devices incorporates many elements from previous generations and serve as foundation

for next generations; and where new products or process are composed of a large number of

separate patentable components.

In discrete technologies, like chemical or drugs (at least before the biotech revolution), the use

of patenting as a direct source of revenues is relatively important, as well as it is for blocking

competing products. The possession of few patented inventions is, in that context, an essential

and often quite sufficient condition (combined with complementary manufacturing

capabilities) for a firm to benefit from its innovations. But even in that case (i.e. sectors

dominated by a regime of discrete technologies) one may argue that a “strong” patent system

may reduce the opportunity for spillovers, and from that point of view may discourage

innovation (Levin, 1988).

In “cumulative technologies”, the story is completely different. The condition for innovation

is the access to various new scientific and engineering knowledge and inventions. As it is

emphasized by Levin : “In such a regime, a high degree of spillovers may not only spur

technical advance, but also encourage R&D investment” (Levin,1988). It means that a

relatively “loose” intellectual property regime, facilitating a rapid diffusion of new

technologies, fosters innovation, and more particularly innovation by new small firms,

notably by reducing the risk of litigation with established (large) firms. A loose IP regime

allowing a systematic use of “reverse engineering” by rival firms (until 1984 and the vote of

the SCPA) is one of the key factors explaining the exceptional dynamism in the

microelectronics and computer industries in the US (Mowery and Rosenberg 1998, Hunt

1999). The strengthening of patent protection during the last twenty years can thus imply, in

that industries a profound change in the innovation regime. Cohen et al. (2000) are showing

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that this strengthening of patent protection seems to go with an increasing use of patents in

“litigation-intensive strategies”, the prevention of suits being one of the most important reason

to patent in all industries. This factor is exceptionally important in computers, with another

one: the use in negotiation, resulting from the dispersion of patented complementary

inventions between numerous firms (See table 3). The development of “patent portfolio

races” in complex and cumulative technologies can thus have a negative impact on innovation

(See Cohen et al, 2000, or Shapiro, 2001), by preventing improvement upon an original

inventions, by raising the risk of litigation and the cost of innovation, and by increasing the

number of patent registrations motivated by pure strategic motivations. On the other side, it

can oblige firms to disclose their inventions, in order to be able to negotiate the access to

complementary inventions. The negative impact of this overall expansion of the use of

patents, if not certain, is thus very likely. It can concern particularly the capacity of small

firms to innovate.

A point is worth noting: the difference between discrete and complex and cumulative

technologies is not explained by the “natural” characteristics of the knowledge base and the

“physical” character of products and processes only, it is as well (and often firstly) the result

of the patent policy itself (Cohen et al. 2000), and more generally of organizational and

institutional factors, framing and orientating the technological strategies of firms. The

decomposition of a technology, or of a body of knowledge into different patentable

components can be more or less easy to achieve; it will depend on the prevailing patent rules

and system (i.e. the precise definition of what is patentable, and so…).

II. SCIENCE-BASE I ET SCIENCE-BASE II

Let’s now consider more systematically the place of institutional and organizational patterns

in the shaping of innovation regimes We will first consider briefly some institutional

dimensions critical for science-based technological change, and how they have been

combined in coherent systems in the fordist and “post-fordist” era, and then, we will try to

show how the biotech case can be analyzed as the establishment of a new science-based

innovation system, and finally we shall wonder if it can have, beyond that sector, a more

general scope.

II-1 Institutional (and organizational) dimensions. The « classical » model and his

transformations

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The systematic application of scientific knowledge to economic development is one of the

distinctive feature of industrial societies (Kuznets, 1966, Rosenberg, 1982). It has been

realized through the creation of specific institutional and organizational forms, affecting the

industrial structure, the scientific sphere and the political and legal system. After the World

War II, it seems possible to identify an “ideal” model typical of large industrialized countries

– with variation between them – and more particularly of the high-tech sectors characterized

by the importance of R&D expenditures. This model, which emerge during the first half of the

twentieth century, was well in accordance with the “Schumpeter Mark I” model, and with the

vision of firm structure and behavior given by Chandler. It has been beginning to change in

the US, with the emergence and the growing importance of small, new firms, mainly in the

microelectronic and computer industries. Let’s try to summarize the key characteristics of that

institutional system.

