Deo42 DP Series 3
Deo42 DP Series 3
Deo42 DP Series 3
December 2011
Abstract
To succeed in the market, companies have to address the marketing issues and tackle
them adequately. Biotechnology companies are a special case, because the strategic
decisions and the marketing issues to handle may not be ordinary. In fact, due to the
science based nature of the sector, most companies are technology intensive, being
often involved in the development of highly innovative products within a new, still
evolving, field, while struggling to gain a leading edge over competitors in the
market. Thus, companies have to leverage their technological capabilities by selecting
R&D projects that lead to a competitive advantage, still leaving ample space for
knowledge creation that will feed a system of innovation serving both, market success
and academic excellence. The inevitable university-industry interplay is not always
straightforward, owing to the different scopes and strategies of each side. This works
presents the challenges to knowledge exploitation, using the case of biosensors as an
exemplar for highlighting efficient knowledge transfer mechanisms from lessons
learnt.
not be ordinary. In fact, due to the science based nature of the sector, most companies
are technology intensive, being often involved in the development of highly
innovative products within a new, still evolving, field, while struggling to gain a
leading edge over competitors in the market. Thus, companies have to leverage their
technological capabilities by selecting R&D projects that lead to a competitive
advantage (Siontorou and Batzias, 2010). Options cover mainly two major areas. The
first is selecting the pioneering posture, where a company, acting as a knowledge
creator, aims at introducing niche products and technologies into the market;
biotechnology being still strongly bound to basic research, readily available from
academia, makes innovation and novelty more feasible in comparison with other
traditional technology sectors, provided that a company can afford the high cost and
risk of extensive research, development, authorization and promotion; clearly, this
option can be sustained only by large multinational corporations. The second option is
choosing a combination of applied and basic research projects by using the company’s
internal and external R&D resources and building on already existing knowledge. The
former usually refer to in-house R&D activities, whereas the latter may include
purchasing or licensing of technology from other companies, or joining strategic
alliances to acquire that technology. Inter- and intra- technical/scientific knowledge
and competency may be disseminated in a variety of ways: patent disclosure,
publications, technical meetings, conversations between employees of the same or
competing companies, partnership within the same consortium that carries out a big
project, hiring of employees from rival companies and reverse engineering of
products (Nonaka et al., 1996; Luo et al., 2005; O’Connor and DeMartino, 2006).
Opportunities arise mainly from the specific, and often difficult to fulfill,
deficits of marketed products, requiring a lot of ‘speculative’ R&D, which is a
valuable path for strengthening the company’s position (Bernstein and Singh, 2006).
Depending on the company’s resources and capabilities, technological development
may start from advancing basic biochemical research on an early-stage candidate, or
from re-engineering/re-designing later stage products. The more basic the ‘product-to-
be’ is, the higher the investment required and the uncertainty of the outcome, but the
more prominent becomes the differentiation of the product for gaining a satisfactory
market share.
When a biotechnology company seeks to define the balance between R&D in
established areas of corporate knowledge and speculative R&D for enhancing its
Page 5
2. Systems of Innovation
Innovation systems and science policies predominantly focus on linkages
between universities and industry, and the commercial translation of academic
discoveries. Overlooked in such analyses are the knowledge discovery processes
within academic research and the non-commercial aspects of science. The desire to
move research into practical applications in order to capture the benefits derived from
scientific discovery has long motivated science funding and program development,
especially in the biotechnology sector. Distinctions between ‘pure’ and ‘applied’
science were common during the 1960’s through the 1980’s. However, it is now
widely recognized that this linear model of innovation, in which pure science is
published in the academic literature, then picked-up by industry and developed into
useful applications, is unnecessarily simplistic and frequently inaccurate; more likely,
Page 6
scientific research contains aspects of both, basic inquiry (discovery) and practical
application (utility), and moves back and forth between the two (Stokes, 1997). These
movements take place at a deeper phenomenological level and their traces become
somehow evident only to researchers who actually incorporate instinctively the
relevant methodological paths into their hypotheses. On the other hand,
methodologists or technology managers, engaged with the theoretical or the practical
aspect, respectively, of research but not with the research itself, stay usually on a
surface level being able to discriminate only quasi-linear segments of a trace which is
rather complicate, sometimes tending to cover part of the surface like a Peano curve.
Bio-related academic research remains at the forefront of the scientific and
industrial infrastructure for two decades now, feeding a push-pull mechanism that
serves both, academic excellence and product innovation, through an efficient
technology transfer stream (Schmoch, 2007; Bishop et al., 2011). The impact of bio-
technology on the pharmaceutical sector is a case in point . The innovative network
developed has not only altered the technological profile of the sector, by driving
chemical production to bioprocesses, but has also shifted drastically the trajectories
from chemistry towards life-sciences (Gilsing and Nooteboom, 2006). The network’s
grounding in basic research, together with its multidisciplinary and decentralized
dynamics, increased the relevance of academic research outputs, fostered the
emergence of specialized biotechnology firms that necessitated (and promoted) intra-
industrial cooperations and university-industry links, while obliged the
pharmaceutical firms to reposition their strategies (Salicrup and Fedorková, 2006;
Canongia, 2007). Markedly, the high transformative capacity of the science-enabled
technology, i.e., the high capability of the scientific bodies involved to constantly
redefine the portfolio of their products based on endogenously produced knowledge
(Garud and Nayyar, 1994), brought about significant structural and institutional
changes to the sector, giving rise to new scientific and technological opportunities.
