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European Trend Chart on Innovation
2002 European Innovation Scoreboard Technical Paper No 7 Biotechnology Innovation Scoreboard Innovation/SMEs Programme European Trend Chart on Innovation Table of Content
PREFACE. 3
EXECUTIVE SUMMARY . 4
INTRODUCTION . 6
CHARACTERISTICS OF INNOVATION IN BIOTECHNOLOGY . 7
THE BIOTECHNOLOGY INNOVATION SCOREBOARD (BIS) . 10
HUMAN RESOURCES AND CREATION OF NEW KNOWLEDGE . 10 TRANSMISSION AND APPLICATION OF NEW KNOWLEDGE IN BIOTECHNOLOGY. 11 INNOVATION FINANCE, OUTPUTS AND MARKETS . 11 MAIN FINDINGS. 13
AVAILABILITY OF INDICATORS. 13 RESULTS FOR EUROPEAN COUNTRIES. 15 THE BIS COMPOSITE PERFORMANCE INDEX . 16 NATIONAL STRENGTHS AND WEAKNESSES . 18 CORRELATIONS . 20 REFERENCES . 24
ANNEX A. INDICATOR DEFINITIONS. 25
ANNEX B. THE DIFFERENCE BETWEEN MISSING AND ZERO VALUES. 31
BIOTECHNOLOGY INNOVATION SCOREBOARD. DATA DEFINITIONS,
SOURCES AND RESULTS . 32
The Biotechnology Innovation Scoreboard 2002 European Trend Chart on Innovation 1. Preface
The European Trend Chart on Innovation
Innovation is a priority of all Member States and of the European Commission.
Throughout Europe, hundreds of national policy measures and support schemes aimedat innovation have been implemented or are under preparation. The diversity of thesemeasures and schemes reflects the diversity of the framework conditions, culturalpreferences and political priorities in the Member States.
The European Trend Chart on Innovation serves the "open policy co-ordination approach" laid down by the Lisbon Council in March 2000. It delivers summarised andconcise information and statistics on innovation policies, performances and trends inthe European Union. It is also a European forum for benchmarking and the exchange ofgood practices in the area of innovation policy.
The Innovation Scoreboard and other Trend Chart products
The European Innovation Scoreboard (EIS) is one of the products of the Trend Chart. Initially developed at the request of the Lisbon European Council in 2000, it isnow being published on a yearly basis1. The scoreboard focuses on high-techinnovation and provides indicators for tracking the EU's progress towards the Lisbongoal of becoming the most competitive and dynamic knowledge-based economy.
The European Innovation Scoreboard is complemented by thematic scoreboards such as the present "Biotechnology Innovation Scoreboard".
The scoreboards and all other Trend Chart products (annual country reports; a database of innovation policy measures; annual trend reports; etc) are all available fromthe Trend Chart website (www.cordis.lu/trendchart).
This study has been produced by Lionel Nesta (SPRU), Pari Patel (SPRU) and AnthonyArundel (MERIT) under a service contract with the European Commission. The viewsin this study are those of the authors and do not necessarily reflect the policies of theEuropean Commission. Copyright of the document belongs to the EuropeanCommission. Neither the European Commission, nor any person acting on its behalf,may be held responsible for the use to which information contained in this documentmay be put, or for any errors which, despite careful preparation and checking, mayappear.
Commission contact: Peter Löwe, Innovation Policy Unit ([email protected]) 1 COM(2000) 567; SEC(2001) 1414; SEC(2002) 1349 The Biotechnology Innovation Scoreboard 2002 European Trend Chart on Innovation 2. Executive Summary
1. The Biotechnology Innovation Scoreboard (BIS) is a benchmarking exercisehighlighting strengths and weaknesses of the EU Member States in biotechnologyinnovation. It also includes data on the US, Japan, Switzerland, Norway and Canada.
The BIS is has been produced under the "European Trend Chart on Innovation". As atheme-specific exercise it complements the Trend Chart and the "European InnovationScoreboard", which both cover the entire range of innovation policies.
2. The BIS is a first attempt to measure the main drivers of innovation in the area ofbiotechnology. One of the main difficulties in constructing this scoreboard is the lackof (publicly available) comparable data, as biotechnology does not yet appear in anyofficial statistical classification scheme. Little is known about the level of R&D,employment, output associated with biotechnology and no information is available onone of the key aspects of innovative activity in this area: collaboration between publicand private organisations. As a result of the scarcity of data, only 11 out of 19 potentialindicators have been retained and no trend analysis can be offered.
3. In addition to these overall limitations in statistical data, the number of availableindicators per country varies greatly across countries, with a median of 10 indicatorsper country. Therefore, the findings of the BIS should be treated with care and no directlink should be made between BIS performance and the efficiency of national policies.
The database of innovation policies under the Trend Chart and the findings of the morespecialised EPOHITE project in assessing the effectiveness of national biotechnologypolicies are very useful in this respect.
4. The BIS data suggest that the Nordic countries (Denmark, Sweden and Finland) arethe leading EU performers in biotechnology. Sweden is in a leading position inbiotechnology publications, the number of dedicated biotechnology firms and thepublic knowledge about biotechnology. Denmark is the top performing country interms of USPTO patents and drug approvals. Other small EU countries are alsoamongst the leaders. For example Belgium is in a leading position in terms ofgovernment R&D spending venture capital, and field trials of GMO crops. Switzerlandhas also a high level of innovation in biotechnology.
5. The larger countries, Germany, the United Kingdom and France are in the secondtier, achieving very similar level of performance. They are relatively strong in eight outof the 11 indicators. The UK is relatively strong in public spending in biotechnology,biotechnology publications and in the number of DBFs. Germany is relatively strong inthe number of citations per paper, in biotechnology patent applications at the EPO andin venture capital. France is relative strong in the number of PhD graduates and in fieldtrials in GMO crops.
6. The composite Best Performance Index (BPI) was constructed in order to give an "ata glance" overview of countries according to their general performance inbiotechnology. For a given indicator, each country's score is first converted into astandardized value (z score). Each score is then re-scaled to vary within an identicalrange (0 to 1). The BPI is then the average of the re-scaled z-values and reveals theaverage relative performance for all the eleven indicators for which data are available.
The Biotechnology Innovation Scoreboard 2002 European Trend Chart on Innovation Best Performance Index in the Biotechnology Innovation Scoreboard
(All BPI means have been multiplied by 100) 7. While the European Union as a whole lags significantly behind the USA, the topperforming EU countries have a comparable level of performance. However this resultneeds to be treated with care as two key indicators for the USA are missing in theabove analysis: government spending in biotechnology and venture capital. Theinclusion of these may substantially improve the US position.
8. There are some interesting correlations amongst the different indicators of BIS. Forexample government spending in biotechnology is linked positively to the number ofcitation per paper, USPTO patents, venture capital and the public knowledge aboutbiotechnology. This suggests that countries with a relatively high level of publicspending on biotechnology are relatively more successful in terms of knowledgecreation and also attract a higher level of venture capital. Additionally publicknowledge about biotechnology is linked to seven BIS indicators covering almost allaspects of biotechnology. This is consistent with the view that the public awareness ofbiotechnology goes hand in hand with the development of biotechnology.
9. Importantly, the BIS offers hints how the EU Member States might mobilise theirvarious strengths jointly in order to increase the overall critical mass of the EuropeanUnion in biotechnology innovation. This could encourage the development ofbiotechnology in Europe on a scale comparable to the US.
The Biotechnology Innovation Scoreboard 2002 European Trend Chart on Innovation Many analysts and policy makers regard biotechnology as a major contributor to futureeconomic development and structural change in a variety of industries, namelypharmaceuticals, food, agriculture, energy and chemicals. It is also perceived to haveimportant implications for the quality of life of human beings in terms of their health,environment and nutrition. As the recent communication from the EuropeanCommission to the European Parliament, the Council and the Economic and SocialCommittee, and the Committee of the Regions states: "Life Sciences and biotechnology are widely recognised to be, after informationtechnology, the next wave of the knowledge-based economy, creating new opportunitiesfor our societies and economies" (Life Sciences and Biotechnology – A Strategy forEurope, EC (2002), p. 7).
That communication also outlines a strategy for Europe to develop sustainable andresponsible policies to benefit from the positive potential of biotechnology. At the sametime Member States have also undertaken a broad range of policies to achieve similaraims.
