Are Research and Development Processes Independent
in the Pharmaceutical R&D?
Miyashige, T. 1, A. Fujii 2 and K. Kimura 3
1

Department of International Trade and Transport, Toyama National College of Maritime Technology, EbieNeriya 1-2, Imizu,Toyama, 933-0293 Japan.
2
Faculty of Economics and Business Administration, The University of Kitakyushu, Kitagata 4-2-1,
Kokuraminamiku, Kitakyushu, Fukuoka,802-8577 Japan.
3
The Graduate School of Natural Science and Technology, Kanazawa University, Kakuma-machi,Kanazawa, Ishikawa, 920-1192 Japan
Email: miyasige@toyama-cmt.ac.jp

Keywords: Blockbusters, pharmaceutical R&D, research process, development process, Poisson regression
EXTENDED ABSTRACT
Blockbusters have become internal resource ofpharmaceuticalcompanies
forcompetitiveadvantage. This article divides the pharmaceuticalR&D into two processes: The research process andthe development process. Based on the RBV theory
with VRIO framework, we argue that it is better toanalyze the performance of the development
process rather than the research outcome in order todetermine the relation between innovation and the1035

proprietary firms’ activity. As an outcome index of
the drug development process, the number ofblockbusters is utilized. Our result of simultaneous
estimation of patent and blockbuster equations are
summarized as follows: (i) The development
process is much more affected by the company
scale than the research process is; (ii) The empiricaleffect of patents on the number of blockbuster issmall compared to the scale elasticity on thedevelopment output.

1.

INTRODUCTION

In this article, we will empirically analyze whether
the research and the development processes areindependent in the pharmaceutical R&D. By‘independent’ we mean that the outcome of theresearch process does not affect empirically theoutcome of the following development process.
To quantify the outcome of the R&D process, wethe‘value-rareness-inimitabilitywill
useorganization (VRIO)’ framework based on the‘resource based view (RBV)’ theory, which isfrequently used in the field of the management
science.
Since the 1980’s, RBV theory, which claims eachcompany’s internal resource contributes to its
competitive advantage, has come to the forefront(Barney, 1991; Wernerfelt, 1984). Barney (1991)
noted such internal resource should have economic
value, rareness and inimitability jointly. These threecriteria constitute VRIO framework.
Kranzler et al. (1995) and Boulton (2000) suggested
the use of ‘blockbuster’ (a new drug with big sale)
as a measure of effective internal resource, because
it enables business organizations to satisfy VRIO
criteria. Their suggestion emphasizes proprietaryfirms' profit motivation, and reveals that previous
studies have shortcomings in the selection of target
variable as described below.
Using this suggested concept, we categorize
previous pharmaceutical R&D studies into fourgroups as follows.
The first group is the empirical studies byGambardella (1992), Henderson and Cockburn(1996), and Schwartzman (1976), which measured
internal resource by the number of pharmaceuticalpatents. The second group is those by Graves andLangowitz (1993), Jensen (1987), and Odagiri andMurakami (1992), which used the number of new
chemical entities (NCEs). These variables lackrareness and economic value except forinimitability.
The third group is by Comanor (1965),
Schwartzman (1976), and Vernon and Gusen(1974), which used a combination of the number ofNCEs and the sales amount. Explained variables inthis group have both inimitability and economicvalue, but lack rareness.
The fourth group is by Cockburn and Henderson(2001), which used the number of approved newdrugs. The explained variable has inimitability andlimited economic value, but it lacks rareness.

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Therefore, by introducing blockbuster as an output
measure, we are able to overcome theseshortcomings. Moreover, if we take blockbuster as
final output measure, the patents and NCEs shouldbe treated simply as intermediate inputs to thewhole R&D process. These two improvements canbe made by estimating patent equation andsubsequent blockbuster equation simultaneously,
and are our main concern. Before presenting theestimation model, we propose dividing the R&D
into two sub-processes in the next section.
2.

