Consequences, opportunities and challenges of

Consequences, opportunities and challenges of modern biotechnology for Europe (Bio4EU) Task 1 – A preparatory study mapping modern biotechnology applications and industrial sectors, identifying data needs and developing indicators FINAL REPORT DELIVERABLE 3

Version no. 4

This report has been produced by the following ETEPS AISBL project team:

Thomas Reiss (PM), Fraunhofer Institute for Systems and Innovation Research, Germany Sibylle Gaisser, Fraunhofer Institute for Systems and Innovation Research, Germany Bernhard Buehrlen, Fraunhofer Institute for Systems and Innovation Research, Germany Christien Enzing, TNO Innovation Policy Group, Netherlands Annelieke van der Giessen, TNO Innovation Policy Group, Netherlands Anthony Arundel, Maastricht Economic Research Institute on Innovation and Technology (MERIT), Netherlands Cati Bordoy, Maastricht Economic Research Institute on Innovation and Technology (MERIT), Netherlands Susan Cozzens, Georgia Tech Technology Policy Assessment Center (TPAC), USA Pablo Catalán, Georgia Tech Technology Policy Assessment Center (TPAC), USA Sonia Gatchair, Georgia Tech Technology Policy Assessment Center (TPAC), USA Gonzalo Ordóñez, Georgia Tech Technology Policy Assessment Center (TPAC), USA

Consequences, opportunities and challenges of modern biotechnology for Europe Final Report/Deliverable 3 Page 2 of 172

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Table of Contents List of figures ..................................................................................................................... 5 List of tables ...................................................................................................................... 6

Executive summary .......................................................................................8 I. Introduction ...............................................................................................10 II. Results ......................................................................................................12 1. Introduction (see section I)........................................................................................... 12 2. Key biotechnologies .................................................................................................... 12 3. Biotechnology applications .......................................................................................... 18 4. Concept for elaborating indicators................................................................................ 43 5. Input statistics and indicators....................................................................................... 48 6. Medical and pharmaceutical applications: applicationspecific output and impact indicators..................................................................................................................... 61 7. Agrofood: applicationspecific output and impact indicators......................................... 79 8. Industrial manufacturing, energy, environment: applicationspecific output and impact indicators..................................................................................................................... 91 9. Generic impact indicators .......................................................................................... 123

III. Conclusions .......................................................................................... 129 IV. Annexes................................................................................................. 132


List of figures Figure 3.1: The Industrial Biotechnology Production Chain ............................................... 37 Figure 4.1: Conceptual framework for biotechnology indicators......................................... 43


List of tables Table 2.1: Table 2.2: Table 3.1: Table 3.2: Table 4.1: Table 5.1: Table 5.2: Table 5.3: Table 5.4: Table 6.1: Table 6.2: Table 6.3: Table 7.1: Table 7.2: Table 7.3: Table 7.4: Table 8.1: Table 8.2: Table 8.3: Table 8.4: Table 8.5: Table 8.6: Table 8.7: Table 8.8: Table 8.9: Table 8.10: Table 8.11: Table 8.12: Table 8.13: Table 8.14: Table 8.15: Table 9.1: Table 9.2: Table A.6.1: Table A.6.2: Table A.7.1: Table A.7.2: Table A.8.1.1: Table A.8.1.2: Table A.8.1.3: Table A.8.2.1: Table A.8.2.2: Table A.8.2.3: Table A.8.3.1: Table A.8.3.2: Table A.8.3.3: Table A.8.4.1: Table A.8.4.2:

Listbased definition of modern biotechnology.............................................. 12 Webbased information sources for description of key biotechnologies......... 12 Overview of use of key technologies in research and production in the three sectors ........................................................................................................ 18 Selected examples of biopharmaceuticals for low incidence diseases in the US and European Markets........................................................................... 21 Typology of biotechnology indicators with examples..................................... 44 Business sector input indicators from government surveys (consulting firms when no official data)................................................................................... 51 Public sector input indicators ....................................................................... 53 Availability of business sector input indicators by application field. ............... 55 Value of input indicators for assessing investments in biotechnology and future potential outputs ................................................................................ 57 Output indicators for medical and pharmaceutical applications of biotechnol ogy .............................................................................................................. 63 Key indicators and methods for data collection for a study in the medical and pharmaceutical sector.................................................................................. 71 Phenomena and indicators that characterize the impact of biotechnology on the medical and pharmaceutical sector ........................................................ 74 Classification system for field trial traits........................................................ 81 Output indicators for agrofood biotechnology/GM........................................ 83 Key missing data for agrofood outputs........................................................ 85 Impact indicators for agrofood biotechnology .............................................. 88 Output phenomena and indicators for biotechnology in the chemical sector . 93 Output phenomena and indicators for biopolymers....................................... 96 Output phenomena and indicators for enzymes in downstream sectors........ 98 Output phenomena and indicators for biofuels ........................................... 101 Output phenomena and indicators for bioremediation................................. 104 Recommended output indicators for biotechnology in the chemical sector.. 107 Recommended output indicators for biopolymers....................................... 108 Recommended output indicators for enzymes in downstream sectors ........ 108 Recommended output indicators for biofuels.............................................. 109 Recommended output indicators for bioremediation................................... 110 Impact phenomena and indicators for biotechnology in the chemical sector 112 Impact phenomena and indicators for biopolymers..................................... 115 Impact phenomena and indicators for enzymes in the downstream sectors 118 Impact phenomena and indicators for biofuels ........................................... 121 Impact phenomena and indicators for bioremediation................................. 123 Statistics for biotechnology turnover........................................................... 124 Generic impact indicators .......................................................................... 126 Data availability ......................................................................................... 133 Sources for output indicators ..................................................................... 138 Data availability ......................................................................................... 141 Sources for agrofood indicators ................................................................ 142 Data characteristics chemicals................................................................... 144 Data availability of sources for chemicals (excl polymers) .......................... 148 Source Key Chemicals............................................................................... 150 Data characteristics biopolymers ............................................................... 151 Data availability of sources for biopolymers................................................ 155 Source Key Biopolymers............................................................................ 156 Data characteristics enzymes in downstream industries............................. 157 Data availability of sources for enzymes in downstream industries: (food and feed, textile and leather, pulp and paper, mining and others) ............... 159 Source key for enzymes in the downstream sector..................................... 160 Data characteristics biofuels ...................................................................... 161 Data availability of sources for biofuels ...................................................... 164


Table A.8.4.3: Table A.8.5.1: Table A.8.5.2: Table A.8.5.3: Table A.9.1: Table A.9.2:

Source Key for Biofuels ............................................................................. 165 Data characteristics bioremediation ........................................................... 166 Data availability of sources for bioremediation............................................ 168 Source Key for Bioremediation................................................................... 169 Data availability ......................................................................................... 171 Sources for generic impact indicators......................................................... 172


Executive summary In response to a request from the European Parliament, the European Commission, and in particular its Joint Research Centre initiated a study aiming at providing a comprehensive assessment of the economic, social and environmental consequences, opportunities, and challenges from the application of modern biotechnology in Europe. This assessment should keep in mind major European policy goals: to become the most competitive and dynamic knowledgebased economy in the world, capable of sustainable economic growth with more and better jobs and greater social cohesion and respect for the environment. The present Task 1 prepares the ground for a number of empirical analyses within the Bio4EU study by 1) elaborating a comprehensive picture of relevant existing modern biotechnologies, 2) identifying and describing existing biotechnology applications, 3) identifying appropriate indicators to enable an analysis of biotechnology applications and their consequences, and 4) identifying and evaluating required data and sources. A precondition for this assessment is a suitable definition of modern biotechnology. We recommend using the latest OECD definition from 2005 which 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”. A combination with a listbased definition ensures that traditional biotechnologies are excluded. Using the OECD definition will improve international comparability, since this definition is the most widely used in government biotechnology surveys and has resulted in several useful statistics. The analysis of applications of modern biotechnology in various industry and service sectors shows that the main application areas of modern biotechnology can be classified into three groups: medical and pharmaceutical applications, biotechnology applications in primary production and the agrofood sector, and biotechnology in industrial manufacturing, energy and environment. For elaborating indicators and identifying data needs a conceptual approach was developed which differentiates between three main categories. Firstly, we use input indicators which describe capabilities and capacities in biotechnology. Secondly, we use output indicators that evaluate the extent of the adoption of biotechnology within the different application sectors. Thirdly, impact indicators are proposed which assess the economic, social and environmental impacts of modern biotechnology applications. The most important input indicators are of a generic nature and not disaggregated by applications. Key input indicators are based on private and public R&D expenditures, the number of employees, patent data and bibliometric data. The main sources for input indicators comprise business sector statistics from official surveys or reports, public sector statistics from official surveys or reports, database statistics such as publications and patent databases, and consulting firm statistics. Data availability is almost inversely proportional to the value of the input indicator. Availability is greatest for basic firm counts, which is a highly misleading indicator, and lowest for R&D investment and employment by field of applications, which would be among the most useful indicators. Output indicators are both sectorspecific to application areas in terms of sectorspecific products or processes to be measured and generic, as many of the phenomena to be measured in the different application areas are identical, such as building up biotechnology knowhow in the sector, product approval, producing biotechnologybased products, gaining Consequences, opportunities and challenges of modern biotechnology for Europe Final Report/Deliverable 3 Page 8 of 172