Despite this widespread policy interest there is a general perception that we lack
systematic (internationally comparable) data on many aspects of biotechnology and its
effects on the economy and society. The purpose of the Biotechnology Innovation
Scoreboard (BIS) is to see the extent to which we can assemble a set of indicators
related to one aspect, namely the innovation process in biotechnology. The idea is to
gather readily available data from a number of disparate sources to make systematic
comparisons of innovative activities of EU countries, and where possible compare them
to the US and Japan. A number of recent studies (e.g. Chapter 5 in the EC
Competitiveness Report (2001), and OECD (2002a, 2002b) have addressed similar
issues at length, and information from these will be utilised here. Hence this report is
mainly about assembling and interpreting available data in a readily accessible form
similar to the European Innovation Scoreboard (EIS). However given the experimental
nature of such thematic scoreboards, the information and analysis is not as systematic
and comprehensive as in the EIS.
The main contribution of BIS is to provide readily available data and indicators onwhich informed policy debates could be based. It will allow policy makers to relatetheir existing set of S&T policies to a set of indicators charting innovative activities inbiotechnology. It is worth noting that another EU funded project aims at assessing theeffectiveness of biotechnology policies in all EU countries (the EPOHITE project)2.
This project utilises two methods in order to link biotechnology policies to countryperformance. First, at a macro level the aim is to link gross national indicators (similarto those included in BIS) to some policy profiles. Of course the main difficulty is thatonly a very small number of policies are specifically aimed at a specific area of 2 More details on EPOHITE can be found at: http://www.epohite.fhg.de/index.html.
The Biotechnology Innovation Scoreboard 2002 European Trend Chart on Innovation technology, such as biotechnology. Secondly, this project involves a set of interviewswith firms and public sector research organisations that are the likely beneficiaries ofgovernment policies in the various EU countries. Preliminary EPOHITE results suggestthat there are a number of difficulties in relating specific policies to a set of macroindicators. Thus it will be difficult to use BIS to assess policy effectiveness. Rather itshould be seen as a first step towards a more rigorous assessment of the impact of givenpolicies within the realm of biotechnology.
Section 2 outlines the main characteristics of biotechnology and how these are relatedto the innovation process. Section 3 discusses the main elements of the scoreboard andthe indicators, and section 4 presents the main results.
4. Characteristics of Innovation in Biotechnology
The first step in characterising innovation in biotechnology is a discussion of what thetechnology entails. Biotechnology can be defined in many ways. For example we couldbegin by listing the main areas of technology. This would produce a list of variousscientific and technical disciplines such as genetic engineering (gene manipulation),cell culture (preparation of given tissues), fermentation techniques, bioinformatics(storage, retrieval and analysis of DNA sequences), etc. Alternatively one could list thevarious areas of application, such as the preparation of biological material fortherapeutic solutions (pharmaceuticals), manipulation of animal (e.g. proteinproduction), plants (e.g. food production) and microorganisms (mainly viruses andbacteria). Such an approach would then result in mapping the national knowledge baseand market specialisation of a given set of countries. This is the approach adopted inEC Competitiveness Report (2001) and is suitable for detailed surveys of firms andother institutions involved in the innovation process.
However BIS is concerned with providing a set of macro-level indicators that coulddescribe innovative activities within Europe in a summary fashion. Thus the definitionof biotechnology used in this report is the one suggested by the OECD working party ofNational Experts on Science and Technology Indicators (NESTI): "Biotechnology is the application of science and technology to living organisms, aswell as parts, products and models thereof, to alter living or non-living materials for theproduction of knowledge, goods and services."(A Statistical Framework forBiotechnology Statistics (OECD, 2002a), p. 4) The Biotechnology Innovation Scoreboard 2002 European Trend Chart on Innovation Importance of Public Sector Research
This definition makes it clear that although much has been written about the death ofthe linear model of innovation, in biotechnology the linear model lives on. Unlike manyother technological fields, the main characteristic of the innovation process inbiotechnology is that it depends crucially on developments in basic science. One of theimplications of this is that publicly funded basic research is vitally important ifcountries are to succeed in creating new products and new processes. Such researchproduces specific scientific discoveries leading directly to new products and processesand new instrumentation, as well as trained graduates and researchers.
Collaborations between PSROs and firms One of the ways in which the scientific knowledge developed by public sector researchorganisations (universities, government laboratories, etc.) gets translated into newbiotechnology related products and services is by means of collaborative activitybetween such institutions (PSROs) and industrial firms. Most EU countries have arange of policies aimed at encouraging such collaboration, from subsidies for firms tocontract out research to PSROs, to providing incentives for supplying consultancy andtechnical services to industry, to funding for collaborative programmes of research.
Importance of Commercialisation Ultimately biotechnology is about applying knowledge about living organisms todeveloping new products and processes. Thus the expected end result is the launchingof new medicines (pharmaceuticals), or new productive processes (e.g. fermentationtechniques in the food industry), or new crops (seed industry). This may arise fromstaff of PSROs getting directly involved in commercialisation by launching spin-offfirms. Alternatively it may be the result of licensing arrangements between firms andPSROs. Policies to encourage such activities are widespread among EU countries.
Role of large and small firms Although public research has been widely recognised to be a major factor towards thedevelopment of biotechnology, one should not downplay the critical role played byprivate actors. Because biotechnology is at the forefront of scientific research,researchers have a natural advantage in foreseeing potential applications. A substantialnumber of dedicated biotechnology firms (DBFs) have been created, many founded byformer university scientists. DBFs are deemed to have 3 roles: (i) they play the role ofknowledge explorers in an enormously complex space of innovative opportunities; (ii)they transform scientific knowledge into technological and commercial applications;and (iii) they are crucial agents in the division of innovative labour (Saviotti, et al.,1996; EC Competitiveness Report, 2001). Initially aiming at replacing incumbents in aparticular market, DBFs have met great difficulties in reaching the market and thus inbecoming profitable. Hence they have had to re-position themselves as collaboratorswith larger firms, who have the necessary financial and marketing expertise to The Biotechnology Innovation Scoreboard 2002 European Trend Chart on Innovation commercialise new products. Large firms themselves have invested heavily in theacquisition, integration and exploitation of biotechnology knowledge. In the long runsuccessful developments in biotechnology require a strong partnership between smalland large firms.
Contributions to the quality of life The belief that biotechnology will become the next major wave of economictransformation and development is based on the pervasive character of biotechnology.
Biotechnology offers new technological solutions for a variety of industries, i.e.
pharmaceuticals, food, agriculture, energy and chemicals. Yet estimations on the extentto which productive activities are affected by biotechnology challenge this view. Forexample, the Ernst & Young report on the economic contribution of the biotechnologyindustry to the US Economy estimates that in 1999, the direct and indirect impact ofbiotechnology amounts to 0.22%, and 0.5% of GDP3, respectively (Ernst & Young,May 2000). However such estimations miss out what may well turn out to be the mostimportant impacts of biotechnology, i.e. those on the quality of life (nutrition, healthand environment). The main challenge is how to measure and assess these.
Role of public perceptions in shaping biotechnology Biotechnology is the subject of vigorous public debates in a number of different areas:GMO crops, manipulation of human cells and embryos for pharmaceuticals research,human and animal cloning. The rate and direction of research and innovation in thesefields is likely to be shaped by public attitudes to these issues. The Eurobarometerreport 52.1 "The Europeans and Biotechnology" published by the EuropeanCommission (DG Research) in 2000 shows that there exists a positive relationshipbetween knowledge about biotechnology and optimism concerning the benefits that onemight expect for future developments in this domain.
3 In nominal values, the direct and indirect impacts amount to US$20.2 billion and $46.5 billion.
The Biotechnology Innovation Scoreboard 2002 European Trend Chart on Innovation 5. The Biotechnology Innovation Scoreboard (BIS)
BIS adopts the framework used in the European Innovation Scoreboard (EIS) inorganising the relevant indicators, with some modification. One modification is a newcategory that includes both Human Resources and Creation of New BiotechnologyKnowledge. The other two categories remain the same: Transmission and Applicationof Biotechnology Knowledge, and Innovation Finance, Output and Markets inBiotechnology. The 19 potential indicators chosen for BIS are identified and brieflydiscussed in the next three subsections. Annex A presents them in greater detail.
