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Investigating the adoption of open Adoption of open

innovation
innovation in the
bio-pharmaceutical industry
285
A framework and an empirical analysis
Davide Chiaroni, Vittorio Chiesa and Federico Frattini
Dipartimento di Ingegneria Gestionale, Politecnico di Milano, Milano, Italy

Abstract
Purpose – The purpose of this paper is to focus on the adoption of the open innovation paradigm in
the bio-pharmaceutical industry and investigate through which organisational modes (e.g.
collaborations, in- and out-licensing) open innovation has been implemented and how these modes
are interwoven with the different phases of the drug discovery and development process. Open
innovation is currently one of the most debated issues in management literature. Few contributions,
however, have paid attention so far to systematically and longitudinally addressing the adoption of
open innovation in a specific industry.
Design/methodology/approach – A two-step research strategy has been adopted. First, a panel
study of top industry representatives was organised to operationalise the concept of organisational
modes of open innovation in the bio-pharmaceutical industry. Second, the open innovation modes used
by the first 20 pharmaceutical biotech firms worldwide have been documented over the period
2000-2005 in the various phases of the drug discovery and development process.
Findings – A framework of analysis, establishing the relations between open innovation modes and
the phases of the drug discovery and development process, has been developed and assessed in the
industry, allowing the determinants of adoption of different modes and their managerial implications
to be discussed and to relate them to the peculiarities of the biotech industry.
Originality/value – The paper contributes to the ongoing debate on open innovation by
representing one of the first attempts to systematically and longitudinally assess the extent and
particularly the determinants of the adoption of open innovation in a specific industry.
Keywords Innovation, Biotechnology, Research and development, Italy
Paper type Research paper

1. Introduction
The external environment in which firms have been competing in the last decades has
profoundly evolved, both in high-technology and in more mature industries, as a result
of increased dynamicity and turbulence (Wolf, 2006), the globalisation of markets and
business activities, accrued competition (Gupta and Wilemon, 1996), and rapid
advances in technology development (Bayus, 1994). Accordingly, a significant change
in the way in which companies manage the technological innovation process has
occurred as well. Since innovation is often the single most important driver of economic
value creation, most innovative and successful firms have adapted indeed their
approach to innovation management to the changing external environment, in an European Journal of Innovation
attempt to protect or nurture their competitive advantage. This has resulted in the end Management
Vol. 12 No. 3, 2009
of the linear model of innovation (Ortt and Smits, 2006), an increased reliance on pp. 285-305
q Emerald Group Publishing Limited
external sources of technology (Chatterji, 1996; Roberts, 2001), the use of multiple 1460-1060
channels for technology exploitation (Lichtenthaler, 2004), the birth and growth of DOI 10.1108/14601060910974192
EJIM markets for technology (Arora et al., 2001) and the internationalisation of R&D and
12,3 innovation activities (Jones and Teegen, 2002).
These foremost changes in technology management have been carefully studied by
Henry Chesbrough (2003a), who has systematised them into an insightful paradigm
labelled “open innovation”, which has rapidly become one of the most debated concepts
by management scholars (Haour, 2004; West et al., 2006; Chesbrough et al., 2006;
286 Dogson et al., 2006; Gassmann, 2006). According to Chesbrough (2003a), companies
have historically invested in large R&D functions to nurture innovation and sustain
growth. This “closed innovation” is “a view that says successful innovation requires
control. Companies must generate their own ideas, and then develop them, build them,
market them, distribute them, service them, finance them, and support them on their
own”. This logic is no longer sustainable in many competitive situations where some
“erosion factors” are in place (i.e. the growing mobility of highly experienced and
skilled people, the increasing presence of private venture capital, the existence of a
market for technology). In these cases, a new approach is emerging, that assumes that
firms “can and should use external ideas as well as internal ones, and internal and
external paths to market” (Chesbrough, 2003a) as they look to advance their
technology. In other words, the open innovation model implies that valuable technical
ideas may originate from inside or outside the company as well, and that the
innovation-to-cash process can follow both internal and external paths.
The issue of whether open innovation should be considered as a new paradigm for
managing innovation or not is still debated in the literature. On the one side, some
authors (Herzog and Lecker, 2007; Bröring and Herzog, 2008; Ortt and van der Duin,
2008) suggest that open innovation simply represents an evolution of the so called fourth
generation innovation management model (Niosi, 1999), where the routines designed for
making R&D activities more flexible include new practices for accessing the knowledge
of users, suppliers and competitors and for exploiting internal knowledge. Similarly, they
advance that open innovation can be seen as basically a holistic approach to innovation
management that systematically encourages access to external sources, both for
generating and exploiting business opportunities. These arguments are generally
supported by empirical evidence collected in technology intensive industries (such as
biotechnology) where the “open” or “network” approach to innovation is particularly
common (Powell et al., 2002). On the other side, however, Chesbrough and other authors
(Chesbrough et al., 2006; Lichtenthaler and Ernst, 2007; Maula et al., 2006; Maurer and
Scotchmer, 2006; West and Gallagher, 2006; Perkmann and Walsh, 2007) further
inquired into the theoretical antecedents and implications of open innovation. They show
that open innovation accounts for anomalies in the management of innovation that are
not fully explained in earlier paradigms (Kuhn, 1962) and therefore it should be
recognised as a truly new paradigm for industrial innovation. In fact, open innovation:
.
requires a firm to effectively inflow and integrate into its innovation processes
knowledge from actors outside its boundaries (e.g. Universities, competitors,
suppliers, clients), giving to the external knowledge an “equal role” to that
afforded to internal knowledge by earlier approaches (Chesbrough et al., 2006);
.
requires changes to be promoted and coordinated contemporarily at the level of
its external (e.g. network of inter-organisational relationships) and internal (e.g.
roles and responsibilities) organisation;
 .
forces the development of new collective cognitive processes (e.g. to overcome the Adoption of open
Not-Invented-Here and Not-Sold-Here syndromes) as well as the introduction of innovation
new structures and management systems;
.
gives to the firm’s business model a key role, as it represents the cognitive device
through which the firm elaborates its decisions about innovation.
These anomalies are more evident in technology intensive and high tech industries. 287
The paper, following the second line of reasoning mentioned above, focuses on the
adoption of the open innovation as a new innovation management paradigm in the
biotechnology (pharmaceutical) industry. Besides studying the extent to which biotech
companies have conformed to the open innovation philosophy, the authors are
interested in understanding through which organisational modes the latter has been
implemented and how these modes are interwoven with the different phases of the
drug discovery and development process. As it will be discussed ahead in the paper, it
is believed that the biotechnology industry is a fertile ground for the diffusion and
hence for the study of the open innovation model.
The paper is structured as follows. The next section reviews literature about the
implementation of the open innovation paradigm, with a focus on the biotechnology
industry, whereas the third one describes the research strategy adopted in the paper.
The fourth section reports and discusses the results of the empirical analysis; finally,
some conclusions and future directions of research are outlined.