There are cases, however, where several new technologies, incubated and
fostered within the same evolutionary frame of bio-sciences, had only an indirect,
supportive, and subsidiary impact and failed to challenge the sectoral system and its
established structures in any substantial way. Biosensor technology, for example, was
set off to revolutionize instrumentation and measurement (see e.g., Churchouse et al.,
1986; Griffiths and Hall, 1993), as well as medical diagnostics and treatment (see e.g.,
Mascini, 1992; Wilson et al., 1992). Yet, the industry was very reluctant to capitalize
Page 7
innovation under consideration: the new technology was called to address fast the
needs of 5% of the US population and 0.4% of the world population, at an increasing
rate of 3-5% annually and at a direct health care cost of $2000 per patient (Steck and
Rewers, 2004). This innovation gave a straightforward cost reduction trajectory at a
performance level higher than that of the earlier processes that it cancelled out. Four
strategies have been consecutively followed in industrial research to deal with the
challenges and opportunities of diabetic management (Fig. 3), as determined by patent
searching for mapping scientific knowledge: (i) steepening of the slopes of the market
trajectories using marketing initiatives so that the performance improvements
demanded by the health care providers could be successfully addressed by the
industry (R&D on performance), (ii) ascending the trajectory of sustaining technology
into ever-higher tiers of the market (R&D on reliability), (iii) aligning with the needs
of end customers (R&D on convenience), and (iv) increasing the market share with
less costly formats and processes.
When the marketed technologies became comparable in most critical aspects,
the real clinical needs for detecting unsuspected hypoglycemia, neonatal screening,
and adolescence diabetes monitoring, urged the industry to look into the science push-
pool for alternate testing, giving rise to minimally invasive glucose monitoring (Fig.
4). Knowing that this shifting was not enough to maintain the competitive advantage,
non-invasive ‘glucometry’ became rapidly the new target of the industries, enabling
the renewed intensification of university-industry relation seen today.
Researcher patents increased although very few have been managed to support
their claims or find their way to the market. Much of the work has been done in
secrecy by science based enterprises. At the early 1990s, research papers have
dramatically increased, prompting various universities and institutes to specialize first
in biosensor (academic spin off) and long after to provide biosensor courses. Some of
the researchers have turned to private companies and institutes to offer their insight
and experience. Biacore, for example, began operating in 1984, when expertise from
Pharmacia, Linköping Institute of Technology and the Swedish National Defense
Research Institute, were brought together with Biacore’s predecessor, Pharmacia
Biosensor AB. Approximately 65 million US$ has been invested in the development
of Biacore and the technology on which it is based. An initial research phase which
essentially included development of the fundamental affinity-based biosensor
technology comprising surface chemistry, flow systems and optical detection methods
was completed in 1989. The result was Biacore ®, a biosensor-based analytical
instrument for studying molecular interactions, launched in 1990. Further products
followed, all based on surface plasmon resonance technology. The business evolved
into a largely independent commercial enterprise, which posted its first profit in 1994.
Another example of know-how transfer from academics to industry is the
establishment of Agamatrix in 2001 from the collaboration between S. Vu, an expert
in machine-learning algorithms, and S. Iyengar who has just finished his PhD in
biosensors at Cambridge University.
A considerable increase of research funding for biosensors has been seen in
2004, along with new lines of funding for technology demonstrators and industrial
investment in prototype systems. This can boost the supply side, provided that
universities will be encouraged to support the area. This presupposes liberation of
university staff time for R&D, longer term funding for individuals who can
demonstrate the quality of their work and its relevance to user requirements, as well
as improved support for graduates. For example, the alcohol wristwatch (Dummet et
al., 2008) has been developed through a collaboration between the University of
Southern California and the Brown University Medical School, investing largely on
simulation of alcohol metabolism (Fig. 5).
The demand side, on the other hand, has proved to provide a strict market-
orientation as well as resources necessary for successful commercialization. Most
companies, however, realizing the huge cost of research, have decided to collaborate
Page 11
5. Concluding remarks
The key issues emerging from the experience gained in biosensor progress and
development, taken as a representative example of university-fostered biotechnology
revolution, refer to early information transfer and utilization, product innovation,
product quality, and efficient collaboration. Commercialization and research progress
entails the capability of research institutions and organizations to introduce new
concepts, products and features. The fast pace of technological change and the market
demands for novel and better products requires continuous innovation and fast market
introduction. This implies primarily a market-targeted research strategy, focusing on
needs requiring attention and not on substitution of niche technologies, especially on
the misjustification of cost-effectiveness. Progress should be quick to assimilate side-
technological advancements as these become available. The momentum increase
Page 12
largely relies upon information flow, which is expected to benefit largely from
concurrent engineering practices
Technology perfection will not be enough to assure biotechnology success in
the near future, however. Successful products will have to fulfill unmet market needs
at a highly competitive arena. The successful biotechnology marketer, therefore, will
have to come up with convincing evidence to prove that his/her system has a clear
advantage over existing, well-known and public-accepted technologies.