5.1. Human Resources and Creation of New Knowledge Biotechnology is one of the most "science-intensive" areas of technology. This meansthat the generation of new knowledge is one of the most crucial aspects of theinnovation process. Such new knowledge is firstly incorporated in scientists trainedwithin universities and other public sector institutions. Thus indicator 1.1 (PhD.
Graduates in Life Sciences) reflects the capacity of countries to produce a pool of suchhighly skilled labour.
One way of gauging the priority given by governments to the creation of newknowledge in biotechnology is by examining the amount of government expenditure onresearch (indicator 1.2). The 1990s have witnessed a substantial increase in theintervention of public authorities in such research. Public programmes are aimednotably at strengthening the national knowledge base and tightening the links betweenpublic research bodies and research undertaken in private organisations.
Creation of new knowledge can also be measured using counts of scientificpublications. Thus indicator 1.3 captures very well the scientific capacity of a country.
A measure of the "quality" of a scientific publication is the number of times it issubsequently cited by other publications (1.4). The other two indicators of knowledgecreation are based on patenting at the EPO and at the USPTO (indicator 1.5 and 1.6respectively).
New knowledge can also be created by private firms engaged in biotechnology relatedresearch and BIS includes 3 indicators to capture this process. The first is simply theprivate investments in biotechnology R&D (indicator 1.7).
The Biotechnology Innovation Scoreboard 2002 European Trend Chart on Innovation 5.2. Transmission and Application of New Knowledge in Biotechnology The Inventory report (1999) has shown that many EU countries have extensive publicprogrammes in biotechnology aimed at supporting knowledge transfer from publicresearch institutes to private organisations, be they large companies or DBFs. This iscrucial as successful innovative activities in biotechnology require a network ofrelationships between heterogeneous actors, ranging from those engaged in upstreamresearch to those involved in downstream development activities (Kenney, 1986;Orsenigo, 1999; Orsenigo, et al., 1998). Thus it is not surprising that a key objective forpolicy markers in most countries is to encourage research collaborations betweenpublicly funded basic research organisations and private firms. A commonly usedincentive relies on allowing scientists to devote a substantive part of their allocatedtime to private research and consultancy.
In order to capture evidence of such inter-institutional flows of knowledge andexpertise, one source of information is the number of collaborative agreements betweenpublic research organisations and companies (indicator 2.1). An alternative, moreindirect way of capturing such linkages is to count the number of joint publications andjoint patents, between public sector scientists and those engaged in R&D and otheractivities in industry (indicators 2.3 and 2.4).
Another way of transferring knowledge is by encouraging scientists to create firms toexploit research conducted within universities and other public research organisations.
As well as providing financial incentives to create new firms, many EU member stateshave modified the legal status of public researchers to enable this process. Thus thenumber of university spin-offs is a potential indicator for inclusion in BIS (2.2).
5.3. Innovation finance, outputs and markets Innovative activities in biotechnology can lead to the introduction of a new product tothe market, improvement in some process technologies, or to the introduction of newinstrumentation. This section of the scoreboard is concerned with measuring someaspects of this process of commercialisation. In biotechnology creation of new firms(DBFs) remains one of the most effective means of bringing scientific knowledge to themarket. The creation of such new firms has also been a policy priority in mostEuropean countries, as revealed in the Inventory report (1999). Indicator 3.1 thuscounts the number of DBF by country. The availability of venture capital is an essentialingredient for creating new firms. The underlying rationale is that bringing successfulproducts to market in biotechnology is a long term and risky process, requiringsubstantial funds. The availability of such funds is also perceived to be one of the majorreasons for the US lead in the commercialisation of biotechnology. Indicator 3.1measures the amount of venture capital by country.
One measure of the success of biotechnology is the amount of employment generated.
As shown in successive Ernst & Young reports, the creation of new firms in EU has notled to a corresponding growth of employment in DBFs. European DBFs are found The Biotechnology Innovation Scoreboard 2002 European Trend Chart on Innovation significantly smaller to those of the USA. Thus indicator 3.2 compares employmentlevels associated with biotechnology. Another related measure of economic success isthe amount of revenue generated (indicator 3.5). Data availability is problematic forboth these indicators as biotechnology related activities are undertaken not only byDBFs (as identified in indicator 3.1) but also by large firms involved in a number ofindustries such as Pharmaceuticals and Food.
One of the key ways in which biotechnology products may reach the marketsuccessfully is through a partnership between DBFs and large firms. Many DBFsinitially aimed at replacing incumbent large firms, but they often lacked the necessaryfinancial/managerial/marketing resources to bring major products to market. Largefirms typically possess such skills but often do not have in house knowledgecapabilities possessed by the DBFs. This situation has led to the latter specialising inniches of knowledge exploration (Pyka and Saviotti, 2002) and setting upcollaborations with the former to commercialise innovations. Indicator 3.4 is a measureof this process.
Indicators 3.6 and 3.7 focus on biotechnology outputs in two major applications ofbiotechnology: pharmaceuticals and GMO crops. Indicator 3.6 focuses on the numberof biotechnology drug approvals. Such drug approvals are a rare occurrence, but lead tomajor pay-offs for the company introducing them. Indicator 3.7 counts the number offield trials of GMO crops being undertaken in each country. National field trial countsfor GM organisms provides an indication of national capabilities in GM crop research.
Here we use the number of field trials summed over the period 1996-2001. The annualdata show that, in Europe, the number of field trials (trial-trait combinations) declinedafter 1998, possibly due to the effect of the de facto moratorium on thecommercialisation of GM crops in July 1998. For example, the total number of EUfield trials in 1999-2000 inclusive declined by 33.6% in comparison with the two yearperiod of 1996-1997 before 1998. In comparison, the number of field trials in the USincreased by 38.4% over the equivalent time period.
The last indicator (3.8) provides information on public awareness of biotechnology,i.e., it measures the extent to which people have knowledge about biotechnology. Otherindicators could have served a similar purpose, for example by focusing on publicattitude (expected benefits, acceptation and risk) to the development of biotechnology.
Here, it is assumed that greater knowledge leads to greater acceptance ofbiotechnology.
The Biotechnology Innovation Scoreboard 2002 European Trend Chart on Innovation 6. Main Findings
6.1. Availability of Indicators The complete results for the Biotechnology Innovation Scoreboard are given in AnnexC. Table C1 defines each indicator, gives the reference year and provides the datasources. Table C2 provides the actual results in relative terms, for the 15 Europeancountries and for Norway, Switzerland, the USA, Canada and Japan. An importantconsideration in the construction of BIS is the unavailability of data and Annex Bdiscusses further the way missing values and zero values have been handled in BIS4.
Table 1. Number of countries per indicator
Number of
PhD. Grads in Life Sciences Gov. Biotech. R&D Biotech Publications Citations per publication in Biotech Biotech EPO patents Biotech USPTO patent applications Business Biotech R&D Coll. Res. Agreements PSRO-Industry University Spin-offs Joint Pub. PSROs and Industry Joint EPO patents PSROs and Industry Dedicated Biotech Firms Biotech Employment Biotech Venture Capital Alliances large firms and DBFs Field Trials in GMO crops Average Score Knowledge About Biotech Table 1 displays the number of observations per indicator (Column 3) and the regionalorigin (Columns 4 and 5). Information for only 12 of the 19 indicators has been found,reflecting the general scarcity of systematic data in emerging fields such asbiotechnology. Moreover data availability is unevenly distributed across the three partsof BIS. In part 1, Human Resources and Creation of New Knowledge, we haveinformation on 6 of the 7 indicators. However very little information is available forindicators in part 2, Transmissions and Application of New Knowledge. This issurprising given the importance of research collaborations between public and privateinstitutions in the development of biotechnology. The only indicator for which anyinformation was found was the number of collaboration agreements between PSROsand firms (indicator 2.1). Even in this case the data only exist for two EU countries.
4 This has important implications for the way in which the EU mean has been calculated as well as BPI.
The Biotechnology Innovation Scoreboard 2002 European Trend Chart on Innovation Thus, indicator (2.1) is not used in the analysis below. In the case of Innovationfinance, outputs and markets (part 3) data exist for 5 out of the proposed 8 indicators.