2. Implementing open innovation in biotechnology: a literature review

As pointed out in the previous section, open innovation has been extensively debated
by academic and managerial literature in the last years (for an up-to-date bibliography
on this issue see the web site: www.openinnovation.net). Nevertheless, two relevant
gaps can be identified that are relevant in light of the purpose of this paper:
(1) the lack of contributions that systematically and longitudinally assess the
extent and the determinants of diffusion of the open innovation paradigm in a
specific industry;
(2) the scarce attention dedicated to study the organisational and managerial
implications of this new paradigm.

As far as the first literature gap is concerned, Chesbrough (2003a) supported the
development of its open innovation model through the analysis of the innovative
behaviour of several firms belonging to high-technology industries, e.g. Lucent, 3Com,
IBM, Intel, Millennium Pharmaceuticals. More recently, a work by Chesbrough and
Crowther (2006) investigate the diffusion of open innovation concepts in more
traditional sectors. The authors interview vice presidents for R&D or business unit
executives of 12 companies working in mature and/or asset-intensive industries, such
as chemicals, consumer packaged goods, thermoplastics, inks and coatings, and
conclude that certain open innovation concepts are finding application also in these
contexts, this suggesting a broader applicability of the open innovation paradigm than
that implied by the first book by Chesbrough (2003a). Christensen et al. (2005)
investigate the open innovation model from an industrial dynamics and applied
evolutionary economic perspective, focusing on a specific sectoral system of
innovation (i.e. consumer electronics) and studying the industrial dynamics
EJIM associated with the development of the class D amplifier technology. As a result, the
12,3 authors are able to document the determinants of more or less open modes of
innovation associated with the industrial dynamics of this specific industry segment
undergoing a phase of radical technological innovation. Other authors (West and
Gallagher, 2006; Vujovic and Ulhoi, 2008) study the strategies that firms involved in
open-source software development employ for addressing some key challenges implied
288 by the open innovation paradigm, i.e. finding creative ways to exploit internal
innovation, incorporating external innovation into internal development and
motivating outsiders to supply an ongoing stream of external innovations. In
particular, West and Gallagher (2006) document the existence of four basic strategies,
i.e. pooled R&D/product development, spinouts, selling complements and attracting
donated complements, and discuss their generalisability to other industrial sectors.
Finally, O’Connor (2006) revises the data collected in the long lasting research program
on Radical Innovations at the Rensselaer Polytechnic Institute, to discuss how firms
that are pursuing radical innovations adopt certain principles of open innovation.
Besides these contributions, literature has not systematically investigated so far how
industry-specific factors can influence the effectiveness and the determinants of
adoption of open innovation, although this would be a crucial prerequisite for
enhancing the external validity of the paradigm.
As a result of this gap in the extant literature, the adoption of open innovation in the
biotechnology industry has not been addressed in literature so far. Besides sparse
anecdotic evidence, such as the interesting case of Millennium Pharmaceuticals,
reported in Chesbrough (2003a), to the best knowledge of the authors there is only one
contribution (Fetterhoff and Voelkel, 2006) that is specifically focused on this issue.
This contribution advances a model of the external innovation value chain, that
encompasses five key stages:
(1) seeking opportunities;
(2) evaluating the market potential and the inventiveness of a given opportunity;
(3) recruiting potential partners by building a convincing argument;
(4) capturing value from commercialisation; and
(5) extending the innovation offering.