Cross-functional teams provide an avenue for constituents to express concerns
and a mechanism for capturing learning. Early involvement empowers downstream
participants; they have a say before decisions are finalized. Simultaneous planning of
product, process, and manufacturing allows issues of manufacturability to be
evaluated and incorporated in the final product design. This approach affords a group
a stream of integrative innovations that may improve the value of the end-product,
enhance quality, and reduce development cost. With early release of information,
engineers can begin working on different phases of product development process
while final designs are evolving. The early release of information reduces uncertainty
and promotes the early detection of problems, which enables groups to avoid time-
consuming changes.
Moreover, the economic aspects of biotechnology are not been taken into
account when research strategies are considered. For the immediate future,
nanotechnology could be still expensive. If high volumes and low-cost products are
achieved, the markets could be huge. The question is whether the increased capability
of nano-products will be sufficient to open up large markets quickly, and thus
engendering a rapid decrease in costs. A related question is whether there will be
scope for small firms to invest on nanotechnology.
References
Bernstein, B. and Singh, P.J. (2006). An integrated innovation process model based on
practices of australian biotechnology firms. Technovation 26, 561-572.
Bishop K., D’Este P., Neely A. (2011). Gaining from interactions with universities:
Multiple methods for nurturing absorptive capacity. Research Policy 40, 30-40.
Canongia C. (2007). Synergy between competitive intelligence (CI), knowledge
management (KM) and technological foresight (TF) as a strategic model of
Page 13
Sidiras D.K., Koukios E.G. (2004). Solar systems diffusion in local markets. Energy
Policy 32, 2007-2018.
Siontorou C.G., Batzias F.A. (2010). Innovation in biotechnology: moving from
academic research to product development—The case of biosensors. Critical
Reviews in Biotechnology 30, 79-98.
Steck A.K., Rewers M.J. (2004). Epidemiology and geography of type 1 diabetes
mellitus. In: DeFronzo RA, Ferrannini E, Keen H, Zimmet P, editors.
International textbook of diabetes mellitus. West Sussex: John Wiley & Sons
Ltd., pp. 15–32.
Stokes D.E. (1997). Pasteur’s quadrant: Basic science and technological innovation.
Washington DC: Brookings Institute Press.
Tashkova K., Šilc J., Atanasova N., Džeroski S. (2012). Parameter estimation in a
nonlinear dynamic model of an aquatic ecosystem with meta-heuristic
optimization. Ecological Modelling 226, 36-61.
Thompson, E. and Vonortas, N.S. (2005). Biotechnology evolution and regulation of
pharmaceuticals. In: R. Carruth, Ed., Global governance of the pharmaceuticals
industries: Transatlantic and trilateral regulatory harmonization and
multilateral policy cooperation for drug safety. The George Washington
University, Ch. 9.
Tschmelak J., Proll G., Riedt J., Kaiser J., Kraemmer P., Bárzaga L., et al. (2005a).
Automated Water Analyser Computer Supported System (AWACSS) Part I:
project objectives, basic technology, immunoassay development, software
design and networking, Biosensors and Bioelectronics 20, 1499-1508.
Tschmelak J., Proll G., Riedt J., Kaiser J., Kraemmer P., Bárzaga L., et al. (2005b).
Automated Water Analyser Computer Supported System (AWACSS): Part II:
intelligent, remote-controlled, cost-effective, on-line, water-monitoring
measurement system, Biosensors and Bioelectronics 20, 1509-1519.
Vadgama P. (1984). Enzyme electrodes for continuous in-vivo monitoring. TrAC –
Trends in Analytical Chemistry 3, 13-6.
Wilson G.S., Zhang Y., Reach G., Moatti-Sirat D., Poltout V., Thévenot D.R., et al.
(1992). Progress toward the development of an implantable sensor for glucose.
Clinical Chemistry 38, 1613-7.
Page 16
Figure 1. Schematic of the glucose probe manufactured by YSI Inc. that later termed
‘first generation’ biosensor system.
Page 17
Figure 4. The three phases of glucose monitoring, invasive, minimally invasive and
non-invasive, represented industrial efforts to produce devices according to
specifications set by the intermediate customers (health care providers) and the end-
users (patients). Each phase apprehended available (at the time) technologies, each
with drawbacks that pushed the path forward. Interestingly, R&D was not about
improving performance and/or minimizing faults but kept focusing on the next phase
generation and moving fast between technology platforms in order to get ahead of
competition. The last phase is clearly dependent upon university research, setting off
again strong pull mechanisms and high speed information flow patterns.
Page 19
Figure 5. The development of the alcohol wristwatch has been realized through an
inter-university cooperation under a governmental financial framework addressed to
the Psychology Department of Brown University for controlling alcoholism.