The data collection exercise involved a widespread search of empirical literature5. Thisresulted in the identification of a number of indicators that were available at thenational level for some countries. Examples are indicators 1.7 (Business Biotech R&D),2.2 (University Spin-offs), 3.2 (Biotech Employment) and 3.5 (Biotech Revenues). Thesefirm-level data are contained in national reports, journal articles or privately helddatabases. They are often based on differing definitions of what constitutes abiotechnology firm and its subparts, and therefore are not comparable. The result is thatvery few firm-level indicators are included in BIS. Data for most of the 11 indicatorsthat are included in BIS are either gathered by some government or public body or areavailable from publicly available databases (e.g. on patents and publications).
Table 2 displays the number of indicators found per country (Column 5) and theirrelated themes (Columns 2 to 4). The median number of available indicators percountry is 10, but ranges from 5 (Luxembourg) to 12 (Germany and the UK). There isvery little difference in the mean number of indicators found between the EU (withmean 9.9) and non-EU countries (with mean 8.0).
Table 2. Number of indicators per country
BIS-PART 1
BIS-PART 2
BIS-PART 3
5 We are most grateful to M. Bernhard Zechendorf and Waldemar Kütt (Scientific Officers at theEuropean Commission – DG Research) who provided us with a substantial support in our search fordata.
The Biotechnology Innovation Scoreboard 2002 European Trend Chart on Innovation One of the main difficulties in collecting data and organising BIS is that biotechnologydoes not yet appear in any official statistical classification scheme. This means that wecannot make use of the usual data sources such as CIS and R&D surveys. It also meansthat a number of important datasets have been collected privately, for example by Ernst& Young or by academic researchers at the University of Sienna (the so-called BIDdatabase (Biotechnology Information Databank)). It is very difficult to check thevalidity of these databases, as there is very little information on how the data werecollected. Additionally although some data for constructing some of the proposedindicators may exist, for example in the BID database, they were not available for theconstruction of BIS.
6.2. Results for European Countries Table 3 summarizes the main findings of BIS. For each indicator, table 3 provides theEU mean, the first two leading countries in Europe and the coefficient of variation(CV), multiplied by a hundred. The latter informs us on the degree of dispersionthroughout EU countries around the mean.
Table 3. Main Findings in the Biotechnology Innovation Scoreboards
PhD. Grads in Life Sciences pmC Gov. Biotech. R&D % GDP Biotech Publications pmC Citations per publication in Biotech Biotech EPO patent applications pmC Biotech USPTO patents pmC Dedicated Biotech Firms pmC Biotech Venture Capital % GDP Drug Approvals pmC Field Trials in GMO crops per 109. GDP in Agr Average Score Knowledge About Biotech The Scandinavian countries (Denmark, Sweden and Finland) dominate the EUleadership in biotechnology, as they are among the top two EU leading countries in 5 ofthe 12 indicators. Sweden is in a leading position in biotechnology publications (1.3),the number of dedicated biotechnology firms (3.1) and the public knowledge aboutbiotechnology (3.8). Denmark is the top performing country in terms of USPTO patents(1.6) and drug approvals (3.6). Other small EU countries are also amongst the leaders.
For example Belgium is in a leading position in terms of government R&D spending(1.2) venture capital (3.3), and field trials of GMO crops (3.7).
The Biotechnology Innovation Scoreboard 2002 European Trend Chart on Innovation As for the large EU countries, France has a lead in PhDs in life sciences. Germany isamongst the leaders (citations per publication) and venture capital provision. The UKtakes the lead in the quality of its science base and is in second position for governmentbiotechnology funding.
The coefficient of variation (CV) provides a measure of the variation of each indicatoracross the member states for which data are available. Indicator (3.6) has the largestvalue for CV, showing a highly skewed distribution of drug approvals across countries.
This partly reflects the fact that a large part of research in biotechnology does notnecessarily lead to new drugs. Rather, innovation in the bio-pharmaceutical industryfollows a Poisson distribution, where a few successes result from a very large numberof trials.
Likewise, the higher CV value for indicator (1.6) as compared to that of indicator (1.5)indicates that differences amongst EU countries tend to increase when patenting in theUSA. This must be interpreted with care, as it is likely to reflect two different effects.
First, it may be the result of the fact that it is harder for EU inventors to patent in theUSA (compared to patenting at the EPO), and that this process may be harder for someEU countries than others. The second effect might be due to differences in the nature ofthe two indicators: indicator (1.5) counts patent applications (at the EPO) whileindicator (1.6) counts patent granted (at the USPTO).
Results are more uniform for knowledge about biotechnology (3.8) and citations perpublication in biotechnology (1.4). Comparing CV values between the number ofpublication per country (indicator 1.3) and the number of citations received (indicator1.4) shows that differences amongst countries in the volume of scientific activity aregreater than those in the quality of that output.
6.3. The BIS Composite Performance Index A composite Best Performance Index (BPI) was constructed along the lines suggestedin the EIS Methodology Report (2002) for TrendChart. Briefly for a given indicator,each country's score is first converted into a standardized value (z score). Each score isthen re-scaled to vary within an identical range (0 to 1). The BPI is then the average ofthe re-scaled z-values and reveals the average relative performance for all the elevenindicators for which data are available. This measure was preferred to the SummaryInnovation Index (SII) as proposed in the methodological report of the 2002scoreboard6 because the SII measure is very sensitive to cross country differences in theavailability of data7. 6 Dowloadable from ttp://trendchart.cordis.lu/Scoreboard2002/html/download_area/download_area.html7 The SII is equal to the number of indicators that are 20% above average minus the number of indicatorsthat are 20% below average. While this technique could prove suitable when we have the same numberof indicators across countries, its relevance declines sharply when observations are unevenly distributedacross countries, as is the case here.
The Biotechnology Innovation Scoreboard 2002 European Trend Chart on Innovation Although the BPI is less sensitive to the uneven distribution of indicators acrosscountries than the SII, the results should still be interpreted with care. The number ofindicators per country ranges from 5 (Luxembourg) to 11 (Germany and the UK). Thusfor the latter countries the BPI is a fairly good reflection of performance in a widerange of innovative activities within biotechnology. However the same cannot be saidfor Luxembourg. Interestingly, the correlation coefficient between the number ofindicators per country and the BPI is 0.67 (p-value = 0.009) for the Europeancountries8.
Graph 1. Best Performance Index in the Biotechnology Innovation Scoreboard
(All BPI means have been multiplied by 100) Graph 1 shows that Denmark, Sweden and Belgium are leaders in innovation inbiotechnology within the EU. The larger EU countries such as Germany, the UK andFrance are a part of the second group of countries around the median (•30). Theseresults reflect two different patterns of biotechnology development in the EU. The firstgroup could be labelled specialised biotechnology countries, where innovativeactivities are of a smaller scale, and in niche areas but which enables these countries tobe world leaders. The second group of countries has a high volume of activity spreadacross a range of biotechnology areas. This is quite important insofar as thedevelopment of biotechnology is increasingly reliant on the availability of heavyequipment and on large-scale research programs, be they public (as is the case for mostcountries in Europe), or private (as in the case in large firms). The remaining countriesreflect heterogeneous country performances. The Netherlands and Finland perform 8 This suggests that better performing countries may monitor their biotechnology related activities morethan others.
The Biotechnology Innovation Scoreboard 2002 European Trend Chart on Innovation well, while there is substantial gap that separates Southern European countries from thebetter performing groups.
Graph 1 displays the BPI of other non-EU countries. It illustrates the significant lead ofthe USA over the European Union. The position of the USA is not surprising, as it iswidely acknowledged to be the leader in biotechnology innovation, with considerablefirst-mover advantages. Moreover the BPI of the USA is likely to be underestimateddue to the unavailability of two key indicators, namely government biotechnologyR&D spending (1.2) and biotechnology venture capital (3.3). The inclusion of theseindicators would positively affect the overall position of the US.
Graph 1 also shows that Switzerland has a higher BPI than all European countries. Thecase of Switzerland is interesting, as it is a country where the development ofbiotechnology is tightly linked to the translation of biotechnology knowledge into newproducts, mainly in the pharmaceutical industry. The performance of Canada andNorway conforms to that of the EU-15, while that of Japan appears to lag significantlybehind.
6.4. National Strengths and Weaknesses Table 5 identifies the countries' main strengths and weaknesses across the 11indicators. These are limited to the first three indicators that are 25% above or belowthe EU mean. The countries are ranked according to their BPI.