This model should help biotechnology firms capture the full value of partnerships with
external technology providers, and is supported through examples drawn from Roche
Diagnostics’s experience. Despite this gap in the literature, the biotechnology and,
especially, the bio-pharmaceutical industry, show several characteristics that make
them a fertile ground for the diffusion of open innovation and hence for the study of its
managerial and organisational implications. In this respect, it is worth mentioning its
extraordinarily technology intensity (DeCarolis and Deeds, 1999), the complexity of the
innovation process and the heterogeneity of the competences it requires (Koput et al.,
1996), the importance of technology transfer mechanisms for the development of the
industry as a whole (Madhok and Osegowitsch, 2000), the intensity of the relationships
between biotechnology firms, Universities and research centres (Owen-Smith et al.,
2002) and the birth of a venture capital market, at least in Anglo-Saxon countries,
specialized in supporting biotech ventures (Powell et al., 2002).
 As far as the second gap in the extant literature is concerned, it should be Adoption of open
noted that the open innovation paradigm, as discussed by Chesbrough and innovation
colleagues, has a very general nature, since it basically captures the underlying
logic at the roots of most innovative firms’ choices in the area of technology
management; anyway, companies that are willing to implement the open
innovation “philosophy” need to select specific organisational modes through
which to lever their knowledge-abundant external environment. Scholarly literature 289
has not addressed this issue systematically and in-depth so far, besides a few
attempts by Chesbrough himself to discuss the intellectual property strategies
(Chesbrough, 2003b) and the performance metrics (Chesbrough, 2004) that are the
most appropriate for supporting open innovation, and a work by van de Vrande
et al. (2006) who study the criteria affecting the choice of the governance modes
for external technology sourcing from an open innovation perspective. Moreover,
anecdotic evidence is available about how most innovative and successful
enterprises have been managing and organising their transition toward open
innovation. For instance, Huston and Sakkab (2006) describe the different types of
networks and the strategic planning process which are at the heart of Procter &
Gamble’s open innovation approach, which is called “Connect & Develop”; Haour
(2004) documents the organisational modes that Generics applies for sustaining its
“distributed innovation” system; Kirschbaum (2005) explains how the multinational
life cycle and performance materials company DSM has built a teamwork and an
entrepreneurial culture for opening up its innovation process. Nevertheless, a
structured theory of the managerial and organisational enablers of the open
innovation paradigm has not been developed yet. In this paper, particular
emphasis will be put on the analysis of the organisational modes through which
firms can open up their innovation process to the external environment. In this
respect, it is necessary to distinguish between, and to contemporarily account for,
the two sides of the open innovation model, as suggested by Chesbrough and
Crowther (2006):
(1) “inbound open innovation”, which is “the practice of leveraging the discoveries
of others” and entails the opening up to, and establishment of relationships
with, external organisations with the purpose to access their technical and
scientific competences for improving its own innovation performance;
(2) “outbound open innovation”, which suggests that, “rather than relying entirely
on internal paths to market, companies can look for external organizations with
business models that are better suited to commercialize a given technology”.

In other words, it is the practice of establishing relationships with external

organisations with the purpose to commercially exploit technological opportunities.
Examples of organisational modes for “inbound open innovation” are: licensing in,
minority equity investments, acquisitions, R&D contracts and research funding,
alliances, networking. Examples of organisational modes for “outbound open
innovation” are instead: licensing out, spinning out of new ventures, sale of
innovation projects, provision of technical and scientific services, corporate venturing
initiatives.
In conclusion, this brief literature review highlights the potential relevance of the
managerial and research implications of this paper, which is aimed at investigating the
EJIM determinants of the adoption of open innovation by bio-pharmaceutical firms and the
12,3 organisational modes through which they open up their innovation process to the
external environment.

3. Research methodology
In order to achieve the aforementioned objectives, a two-step research strategy has
290 been adopted. The aim of each step can be described as follows:
(1) to operationalise the concept of open innovation in the bio-pharmaceutical
industry, taking into account the peculiarities of innovation activities
undertaken by biotech companies;
(2) to apply the framework resulting from the previous step to a longitudinal and
extensive empirical set.

As far as the first step of the research is concerned, a panel study was organised,
involving 20 people (business development managers, R&D directors, Chief Executive
Officers of biotech companies, as well as academics and consultants with a significant
experience in the field) among the most representative of the Italian biotech industry.
The full list of participants in the panel study is reported in Table I.
Because of the paucity of research into the adoption of open innovation in the
bio-pharmaceutical industry, we decided to carry out a panel study, following the
recommendation of Yin (2003), to increase the validity of the framework used to
inform the ensuing quantitative analysis. As acknowledged by other studies in
related disciplines (e.g. Blanton et al., 1992; Hambrick, 1981), the use of an expert

Name Position (organisation)

Luca Benfatti Chief Executive Officer (Newron)

Karima Boubekeur Head of External R&D Policy (Roche)
Fabrizio Conicella Business Development Manager (Bioindustry Park Canavese)
Lucio da Ros Manager (GlaxoSmithKline)
Marina del Bue Chief Executive Officer (MolMed)
Laura Ferro Chairman and Chief Executive Officer (Gentium)
Giovanni Gaviraghi Chairman and Chief Executive Officer (Siena Biotech)
Luca Liberatore Corporate Affaire Director (Amgen)
Ennio Ongini Chief Executive Officer (NicOx)
Stefano Milani Chief Executive Officer (Blossom Associates)
Holger Neecke Business Development Manager (MolMed)
Rodolfo Paoletti Director (Department of Pharmacological Sciences - Università degli Studi
di Milano)
Danilo Porro Full Professor (Department of Biotechnology - Università degli Studi di
Milano-Bicocca)
Alvise Sagramoso Chief Executive Officer (Bioxell)
Julia Schuler Senior Industrial Specialist - Health Sciences (Ernst&Young)
Francesco Senatore Business Development Manager (Toscana Life Sciences)
Alessandro Sidoli Chief Executive Officer (Axxam)
Table I. Mark Supekar Life Science Senior Consultant (ATA – Advanced Technology Assesment)
List of participants in the Salvatore Toma Director R&D (MolMed)
panel study Leonardo Vingiani Director (Assobiotech – Italian association of biotech companies)
panel allowed us not only to identify different organisational modes of open Adoption of open
innovation in bio-pharmaceutical firms but also, and more importantly, to provide innovation
an explanation and an interpretation of the evidence collected through the
quantitative analysis, thanks to the familiarity of the experts with the industry’s
dynamics.
Two rounds of interviews have been conducted directly by the authors to
accomplish a main task, respectively: 291
(1) To distinguish, on a shared and initially validated model of the drug discovery
and development process in the bio-pharmaceutical industry, the phases of the
process where each of the two dimensions (“inbound” and “outbound”) of open
innovation is expected to impact and the organisational modes of open
innovation (chosen from the ones identified by the literature) that are
consequently more suitable to be implemented by biotech firms.
(2) To discuss the reasons and the determinants explaining the choices of biotech
firms in terms of organisational modes for open innovation, on the basis of the
characteristics and peculiarities of the bio-pharmaceutical industry.