market shares for biotechnology products, or replacing established processes by bioprocesses. Sectorspecific output indicators for pharmaceutical and medical applications include indicators for the early developmental stages, such as the share of clinical studies with novel biobased approaches, the number of patents and publications, the specific legal framework conditions, such as the reimbursement situation, information to the public about bio procedures, and finally the adoption of biotechnology processes for small molecules. For agrofood applications, the most important available indicators are based on the number of GM field trials and GM acreage, but there is a need for new indicators for the use of biotechnologybased techniques, such as Marker Assisted Selection, for the development of nonGM plant and animal varieties and for the use of diagnostics and other veterinary applications. In industrial applications new production processes via biotechnology form the basis for typical indicators. Data availability and data quality are very heterogeneous in the different application areas. In the case of pharmaceutical and medical applications, we find reasonable data sources for only some of the key indicators. For GM crops we observe a nearly complete coverage of all countries and all indicators, other agrofood applications are characterised by poor data availability. In industrial biotechnology data availability and data quality are rather poor. Important generic impact indicators include the number of employees, sales or turnover from biotechnology products, valueadded from biotechnology products, and the financial costs or benefits from the use of biotechnology processes. Applicationspecific indicators for the medical and pharmaceutical field are morbidity, surrogate endpoints, mortality and composite indicators such as the costbenefit ratio of treatments. Indicators for agrofood applications include environmental effects such as carbon gas savings, nutrient efficiency, effects on soil erosion and pesticide use, and societal effects. Relevant indicators for industrial applications of biotechnology include environmental effects such as the ecological footprint, energy saving, changes in greenhouse gas emissions, savings of toxic chemicals, savings of water, and effects on land use. In general, for most impact indicators, data availability and data quality are low. In many cases we find only casespecific data. In summary, a number of good indicators for all three application fields and also for the input and impact side of the use of biotechnology has been identified. However, for a considerable number of indicators, the available data (mainly based on different types of statistics) is not sufficient. Therefore, we recommend not restricting data gathering during the following empirical studies to the analysis of available statistical and survey materials. Rather, additional methodological approaches are required. In particular we suggest: · Including specific questions on R&D expenditure and employees in European company surveys, · Conducting case studies, such as life cycle analyses in the case of industrial biotechnology or costbenefitanalyses in the case of biotechnologybased medical treatments, · Including patent and bibliometric analyses in all planned sector studies in order to provide highly comparable indicators about biotechnology capabilities and capacities. In conclusion, this study shows the feasibility of carrying out a quantitative assessment of the use and impact of modern biotechnology. Implementing our recommendations should contribute to an improved evaluation of the consequences, opportunities and challenges of modern biotechnology for Europe.