The table shows that only the USA and Sweden do not have any major relativeweaknesses while Austria, Italy, Spain, Portugal and Greece do not have any majorrelative strength. All other countries exhibit both heterogeneous strengths andweaknesses, though their number varies consistently with their rank in the BPI.
Not surprisingly, most countries with major relative strengths have few majorweaknesses and conversely, most countries with major relative weaknesses have fewmajor strengths. This is quite consistent with the idea that the development ofbiotechnology requires investment in many different areas, ranging from humanresources and the creation of new knowledge to the creation of new firms and markets.
Moreover, the fact that countries cannot bypass the general path from mere knowledgeto markets may prove difficult for countries that lag behind. It is quite likely that thesecountries have not only to cope with low resources in biotechnology in some givenareas, but are also facing more general shortcomings in public and privateinfrastructures.
The Biotechnology Innovation Scoreboard 2002 European Trend Chart on Innovation Table 5. Strengths and Weaknesses in the Biotechnology Innovation Scoreboard
Major Relative Strengths
Major Relative Weaknesses
1.3 Biotech Publications; 1.5 Biotech EPO patents 1.2 Gov. Biotech. R&D; 3.3 Biotech VC Appl.; 3.6 Drug Approvals 1.5 Biotech EPO patents Appl.; 1.6 Biotech 1.2 Gov. Biotech. R&D USPTO patents; 3.6 Drug Approvals 1.3 Biotech Publications; 1.6 Biotech USPTO patents; 3.1 DBFs 1.6 Biotech USPTO patents; 3.6 Drug Approvals; 3.7 Field Trials in GMO crops 1.5 Biotech EPO patents Appl.; 3.3 Biotech VC; 1.1 PhD. Grads in LF 3.7 Field Trials in GMO crops 1.2 Gov. Biotech. R&D; 1.6 Biotech USPTO 1.5 Biotech EPO patents Appl.; 3.3 Biotech VC; patents; 3.1 DBFs 3.7 Field Trials in GMO crops 1.3 Biotech Publications; 1.5 Biotech EPO patents 1.2 Gov. Biotech. R&D; 3.3 Biotech VC; 3.7 Field Appl.; 1.6 Biotech USPTO patents Trials in GMO crops 1.2 Gov. Biotech. R&D; 1.3 Biotech Publications; 1.4 Citations per publication; 1.5 Biotech EPO 3.6 Drug Approvals; 3.7 Field Trials in GMO patents Appl.; 3.3 Biotech VC 1.1 PhD. Grads in LF; 3.7 Field Trials in GMO 1.5 Biotech EPO patents Appl.; 3.3 Biotech VC 1.4 Citations per publication; 1.6 Biotech USPTO 1.1 PhD. Grads in LF; 3.6 Drug Approvals patents; 3.1 DBFs 3.1 DBFs; 3.6 Drug Approvals 1.6 Biotech USPTO patents; 3.3 Biotech VC; 3.7Field Trials in GMO crops 1.6 Biotech USPTO patents 1.3 Biotech Publications; 1.5 Biotech EPO patentsAppl.; 3.1 DBFs 1.2 Gov. Biotech. R&D; 3.1 DBFs; 3.7 Field Trialsin GMO crops 1.2 Gov. Biotech. R&D; 1.5 Biotech EPO patentsAppl.; 3.3 Biotech VC 1.2 Gov. Biotech. R&D; 1.5 Biotech EPO patentsAppl.; 3.3 Biotech VC 1.3 Biotech Publications; 1.5 Biotech EPO patentsAppl.; 1.6 Biotech USPTO patents 1.5 Biotech EPO patents Appl.; 1.6 BiotechUSPTO patents; 3.3 Biotech VC 1.5 Biotech EPO patents Appl.; 1.6 BiotechUSPTO patents; 3.3 Biotech VC Table 5 also shows that government policies can have a major role in alleviating someof the major weaknesses of the leading EU countries. In Denmark and Netherlandsthese relate to government funding of biotechnology related R&D, and in Belgium andFinland the number of PhDs is a major concern.
Turning to the 3 larger countries we see that together they are relatively strong in 8 outof the 11 indicators. The UK is relatively strong in public spending in biotechnology(indicator 1.2), biotechnology publications (indicator 1.3) and in the number of DBFs The Biotechnology Innovation Scoreboard 2002 European Trend Chart on Innovation (indicator 3.1). Germany is relatively strong in the number of citations per paper(indicator 1.4), in biotechnology patent applications at the EPO (indicator 1.5) and inventure capital (indicator 3.3). France is relative strong in the number of PhD graduates(1.1) and in field trials in GMO crops (indicator 3.7). Importantly, the jointmobilisation of these strengths may provide a minimal critical mass in Europe thatcould encourage the development of biotechnology on a scale comparable to the US.
6.5. Correlations We conducted an analysis of the 11 indicators of the biotechnology innovationscoreboard for which data are available in order to detect correlations amongstindicators and with BPI. The aim of this analysis is to provide a picture of the linkswithin the BIS, and at the same time to look at some of the relationships amongstdifferent aspects of the innovation process within biotechnology. Table 6 displays theSpearman correlation coefficients9, their associated p-values and the number ofobservations. All correlations that are significant at 5% level are highlighted.
An examination of the correlations amongst the 11 indictors shows that 25 out of 55correlation coefficients are significant. Most indicators in part 1 (Human Resources andCreation of New Knowledge), with the exception of 1.1, are highly correlated amongsteach other. This suggests that countries that perform well in terms of the volume andquality of the science base are also likely to perform well in terms patenting. Thisshows that both these set of activities are linked to some common underlying structure,which is likely to be related to public sector research activities. This result implies thatpublic programmes aimed at improving knowledge creation in various different formsmay follow common or complementarity channels. Conversely, indicators in part 3(Innovation finance, outputs and markets), with the exception of 3.8, have very fewsignificant correlations amongst each other. There is a positive correlation between theventure capital (3.3) and the number of field trials (3.7), though the exact nature of therelationship between these two indicators is not clear. This result suggests that eachindicator in this part is capturing a different aspect of innovative activity.
From a policy perspective it is interesting to note that indicator 1.2 on governmentspending in biotechnology is linked positively to citations (indicators 1.4), USPTOpatents (indicator 1.6), venture capital (indicator 3.3) and the public knowledge aboutbiotechnology (3.8). These results suggest that the countries with a relatively high levelof the public spending on biotechnology are relatively more successful in terms ofknowledge creation and also attract a higher level of venture capital. However it isdifficult to argue on the basis of these correlations that government policies are highlyeffective in stimulating innovative activities in biotechnology.
9 The Spearman rank correlation is a non-parametric measure of correlation between two ordinalvariables. The values of each of the variables are ranked from smallest to largest, i.e. all countries areranked, and a Pearson correlation coefficient is computed on the ranks. The advantage in using theSpearman calculation is that it does not assume normality in the distribution of the variables, anassumption that is likely to be violated here when considering the number of observations at hand.
The Biotechnology Innovation Scoreboard 2002 European Trend Chart on Innovation Table 6. Correlations amongst BIS indicators (p-values in Italics) There are a number of reasons for this. Firstly, such an argument ignores the inherenttime lag between the actual implementation of biotechnology policies and their endresults. Innovation in biotechnology is a time consuming process with a highprobability of failure. Secondly government programmes have a variety of aims. Forexample many programmes are aimed at promoting collaborations betweenbiotechnology actors (PSROs, DBFs, large firms), but, as discussed in section 4.1,indicators related to such collaborative activities are not available. Others programmeshave been directed towards the creation of DBFs, but Table 6 shows that there is nocorrelation between relatively high levels of government spending (1.2) and the numberof DBFs (3.1).
There is a puzzle regarding the lack of relationship between the number of PhDgraduate students (1.1) and other indicators. This suggests that a country's performancein many aspects of innovative activities in biotechnology is not correlated with itssuccess in producing a relatively high volume of qualified scientists. This supportssome analysts who have repeatedly warned that the production of high skilled labour in The Biotechnology Innovation Scoreboard 2002 European Trend Chart on Innovation Life Sciences may prove dramatic for cohorts of young researchers who face little jobopportunities that correspond to their educational background10 (Dany andMangematin, 2001; Robin, 2003).