A) Modes if institutionalization

First, as explain before, it was based on a distinctive mode of institutionalization of science,

linked to a mode of division of R&D labor between the scientific institutions and firms.

University (or public) research laboratory on one side and industrial research laboratory, in

large corporations, on the other side can be seen as the two fundamental organizational

forms in that system. As we know, the principles of functioning – in particularly as regards

rewards and incentives systems - where completely different in the two spheres, based on

non-market interactions in the spheres open science, and to market-oriented finalities in the

industry (Even if the status of the industrial researchers could have been particular inside the

firm). And, as previously explained, this institutional arrangement is supposed to be based on

a strict differentiation as regard the legal status of two types of knowledge. The scientific

knowledge, produce mainly by academic institutions is a free good, whether the

technological knowledge produced by firms (and notably the “inventions”) is indented to be

privately appropriate, by legal devices or by other means. It is important to notice that the

activities of universities (or public research institutions) has not been restricted to basic

science, they have also cover engineering and applied science disciplines. The development

of such disciplines has been in fact a central aspect of the evolution of the science system,

particularly in the US, and of the constitution of science-based innovation regimes.

Until the seventy, industrial R&D and innovation was mainly realized inside large firms. The

internalization of R&D activities being one of the standard feature of industrial structures.

The growing role of new small firms in the US, particularly in science-based sectors, means

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a profound change in the division of labor in R&D activities, and in the all science-industry

system. A change connected to others institutional transformations.

Another aspect of the science-industry system, which remained important after the

emergence of small high-tech firms, deserve consideration: the relations between academic

institutions and firms, and the circulation of knowledge, was realized mainly through non-

market relationships. It concern the codified knowledge as well more tacit ones, circulation

trough diverse modes of personal and networks relations. This “free” diffusion of knowledge

has clearly contribute to foster innovation, it can even concern relations between firms,

inasmuch the “culture” of open science penetrate the economic sphere.

B) Financing of Innovations

The conditions of financing of R&D and innovative activities is a critical question,

considering the peculiar traits of that activity, and of knowledge as an economic good. The

“classical” model was based first on what seems to be a coherent system: a public funding of

academic research, in accordance with the character of public good of its outcomes; and an

industrial in-house R&D funded mainly by large firms, and made possible by the different

modalities of appropriation we have seen before, secret, patent and other legal means,

specific and tacit collective technical knowledge…. From the second world war, the public

funding became much more important, concerning not only the universities and public

research institutions but also industrial R&D, which means that the private financing has

been judged insufficient, according to economic, and above all political criteria.

Here again, there as been, as we know, a crucial change, in the US, linked to the emergence

of small innovative firms: the creation of a new private financial system specialized in the

financing of new firms, the venture capital system. It has concerned in the first place science

based technologies, and first microelectronics and computers. It is, in our view a central

component of a new science based innovation regime, connected to more global changes in

financial institutions, as we will see later on.

C) IPR Regime

Last, but not least, the intellectual property regime, and other regulations have played, and

are playing today, a key role to explain the evolution of innovation regimes. The “classical”

model is based, as explain before, on a division between two types of knowledge, subject to

different property regimes, leading to different modes of circulation and diffusion of

information and knowledge. But the boundary between “public” and “private” knowledge is

not strictly defined, it will depend on the legal system, particularly on the strength and scope

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of the patent system, and of the practices of actors as regard the disclosure and exchange of

information, framed by the informal rules and norms of the professional and scientific

communities.

That dimension has been clearly very important to explain the innovation regime in

microelectronics and computers in the US from the sixties: “Commercialization of

microelectronics and computer hardware and software innovations by new firms was aided

by permissive intellectual property regime that facilitated technology diffusion and reduced

the burden of new firms of litigations over inventions that originated in part within

established firms” (Mowery and Rosenberg 1998). The strengthening of patent protection

since the eighties and the growing importance of patent strategies by established firms imply

a deep break with this regime.

Intellectual property leads directly to situations of monopoly, it is therefore usefully to

consider at the same time the antitrust regulation. The US experience show clearly the

relevance of this aspect. The US antitrust policy explained partly first, after the war, the

orientation of large firms towards internal creation of new technologies (by making difficult

the acquisition of firms in related technologies), and thus the development of in house R&D,

and then, the diffusion of technologies in the microelectronic and computer industries, and

the entry of new firms, through liberal licensing policies (resulting from antitrust litigation)

(See Mowery and Rosenberg 1998).