I. Introduction st

Modern biotechnology is one of the key enabling technologies of the 21 century, with a po tentially wide range of applications in health care, agriculture and industrial processes. How ever, recent analyses suggest that the actual adoption of modern biotechnology by various European industry sectors could be lower than anticipated. In general, data on the actual uptake of modern biotechnology by various sectors and its socioeconomic consequences in Europe are still scarce. Against this background, the European Parliament requested the Commission in late 2004 to carry out an assessment of the opportunities and challenges of modern biotechnology applications in Europe. This assessment will be carried out in the con text of the study "Consequences, opportunities and challenges of modern biotechnology for Europe“, under the responsibility of the JRCIPTS. The objective of the study is to provide a comprehensive assessment of the economic, social and environmental consequences, opportunities and challenges of applications of modern biotechnology in Europe, while keeping in mind major European policy goals: to become the most competitive and dynamic knowledgebased economy in the world capable of sustainable economic growth with more and better jobs and greater social cohesion and respect for the environment. The study includes a number of tasks. Task 1 provides a comprehensive picture of relevant existing modern biotechnologies, the identification and description of biotechnology applications (work package 1), the identification of appropriate indicators to enable an analysis of biotechnology applications and their consequences (work package 2), and the identification and evaluation of available sources of required data to prepare the ground for searches, surveys and interviews in different biotechnology application sectors (work package 3). Task 1 is the preparatory study for a number of following empirical analyses which comprise the core data gathering and evaluation exercise of the study. These empirical analyses will focus on biotechnology application in human and animal health; agriculture, fisheries and food and food production; industrial processes, energy and environment. This report presents the results of Task 1. It is organised in the following way: Chapter 2 defines the key technologies that are the basic tools in modern biotechnology research and production in one or more application fields. The selection of these key biotechnologies has been made on the basis of the OECD listbased definition of biotechnology (OECD 2005 1 ). Chapter 3 describes the main applications of modern biotechnology in the three sectors planned for the empirical analyses: applications of biotechnology in the medical and pharmaceutical sector, biotechnology applications in primary production and the agrofood sector and biotechnology applications in industrial manufacturing, energy and environment. Chapter 4 describes the conceptual framework which was used during Task 1 for the elaboration and assessment of indicators. In chapter 5 general input indicators are presented which illustrate the capabilities of a national system in biotechnology. Chapters 6, 7 and 8 elaborate on output indicators that are used for evaluating the adoption of biotechnology within the three sectors under consideration and on applicationspecific impact indicators for assessing the economic, social and environmental impacts of modern biotechnology applications. These sectororiented chapters are organised in the following way: In the first section output indicators are described. The elaboration starts with a 1

OECD (2005) Biotechnology Statistical Framework, Paris.


description of the phenomena in the adoption process which should be measured by suitable indicators. Indicators are presented and the required data assessed in terms of availability and quality. Additional information on these indicators in particular on their availability by country are summarised in a number of tables in the annex. Finally, recommendations for the empirical sector studies in terms of indicators, sources and methods are given. The second part of these chapters discusses impact indicators which are sector specific. In chapter 9 general impact indicators which are not sector specific are presented. Chapter 10 summarises the results of the study and presents conclusions for the carrying out of the empirical analyses.


II. Results 1. Introduction (see section I) 2. Key biotechnologies 2.1

Introduction

Biotechnology can be defined 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’ (OECD 2005 2 ). This definition includes traditional biotechnology processes that have been used for a very long time in the food and drinks industry as well as modern biotechnological processes. The focus of the project is on modern biotechnology, although in some cases modern biotechnology combines DNA, protein or cellbased technologies with traditional processes, such as fermentation and cell culture. Table 2.1:

Listbased definition of modern biotechnology

Nucleic acid (DNA/RNA)related technologies Proteinrelated technologies

Metaboliterelated technologies Cellular/ subcellularrelated technologies

Supporting tools

· · · · · · · · · · · · · · · ·

Highthroughput sequencing of genome, gene, DNA DNA synthesis and amplification Genetic engineering Antisense technology High throughput protein/peptide identification, quantification and sequencing Protein/peptide synthesis Protein engineering and biocatalysis High throughput metabolite identification and quantification Metabolic pathway engineering Cell hybridisation/fusion Tissue engineering Embryo technology Stem cellrelated technologies Gene delivery Fermentation and downstream processing Bioinformatics

Table 2.1 provides a listbased definition of the key technologies used in modern biotechnol ogy research and production. The list includes four general categories for nucleic acid, pro tein, metabolite, and cellrelated technologies, plus a fifth category for supporting tools. Some of these tools include a number of technologies. The description of the key technologies has been made using a number of sources. Several websites that provide extensive descriptions of biotechnology are given in table 2.2.

Table 2.2:

2

Webbased information sources for description of key biotechnologies

OECD (2005) Biotechnology Statistical Framework, Paris.


http://biotechterm.org/sourcebook/index.phtml http://www.fao.org/biotech/index_glossary.asp?langen http://www.biologydaily.com/biology/ http://biotech.icmb.utexas.edu/search/dictsearch.html http://filebox.vt.edu/cals/cses/chagedor/glossary.html