Meanwhile, indicator 3.8 on public knowledge about biotechnology is linked to sevenBIS indicators, ranging throughout almost all aspect of biotechnology. This isconsistent with the view that the public awareness of biotechnology goes hand in handwith the development of biotechnology. However, considering the statisticalindependence (r = -0.036) between indicators 1.1 and 3.8, it appears that such generalknowledge is not channelled through the educational system in Life Sciences. It is quitelikely that it follows other routes.
Indicator 3.3 on venture capital is significantly correlated with seven other indicators,ranging across all aspects of BIS-part 1 (except indicator 1.1) and only some aspects ofBIS-part 3. This suggests that private venture capital investment in biotechnology isrelatively more attracted to EU member states with a strong overall knowledge baseand where public funding is rather high. However there is an absence of correlationbetween venture capital and the number of firms (indicator 3.1). This is surprising asthe (lack of) availability of venture capital has often been cited as seriously hamperingfirm creation in Europe. The result of our analysis suggests that countries with a highlevel of firm creation are not necessarily those with readily available venture capital.
One explanation could be that venture capital investments are directed more atsustaining the growth rate of existing firms than at investing in new companies.
Graph 2. The relationship between BPI for Part 1 and BPI for Part 3 indicators
10 In other words more does not imply better. More PhDs in life Sciences may well lead to an increase inunemployment related to this discipline.
The Biotechnology Innovation Scoreboard 2002 European Trend Chart on Innovation Nine of the 11 indicators are significantly linked to the overall BPI. Indicators on thenumber of PhD graduates (1.1) and on drug approvals (3.6) do not contributesignificantly to the overall performance of a country. Additionally, the relationshipbetween BIS-Part 1 and BIS Part-3 is illustrated in graph 2. Graph 2 plots each countryaccording to its BPIs calculated for part 1 and part 3 respectively. The R2 between part1 and part 3 is 0.66 when excluding Luxembourg, dropping to 0.41 when including it.
This result is consistent with the above discussion that country performance inknowledge creation is related to the performance in innovation finance, output andmarkets.
Biotechnology is often referred to as the prime mover in the next major wave oftechnological change, with profound effects on economic growth and structural change.
It is seen as a major opportunity to improve the quality of life by developing newproducts in the pharmaceutical and agro-food industries, while bringing new technicalsolutions for problems related to the environment. The Biotechnology InnovationScoreboard (BIS) assembles 11 indicators to examine the performance of EU countriesin this technology.
The analysis shows that the smaller European countries, i.e. Denmark, Sweden, andBelgium, and to a lesser extent Finland and the Netherlands, are the leaders within theEU. The Nordic countries are also leaders in terms of overall innovation performancewithin Europe, as shown in the Trend Chart European Innovation Scoreboard (EIS). Atthe same time Switzerland has a high level of innovation in biotechnology. The largercountries, Germany, the United Kingdom and France are in the second tier, achievingvery similar level of performance. There is a substantial gap between these and theremaining EU countries.
Further while the European Union as a whole lags significantly behind the USA, thetop performing EU countries have a comparable level of performance. However thisresult needs to be treated with care as two key indicators for the USA are missing in theabove analysis: government spending in biotechnology and venture capital. Theinclusion of these may substantially improve the US position.
These problems highlight the main difficulty in constructing this Scoreboard, namelythe lack of publicly available systematic data. Thus we know little about the level ofR&D, employment and output associated with biotechnology. Moreover there is noinformation on one of the key aspects of innovative activity in this area: collaborationbetween public and private organisations. Finally for many of the indicators in BISthere are great difficulties in obtaining data over time, making trend analysisimpossible.
The Biotechnology Innovation Scoreboard 2002 European Trend Chart on Innovation Ernst & Young (2000). The Economic Contributions of the Biotechnology Industry to the US European Commission (1999). Inventory of public Biotechnology R&D programmes in Europe. Analytical Report. DG Research.
European Commission (2000). The Europeans and Biotechnology. DG Research.
European Commission (2001). Enterprise Paper No 7. "Innovation and Competitiveness in European Biotechnology (Allansdottir, et al).
European Commission (2002). Life sciences and biotechnology – A Strategy For Europe.
Kenney, M. (1986). Biotechnology: The University - Industrial Complex. New Haven & London, Yale University Press, 306 pages.
OECD (1998): Economic Aspects of Biotechnologies Related to Human Health, part II.
OECD (2001) Biotechnology Statistics in OECD Countries: Compendium of Existing National Statistics. DSTI/DOC (2001)6.
OECD (2002a) A Statistical Framework for Biotechnology Statistics. DSTI/EAS/STP/NESTI (2001)3. REV3.
OECD (2002b) Biotechnology Indicators and Public Policy. DSTI/EAS/STP/NESTI (2002)8.
Orsenigo, L. (1989). The Emergence of Biotechnology. New York, St. Martin's Press, 230 Orsenigo, L., Pammolli, F., et al. (1998). "The Evolution of Knowledge and the Dynamics of Industry Networks." Journal of Management and Governance, Vol.1, 147-175.
Pyka, A. and P. Saviotti (2002). Networking in Biotechnology Industries - From Translators to Explorers, Working Papers, University of Augsburg.
Saviotti, P. P., Joly, P.-B., et al. (1996). The Role of SMEs in Technology Creation and Diffusion: Implications for European Competitiveness in Biotechnology. Grenoble,Report for the European Commission.
The Biotechnology Innovation Scoreboard 2002 European Trend Chart on Innovation Annex A. Indicator definitions
PhD. Graduates in Life Sciences Per Million Capita
Biotechnology is a science-based activity with a strong reliance on highly skilledlabour. This indictor reflects the capacity of a country to produce a pool of such highlyskilled labour. Of course not all PhD's will be eventually be employed inbiotechnology related activities, and some may end up working outside the country inwhich they trained. Alternative indicators could be based on first degrees or Masters inLife Sciences. However the proportion of graduates ending up doing biotechnologyrelated work would be even less than above. The data will be those of Education onlinedatabase (EOL- OECD). The database is constructed from data as delivered by OECDcountries. However the definition of what constitutes Life Sciences is not standardised,which in turn may yield artificial differences amongst countries (e.g. see Italy).
Government Biotechnology R&D Expenditures As Percentage of GDP
This indicator is the share of Government R&D expenditures that are devoted tobiotechnology, as percentage of GDP. This provides an overall picture of the prioritygiven by governments to the creation if new knowledge in biotechnology. Datacollected for the EC funded project, Inventory of Public Biotechnology Programmes inEurope (INV) are used. The aim of the project was to collect detailed information ongovernment funding of biotechnology related research across EU countries. TheInventory project was a unique attempt at quantifying public R&D expenditures inbiotechnology. However some of the inter-country differences might reflect differencesin the degree of difficulty in gathering the information. The data are only available forthe period 1994-1998 as a whole (i.e. there are no annual data). The denominator thussums the country's GDP for the same years.
Biotechnology Publications Per Million Capita
This indicator counts the number of biotechnology publication per million capita.
Country level data are based on the institutional address of one of the authors of thepublication. The indicator provides an overall picture of scientific output of a country.
Institute for Scientific Information's (ISI) National Science Indicators Database. Thiscontains information by scientific field, country and over time (1981-2000). There are anumber of scientific fields that are relevant to biotechnology, namely Biochemistry &Biophysics, Biology, Biotechnology & Applied Microbiology, Cell & DevelopmentalBiology, Experimental Biology, Molecular Biology & Genetics, Microbiology. Citations Per Publication in Biotechnology
The mean number of citation per publication, i.e., the ratio of total citations received,over the sum of biotechnology publications for a given year (or a set of years) aims atgrasping the quality of biotechnology research for a given country. Thus, citations areused as a measure of the impact of scientific output. The data source is identical to The Biotechnology Innovation Scoreboard 2002 European Trend Chart on Innovation those of indicator (1.3). The measure developed here takes into account the timetruncation inherent in citation data. Because the number of citations received by apublication increases over time, it is important not to focus simply on the last year forwhich the data is available, i.e. 2000. Here we use the average number of citations perpublications produced between 1996 and 2000.
Biotechnology EPO Patents Applications Per Million Capita
The indicator is the number of patent applications at the EPO in biotechnology permillion of population. The data are aggregated according to the country address of theinventor. This is an indicator of inventive activity within a country. Biotechnology is anarea with a high propensity to protect innovations by means of patenting. The EuropeanPatent Office provides the data. The following IPC codes are included in the analysis.