Thus, the early development of the computer and microelectronic industries in the US has

been based on a combination of a “loose” intellectual property regime and a strong antitrust

policy. This specific configuration have played a key role for the direction and profile of the

innovation regime, as regards the “division of labor” and the modes of relations between

large corporations, small new firms and scientific institutions, as well as for the

“performances” of this regime. As we know, the evolution of the institutional setting since

the eighties is going in the opposite direction, towards a strong intellectual property regime,

and a loose antitrust policy.

What can be the implications for innovation regimes of this transformations, combined with

the evolution of the financial system and the transformations of scientific institutions? The

study of the biotech sector can give us some insight into this complex questions.

17

II-2 Towards a new “science-based” system of innovation : the case of Biotech.

The case of biotech, now regarded as a quasi-autonomous and specific « industry » (with clear

distinctive features) provides a unique example of the way science based sectors evolve.

Moreover, this evolution raises the question wither a new “type” of science based sector is

emerging.

Grounded on a “scientific revolution” in the field of molecular biology, the biotech sector is

born basically in the academic laboratories, as “pure” (basic) science, mainly publicly

founded, and has grown up – just like most of the new branches of science -- in a typical

“open science” environment2. But soon (the end of the 1970’s and the 1980’s), the new

discoveries in the field of genetic engineering, gave rise in the United States, to a new type of

firms, which considered as a whole, where soon regarded as the core of a new very dynamic

and promising “industry”.

Thus, the relevant questions one has to answer are : how and why molecular biology has

given rise to a new and distinctive industry ? what are the specific features it has endorsed

and how can they be described ?Moreover taking into account these unique features (at least

new and original ones, compared to most of existing “classical” science based sectors), to

what extend the biotech sector can be regarded as a new type of science based sector ? Finally

: are these features condemned to stay “unique”, or do they announce the coming of a new

series (a new type) of science base sectors ?

To answer to these questions we have chosen first to try to concentrate on the “stylized facts”

typical of the sector. And then to propose a more theoretical view aiming at contrasting the

two models

A) Key stylized facts as regards Biotech According to most of observers, the emergence of the biotech sub-sector is at the crossroad of

the evolution of three types of events, each one influencing the direction taken by the others.

It is thus a perfect case where co-evolution developed in such a way that some strong and very

specific “complementarities” took shape, to finally give birth to a new sub-sector which can

also be regarded as a new type of science based model.

2 (In that case, note that the open science community was formalized inside the HGP).

18

If we concentrate on the basic stylized facts, the anatomy of the new model can be

reconstructed as follows.

1.Changes in the knowledge base : The development of molecular biology and genetic engineering and the birth of a new scientific and technological paradigm

The starting point is clear. To understand the birth of the new industry, one has first to refer to

scientific events that took place in the filed of molecular biology. The fact is that in the

postwar years, molecular biology (which was launched as an academic sub-field in the late

thirties, mainly in the most famous American universities) have undergone unprecedented

developments (Kenney, 1986, or more recently Henderson, Orsenigo and Pisano, 1999). It is

important to remember that the discovery of the structure and operation of DNA molecule in

1953 is traditionally considered as the scientific event at the origin of this tremendous growth

of the field of molecular biology by paving the way to a new "scientific paradigm" as defined

by Kuhn (Kuhn, 1953) 3. While, the new academic subjects opened by the discovery of the

structure of the DNA appeared, as new and full-fledged sources for knowledge and

discoveries, it is of key importance to note that this scientific breakthrough was soon followed

by a key invention which was going to mark the growth of molecular biology : the birth of

genetic engineering in the mid 1970’s4 that was expected, especially in the medical field, to

revolutionize the existing therapies and treatments and to constitute, in the medium-term, a

source for new and original products. Thus, according to Orsenigo, these new techniques in

the genetic engineering opened to a new "technological paradigm" (Orsenigo, 1989) . Those

discoveries are not solely related to traditional pharmaceuticals, but to the whole structure of

life (DNA) and, in that capacity, from the outset have an all-purpose vocation : from the

treatment of human diseases to staggering potential developments in the agro-business sector

through the selective setting-up of transgenic species and plants. Cross-breeding and cloning

are as much concerned as are all the applications related to human diseases. The economic

fall-out of such discoveries was very quickly predicted, and numerous incentives were

devised so as to urge universities to commit themselves to such activities and to foster the