In the second step of the research, we selected the first 20 pharmaceutical biotech firms
worldwide (considering their market capitalisation at the end of December 2006, see
Table II) and, for each company, we documented the open innovation modes they used
in the various phases of the drug discovery and development process. Further details
about the empirical investigation and concerning: the selection of the sample; the time
period covered in the analysis; the type of data collected; and the data sources, are
provided below.

Market capitalisation
Name 29 December 2006 ($billion)

Genentech 85.8
Amgen 85.7
Gilead Sciences 32.0
Celgene 19.8
Genzyme 17.7
Biogen IDEC 17.7
Serono 12.7
Medimmune 7.9
Elan 5.8
Amylin Pharmaceuticals 5.6
Vertex Pharmaceuticals 5.0
Cephalon 4.8
Millennium Pharmaceuticals 3.6
ImClone Systems 2.7
PDL BioPharma 2.6
Human Genome Sciences 1.7
MEdarex 1.7
Alkermes 1.6 Table II.
BioMarin Pharmaceuticals 1.6 List of companies in the
MGI Pharma 1.5 sample
EJIM First, it is worth mentioning that the selection of the top 20 biotech firms in terms of
12,3 market capitalisation is consistent with the purpose of the paper for a twofold reason:
on the one side, companies listed on public stock exchange markets have to disclose
information about their R&D activities (as for their impact on the share value) and this
allows to access relevant information on the organisational modes for open innovation;
on the other side, firms in the sample represent the top players in the industry and are
292 therefore more suitable to highlight relevant trends and best practices in the
management of the innovation process. The time period chosen for the analysis covers
the years from 2000 to 2005, in the attempt to balance the relevance of the collected
information for the research objective with the efficiency of data gathering procedures.
Moreover, it is to state that the year 2000 represents in almost all the cases the last year
where documentations and archival records for the firms in the sample are available.
The collected data concern:
.
the number and typology of different organisational modes (as identified in the
research framework developed through the panel study) adopted by the firms;
.
the phase of the drug discovery and development process each of the above
modes refers to;
.
the typology of partner involved (pharmaceutical firms, biotech firms –
accordingly to the widely acknowledge distinction between product and
platform firms (Chiesa and Chiaroni, 2004) – , Universities and research centres);
.
the therapeutic area (where applicable and following the classification proposed
by the Biotechnology Industry Organisation) within which the object of the open
innovation relationship can be classified (i.e. the target disease of a new drug).

As primary source of data, the annual reports of the selected firms in the time period
2000-2005 have been analysed. Nevertheless, in order to validate the gathered data,
they have been triangulated with information drawn from professional databases and
reports (Recombinant Capital, Biospace Directory, Canadian Biotech).
Finally, as far as the reliability of the data is concerned, it is should be highlighted
that, for the purpose of the paper, the identification of general trends is far more
relevant than the completeness of the information for each single firm. Indeed, even if
completeness might be ensured by the fact that firms in the sample are listed on public
stock exchanges, it is anyhow reasonably to expect that if there are omissions they are
equally distributed in the sample, this not affecting the results of the analysis.

4. Putting open innovation into action

In this section of the paper the results of the empirical investigation are presented.
Specifically, in the next paragraph the framework of analysis developed through the
panel study is described; the outcome of the longitudinal inquiry is discussed at length
in the second part of the section.