C12M (apparatus for enzymology or microbiology); C12N (micro-organisms orenzymes; compositions thereof), C12P (fermentation or enzyme-using processes tosynthesise a desired chemical compound or composition or to separate optical isomersfrom a racemic mixture), C12Q (measuring or testing processes involving enzymes ormicro-organisms), C12S (processes using enzymes or micro-organisms to liberate,separate or purify a pre-existing compound or composition).
Biotechnology USPTO Patents Per Million Capita
The indicator is the number of patents granted by USPTO in biotechnology per millionof population. The data are aggregated according to the country address of the inventor.
As the US is perceived to be the leader in biotechnology related research, there arestrong incentives to protect innovations in that market. The data are provided byUSPTO. The analysis is based on class 435 of the USPTO classification system:Molecular biology and microbiology, in 2000. SPRU database.
Biotechnology Business R&D Expenditures As Percentage of GDP
This indicator is the amount of R&D funded and performed by business firms, aspercentage of GDP. It provides an overall picture of biotechnology effort by the privatebusinesses. Data Source: At present these data are not available. However they may beavailable in the future through the surveys of biotechnology companies currently beingundertaken, co-ordinated by the OECD. As such, it is not in a usable or reliable formatfor BIS.
Collaborative Research Agreements Between PSROs and Industry per
Million Capita.
Count of the number of technology related agreements involving at least one PublicSector Research Organisation (PSRO) and one firm, divided by million of population.
The indicator provides information on extent of linkages between public researchorganisations and private firms. Such linkages are crucial to the commercialisation ofbiotechnology. The information used here is contained in an OECD publication, The Biotechnology Innovation Scoreboard 2002 European Trend Chart on Innovation Economic Aspects of Biotechnologies Related to Human Health (part II, 1998, p. 103).
However, the OECD document refers to information from two independentpublications: The New scientist (2 March, 1996) and Nature Biotechnology, 14 April1996). These figures refer to year 1994. A substantial effort in building more accuratedata is needed, given the persistence of collaborations agreements between public andprivate actors. Latest information maybe available in the BID database (BiotechnologyIndustry Database) located at the University of Siena. See the recent DG Enterprisereport on Innovation and Competitiveness in European Biotechnology (EnterprisePaper no. 7), but the data are not publicly available.
University Spin-offs, per million capita.
This indicator counts the number of university spin-offs in biotechnology per capita.
The indicator directly measures the commercialisation of university knowledge. It isoften argued that the success of US in biotechnology is the result of a large number ofspin-offs coming out of research conducted in US Universities. Such data are notavailable at present.
Joint Scientific Publications Between PSROs and Industry Per Million
Capita.
This indicator counts the number biotechnology publication involving at least onePSRO and one firm, divided by millions of population. This is a measure of researchcollaboration between PSROs and industry. Such data are not available at present.
Joint EPO Patents Applications Between PSROs and Industry Per Million
Capita
This indicator counts the number of EPO patent applications assigned to at least onePSRO and one firm, divided by millions of population. This is one of the results fromresearch collaboration between PSROs and industry. Such data are not available atpresent.
Dedicated Biotechnology Firms (DBFs), Per Million Capita
This indicator counts the number of dedicated biotechnology firms, per capita. DBFsare deemed to have 3 roles: (i) they play the role of knowledge explorers in anenormously complex space of innovative opportunities; (ii) they transform scientificknowledge into technological and commercial applications; and (iii) they are crucialagents in the division of innovative labour. There are two main sources of systematicdata: Ernst & Young and the BID database (University of Siena). BIS uses the BID aspublished in the Competitiveness Report. The main problem with both these databasesis that very little is known about how the data are collected and hence their reliability.
Biotechnology Employment Per Million Capita
The Biotechnology Innovation Scoreboard 2002 European Trend Chart on Innovation This indicator counts the number of employees in DBFs per million capita. It is notenough just to count the number of DBFs, we need some indication of their economicimportance. An alternative could be the mean size of DBFs by country, with theunderlying assumption that bigger DBFs have a higher chance of survival and growthand are a sign of vigorous biotechnology industry. Such data are not available on asystematic basis.
Biotechnology Venture Capital As Percentage of GDP
The amount of venture capital raised in biotechnology is expressed as a proportion ofGDP. The availability of venture capital is widely recognised as an essential ingredientof entrepreneurship in biotechnology. The underlying rationale is that bringingsuccessful products to market in biotechnology is a long term and risky process,requiring substantial funds. The availability of such funds is also perceived to be one ofthe major reasons for the US lead in the commercialisation of biotechnology. TheEuropean Venture Capital Association (EVCA) provides such data with a breakdowninto several industries or areas. Biotechnology is defined as: Agricultural and animalbiotechnology (e.g. plant diagnostics); Industrial biotechnology (e.g. derivedchemicals); Biotechnology related research and production equipment. EVCAdistinguish medical and health care venture capital to biotechnology venture capital,though the definition of the health related venture capital could well comprise somepharmaceutical research using some biotechnology (see EVCA, pp. 305-306).
Alliances Between Large Firms and DBFs Per Million Capita
This indicator counts the number of biotechnology related strategic alliances betweenDBFs and large firms divided by millions population. One of the key ways in whichbiotechnology products may reach the market successfully is through a partnershipbetween DBFs and large firms. The former often lack the necessaryfinancial/managerial/marketing resources, which can be provided by large firms. Dataare not available but they possibly exist in the BID database from the University ofSiena.
Biotechnology Revenues As Percentage of GDP
Revenues derived from commercial activities involving biotechnology (as percentageof GDP) provide an overall picture of biotechnology activities other than pureknowledge creation. As such, it is much closer to market that other indicatorstraditionally concentrating on R&D. Data are not available.
Drug Approvals PmC
This indicator counts the number of biotech drugs approved between 1980 andSeptember 2002 divided by population. The indicator provides an overall picture ofbiotechnology innovation by the private businesses. The data are provided by MERIT.
The Biotechnology Innovation Scoreboard 2002 European Trend Chart on Innovation Biotechnology drugs are difficult to define, since they can include small chemical drugsthat have been in production for years but for which there is a recent stereoisomer formproduced using GM microorganisms. We exclude vaccines, rattlesnake anti-venom,topical drugs, and diagnostics. Stereoisomers are included when the drug is a largemolecule, but not if it is a stereoisomer of a small chemical drug. For example, we donot include Fluoxetine (Prozac) because first, there are alternative methods ofmanufacturing stereoisomers that are increasingly used and that may replacebiotechnology and secondly, the development of the drug did not depend onbiotechnology. Importantly, these numbers include double counts, for instance, if adrug has been jointly developed by a US and a French firm the drug is assigned both tothe United States and to France. In total, 18 out of 124 drugs have been developedjointly by two countries. Alternatively, Ernst & Young figures can be found in theglobal biotechnology report 2002. Yet we remain sceptical about their data as they mayinclude drugs, which are not biotech drugs. Moreover their data only includes drugsfrom public companies.
Field Trials of GMO Crops Per Billion GDP in Agriculture
This indicator is based on the number of field trials of GMO crops being undertaken ineach country between January 1 1996 and December 31 2001. National field trialcounts for GM organisms provides an indication of national capabilities in GM cropresearch. It is normalised using GDP in Agriculture, thus taking account of differencesin natural endowments: not all countries in Europe can grow most crops - Norway,Sweden and Finland are severely disadvantaged, Denmark moderately so, incomparison with France, Spain and Italy.
The indicator is not perfect because some trials are conducted by national subsidiariesof multinational seed firms. Very little expertise in GM is needed for a Spanishsubsidiary to conduct a field trial of tomatoes. It would be possible to limit the indicatorto GM trials counted by domestic firms, but this would create the opposite error, byexcluding subsidiaries that do have the capabilities to conduct GM research. GM fieldtrial data are available for both the US and Europe from 1990 onwards. In order to limitthe data to a more recent period, the count includes only field trial applications thatwere granted between January 1 1996 and April 2001 for Europe, and for US trialsbetween January 1, 1996 and December 31, 2001. European data for the whole of 2001were not available, but very few trials were conducted in Europe at this time due to themoratorium. The data are provided by MERIT, with the following sources: For EUdata: JRC (Joint Research Council), Summary Notification Information Format (SNIF)database, European Commission; For the US: Animal and Plant Health InspectionService (APHIS) of the USDA.