RESEARCH AND DEVELOPMENT
PROCESSES OF BLOCKBUSTERIn this section, we explain that pharmaceuticalR&D can be divided into the research and thedevelopment processes, as well as the peculiar
determinant of each process.
The research process is the process to determine aNCE candidate for development. Thus a NCE and apharmaceutical patent result from the researchprocess. Each research project is carried out by asmall unit of individual researchers, and these units
seek different NCEs independently. The success ofeach individual research project depends highly on
serendipity, rather than large scale financial
investment. Further, the percentage of useful NCEs
and patents that shows immediate applicability toblockbuster is quite small.
The development process makes up one of theNCEs into a medicinal product. This process goesfrom the preclinical trial to the clinical trial, andthen to the post marketing surveillance (PMS) after
approval and release. In the development process,especially at the clinical trial and PMS, a vast
amount of development investment and many largeorganized activities are required. If the safety andeffectiveness of the medicinal product cannot be
confirmed during PMS, the approval for such
medicinal product will be cancelled. Therefore, ablockbuster that remains approved can be seen as aresult of the development process.
By this argument, although the outputs of research
process (patents and NCEs) are inputs to thedevelopment process, we expect in our empirical
study that (i) the development process is affected bythe organizational scale of R&D to a higher degree
than the research process is; (ii) the effect ofresearch process on the development process islimited. The empirical model to analyze thisrelation is presented in the following section.

3.

MODEL AND DATA

A simultaneous equation model for pooled datawith a count data equation is used to estimate therelation between R&D expense, patents, andblockbusters. The model is:(1)

log PATi ,t −1 | µi ,t −1 ~ N ( µi ,t −1 , σ 2 ) ,(2)µi ,t −1 = α 0 + α R log RDi ,t −1 ,(3)Pr( BBi ,t = b | λi ,t ) =exp(−λi ,t ) ⋅ λi ,t bb!

,(4)log λi ,t = β 0 + β P ⋅ log PATi ,t −1 + β R ⋅ log RDi ,t ,where PAT is the number of patents newly
acquired by the company; BB is the number ofblockbusters sold by the same company; RD is theannual total R&D expense of the company. The
subscripts i and t denote firm and period
respectively. We assume BB has a Poisson
distribution with mean λ (equation (3)). Given thedata for PAT , BB , and RD , the parameters( α 0 , α R , β 0 , β P , β R , σ ) are estimated by themaximum likelihood estimation (MLE) method.
For equation (1), we assume PAT has a lognormal distribution. Though PAT is a count databy nature, the maximum value of PAT is 495 sothat it is too large to apply a conventional countdata model such as a Poisson regression. Instead,
we adopt a normal distribution for log PAT .
For equation (2), we employ log RD as its
explanatory variable which is a proxy variable forthe firm size as well. In many previous studies thelagged values of RD are jointly taken as
explanatory variables. Unfortunately, our data has
relatively short time-series for many firms and thus
we instead focus on the scale aspect of the firm at
the corresponding time period when the explained
variable is observed.
Equation (3) depicts the count data nature of thenumber of blockbusters, with the mean given inequation (4). As explanatory variables of BB , weemploy both the log of the number of patent( log PAT ) at the previous period and log RD at
the current period, as indicated in equation (4). As