2.2

Nucleic acid (DNA/RNA)related technologies

Highthroughput genome, gene and DNA sequencing DNA, RNA, gene or genome sequencing is a process for determining the nucleotide se quence of a DNA or RNA fragment, a gene or the whole genome. The genome comprises the whole hereditary information of an organism encoded in the DNA, including both the genes and the noncoding sequences. The genes are specific regions of genomic sequence that correspond to a unit of inheritance for a specific trait, disease or condition. Messenger RNA (mRNA) encodes and carries information from DNA to sites of protein synthesis. Genomics is the study of an organism's genome and the information contained in it. The rate at which ge nomes have been sequenced has increased enormously since 1995 when traditional DNA sequencing techniques were increasingly replaced by highthroughput versions. Transcrip tomics is the study of the expression level of genes as measured in the set of all mRNA molecules in one or a population of biological cells for a given set of environmental conditions. DNA sequencing serves three main research strategies: the identification of genome struc tures (genomics mapping), the comparative analysis of gene sequences in order to find simi lar sequences, and the prediction of protein structures. The most widely used method for sequencing uses fluorescent ‘tag’ molecules attached to the DNA fragments, followed by spectrophotometry to identify the respective DNA fragments by their differing ‘tags’ (which fluoresce at different wavelengths). This method can be automated and is applied in microarrays. Microarrays are one of the main technologies used in high throughput whole genome sequencing. The major advantage of microarrays is the extent to which the process of genotyping can be automated to sequence and analyse large amounts of DNA fragments of the whole genome. Microarrays are also used to analyse patterns of gene expression and the presence of biomarkers. To manufacture a DNA microarray, cellular mRNA is used to make segments of complementary DNA (cDNA, with length of 5005,000 base pairs), using the reverse transcriptase polymerase chain reaction (see DNA synthesis). The cDNA segments attached to a nylon or glass surface at known spots, hybridize to sample DNA. DNA synthesis and amplification DNA synthesis is the reproduction of a known sequence of nucleotides into genes or gene fragments for use in research, but also in the security sector. The synthesis is carried out through the PCR technique (Polymerase Chain Reaction). First the DNA (a double helix) that has to be copied (i. e. synthesized) is split into two separate DNA strands. After a primer has been attached to each of the strands, a complementary strand to each of the strands is made by the socalled DNA Polymerase. This results in two new double helical DNA molecules, each of which has one strand from the original DNA molecule and one that was newly syn thesized. DNA amplification is a specific DNA synthesis process; it deals with the duplication of DNA sequences. DNA amplification is needed to detect very small amounts of DNA. Genetic fingerprinting or genotyping is the use of specific techniques for the identification of individuals and for distinguishing between individuals of the same species using only sam ples of their DNA. As each individual has its own specific DNA profile, this is an ultimate iden tification tool. It is used in plant and animal breeding, but also in forensic research. PCR is one of the main technologies to produce fingerprints. In this context marker assisted selection (MAS) is to be mentioned. The idea behind marker assisted selection is that there may be genes with significant effects that may be targeted specifically in selection. Specific genes can be detected by genome mapping. Consequences, opportunities and challenges of modern biotechnology for Europe Final Report/Deliverable 3 Page 13 of 172

Genetic engineering Genetic engineering is modifying the genotype, and hence the phenotype, by transgenesis. Transgenesis is the introduction of a gene or genes into animal or plant cells or into microor ganisms, which leads to the transmission of the input gene (transgene) to successive genera tions. Transgenesis can be performed by several techniques, such as injection and the ‘shot gun’ method. The aim is to introduce new characteristics to an organism in order to increase its usefulness. The genetically modified organism can produce endogenous proteins with properties that differ from the original protein or produce entirely different (foreign) proteins. Transgenesis also can include replacing a single functional gene by a nonfunctional form of the gene, in order to knockout specific functions of the organism. Other terms for genetic en gineering are gene splicing, gene/genetic manipulation or modification, or recombinant DNA technology. Antisense technology Antisense technology is the blocking of the transcription of a DNA using antisense mRNA. During transcription, the double stranded DNA produces mRNA from the sense strand; the other, complementary, strand of DNA is termed antisense. Antisense mRNA is a RNA strand complementary in sequence to the mRNA. The presence of an antisense mRNA can inhibit gene expression by basepairing with the specific mRNAs. This technology is used to study gene function: by switching off the studied gene by adding its antisense mRNA tran script. It has applications in the treatment of genetic disorders. 2.3