Open innovation in biotech: a framework of analysis

During the first round of interviews, participants in the panel study were first asked to
agree on the structure of the drug discovery and development process in the
bio-pharmaceutical industry as it is reported in the literature (Muffatto and Giardina,
2003; Chiesa, 2003; Chiesa and Chiaroni, 2004; Gassmann and Reepmeyer, 2005;
Chiaroni et al., 2007). The aim was to reach a consensus about which specific phases Adoption of open
should be included in the framework for the subsequent analysis of the open innovation
innovation paradigm’s diffusion and implementation. The structure of the process the
panel of experts agreed on is reported in Figure 1.
A brief description of the phases included in the framework follows:
(1) Target identification and validation. Target identification has the purpose to
identify a gene or a protein or a sequence of both (target), that is thought to be 293
the pathogenic of a selected disease. It is followed by target validation, which is
concerned with the study of the identified target with the purpose to:
.
define the interactions between the target and the whole human organism;
and
.
check if there are some intellectual property rights on the selected target,
through accessing public databases (e.g. the NCBI in USA).
(2) Lead identification and optimisation. After the genetic base of the disease’s
evolution is known, scientists need to identify the compound that has the
desired effects in treating the selected disease (lead identification). This
compound represents the active principle of the future drug. The lead
optimisation activity, finally, adds to the lead the necessary excipients (i.e.
substances included in the drug formulation) in order to protect, support or
enhance the stability of the active principle and to increase patients’ compliance.
(3) Pre-clinical tests. This first development activity studies, especially through in
vivo testing, the mechanisms of absorption, distribution, metabolism, excretion
and toxicology of the new drug, with the purpose to evaluate its effects on
animals. Before entering clinical trials, a first approval by the public authorities
is required.
(4) Clinical tests. These trials directly involve human patients and are usually
divided into three steps: Phase I, Phase II and Phase III. According to the
procedures set by the US FDA (Food and Drug Administration, see also the
guidelines available at: www.fda.gov/cder/guidance), in Phase I, researchers
test the new drug in a small group of people (20-80) to evaluate its safety and to
determine a safe dosage range. In Phase II, the new drug is given to a larger
group of people (100-300) to evaluate its effectiveness in patients with the
disease and to determine the common short-term side effects and risks. Finally,
the Phase III involves an even larger group of people (1,000-3,000) to confirm the
effectiveness of the new drug and to evaluate its overall benefit-risk ratio. If all

Figure 1.
Structure of the drug
discovery and
development process in
the
biotech-pharmaceutical
industry for subsequent
analysis
EJIM the three phases are successful, public authorities approve the new drug, that
12,3 can reach the market.
(5) Post-approval activities. These comprise the purchasing, production, logistics,
marketing and sales and post-marketing tests for the new drug. In particular,
post-marketing tests involve the monitoring of the drug’s performance along its
whole life-cycle, with the purpose to delineate additional information on its
294 risks, benefits and optimal use in the middle term.

“Inbound” and “outbound” organisational modes for open innovation were then
discussed, with the purpose to spot which specific modes are used by pharmaceutical
biotech firms along the different phases of the development process. The interviewed
experts recognised that “inbound” open innovation takes place mainly in the first
phases of the drug discovery and development process, i.e. target identification and
validation, lead identification and validation and pre-clinical tests. In other words, it is
chiefly in these stages that biotech companies enter in contact with external
organisations for leveraging on their innovation efforts and accessing their highly
specialised knowledge and competences. Instead, “outbound” open innovation takes
place mainly in the second part of the process, i.e. in the clinical tests and post-approval
activities. It is in these stages, in other words, that biotech firms generally open up to
external organisations for commercially exploiting the results of their innovation
activities. This suggests the opportunity to distinguish between two distinct
macro-phases in the pharmaceutical biotech drug discovery and development process,
called “generation” of innovation, where inbound open innovation prevails, and
“exploitation” of innovation, where outbound open innovation is mainly focused (see
Figure 2).
The transition from pre-clinical tests to clinical ones was identified as the
separating point between the generation and the exploitation phases. Because of the
intrinsic characteristics of the biotech innovation process, in fact, it is only at the
end of the pre-clinical tests that the candidate acquires the properties that allow it to
be commercially exploited. Before this point, the drug discovery and development
process is mainly a “trial-and-error”, internal effort, characterised by extremely high
uncertainty levels and unpredictable outcomes. Once the first approval from the
public authorities is obtained, at the end of pre-clinical tests, development risk
lowers, the process becomes much more formalised and externally visible. It is at
this point, therefore, that opportunities for external commercial exploitation can be
identified and pursued. Nevertheless, the interviewed experts recognised a certain
degree of overlapping between the generation and exploitation phases (see Figure 2).

Figure 2.
Generation and
exploitation of innovation
in the pharmaceutical
biotech drug discovery
and development process
This is due to the fact that, according to the characteristics of the drug under Adoption of open
development: innovation
.
commercial exploitation sometimes can start earlier than the end of pre-clinical
tests (e.g. out-licensing of a candidate that has not completed these trials yet);
.
the leverage on the innovative efforts of others can continue beyond this limit (e.g.
in-licensing of a candidate that has already ended-up the phase I of clinical tests).
295
Moreover, the panel study discussion allowed us to identify the organisational modes
for open innovation that pharmaceutical biotech firms use along the phases of the drug
discovery and development process:
(1) Open innovation modes for the generation of innovation:
.
Collaboration for the generation of innovation. In this case the biotech firm
establishes a partnership (without equity involvement) with other biotech
firms, pharmaceutical companies, Universities or governmental research
centres, in order to pursue a common innovative objective (e.g. the validation
of a genetic target).
.
Purchase of scientific services. The biotechnology firm externalises to a
specialised provider a specific phase of its innovation process (e.g. the lead
optimisation activity), under a well-defined contractual agreement (for further
details on the role of technical and scientific services see Chiesa et al., 2007 or,
with a more specific focus on the biotech industry, Chiaroni et al., 2007).
.
In-licensing. The biotechnology company acquires the rights to use a specific
candidate from another biotech firm, a pharmaceutical company and,
sometimes, a University.
(2) Open innovation modes for the exploitation of innovation:
.
Collaboration for the exploitation of innovation. In this case the biotech firm
partners with another company (a biotech firm or, more often, a big pharma)
for accessing some complementary asset (e.g. production capacity or
distribution channels) required to commercially exploit the new drug;
.
Supply of scientific services. The biotechnology company provides to third
parties (typically, other biotech firms) technical and scientific services that
leverage on the outcome of its discovery efforts.
.
Out-licensing. The biotech firm licenses out, usually to other biotech or
pharmaceutical companies, the rights to use a new candidate it has
discovered and developed.