3 According to Kenney : « The key discovery on the road to the creation of biotechnology occurred in 1953, when James Watson and Francis Crick correctly theorized the structure and operation of the DNA molecule » (Kenney, 1986, p.2). 4 Note that this birth is usually traced back to two main inventions. the r-DNA technique, developed in 1973 by Chang and Cohen at Stanford and Boyer at UCLA in San Francisco, and the Hybridoma technology employed in 1975 by Millstein and Kohler in Cambridge to produce monoclonal antibodies.

19

research for applications within newly set-up firms without clear-cut status, i.e. employing

academic researchers, mainly involved in basic research, but dedicated to commercial

activities (cf. the numerous and rich contributions gathered by Branscomb, Kodama and

Florida, 1999). As shown by many authors, the first company devoted explicitly to genetic

engineering was Genentech. Founded in 1976, this firm pioneered in the following years a

remarkable process of creation of new type of companies, specialized in research activities

and known as the new biotech firms (NBFs). According to Orsenigo, the emergence of these

new firms "was essentially an institutional response to the need for the transfer of scientific

discoveries to industry. The birth of the new companies was made possible, first of all by the

nature of the technological regime" (Orsenigo, id, p.123).

As we shall argue it, the view of the authors of this paper is somewhat different. In fact, it is

for us of crucial importance to note that the evolution of molecular biology that took place

firstly in the world of “open science” (see on this point Merton’s on Watson 1986, book), met

some dramatic changes in the field of intellectual property. It is one of the key hypotheses of

the authors of the present paper that these changes in the field of IP have opened the way to a

new trajectory and to the building of a new “autonomous” sphere of commercial activity. The

“technological” dimension of innovation regimes appears to be dependant from the

institutional setting in which it operates..

2. Intellectual Property : new “complementarities” between the Bayh-Dole Act and the Chakrabarty Ruling

By opening the way to the “commodization” of the new discoveries of the field, the changes

in the IP regime regarding living entities, are another key piece of the story of the emergence

and development of the biotech sector

The changes in the IP regime, were achieved through two complementary changes introduced

in the early eighties.

i) First of all, in the United States, where the first “hybrid” organizations designed for the

commercial exploitation of the new scientific discoveries were launched, the Bayh-Dole Act

opened the way a to new direction and future for the results of the basic research produced in

the academic laboratories. By opening the right to patent the results of publicly founded

research and to grant these results through exclusive licenses provided to private for-profit-

firms, the Bayh-Dole Act has dramatically modified the context in which the agents involved

20

in innovative activities used to operate. More specifically in “strongly” science based sectors,

where basic research is of direct relevance and application for innovation, for academic

scholars, the incentives to patent grew dramatically. As a consequence in most of the famous

universities, were installed special TTO’s (Technology Transfer Offices) which function is …

“to mediate the interface between university and industry through procedures of work

practices designed to enact university intellectual property and technology transfer policy”

(Owen-Smith and Powell, 2001). These practices were specially intense in the filed of life

sciences (Mowery et al, 1999, Mazzoleni and Sampat, 2002).

The Bayh-Dole Act, as well as the other regulations installed at that period5, largely favored

the “commodization” of those activities by fostering the setting up of new firms and the

registering of patents on discoveries and/or inventions related to molecular biology and

genetic engineering. Thus, were installed some of the key permissive conditions for the

emerging research domains related to genetic engineering, to be turned into effective

commercial economic activities

ii) At the same time, the Courts Doctrine regarding living entities took a new and dramatic

orientation. As soon as 1980 (the year of the passing of the Bayh-Dole Act) the Chakrabarty

Ruling, by introducing a new distinction between “products of man” and “products of

nature”), paved the way for a completely new doctrine as regards the patenting of living

entities6. The decision taken by the Supreme Court (obtained after many years of proceedings

and a very narrow 5 to 4 vote… ) was to lead to a completely new situation. By granting a

patent on a genetically modified organism (thus going back over a constant USPTO doctrine),

the Supreme Court of the United States opened the way to a complete swing, by making it

possible to patent scientific discoveries regarding “living entities”.