Protein/peptiderelated technologies

Highthroughput identification, quantification and sequencing There are a number of technologies that play an important role in the study of the structure and function of proteins (proteomics). They include twodimensional gel electrophoresis, mass spectroscopy and nuclear magnetic resonance. These methods are part of the standard set of analytical research tools and are continuously being upgraded and turned into faster (medium/high) throughput versions. Gelelectrophoresis (GE) techniques are used to separate, identify and quantify levels of proteins and peptides in a mixture. Proteins consist of one or more peptides. Both peptides and proteins consist of amino acids linked by peptide bonds, but proteins are much longer (consisting of more amino acids) than peptides. In 2dimensional GE the technique separates the proteins in two steps, according to two dimensions: isoelectic points through isoelectric focusing (IEF) and mass through sodium dodecyl sulfatepolyacrylamide gel electrophoresis (SDSPAGE). The separated proteins can be detected by a variety of means; the most com mon is silver staining. Mass spectroscopy (MS) is used to identify proteins or other macromolecules through their molecular weights (mass) and to sequence protein molecules (composition and order of amino acids). For the identification of proteins, the protein molecules are first separated, mostly through gel electrophoresis followed by alkylation and breakdown in specifically known ways via enzymes into peptides. Separation on the basis of their mass/charge ratio can be done by several techniques, including timeofflight mass spectrometry, electrostatic quadrupole, confronting it with a magnetic field, or by using FTMS (Fourier Transform – mass spectrometry). When passed through the mass spectrometer, the ionised peptides (and by derivation, the initial proteins) are identified by comparing their masscharge spectra to those within a database of known proteins. The peptides need to be counted, done by letting them bump against a target, resulting in a number of electrons. The nuclear magnetic resonance (NMR) technique is used to characterize the threedimen sional structure of proteins, peptides and other macromolecules. NMR is a physical phe nomenon based upon the magnetic property of an atom’s nucleus. NMR studies a magnetic nucleus by aligning it with an external magnetic field and perturbing this alignment using an Consequences, opportunities and challenges of modern biotechnology for Europe Final Report/Deliverable 3 Page 14 of 172

electromagnetic field. NMR spectrometry is the only technique that can provide detailed in formation on the exact threedimensional structure of biological molecules in solution. Protein/peptide synthesis Protein or peptide synthesis is the chemical construction of a known protein or peptide mole cule. The basic methodology is solid phase synthesis. In this method molecules are bound to a bead and synthesized stepbystep in a reactant solution. The constituent amino acids are repetitively coupled to a growing polypeptide backbone which itself is attached to a polymeric support (substrate). This procedure has been automated, so it is now possible to make pro teins via automated synthesizers. Protein engineering and biocatalysis Protein engineering is the selective, deliberate design and synthesis of proteins in order to alter specific functions, mostly applied for enzymes in industrial production processes but also in bioremediation. The use of enzymes as catalysts to perform transformations on organic compounds is called biocatalysis. Enzymes can be used in isolated form, or inside living cell lines or microorganisms (bacteria, fungi, yeasts). There are two general strategies for protein engineering: 1) rational design: using the detailed knowledge of the structure and function of the protein to make desired changes and 2) directed evolution. In the latter, random mutagenesis (such as DNA shuffling) is applied to a gene and a selection regime is used to pick out variants that have the desired qualities. DNA shuffling involves taking a set of closely related DNA sequences, fragmenting them randomly, and reassembling the fragments into genes. This process rapidly produces a combination of positive – i. e. desired – mutations as the output of one cycle becomes the input for the next cycle. This reiterative DNA shuffling leads to effective directed evolution and can be applied to evolve any protein rapidly, even if the structure or the catalytic mechanism is unknown. 2.4

Metaboliterelated technologies

Metabolites are molecules that are the intermediates and products of metabolism. They are the end product of the gene expression process and are involved in the normal growth, de velopment, and reproduction of living organisms. Cell metabolites are also active moieties of antibiotics, therapeutic drugs, and pigments. The metabolome is the complete set of small molecule metabolites (such as metabolic intermediates, hormones and other signalling mole cules, and secondary metabolites) present in an organism and which are formed by metabolic pathway reactions. Highthroughput technologies for identification, quantification and analysis A number of technologies that are used in protein identification and quantification are also applied to metabolites. MS and NMR are the two leading technologies for metabolomics. MS is used to identify and to quantify metabolites after separation (the mostly commonly used separation technology is gas chromatography in combination with MS). These technologies are presented in the previous section. Metabolic pathway engineering Metabolic pathway engineering includes the modification of endogenous metabolic pathways of microorganisms and the introduction of metabolic pathways into new host organisms. In addition, metabolic engineering also deals with the upregulation of the production of mole cules. It is one of the most important tools in the industrial biotechnology. The metabolism of microorganisms is engineered in order to improve their suitability for biotechnical processes and for efficient production of many sorts of chemical compounds. Metabolic pathway engi neering encompasses a combination of technologies, including technologies used in ge nomics and proteomics studies, genetic engineering, etc. 2.5

