The Impact of Internal and External Basic Science on
Research Productivity in the Pharmaceutical Industry
Bart Leten
Faculty of Economics and Business, K.U. Leuven, Naamsestraat 69, B-3000 Leuven,
Belgium; [email protected]
Stijn Kelchtermans
Faculty of Economics and Management, H.U. Brussel, Stormstraat 2, B-1000 Brussel
K.U. Leuven, Leuven, Belgium; [email protected]
Rene Belderbos
Faculty of Economics and Business, K.U. Leuven, Naamsestraat 69, B-3000 Leuven,
Belgium; [email protected]
UNU-MERIT, Maastricht, The Netherlands
Faculty of Economics and Business Administration, Maastricht University,
The Netherlands
Preliminary Version – Please do not cite
Abstract
This study examines the impact of basic science on the research productivity of
private for-profit firms in the pharmaceutical industry. We distinguish between the
effects of in-house self-performed basic scientific research (internal basic science)
and the exploitation of public basic scientific research (external basic science). We
hypothesize that firms that engage in internal basic science increase their
technological performance, in particular when these activities are undertaken in
collaboration with academics. In addition, a positive impact of the exploitation of
external basic science on firms’ technological performance is expected. We test
hypotheses on a panel data set (1995-2002) of the patent and publication activities of
61 US, European and Japanese pharmaceutical and biotechnology-based firms.
Keywords: Basic Science; Innovation. Pharmaceutical Industry
1
Introduction and Theoretical Background
In the 20th century, pharmaceutical companies have developed, created and
marketed drugs that have greatly enhanced quality of life. The drug discovery process,
which is at the heart of pharmaceutical firms’ innovative activities, is the driver
behind the generation of new drugs. Drug discovery is a high-risk activity: it requires
large upfront investments and the risk of failure is high. On the other hand financial
rewards for successful new drugs can be commensurately high and offset the
development risks (Campbell, 2005).
Prior work has shown that there exists a strong link between basic science and
innovation in the pharmaceutical industry (Gambardella, 1992; Lim, 2004).
According to the NSF definition, basic science seeks to understand phenomena
without specific applications in mind. Applied to the pharmaceutical industry, basic
science includes attempts to understand biochemical processes associated with a
disease, but does not include activities such as compound screening, clinical trials and
dosage testing. Basic science has a direct impact on the drug discovery process of
pharmaceutical firms. Based on detailed histories of the discovery and development of
21 highly influential drugs, Cockburn and Henderson (1998) found that fundamental
insights in basic scientific knowledge often formed a basis for drug discovery.
Additional evidence for the role of basic science in drug discovery is provided in the
work of Francis Narin and colleagues. Examining citations from US patents to
scientific research papers, they found that patents in drugs and medicine classes cite
significantly more scientific papers than patents in other fields (Narin et al, 1997), and
that these patents cite papers in basic research journals more heavily (Narin and
Olivastro, 1992).
The role of basic science in drug discovery appears to have increased in the
last two decades. Firms have moved away from randomly screening a large number of
potentially useful chemical or molecular compounds against a certain disease, towards
a more systematic approach called ‘rational drug design’. This approach involves the
use of basic scientific knowledge on the biochemical mechanisms causing a certain
disease in order to identify compounds that inhibit such mechanisms (Pisano, 1997).
Prior work (Gambardella, 1992 & 1995), based on case studies of US pharmaceutical
firms, has however shown that pharmaceutical firms pursued different strategies with
2
respect to the importance given to internal and external science in their drug discovery
process. For example, Merck has always invested heavily in internal basic science,
and used this knowledge to exploit and further build on external basic scientific
findings; Bristol-Myers on the other hand has had only modest internal basic science
skills (Gambardella, 1992)
Several arguments have been advanced as to how internal and external basic
science could affect the productivity of firm invention activities. These include the
‘map’ function of basic science for applied research (Rosenberg, 1990; Fleming and
Sorenson, 2004), the development of absorptive capacity to plug into the outside
scientific community (Gambardella, 1992; Fabrizio, 2009), an admission ticket to
R&D partnering and networking with universities (Liebeskind et al, 1996; Cockburn
and Henderson, 1998), and an incentive in recruiting qualified researchers (Henderson
and Cockburn, 1994; Stern, 2004).
Despite the large interest in the effect of basic science on the technological
performance of firms, the number of empirical studies addressing this issue is limited.
A first set of studies examined the relationship between internal basic science and
innovation for small samples of pharmaceutical firms, finding mixed results.
