OECD Biotechnology Statistics 2006 (link)

May 23, 2006

Paris, 22 May 2006

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This report provides statistics on biotechnology activities in up to 23 OECD countries and 2 observer countries, plus China (Shanghai), based on the results of 33 separate studies. The main methodological challenges concern the production of comparable statistics across countries that have used different definitions and survey designs. Table 1 summarises the main methodological characteristics of the studies of biotechnology in each country.

Biotechnology is used for producing existing products in new ways, identifying new product opportunities (as in drug discovery), and for producing new products that could not be commercially produced before (as with many large molecule therapeutics and some GM plant varieties). The wide range of uses for biotechnology means that it is a generic technology with applications in many different economic sectors. Biotechnology is also better described as a group of related biotechnologies.

The diverse types of biotechnologies and the range of possible applications create two main challenges for developing comparable biotechnology statistics: how to define biotechnology and how to define a biotechnology firm.

Definition of biotechnology

The OECD has developed both a single definition of biotechnology and a list-based definition (see Box below) of different types of biotechnology. The single definition defines biotechnology as "the application of science and technology to living organisms, as well as parts, products and models thereof, to alter living or nonliving materials for the production of knowledge, goods and services."

The OECD list-based definition, or close variants, were used in surveys in 15 countries, but different definitions of biotechnology were used in the other 11 countries: 7 studies limit biotechnology to 'modern' or third-generation biotechnologies that are similar to the OECD list-based definition in practice, 2 studies use mixed definitions that include second generation biotechnologies (Japan and South Africa), and 2 do not define biotechnology, but leave it to the survey respondent to decide if their firm is active in biotechnology. As the latter two studies cover Denmark and Sweden, a large majority of the respondents are likely to interpret biotechnology as modern biotechnology.

OECD list-based definition of biotechnology techniques

DNA/RNA: Genomics, pharmacogenomics, gene probes, genetic engineering, DNA/RNA sequencing/synthesis/amplification, gene expression profiling, and use of antisense technology. Proteins and other molecules: Sequencing/synthesis/engineering of proteins and peptides (including large molecule hormones); improved delivery methods for large molecule drugs; proteomics, protein isolation and purification, signaling, identification of cell receptors.

Cell and tissue culture and engineering: Cell/tissue culture, tissue engineering (including tissue scaffolds and biomedical engineering), cellular fusion, vaccine/immune stimulants, embryo manipulation. Process biotechnology techniques: Fermentation using bioreactors, bioprocessing, bioleaching, biopulping, biobleaching, biodesulphurisation, bioremediation, biofiltration and phytoremediation. Gene and RNA vectors: Gene therapy, viral vectors.

Bioinformatics: Construction of databases on genomes, protein sequences; modelling complex biological processes, including systems biology.

Nanobiotechnology: Applies the tools and processes of nano/microfabrication to build devices for studying biosystems and applications in drug delivery, diagnostics etc.

Definition of a biotechnology firm

The definition of a biotechnology firm is partly linked to the method used in each country to sample firms. Three definitions are in common use. Two different methods are used in separate studies in Finland, Korea, New Zealand, Spain, Sweden and the United States.

Data are only available for 'core' biotechnology firms for seven countries. The definition of a core biotechnology firm varies, but in most countries a core biotechnology firm must perform R&D in biotechnology and biotechnology must be its principal activity. The latter requirement often limits core biotechnology firms to those with less than 500 employees.

At least some of the data for the remaining 19 countries cover all firms with some biotechnology activities, even if biotechnology is only a small part of its total activity. In 13 countries biotechnology firms are identified through a positive response to a question on conducting biotechnology-related R&D in the national R&D survey.

In nine countries all biotechnology firms were surveyed (core firms plus other firms with some biotechnology activities). No information on the definition of a biotechnology firm is available for Poland. In 20 countries at least one survey is limited to firms that develop biotechnology innovations. For four countries, the only available survey includes firms that use biotechnology but do not necessarily perform biotechnology R&D. No data are available for Belgium and China on this issue.

Sampling frame

Two main methods are used for identifying biotechnology firms. Eighteen surveys use secondary sources to identify biotechnology firms. These include industry association membership lists, participants in government programmes to support biotechnology, stock market listings, patent records, information provided by venture capital firms, and any other possible source for identifying a biotechnology firm. Thirteen surveys use the national R&D sampling frame. The survey in Korea is based on activity in specific sectors, while no information is available for Poland.

Accuracy of the results

Table 1 includes three characteristics that could influence the accuracy of the biotechnology statistics: the organisation conducting the survey (Source), the response rate (RR), and whether or not results were imputed to account for non-respondents, or if a random survey, extrapolated to the total population (Extrapolation). Twenty of the 33 studies were conducted by government agencies (GOV), 6 by non-profit organisations acting at the request of a government agency (NP-GOV), and 7 by a consulting agency (name given in Table 1). Generally, governments have the most resources to conduct a full survey of biotechnology and consequently the data quality should be better than the results obtained by consulting agencies, although this might not always be the case.

Data accuracy is strongly dependent on a high response rate, which will reduce possible biases due to differences in the types of biotechnology firms that choose or do not choose to respond to a survey and include most firms active in biotechnology. Low response rates could result in serious underestimates of the number of biotechnology-active firms or biotechnology activities such as R&D.

Surveys were not used in six studies, so the response rate is not relevant. Out of the surveys, 14 had high response rates above 80%, while 4 had low response rates (50% or less). When the response rate is not 100%, the results can be extrapolated to estimate biotechnology activity in the estimated number of biotechnology firms that did not respond to the survey. However, the accuracy of extrapolation depends on having good information on the number of eligible non-respondent firms. It is also possible that this number is zero, for example if firms that were not active in biotechnology did not answer the questionnaire because they did not consider it relevant to them.


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