Other developments in this line are the Re Brana ruling of the CAFC, and later on, in

accordance with the new guidelines publicized by the US PTO (1995, and 2001), the granting

of patents to EST’s and human genes. Finally, most of the results of basic science research,

including “research tools” became patentable subject matter (Eisenberg, 1995, and 2000, Rai,

5 In fact the Bayh-Dole Act is just the most known of a series of new regulations installed by the Congress and aiming at bridging the gap between basic and academic research on one hand, industry and commerce on the other side. (Slauhgter and Roades 1996, Coriat and Orsi 2002)

21

2001, for a recent review of the US doctrine on living entities see Orsi 2002). Moreover this

possibility opened to patent small pieces of knowledge (separate gene fragments and so on

…) pushes towards a change in the technological regime, from a “discrete” to a “cumulative”

one.

Thus the conditions were set up for the development of an independent sphere of the division

of labor in various domains of activity. As a consequence of these changes, for the first time

in history, a series of new firms which central activity is basic research were installed and

launched in market activities. Table 4 gives an illustration of the type of activities of the most

recent generation of biotech firms, the so-called "genomic" firms all involved in basic

research on the human genome. It is important to highlight that their basic activity (discovery

of human genes and building of cDNA data bases) are exactly the same than the ones

achieved in academic laboratories

Table 4 Main US genomic firms founded in early 90' and currently listed on Nasdaq

Firms

Date of creation

Main Activities

Incyte Pharmaceuticals

1991 Databases of cDNA sequences

Millennium

Pharmaceuticals

1991 Discovery of human genes of

interest :

Obesity, diabetes, cancer, Psych.

Diseases, asthma ,osteoporosis

22

Myriad Genetics

1991 Discovery of genes involved in human

diseases :

Obesity, cancer, asthma

osteoporosis

cancer,

CNS disorders

Human Genome Sciences

1992 Databases of cDNA sequences

It is noteworthy however, that most of these new firms (as it is the case for the bio-tech sector

considered as a whole) were -- and still are -- loosing firms. Most of them have very few

products to sell, and their “revenues” (adding to the sales of the products effectively sold, the

other revenues coming from alliances with big pharmas) are far to cover their expenses.

Biotech Highlights 1996 - 1999 ($ billions)

1999 1998 1997 1996 Product sales 13.6 12 10.6 8.9 Revenues 18.8 16.6 14 11.5 R&D expenses 6.9 6.7 5.6 4.6 Net loss 3.1 1.9 1.8 2.2 Market capitalisation 97 93 83 52 Number of companies 327 317 294 260 Employees 114.000 106.000 94.000 73.000 Source : Ernst & Young, 1998 ; 1999

3. The key role of venture-capital, and the rise of a new mode of financing innovation.

The last stylized fact to consider concerns the way these firms are promoted and financed.

Here again it is noteworthy that a completely new engineering as regards the financing of

innovative activities was installed, so as to insure their launching.

Such opportunities, have been made possible only thanks to venture capital and later on to

specialized stock markets. The Genentech case can be taken as a model. In the case of

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Genentech : a group of academic researchers who had come across major discoveries (namely

Cohen and Boyer’s technique of rDNA) were sought-after by venture capital (Mr Swanson)

to launch a start up which, a few years later, achieved a spectacular IPO on Nasdaq. This case

was regarded as a model and, after Genentech, the whole biotechnology sector, later followed

by that of genomics, became self-supported sectors. It is noteworthy that in this process the

emerging biotech sector, born in the laboratories of American research universities, greatly

benefited from the networks already in place for financing computer start-ups (Kenny, 1986).

At the heart of such a model, lies the fact that new start up firms are established with venture

capital, after very specific “business models”. The aim of venture capital is to pave the way

for successful listings. The “business model” is thus set up after the idea that the firm holds

intangible assets and high-level “intellectual capital” (mainly based on patents and other

property rights on scientific discoveries) that will lead to future commercial products. The

research activity as such is sought after, to be promoted among potential investors.

Henceforth, the presence of well-known scientists (the famous “star scientists”) within those

new firms and their holding of a patent portfolio are the key elements in their setting up.