Gambardella (1992) found that US pharmaceutical firms with more in-house scientific
research skills produced a greater number of patents. Cockburn and Henderson (1998)
did only find positive effects from internal scientific research when firms did conduct
these science activities in close collaboration with academics. Lim (2004) did find no
significant effect of internal basic science on corporate technological performance.
A second set of studies examined the effect of the exploitation of external
basic science on firms’ technological performance, assessing the exploitation of
science from citations to scientific literature on firms’ patent documents. Branstetter
and Kwon (2004) found a positive relationship between the rate of patenting and the
number of scientific references in prior patents by Japanese firms. In contrast,
research by Fleming and Sorenson (2004) and Cassiman et al. (2008) were less
supportive of a contribution of public basic science to the technological impact of
corporate patents. Cassiman et al (2008) reported an insignificant relationship
between the presence of scientific references on patents and their technological
impact, as measured by forward citations. Fleming and Sorenson (2004) did find a
positive relationship but only for patents in complex industries, suggesting that the
3
benefits of exploiting public basic science may depend on the difficulty of the
inventive problem addressed.
In this paper we extend the limited body of prior work on firms’ basic science
activities by jointly examining the impact of internal and external basic science on the
research productivity of firms We examine what type of basic scientific research
activities has the largest relative contribution to research productivity, using a panel
data set of the patent and publication activities of 61 pharmaceutical and
biotechnology-based firms. Our study further differs from prior work by using
improved measurement tools for internal and external basic science. Prior studies
have used the number of corporate scientific papers as proxy for internal basic
scientific capabilities1, and references to scientific papers in corporate patents as
proxy for the exploitation of external basic scientific findings. However, publications
are an imperfect measure of basic scientific research because a large share of papers
published by pharmaceutical companies are in clinical research, i.e. the ‘hands-on’
analysis of the effects of new drugs on patients (Hicks, 1994), which cannot be
labelled as basic science. Using information on the journals in which scientific papers
are published and the CHI classification scheme (Hamilton, 2003) for basic vs.
applied research, we construct more accurate measures of internal and external basic
science by relying on the subset of scientific papers in ‘basic science’ journals.
The next section contains an overview of the hypotheses that are advanced and
tested empirically in our study.
Hypotheses
Company researchers often consult scientific literature to solve technical
difficulties in their inventive processes (Allen, 1977; Gibbons and Johnston, 1974).
Organizations that frequently consult and exploit external basic scientific findings in
their inventive activities are expected to develop a deeper understanding of the
phenomena under study. Basic science can hence serve as a ‘map’ of the
technological landscape in which firms search for inventive solutions, guiding firms
to the most promising technical directions (Fleming and Sorenson, 2004). It also helps
to evaluate and interpret the outcomes of applied research and to understand its
1
The study of Lim (2004) is a notable exception.
4
implications (Rosenberg, 1990). A firm that exploits more public basic science in
innovation processes is therefore expected to increase its research performance.
Hypothesis 1: The exploitation of external basic science has a positive impact on
firms’ research productivity.
Organizations that conduct in-house basic science activities benefit from the ‘map’
function of basic science in a similar way as firms that are exploiting external basic
science. Conducting in-house basic science however has additional advantages for
firms’ research productivity. First of all, internal basic science capabilities may act as
an admission ticket to R&D partnering with universities and public research institutes
(Liebeskind et al, 1996; Cockburn and Henderson, 1998). Second, firms with better
in-house scientific capabilities may be better positioned to identify, and learn from,
externally available basic scientific findings (Gambardella, 1992; Fabrizio, 2009).
Third, companies that conduct internal basic science -and have a ‘pro-publication’
culture- are better positioned to attract ‘star’ scientists, who are reluctant to work in
environments in which they are not allowed to publish (Henderson and Cockburn,
1994). Employing ‘star’ scientists has a large and positive impact on the research
productivity of firms (Darby and Zucker, 2001). Fourth, as publishing is an important
way to establish scientists’ reputations (Stephan, 1996), scientists are found to be
willing to accept lower wages in exchange for the permission to conduct and publish
scientific research (Stern, 2004). Taken altogether, these arguments suggest that firms
can increase their research productivity by conducting internal basic science activities.
Hypothesis 2: Internal basic science activities have a positive impact on firms’
research productivity.
There are reasons to believe that the benefits of internal basic science activities will be
larger when they are conducted in close collaboration with scientists at universities.