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is clear by the argument in the previous section, thepharmaceutical companies seek to turn theirforegoing patents into profitable products.
Therefore we take the lagged value of log PAT as
explanatory variable together with the firm scale
proxy log RD at the observed time period.
Our data were collected from several sources. For
the number of blockbusters ( BB ), the source is asfollows: Data for years 1990 to 1995 were fromvarious issues of Scrip Magazine (Informa in U.K.,
1990 to 1995); Data for 1996 was from Pharma
Future Magazine (UTO-BRAIN in Japan, 1996);
No data could be obtained for 1997; Data for 1998
was from Pharma Japan Handbook (YakugyoJihosha in Japan, 1998) and were available for U.S.
firms only; Data for 1999 and 2000 were from apress release by Yoshikawa Pharma Institute inJapan (dated May 28, 2001); Data for years 2001 to2003 were from Monthly Mix Magazine (ElsevierJapan , issues in 2003 and 2004). Blockbusters withan annual sale exceeding one billion U.S. dollars
were examined.
The R&D investment ( RD ) and the number ofpatents ( PAT , international classification A61Kin Japan) were obtained from DATABOOK (19922005) published by Japan Pharmaceutical
Manufacturers Association (JPMA). The RD data
were converted to U.S. dollars by the Purchasing
Power Parity (PPP) issued by Organisation for
Economic Co-operation and Development (OECD),
and is expressed in million U.S. dollars.
After eliminating observations which lacknecessary data, we obtained 136 observations for 29
pharmaceutical companies. Sample years range
from 1992 to 2003 except for 1997. The descriptivestatistics of the data described above are shown inTable 1.
Table 1. Descriptive statistics.
VariableMeanStd. Dev.

MinMaxBB

1.926

1.961

0.000

10.000log PAT

3.717

0.861

1.609

6.205

log RD

7.337

0.596

6.122

8.872

*Number of Observation is 136.

4.

ESTIMATION RESULT

Table 2 shows the estimation result of the equations(1) through (4). The scale effect parameter in theblockbuster equation, β R , is estimated to be 0.903

with the standard error 0.184. These figures show
no evidence of increasing or decreasing returns toscale in the production of BB . On the other hand,
α R , the scale effect parameter in the patentequation, is clearly less than unity. This result
emphasizes the productivity of pharmaceuticalresearch process is quite different from that ofdevelopment process in terms of company scale.
The parameterβP

reflects how much thedevelopment process is affected by the output of
research process. The estimate is 0.361, whichmeans 1% increase in the number of patents brings
0.361% increase in the number of blockbusters.
This elasticity is definitely less than the scaleelasticity β R . Using the sample means oflog PAT and BB (3.717 and 1.926 respectively),
we roughly calculate in numerical term, 59(=exp(3.717)/1.926/0.361) newly approved patents
are required to issue one additional blockbuster.
Thus the serendipity in each individual research
process may have limited effect on the development
process.
The small effect of patents on the blockbuster,
together with the great difference between the scaleeffects on patents and blockbusters, implies theessential difference in the research and thedevelopment processes in the pharmaceutical R&D.
Therefore it is consistent with the independence ofthe two processes as discussed in the previoussections.
Table 2. Result of MLE of blockbuster and patent.
Parameter

Estimate

Std. Err.

t-statistic

P-valueα0-1.1190.888-1.260

0.208

αR

0.667

0.119

5.597

0.000

β0-7.591

1.283-5.919

0.000

βP

0.361

0.123

2.944

0.003

βR

0.903

0.184

4.897

0.000

1.321

0.087

15.2690.000.

σ −1
Loglikelihood

5.

Therefore our result supports the empiricalindependence of development process and theresearch process due to the qualitative difference inthe characteristics between the two sub-processes,
as discussed in detail in Section 2.
This seems to have two important implications.
First, the productivity or the production structure ofpharmaceutical R&D should be analyzed not onlywith technological focus but also the proprietaryview on the pharmaceutical companies’ behavior,
since the blockbuster brings much more profit to
the company than the patent which is just an
intellectual asset unless it is developed to a selling
product. Second, in the pharmaceutical industrialorganization, M&A for the larger scale to enableefficient blockbuster development may still occur,
if the search for NCE is more specialized by therelatively small ventures.
6.

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CONCLUSION

Our result of simultaneous estimation of patent andblockbuster equations are summarized as follows:(i) The development process is much more affectedby the company scale than the research process is;(ii) The empirical effect of patents on the number ofblockbuster is small compared to the scale elasticity
on the development output.

1038

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