(Darby and Zucker et al …). However, according to their own claims venture capital is “…

not interested in just research proposals… [they] want a concept that evolves into a business

to customers” (quoted by Kenny, 1986, p.139)

To make such stories happen, a last series of institutional prerequisites were required. Indeed,

the problem was to ensure the listing of those peculiar firms that, year after year, would post

heavy losses instead of profits. This was achieved through a new regulation : the so called

“Alternative 2” installed on Nadaq in 1984. According to the new regulations, loosing

companies, if they could exhibit high “intangible assets”, could be launched through IPOs on

Nasdaq7

All those institutional changes, predicted as of the late 70s, and which had been entirely

carried out in the mid 80s, were to ensure both the rise of the Nasdaq and the emergence of

these new “science-based” firms, which most convincing illustration8 is provided by the new

bio-tech firms which started and developed at that period.

7 Note that about at the same period, the transformation of the « prudent man » legislation on pension funds was modified, in order to allow pension founds to penetrate those high-risk firms’ capital. A enormous flow of fresh financial capital was thus ready be invested in the new “start up” firms. More in this Orsi, 2001)

8 It is worth noting too that some sections of the software sector (notably in the case of firms specialized in the design non-embedded products) were developed after the same pattern. In this case, the specific nature of those

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As a conclusion for this section, it ought to be noted that if a change in the knowledge base is

certainly at the origin of the transformations, the formation of a specific” industry” could

occur and develop solely because of the powerful and continuous intervention of the state’s

visible hand (the Byah-Dole Act…), of regulators ( rôle of the NASD to install the Alternative

2 regulations) and of some key Courts rulings (from Chakrabarty to re Brana…). It is the

central thesis of the authors that without this powerful action of the visible hand of the

regulators, those activities would never have developed along the same trajectory.

B) Caracterizing the science based “2” model: additional remarks

The science based type “2” model as a specific mode of R&D organization …

Two traits here may deserve special attention

i) A distinctive feature of the science based type “2” model is the importance of basic

research conducted inside the firm. As explained by Cockburn, Henderson and Stern (1999):

“The nature of science-oriented drug discovery requires that firms become participants in

Science, in a wider sense, rather than just users of scientific knowledge”. To stay at high

competitive levels, the research performed inside the firm should be at the leading edge. This

objective is achieved in particular, as already mentioned, through the recruitment of high-

level researchers, the famous “star scientists”. Publication by the researchers is regarded as an

important objective for the firm. This situation leads to the adoption of “pro-publication”

incentives (Cokburn, Henderson and Stern, 1999), a type of incentives proper to the world of

open science, even if commercial benefits continue to be the main goal pursued by the firms.

It is here interesting to notice that in this model individual skills are regarded as a key factor

of R&D efficiency. The reasons of such a system are diverse. It is a way to maintain

continuous relations with universities and public research institutions, with academic scientist,

and to have access to the most advanced “external” research. Often the relations with

firms as an independent branch of labor division was made possible only thanks to a new change in the field of IPR’s. Indeed, the IPR’s granted to algorithms, (or even to systems of simultaneous mathematical equations), has created, once again, the conditions for the emergence of a commercial sector of activity that is separated from the research core. Firms whose main activity is to design new computer program could thus emerge and develop.

25

university teams transforms the university’s rôle from that of producing “public goods” for

the well being of the general society “…to a function more akin to a leased research team”

for the benefits of private-for-profit companies (Kenny, 1986, p.89). But another dimension

deserve attention. Publications, and the presence of star scientists are often essential for the

technological reputation and credibility of a firm, in a context where the characteristics of the

technological trajectory makes the evaluation of R&D efficiency, its potential effects on

innovations and market success, particularly difficult. This aspect can be important in relation

with the question of financing. As noted by Darby, Liu and Zucker (1999): “Average investor

[…] can observe the indicators on the firm’s intellectual human capital that may contain

useful information about the firms’ current technology status and potential future

development”9.