The specific phases of the pharmaceutical-biotech drug discovery and development

process in which these open innovation modes prevail, according to the results of the
panel study, are schematically described in Figure 3.
In the next section, the results of the longitudinal analysis undertaken applying this
framework are reported and discussed.

Open innovation in biotech: applying the framework

The analysis of the data from the top 20 pharmaceutical biotech firms leads to
interesting results concerning the adoption of open innovation in the
EJIM bio-pharmaceutical industry, that could be interpreted thanks to the information
gathered through the panel study with industry experts.
12,3 First of all, it is possible to highlight a general trend (as reported in Table III)
analysing the trend in the number of times in which organisational modes for open
innovation have been used by the firms in the sample.
The number of items recorded in the sample, 794 as a whole with an average for
296 each firm of nearly 40, is significant and demonstrates a wide adoption of the open
innovation paradigm in the biotech industry. However, a declining trend from 168
items in 2000 to 113 items in 2005 should also be noticed. As far as the determinants of
this trend are concerned, that may appear in contrast with the claimed increasing
adoption of open innovation modes, the following two can be highlighted:
(1) the impact of the overall economic context, with the bursting of the internet (and
high tech) bubble in the year 2000 and the economic downturn following
terrorist attacks in 2001, that reduced the availability of financial resources for
biotech firms;
(2) the progressive evolution towards the maturity stage of some basic
technologies (e.g. gene mapping and analysis, production of monoclonal
antibodies).
The former point implies an overall reduction of the innovative effort (and therefore of
open innovation modes) by biotech firms that are constrained by limited resources. The
latter point implies, on the one side, the increasing concentration of the supply in the
hands of a lower number of organisations offering those technologies and, on the other
side, a push for larger product biotech firms towards internalising mature technologies

Figure 3.
Open innovation modes
and their position along
the phases of the drug
discovery and
development process

Open innovation modes

percentage (number) 2000 2001 2002 2003 2004 2005

Generation of innovation 57.7 (97) 62.0 (85) 59.2 (71) 63.7 (79) 64.4 (85) 67.3 (76)
Exploitation of innovation 42.3 (71) 38.0 (52) 40.8 (49) 36.3 (45) 35.6 (47) 32.7 (37)
Table III. Total 168 137 120 124 132 113
The adoption of open
innovation modes Note: (Total number by year)
into their own boundaries; in both the cases, this results in a reduction of the number of Adoption of open
times in which firms adopt open innovation modes. A further step of the analysis innovation
allows us to distinguish the use of open innovation modes in the two identified
macro-phases of generation and exploitation of innovation.
Table III shows the clear prevalence of open innovation modes in the generation
phase. Indeed, they account in the whole sample for nearly 62 per cent, with a growth
trend over the time period considered, from nearly 58 per cent in 2000 to more than 67 297
per cent in 2005. This implies a clear tendency of biotech firms to open up their
innovation process particularly in the generation phase, where the quest for innovative
products (and enabling technologies) able to support business development of top
players is more relevant. Even more in details (see Table IV), it is possible to highlight
the relative weight (among the modes for the generation of innovation) of the
in-licensing, that passed from 18.6 per cent in 2000 to more than 30 per cent in 2005. It
is interesting to notice that this growth is mostly due to a substitution of collaborations
with in-licensing agreements. Top players in the industry operating as product firms
(i.e. developing new drugs), have to continuously fill in their product pipelines in order
to remain competitive in the market and to sustain their growth against traditional
pharmaceutical firms. However, as far as biotech firms grow and are able to use
revenues from directly marketed drugs to finance their own R&D activities, they tend
to adopt more in-licensing modes, that are relatively more “expensive” than
collaborations, but at the same time allow them both to reduce the risk of competences
spill-over and to better protect intellectual property, besides ensuring a better control
and independence in the management of the drug discovery and development process.
The above remarks are further supported by the fact that the majority of in-licensing
agreements (respectively 24 per cent, 15 per cent and 12 per cent) refers to products in
the major therapeutic areas of oncology, cardiovascular diseases, and central nervous
system diseases, where competition with traditional pharmaceutical and other biotech
firms is most fierce and where top players actually focus.
The relative weight of open innovation modes in the exploitation phase declines in
the time period considered, from more than 42 per cent in 2000 to nearly 33 per cent in
2005. Within these modes, it is interesting to note the relative growth of collaborations
(mostly co-manufacturing and co-marketing agreements). A possible explanation for
this trend is the increasing need for biotech firms (and particularly for product biotech
firms) to expand their geographical coverage so as to reach customers on a worldwide
basis. Collaborations, indeed, are mostly (56 per cent on the average) signed with
pharmaceutical companies, operating with a world-wide productive and distributive
capacity.
An interesting up-and-down trend in the average weight can be also recognised in
out-licensing (passing from nearly 37 per cent in 2000 to more than 35 per cent in 2005,
but with peaks of more than 60 per cent in 2002 and 2003). The analysis of
out-licensing requires further details, taking into account also therapeutic areas. In 43
per cent of the cases, out licensing refers to products in major therapeutic areas
(oncology, cardiovascular diseases, and central nervous system diseases), whereas the
remaining 57 per cent is distributed among a plethora of minor therapeutic areas (e.g.
allergy/immunology, metabolic diseases, infectious diseases, respiratory diseases,
genito-urinary diseases). The determinants of the adoption of out-licensing are rather
different in the two cases. In the former cases, biotech firms adopt out-licensing as a
 12,3