Cellular and subcellular levelrelated technologies Consequences, opportunities and challenges of modern biotechnology for Europe Final Report/Deliverable 3 Page 15 of 172

Cell hybridisation/fusion Basically, cell fusion combines the cell contents of two or more cells in a single cell. Two cells of different species origin can be fused in vitro into a single hybrid cell. The donor nuclei can remain separate or fuse, but during subsequent cell divisions a single spindle is formed so that each daughter cell has a single nucleus containing complete or partial sets of chromo somes from each parental line. The hybridoma technique is the use of cell fusion techniques for the production of mono clonal antibodies. The technique involves the fusion of plasma cells of a B lymphocyte with myeloma cancer cells. The former secretes a single antibody, while the latter confers the property of growing indefinitely in tissue culture. The fusion product of myeloma cancer cells and the plasma cells, a synthetic hybrid cell, is called hybridoma. The hybridoma produces the monoclonal antibodies that react on a single antigenic determinant of an antigen. Monoclonal antibodies are often used in immunoassays as they usually bind to only one site of a particular molecule. An immunoassay is a biochemical test that measures the level of a substance in a biological liquid using the reaction of an antibody to its antigen. The assay takes advantage of the specific binding of an antibody to its antigen. Monoclonal antibodies provide a specific and accurate biochemical test. Both the presence of antigen or antibodies can be measured. Cell and tissue culture and engineering Cell culture technologies, the invitro growth of cells isolated from multicellular organisms, are mainstream technologies. These techniques are very different for plant cell cultures and for animal and human cell cultures. Micropropagation is a specific example of the in vitro growth and/or regeneration of plant material under controlled conditions. Tissue engineering refers to more advanced culture technologies used to induce specific animal of human cells to grow and form entire tissues that can be implanted in the human body, or to induce extant cells within the body to grow and from desired tissues via precise injection of relevant com pounds (e. g. growth factors or growth hormones). Tissue engineering involves the use of a combination of cells, engineering materials and biochemical factors to develop biological sub stitutes that restore, maintain or improve tissue function. Cells are generally implanted or seeded into an artificial structure capable of supporting threedimensional tissue formation, also called scaffolds. Cells can come from the same body as that to which they will be reim planted, from another body, or even from other species. Embryo technology Embryo technology can consist of simply removing an embryo from a human or animal donor and immediately transferring it to a surrogate mother or it can be more complicated, involving microsurgery on the embryo and maintaining the embryo in special culture systems before transferring the embryo to the surrogate mother (including invivo and invitro embryo produc tion). Embryo technologies that already are in use or being adapted to livestock include em bryo transfer (animal embryos are transferred to recipients via artificial inembryonation), embryo splitting (the splitting of young embryos into several sections, each of which de velops into an animal that is genetically identical to the others) and cloning. Embryo technol ogy may also include a number of ancillary technologies such as in vitro fertilization, artificial insemination, hormonal manipulation, semen and embryo sexing etc. Cloning is the process of creating an identical genetic copy of the original organism through asexual processes that do not involve the interchange or combination of genetic material. As a result, members of a clone have identical genetic compositions. A technique to clone an organism is somatic cell nuclear transfer. In this method, the nucleus is removed from an egg cell (oocyte) and replaced with a nucleus extracted from another conventional somatic cell (a cell other than a sperm or egg cell) of the organism to be cloned. The technique is also used to produce embryonic stem cells. In this case, the new egg is stimulated to start dividing and the embryonic stem cells are harvested as soon as the dividing cells have formed a blastocyst. Embryo technologies involving the targeted embryo stem cells can also be em Consequences, opportunities and challenges of modern biotechnology for Europe Final Report/Deliverable 3 Page 16 of 172