This aspect can be understood only by considering a key dimension of the division of labor in

research, specific to this model: the existence of firms specialized in (basic) research : quite

all the new biotech firms are of that type. As seen before, the creation and the development of

this type of firms has been made possible only by crucial change in the rules governing

patents law on one side and the functioning of financial markets on the other side.

ii) Relations between small and medium-sized firms and big firms

One of the most striking features of this system is that it is based on the existence of small and

medium-sized firms whose main activity is focused on research. They can avail themselves of

few or no real commercial products as to ensure their financial independence. Most of them

are showing a loss. Nevertheless, they are promoted by (and on) financial markets : their

assets, mainly “intangible”, are made of 1) their « intellectual capital” and research teams

organized around the reputation of some “star scientists”, 2) the patents and other registered

IPR’s on discoveries and likely to be subsequently converted into rents.

It is then not surprising to verify that the whole sector cannot balance its expenses by its

revenues. It is noteworthy that the biotech and genomics firms can continue their operations

only thanks to their contracts and alliances with the pharmaceutical giants (see Figure 1), the

latter obviously having a strongly ambivalent behavior when dealing with the most recently

born biotech firms. On the one hand, the big pharmas finance, (through equity and contract

9 Darby, Liu and Zucker find a positive correlation between the number of stars and the market value of high-tech firms’ market value. It seems possible to give two interpretations of this observation: (i) the probability of successful innovation is really related to the number of star scientists, or (ii) the investors are believing that the probability of successful innovation is related to the number of star scientists.

26

alliances) the new start-ups, and even more established biotech firms, because the later play

the role of pilotfish in the exploration of the frontier of knowledge for major pharmaceutical

companies. But on the other hand, the big laboratories that are the only ones to possess the

size and skills to exploit this knowledge are intent on protecting their monopolies and power.

One might assume that they are in condition to avoid any type of overlapping of borders that

would threaten them 10. Except in very rare cases, the alliances between big pharmas and the

new firms are to be found at the early stages of the innovation process, at the stage of

"discovery" (cf. Figure 1).

These data highlight the key role played by big firms and their laboratories.

10 It is worth noting that in the field of plant genetics, the current model is mostly the big firm’s which, after a series of takeovers, has managed to control not only the exploitation of innovations but also the design of new transgenic seedlings and seeds (cf. Monsanto’s case). So, the “start up” model is far for being the only way possible to capture the benefits of the genetic revolution.

Taking into account these considerations, the empirical elements that are available lead to think that the Science-Based 2 model can also be regarded as sub-system operating within larger sectoral systems as well as a full-fledged “model”.

27

Figure 1

Comments :

2 points may deserve special attention i) the growing number of contracts: from 1988-1990 (85 contracts) to 1997-1998 (226 contracts), which means a more and more deep engagement of the big pharmas in the financing of the biotech firms; ii) the fact that along the time this engagement occurs more and more early in the life cycle of the products : it as at the stage of "discovery" that most contracts are passed. It is also important to note that 78% of the contracts are based on exclusive licenses

… And as the outcome of specific “institutional complementarities”

As we have argued it before, those activities would never have developed along the same

trajectory, without the powerful action of “the visible hand” of many institutional actors.

To be more precise, the view of the authors is that a series of institutional changes

introduced in different domains and at different levels of the American NSI (namely in the IP

regime and in the financing of innovation) matched ones with the others, in such a way that

they finally opened for the agents new opportunities. A situation that Aoki characterizes as

one where “institutional complementarities” arise (Aoki 2000). On this point, Amable put the

emphasis on the fact that : “The concept of complementary institutions is based on

multilateral reinforcement mechanisms between institutional arrangements: each one, by its

existence, permits or facilitates the existence of the others. …. The constraints and

28

possibilities defined by a given institution favour other institutions’ functioning” (Amable

2001).

These complementarities are indeed the combined outcome of explicit “visions”’ and actions

of the public authorities and agencies in charge of implementing the ‘rules of the game”, and

of emergent properties of complex systems where agents interact. So, in various stages of

their respective evolutions, the systems of resources and constraints provided by given NSI’s

are unevenly favorable and conducive to the deployment of the strategies of the various types

of agents and actors engaged in innovative activities. Thus, the biotech case provides a typical

case of co-evolution of knowledge base and institutions.