Public Understanding of Biotechnology
The average score on biotechnology knowledge as assessed in EUROBAROMETER5.2 (2000) is expressed in percentage of correct answers. The indicator is based on thestudy undertaken on behalf of the DG Research in November and December 1999. It The Biotechnology Innovation Scoreboard 2002 European Trend Chart on Innovation follows similar studies in 1993 and 1996 and looks at the knowledge of Europeans tovarious and general problems connected with biotechnology. Importantly, 16,082people were asked to answer true and false to 12 statements related to biology, geneticsand biotechnology. Out of these 12 questions, we selected 6 questions that we view asconcerning the core of biotechnology knowledge, usage, processes or products. Theseare:1. Ordinary tomatoes do not contain genes while genetically modified tomatoes do.
The cloning of living things produces exactly identical offspring.
By eating a genetically modified fruit, a person's genes could also becomemodified.
Genetically modified animals are always bigger than ordinary ones.
More than half of the human genes are identical to those of the chimpanzees.
It is impossible to transfer animal genes into plants.
The set of questions that were withdrawn from the original questionnaire is: There are bacteria, which live from wastewater.
It is the father's genes that determine whether a child is a girl.
Yeast for brewing beer consists of living organisms.
10. It is possible to find out in the first few months of pregnancy whether a child will have Down's syndrome.
11. Criminal tendencies are mainly genetically inherited.
12. Musical abilities are mainly learned.
The sample was designed to be representative of the population of 15 years of age ormore. The average response provides us with a picture of the diffusion of generalbiotechnology knowledge to the public. The underlying hypothesis is that the greaterthe amount of general knowledge the easier it is for biotechnology related products tosucceed on the market. The EU weighted average has been calculated by using theshare of each country in the total EU population. The data are provided by theEuropean Commission, DG Research.
The Biotechnology Innovation Scoreboard 2002 European Trend Chart on Innovation Annex B. The Difference between Missing and Zero Values
An important question that has arisen in the building of BIS is the treatment of missing
and zero values. Missing values are those for which no information was found in some
EU countries11. Zero values are those values for which the information has been found
to be 0 for a given indicator and for a given country. For example, count data such as
publications (indicator 1.3), citations (1.4), patent applications (indicator 1.5) or patent
granted (indicator 1.6) per country is likely to be zero in some countries, while for
some others it is significantly different than zero. This latter case provides substantial
information on the performance of a given country, and thus zero values are treated as
such.
Table B1. The treatment of zero values
Ph.D. Grads in Life Sciences Gov. Biotech. R&D Biotech Publications Citations per publication in Biotech Biotech EPO patents Biotech USPTO patent applications Business Biotech R&D Coll. Res. Agreements PSRO-Industry University Spin-offs Joint Pub. PSROs and Industry Joint EPO patents PSROs and Industry Dedicated Biotech Firms Biotech Employment Biotech Venture Capital Alliances large firms and DBFs Field Trials in GMO crops Average Score Knowledge About Biotech In some cases, it is not clear whether the missing information indicates missing valuesor zero outcomes. For example, it has been found that some countries do not havededicated biotechnology firms. However, the basis on which the count has been maderemains quite uncertain. Thus the general position adopted in the building of BIS is thefollowing: in cases such as publication and patent data, the quality of the assessment byregulatory offices or public association (e.g. EVCA) allows the inclusion of zerovalues. In other cases, it has been chosen to treat zero values as missing data. Thischoice has consequences in the calculation of the country performance and the EUaverage. Table 3 displays detailed information on the treatment of zero values.
11 When no information is found for all countries, the indicator is de facto screened out of BIS, as shownin table 1.
The Biotechnology Innovation Scoreboard 2002 European Trend Chart on Innovation Biotechnology Innovation Scoreboard. Data definitions, sources and
results
In table C1, details on data sources and definition is provided. Table C2 provides theBiotechnology Innovation Scoreboard. Graphs C1 to C3.8 display the results for eachindicator, by ranking the countries according to their performance. When the EU meanhas been calculated on only a part of European countries, it is referred to as the EU.
When it has been computed on all 15 member-states, the EU is referred to as the EU-15. The graphs are numbered accordingly to their BIS number.
The Biotechnology Innovation Scoreboard 2002 Table C1. Data definition and Sources
No
PART 1. Human Resources and Creation of New Knowledge PhD. Grads in Life Sciences pmC OECD: Education On Line Database. Belgium: Flemish Community only. Italy: PhD graduates students included in other categories.
Gov. Biotech. R&D % GDP European Commission (1999). Inventory of public Biotechnology R&D programmes in Europe.
Biotech Publications pmC Citations per publication in Biotech SPRU. Sums of Citations 1996-2000 over sums of publications 1996-2000.
Biotech EPO patents applications pmC European Patent Office.
Biotech USPTO patent pmC Business Biotech R&D % GDP Existing figures not Reliable.
PART 2. Transmissions and Application of New Knowledge in Biotechnology Coll. Res. Agreements PSRO-Industry pmC OECD: Economic Aspects of Biotechnologies Related to Human Health, part II, 1998, p. 103 University Spin-offs pmC Joint Pub. PSROs and Industry pmC Joint EPO patents PSROs and Industry pmC PART 3. Innovation finance, outputs and markets BID (Biotechnology Information Databank). University of Siena. For other countries: E&Y (USA), JBA (Japan) and Statistics Canada Dedicated Biotech Firms pmC Biotech Employment pmC Existing figures not Reliable.
Biotech Venture Capital % GDP Alliances between large firms and DBFs pmC Biotech Revenues % GDP Existing figures not Reliable.
Excludes vaccines, rattlesnake anti-venom, biotech skin, diagnostics, etc.
Drug Approvals pmC Possible double count for drugs developed by two firms of different nationalities.
Field Trials in GMO crops per 109 GDP in For the US: Animal and Plant Health Inspection Service (APHIS) of the USDA.
For EU data: JRC (Joint Research Council), Summary Notification Information Format (SNIF) database, European Commission.
Average Score Knowledge About Biotech EUROBAROMETER 52.1 The Biotechnology Innovation Scoreboard 2002 Table C2. Biotechnology Innovation Scoreboard
PART 1. Human Resources and Creation of New Knowledge PhD. Grads in Life Sciences pmC1 Gov. Biotech. R&D % GDP Biotech Publications pmC Citations per publication in Biotech Biotech EPO patents applications pmC Biotech USPTO patent pmC PART 2. Transmissions and Application of New Knowledge in Biotechnology CRA2 PSRO-Industry pmC PART 3. Innovation finance, outputs and markets Dedicated Biotech Firms pmC Biotech Venture Capital % GDP 0.0094 0.0028 0.0257 0.0240 0.0229 0.0001 0.0049 0.0051 0 0.0135 0.0051 0.0054 0.0005 Drug Approvals pmC Field Trials in GMO crops 109 GDP in Average Knowledge About Biotech Indicators are highlighted in blue when 25% above the EU mean and in red when 25% below the EU mean.
1. pmC: per million capita.
2. CRA: Collaborative Research Agreements.
The Biotechnology Innovation Scoreboard 2002 Graph C11. PhD. Graduates in Life Sciences pmC (1999)
Graph C12. Government Biotechnology R&D Expenditures As Percentage of GDP (1994-
The Biotechnology Innovation Scoreboard 2002 Graph C13. Biotechnology Publications pmC (2000)
Graph C14. Citations Per Publication in Biotechnology (1996-2000)
The Biotechnology Innovation Scoreboard 2002 Graph C15. Biotechnology EPO Patent Applications pmC (2001)
Graph C16. Biotechnology USPTO Patent pmC (2000)
The Biotechnology Innovation Scoreboard 2002 Graph C31. Number of dedicated Biotechnology Firms pmC (2000)
Graph C33. Biotechnology Venture Capital As Percentage of GDP (2001)
The Biotechnology Innovation Scoreboard 2002 Graph C36. Number of Drug Approvals pmC (1980-02)
Graph C37. Number of Field Trials per Billion GDP in Agriculture (1996-01)
The Biotechnology Innovation Scoreboard 2002 Graph C38. Average Score in Biotechnology Knowledge (2000)
The Biotechnology Innovation Scoreboard 2002

Source: ftp://ftpnl.cordis.lu/pub/trendchart/reports/documents/report7.pdf