Collaboration with university scientists often leads to extensive debate, exchange of
ideas and discussion. This creates opportunities for firms to get access to tacit
knowledge of individual university scientists, which is complementary to the basic
scientific knowledge developed in the joint research projects (Cockburn and
Henderson, 1998). Furthermore, these collaborations may help firms to identify
5
relevant codified scientific knowledge that is not yet published and build on scientific
research results faster in their own research activities (Fabrizio, 2009). Therefore,
firms conducting internal basic science activities in collaboration with university
scientists are expected to benefit more from internal basic science.
Hypothesis 3: Internal basic science activities have a larger impact on firms’ research
productivity when it is done in collaboration with universities.
Data and Empirical Methods
Sample
To examine the effects of internal and external basic science on the research
productivity of private for-profit firms in the pharmaceutical industry, we constructed
a panel dataset (1995-2002) for 61 drug-developing pharmaceutical and
biotechnology-based companies. We selected the firms with the largest R&D budgets
in the pharmaceutical industry from the 2004 industrial R&D Investment Scoreboard.
We augmented this list with biotechnology firms that applied for the largest numbers
of patents at the European Patent Office (period 1990-2000) and are involved in the
development of new therapeutic drugs. Biotechnology firms that develop instruments
and tools for the pharmaceutical industry are not included in our sample. This resulted
in a list of 61 firms with headquarters in the United States, Europe and Japan. For
each firm, annual lists of their (majority-owned) subsidiaries were used to construct
consolidated patent and publication portfolios at the parent firm level.
Dependent variable and Methods
We measure the technological performance of the firms (dependent variable)
as the count of the (consolidated) number of EPO patent applications of a parent firm
in a year, weighted by the number of forward patent citations received by those
patents over a fixed time window of 4 years. This ‘weighting’ allows to control for
variation in the technological and economic importance of patented inventions
(Harhoff et al, 1999; Hall et al, 2005). Patents are a good indicator of technological
activity in the pharmaceutical industry as the majority of inventions in this industry
6
are protected via patents (Arundel and Kabla, 1998). As we include R&D
expenditures as a control variable, we effectively analyze the determinants of
differences in research productivity across firms over time.
Since the dependent variable only takes non-negative integer values, a
negative binomial count data model is estimated to relate the dependent variable to
the set of explanatory variables. To control for the impact of unobserved firm-specific
characteristics (characteristics that may correlate with, and bias the effect of
explanatory variables, if not controlled for), a fixed effects estimation is performed.
Explanatory variables
Internal Basic Science
We proxy firms’ internal basic science activities by the (consolidated) number
of scientific publications of firms in basic science journals. Publications are extracted
from yearly updates of the ‘Web of Science’ database (Science Citation Index) of
Thomson Scientific. Firm publications are identified as publications on which the
parent firm, or one of its consolidated subsidiaries, are listed as publishing institutes.
In line with studies of Hicks et al (1994), and Cockburn and Henderson (1998), we
find that scientists in biopharmaceutical firms publish extensively, both on clinical
research and basic scientific research. We identify ‘basic science’ publications by
using information on the journals in which scientific papers are published and the CHI
basic/applied classification scheme, which classifies all SCI journals in one of four
research levels2 in a spectrum that ranges from very basic, untargeted research, to
very applied, targeted, research (Hamilton, 2003). The internal basic science variable
is measured as the number of basic science publications of a firm per dollar invested
in R&D (expressed in millions). This variable is calculated at the firm/year level and
is one-year lagged in the regressions.
External Basic Science
Our firm-level measure of exploitation of external basic scientific findings is
based on references to scientific literature (NPLs) in firms’ prior patents. Surveys of
2
Journals classified to levels 3 and 4 are considered as basic science.
7
patent inventors (Tijssen, 2001; Fleming and Sorenson, 2004) have shown that
inventors are aware of a significant part of the scientific papers cited in their patents,
qualifying scientific non-patent references as indicators of the ‘usage’ of science by
firms in their R&D activities (Branstetter & Kwon, 2004; Fleming and Sorenson,
2004). Patents cite a variety of non-patent literature (journals, books, newspapers,
company reports, industry related documents etc.) which do not all refer to scientific
sources (Harhoff et al, 2003; Callaert et al, 2006). We only consider non-patent
references to articles in basic science journals to calculate our measure of external
basic science. These references are identified by an elaborate text-matching algorithm.
The variable ‘external basic science’ is the unique number of NPLs to basic science
articles in a firm’s patent portfolio divided by the number of patents in the portfolio.
A firm’s patent portfolio consists of all patents that are applied for by a firm in the
past 4 years (t-4 to t-1).
Collaboration with Universities in Basic Science Activities
The intensity of collaboration between the firm and university scientists in
basic scientific research is measured as the share of firm publications in basic science
journals that are co-authored with universities. To identify firm publications that are
jointly written with university scientists we checked for the presence of the words
university, college or regents in the publishing institute names of firms’ publications.