From a situation dominated by the rules of open science, the evolution lead to a situation

marked by a regime of strong appropriablity of the outcomes of basic research. (more on this,

on the following Table 5 )

Table 5

Main oppositions between the Science Based « 1 » and « 2 » Models

Science based « 1 » Science Based « 2 »

R&D and characteristics of the knowledge base

Publicly Founded Basic Research in Universities and Public Labs

Some « in-house » basic research inside large corporations

Research units inside large corporations oriented towards « applied » research and Development

Idem

+

SME’s specialized in basic research

Research Networks

29

IP regime

« Open science »

« Secret » « patents » and « lead time » as means to protect inventions

« Patent intensive »

patents on genes, EST’s “research tools” and so on…

Financing of innovation

In large corporations : no specific means to finance innovation as such

Venture capital for SME’s specialized in Development

SME’s specialized in basic research and promoted by Venture capital + Nasdaq

Alliances with large corporations

TO CONCLUDE : BEYOND THE BIOTECH MODEL To conclude we shall try to summarize the specific features of the “science based 2” model,

and then raise two questions about the implications of this analysis.

Considering the key characteristics of the biotech sector, it is possible to highlight a very

specific and original science based model. As illustrated by the Table 5 above, in many

respects, the new model endorses very specific traits if it is compared to the patterns of

innovation prevailing in traditional science based sectors.

The central novelty of the new model consists in SME’s specialized in basic research, which

are producing and selling scientific knowledge. The creation of such firms was made possible

by the design and the implementation of new financial regulations (in particular, in 1984, the

so called “Alternative 2” on Nasdaq, opening the way to a “finance driven model of

generation of innovation” (Coriat and Orsi 2002).

The commodization of basic knowledge is at the heart of such a model. It has been achieved

through key institutional provisions, and, first of all, by the extension of the scope of the

patent system, as regards : i) what can be patented (not only inventions, but also basic or

“generic” knowledge) and ii) who can patent (not only individuals and firms, but also

academic institutions). These institutional changes appear to be connected to a profound if not

radical change in the academic science system. The later assumed dramatic deviations from

the usual rules and practices of the “republic of science”, and from the prevailing division of

labor in research between public and private institutions.

Moreover, the new model can be seen as the combined outcome of two general tendencies: i)

a process of extension of “marketization” to new types of goods and services (at the expense

of non-market organizations and institutions), and more particularly the marketization of

30

knowledge; and ii) the “financiarization” of production systems and firms. The creation of

new institutional complementarities, and new rules of behavior have thus been the necessary

conditions for the development of this new regime.

Two questions need a further and deeper investigation

a) Is this model specific to biotechologies or can it be extended to other fields?

Without pretending to give here a definitive answer to this complex question, let’s just remark

that, as just explained, this new system is an expression of profound and general tendencies.

It is based on institutional changes which have the vocation to be applied in other fields of

science and industry. It concerns in particular the transformation of academic institutions, the

extension of the patent system, and the opportunity opened by the new financial system.

In particular, if the biotech regime has been based on the possibility to patent and to

commercialize basic scientific knowledge, it seems possible to conceive, in other domains, the

creation of firms based on the patenting of similar knowledge, (for example on mathematical

algorithms), or to different types of knowledge, notably generic applied knowledge (like for

example “business methods”). What remains to be explored are the implications of the

extension of patenting for innovations regimes, in different fields and sectors (and in counties

others that US!), without forgetting that these implications cannot be fully understood without

considering institutional complementarities.

b) The second question is relative to the future of the regime we have described. Is it just a

transitory configuration, the first phase of the industry life cycle, or a long lasting innovation

regime?

In our view, even if the precise configuration of the biotech industry can of course change in

the future, it will not come back to the classical situation prevailing in other science based

industries (marked by the predominance of large integrated firms). This, precisely because the

structure of the biotech sector cannot bed explained only by the fact that it consists in a new

activity (its structure differing from the structure of other “new” sectors in the past). We argue

in this paper that that the emergence of the biotech sector was driven by a series of radical

and “complimentary” institutional changes which are probably, at least for a near future,

irreversible. The key question is thus to know how will evolve the new institutional system

31

upon which the new regime is based. Or to put in other words : is the new model sustainable?

The strong interrogations about the implications for innovation of the new characteristics of

the patent system, (opening to the “tragedy of the anti-commons” (Heller and Eisenberg,

1998) and/or to the risk of hold-ups (Shapiro, 2001), as well as, if we consider financial

dimension, the recent evolution of the Nasdaq, make that question particularly crucial.

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