298
EJIM

Table IV.

innovation modes by
The adoption of open

typology and by phase

Open
innovation 2000 2001 2002 2003 2004 2005
modes Percentage Number Percentage Number Percentage Number Percentage Number Percentage Number Percentage Number

Generation of innovation
Collaborations 55.7 54 48.2 41 42.3 30 35.4 28 40.0 34 36.8 28
Purchase of
scientific
services 25.8 25 29.4 25 32.4 23 31.7 25 36.5 31 32.9 25
In-licensing 18.6 18 22.4 19 25.4 18 33.0 26 23.5 20 30.3 23
Exploitation of innovation
Collaborations 47.9 34 48.1 25 32.1 17 29.3 12 48.9 23 56.8 21
Supply of
scientific
services 15.5 11 25.0 13 7.6 4 4.9 2 6.4 3 8.11 3
Out-licensing 36.6 26 26.9 14 60.4 32 65.8 27 44.7 21 35.1 13
second-best after collaborations when they are not able to reach autonomously the Adoption of open
market or are unable to find a suitable partner, whereas in the latter cases biotech firms innovation
adopt out-licensing to profit (in a typical open innovation approach) from products
whose development is not consistent with their business focus, i.e. with their
orientation in terms of therapeutic areas. A further remark on the open innovation
modes for the exploitation phase concerns the declining weight of the supply of
scientific services (from 15.5 per cent in 2000 to 8.1 per cent in 2005). This trend is again 299
related to the natural evolution of biotech firms: in their initial stages, they are forced to
supply services (particularly technological services) to create a revenue stream able to
support R&D activities; once products reach the market, revenue stream from ancillary
activities becomes less relevant and firms tend to concentrate their efforts on the
development process of new products.
As far as the typologies of partners involved in the open innovation modes are
concerned (see Table V) it is interesting to note that biotech companies (and more
specifically small product biotech companies) account for about 66 per cent of the
whole open innovation modes in the phase of generation of innovation. Top players in
the industry, indeed, need to sustain their internal drug development process through
accessing the most innovative scientific competencies, technological assets or
products. The marginal role (on average about 8 per cent) of Universities and research
centres has to be highlighted as it contrasts with a wide body of literature (e.g.
Owen-Smith et al., 2002; Chiesa, 2003) claiming for the pivotal role of such actors in
generating biotechnology innovation and in sustaining the creation of new biotech
firms (academic spin-offs). The reason for this evidence can be found in the
composition of the sample that includes only top players in the industry, that have the
attitude to collaborate with firms which have already started the process of
development of the new product (maybe with an academic origin), rather than with
Universities and research centres that usually carry out only basic research. On the one
side, this approach reduces the risk of the development process (as initial stages have
already been successfully completed) and, on the other side, it allows top players to
equally profit from marketed products.
Results are slightly different when the phase of exploitation of innovation is
concerned (see Table V). Pharmaceutical firms play in this phase a pivotal role,
representing on average nearly 57 per cent of the total partners involved in open
innovation relationships. In the exploitation of innovation, top biotech industry players
search indeed for partners to expand their geographical and/or market coverage,
through complementing their existing commercialisation and distribution assets.
Large pharmaceutical firms, that usually operate on a worldwide basis, represent the

Other
Pharmaceutical Biotech (Universities and
firms firms research centres)
Typologies of partners involved (%) (%) (%)

Generation of innovation 26 66 8 Table V.

Exploitation of innovation 57 41 2 Typologies of partners
involved in different open
Note: Average 2000-2005 innovation modes
EJIM best alternative for this purpose. Moreover, pharmaceutical firms gain the “lion’s
12,3 share” in out-licensing agreements, exploiting their competitive advantage in
ownership of complementary assets in comparison with top biotech industry
players, particularly in major therapeutic areas (like cardiovascular and central
nervous system diseases).
A clear pattern of evolution can be therefore recognised in the typologies of partners
300 involved in open innovation. In the generation of innovation, the innovative
contribution of biotech companies (both product and platform firms) plays a key role,
whereas in the exploitation phase pharmaceutical firms prevail, leveraging their
competitive advantage in terms of complementary assets.
Finally, it is possible to analyse the open innovation modes adopted by biotech
firms along the phases of the drug discovery and development process and to assess
the correspondence between the empirical evidence and the model developed through
the panel study (and shown in Figure 3). As far as the phase of generation of
innovation is concerned, it is possible to highlight that:
.
on average more than 60 per cent of collaborations for the generation of
innovation are focused in the phase of target identification and validation. As
identified in the model, in this activity the contribution of external sources of
innovation is particularly relevant indeed, as they allow biotech firms to
complement internal competences in basic research;
.
purchase of scientific services is concentrated in lead identification and
optimisation (48 per cent), where it is specifically concerned with the access to
technological platforms for lead optimisation. The remaining part refers to
clinical tests (mainly to CROs) and, only marginally (7 per cent), to post approval
activities;
.
in-licensing, that increasingly represents a fundamental approach to fill in the
product pipeline, has progressively shifted in the time period considered from
pre-clinical tests (that in 2000 represented nearly 80 per cent of the cases) to
clinical tests. In-licensing in Phase I (and in some cases Phase II) of clinical tests
represented in 2005 nearly 40 per cent of the cases. In-licensing products in later
phases of the process reduces (even significantly) the risks of development, hence
better contributing to filling in the product pipeline and increasing the rate of
market introduction of new drugs. At the same time, however, in-licensing in
later phases of the process is more “expensive”, because the money compensation
required grows as the risk of the product development decreases. As a result,
only mature firms are generally able to use this mode.