Control Variables
We also control for other firm factors that might impact on the technological
performance of firms. First, we include an indicator for the size of a firm’s existing
technology portfolio, measured as the number of patent applications in a firm’s 4 year
patent portfolio. Firms with large technology portfolios may be better able to develop
new technological assets (Nesta and Saviotti, 2006). Second, we control for a firm’s
research and development expenditures in the past year. Third, we add an indicator
for the degree of technology diversification in a firm’s patent portfolio. A diversified
knowledge base implies a broad set of knowledge components that can be
(re)combined to create new inventions, given that invention equals to a large extent
processes of (re-) combining different components into new combinations (Fleming,
8
2001; Henderson and Cockburn, 1996; Leten et al, 2007). Technological
diversification is measured as the spread of a firm’s technology portfolio over 30
technology classes (inverse Herfindahl index). Finally, the empirical models include
time dummies to account for time-specific factors affecting patent numbers. Summary
statistics for the main variables in our study are found in Table 1.
-----------------------------Insert Table 1 about here
-----------------------------
Empirical Results and Conclusions
The results of the fixed effects Negative Binomial models of the relationship
between internal basic science, external basic science and the technological
performance of firms are reported in Table 2.
-----------------------------Insert Table 2 about here
----------------------------Model 1 includes only the control variables. R&D expenditures, patent stock
and technology diversification have the expected positive signs and are significant at
the 5% level. In model 2, the external basic science variable is added to the set of
control variables. This variable is positive and significant, confirming hypothesis 1:
Firms can enhance their technological performance by exploiting more external basic
scientific findings in their invention activities. Model 3 includes the internal basic
science variable and the controls. A positive and significant coefficient is found for
internal basic science. This confirms hypothesis 2: firms can improve their
technological performance by conducting more basic science activities in-house.
Model 4 adds the ‘collaboration with universities’ variable to model 3. In contrary to
what we expected (hypothesis 3), no significant effect is found for the collaboration
variable (not confirming hypothesis 3). Model 5 is the most complete model and
contains, besides the control variables, both internal and external basic science
9
variables. The results are in line with the findings in models 2 to 4. Firms can improve
their research productivity by conducting more basic science activities in-house, and
exploiting more external basic science findings in their R&D activities.
10
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Table 1: Summary Statistics Variables
N=435
Mean
Min
Citation Weighted Patent Count (Dependent Var)
89,13
0
R&D Expenses (millions US dollars)
470,76
3,62
Patent Stock (4 year portfolio)
202,99
2
Technology Diversification
1,06
0,2
External Science (basic NPLs per patent in stock)
1,91
0,14
Internal Science (basic publications per million US dollar)
0,47
0,47
Collaboration with Universities (share of basic publications) 0,51
0,17
Max
Std. Dev
651
132,87
4846,99 740,97
1609
287,83
2,73
0,46
6
1,2
0,02
4,41
0
1
Table 2: Regression Results (Negative Binomial Fixed Effects Models)
Model 1
0.1768*
(0.0702)
0.2838**
(0.0854)
0.6158**
(0.1343)
Model 2
0.2270**
(0.0709)
0.3171**
(0.0862)
0.6592**
(0.1362)
0.2071**
(0.0665)
Model 3
0.2994**
(0.0823)
0.2042*
(0.0894)
0.6515**
(0.1341)
Model 4
0.2921**
(0.0839)
0.2123*
(0.0912)
0.6551**
(0.1350)
Model 5
log (R&D expenses)
0.3143**
(0.0830)
log (patent stock)
0.2514**
(0.0928)
Technology Diversification
0.6826**
(0.1367)
External Basic Science
0.1662*
(0.0685)
Internal Basic Science
0.3261**
0.3306**
0.2825*
(0.1109)
(0.1118)
(0.1132)
Collaboration with Universities
-0.2027
-0.1900
(0.2796)
(0.2770)
Time Dummies
YES
YES
YES
YES
YES
Constant
-2.7299** -3.8537** -4.0366** -3.9128** -4.6264**
(0.6152)
(0.7047)
(0.7729)
(0.8254)
(0.8588)
Number of Observations
442
442
442
435
435
Chi2
262.00**
274.04**
279.13**
276.58**
283.60**
Log Likelihood
-1543.1518 -1538.5823 -1539.4664 -1516.1933 -1513.3778
Standard Errors are reported between parentheses. * and **denote significance at 1 and 5% level
R&D Expenses is measured in thousands of US dollars
14