As far as the phase of exploitation of innovation is concerned, it is worth noting that:

.
nearly 50 per cent of the collaborations in this phase are related to post-approval
activities, where biotech firms need, as already mentioned, to expand their
geographical coverage;
.
supply of scientific services, even if marginal, is concentrated almost only in the
pre-clinical and clinical (Phase I) tests, where biotech firms may particularly
exploit their technological base to offer support services mainly to other biotech
firms;
 .
in the case of out-licensing, the distinction already discussed between the cases of Adoption of open
products in major therapeutic areas versus those in minor therapeutic areas innovation
appears clearly to affect the phase of the process where out-licensing takes place.
In particular, out-licensing for products in minor therapeutic areas concentrates
in pre-clinical tests (from 40 per cent in 2000 to nearly 70 per cent in 2005), this
reducing the financial effort (and risk) of biotech firms in developing products
that are out of their main business scope. Consistently with the open innovation 301
paradigm, these products are developed outside the boundaries of the firm,
which however finds a way to profit from them. Out-licensing for products in
major therapeutic areas, on the contrary, is more largely pursued in the later
phases of the process (and particularly in Phase II and III of clinical tests,
respectively for 45 per cent and 23 per cent in 2005, up to 38 per cent and 15 per
cent in 2000), this highlighting the attempt from biotech firms to reach
autonomously (i.e. with their own products) mainstream markets.

5. Conclusions
The paper represents one of the first attempts to systematically and longitudinally
assess the extent and the determinants of the adoption of the open innovation
paradigm in a specific industry. In particular, it investigates the case of the
bio-pharmaceutical industry which represents, for its intrinsic characteristics, a fertile
ground for the diffusion of open innovation. A framework of analysis has been
developed through a panel study, identifying different organisational modes for open
innovation, their relationships with the phases of the bio-pharmaceutical innovation
process, and the determinants underlying the choice of different organisational modes
for open innovation.
Afterwards, the framework has been applied to an extensive and longitudinal
empirical basis including data about the open innovation modes implemented by top
worldwide industry players over the time period 2000-2005.
The results of the analysis allow us to assess the framework and to further discuss
the determinants of the adoption of different open innovation organisational modes.
The paper has both theoretical and practical implications. As far as theory is
concerned, it suggests that the characteristics of the biotech industry (e.g. the
articulation of the innovation process and its typical risk pattern, the business focus of
biotech firms towards major therapeutic areas, the problems related to the
management of IPRs) are key to analyse the implementation of open innovation. In
this respect, the paper provides support to the idea that the lack of similar
contributions in the literature is a major gap in the current debate on the open
innovation paradigm. Under a managerial perspective, the framework developed in the
paper and the rich empirical basis to which it is applied provide innovation managers,
especially those working in the bio-pharmaceutical industry or similar high-tech
environments, with a comprehensive picture of the tools (i.e. the different open
innovation modes) and rationales (i.e. the phases where different open innovation
modes prevail) for adopting an open innovation approach.
Nevertheless some limitations of the research need to be carefully considered and
will hopefully inform future research. In particular, it is necessary to further
investigate whether and how the composition of the sample, which includes only large
product biotech firms (i.e. firms developing new drugs), affect the results. It might be
EJIM possible to argue, for example, that platform biotech firms are less compelled by the
12,3 need to fill in their product “pipeline” and therefore have a different approach to open
innovation, or that smaller firms adopt in- and out-licensing strategies that are
different (or even exactly the opposite) from those of large firms.
The authors believe, however, that this paper represents a valuable basis for future
research and managerial discussions in the field.
302
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About the authors

Davide Chiaroni is Assistant Professor of Business Economics and Organisation at Politecnico di
Milano. He holds PhD in Management, Economics and Industrial Engineering from Politecnico
di Milano. He was previously Research Assistant at University of Milano-Bicocca, Department of
Biotechnology and Biosciences. His research area is strategy and strategic management in
high-tech industries. He is author of the book Industrial Clusters in Biotechnology: Driving Forces,
Development Processes and Management Practices (with V. Chiesa), (Imperial College Press,
2004). Davide Chiaroni is the corresponding author and can be contacted at: davide.
chiaroni@polimi.it
Vittorio Chiesa is Full Professor of R&D Strategy and Organisation at Politecnico di Milano.
He is member of the Management Council and the Faculty of MIP (the Business School of
Politecnico di Milano), where he is head of the Technology Strategy Area. He is member of the
Steering Committee on Biotechnology of the Italian Ministry of Industry and of the Network of
Biotech Officials at the European Commission. He is author of several books and more than 100
publications in the fields of R&D management, R&D internationalization and technology Adoption of open
strategy.
Federico Frattini is Assistant Professor of Business Economics and Organisation at innovation
Politecnico di Milano. He holds PhD in Management, Economics and Industrial Engineering
from Politecnico di Milano. He was lecturer in Business Economics and Organization at
Università Vita-Salute San Raffaele and previously at Università Carlo Cattaneo – LIUC. His
research interests concern the management and organisation of R&D activities, R&D
performance measurement, and the commercialisation of innovation in high-tech markets. He 305
has published papers in Journal of Engineering and Technology Management, International
Journal of Innovation Management and International Journal of Technology Management.

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