ployed to generate chimeric animals (animals whose cells are not all genetically identical, through somatic mutation, grafting or because the individual is derived from two or more em bryos or zygotes), which are then used to generate the knockout animals, used mainly in re search. Apomixis is related to cloning only applied in plants. It is biological reproduction without fer tilization, with the result that the plant seeds are genetically identical to the parent plant. Stem cellsrelated technologies Stem cells are undifferentiated somatic cells that can grow into different cells or tissues of the body. Stem cells differentiate either in daughter stem cells or in any specialized cell type given the appropriate signals. This ability allows them to act as a ´repair system´. This matu ration process is stimulated and controlled by stem cell growth factor (SCF), granulocyte colony stimulating factor (GCSF), and by granulocytemacrophage colony stimulating factor (GMCSF). Basically, cell isolation and cell cultivation techniques are used, however they need to be adapted to specific requirements of stem cells, which is at the moment still very much in the development stage. Stem cells can be totipotent, pluripotent, multipotent or uni potent, indicating their degree of potency. They can be adult or embryonic, indicating their source. Gene delivery technologies Gene delivery is the insertion of genes into selected cells of an organism. Vectors are small DNA molecules (plasmid, virus, bacteriophage, artificial or cut DNA molecule) that are used to deliver the DNA into a cell. Vectors must be capable of being replicated and contain cloning sites for the introduction of foreign DNA. In order to insert the genes, several gene transfer methods can be used: 1) nonviral methods for instance human artificial chromosomes) 2) viral vectors (retroviral vectors, adenovirus, adenoassociated virus, baculovirus expression vector). Fermentation and downstream processing Fermentation originally is the anaerobic breakdown of complex organic substances, espe cially carbohydrates, by microorganisms, yielding energy. Today, the term fermentation is used in industry to describe both aerobic, anaerobic and microaerofilic culturing of defined microorganisms. Sometimes the term is even extended to cover the culturing of mammalian and insect cells. In a bioreactor or fermenter, a biochemical process takes place which in volves organisms, cells, cell extracts or biochemically active substances (such as enzymes) derived from such organisms. Bioreactors are commonly cylindrical, ranging in size from a litre to several cubic metres, and are often made of stainless steel. A bioreactor can also refer to a device or system to grow cells or tissues in culture, for instance in tissue engineering. After the fermentation process is completed, a large quantity of a dilute mixture of sub stances, products and microorganisms is produced. These must be separated in a controlled way, and the product concentrated, purified and converted into a useful form. This is the downstream processing. 2.6

Supporting tools

Bioinformatics Bioinformatics is the use of techniques from applied mathematics, informatics, statistics, and computer science to solve biological problems. Bioinformatics deals with the generation/ creation, collection, storage (in databases), and efficient use of data and information from all kinds of ‘omics’ and combinatorial chemistry research. Examples of the data that are ma nipulated and stored include gene sequences, biological activity or function, pharmacological activity, biological structure, molecular structure, proteinprotein interactions, and gene ex pression products, amounts and timing. Major research efforts in the field include sequence alignment, gene finding, genome assembly, protein structure alignment, protein structure pre diction, prediction of gene expression and proteinprotein interactions, and the modelling of Consequences, opportunities and challenges of modern biotechnology for Europe Final Report/Deliverable 3 Page 17 of 172

evolution. The terms bioinformatics and computational biology are often used interchange ably, although the latter typically focuses on algorithm development and specific computa tional methods.

3. Biotechnology applications 3.1

Introduction

In this chapter a description is given of the main applications of biotechnology in the three sectors planned for the empirical studies: medical/pharmaceutical sector, primary production and agrofood sector and industrial manufacturing, energy and environment. The overview in this chapter in terms of products is indicative. However, in terms of applications the descrip tion is comprehensive. Table 3.1:

Overview of use of key technologies in research and production in the three sectors MEDICAL/PHARMACEUTICAL SECTOR

KEY TECHNOLOGIES

Therapeutics

Diagnostics

Vaccines

Nucleic acid (DNA/RNA)related technologies Highthroughput sequencing of genome, gene, DNA DNA synthesis and amplification Genetic engineering Antisense technology Proteinrelated technologies High throughput protein identification, quantification and sequencing Protein/peptide synthesis Protein engineering and biocatalysis Metaboliterelated technologies High throughput metabolite identification and quantification Metabolic pathway engineering Cellular/ subcellularrelated technologies Cell hybridisation/fusion Cell and tissue culture and engineering Embryo technology Stem cellrelated technologies Gene delivery Fermentation and downstream processing Supporting tools Bioinformatics AGROFOOD SECTOR Animal pro duction

Crops and forestry

Molecular pharming

Animal pro duction

Crops and forestry

Molecular pharming

Nucleic acid (DNA/RNA)related technologies Highthroughput sequencing of genome, gene, DNA DNA synthesis and amplification Genetic engineering Antisense technology

Table 3.1 continued

Proteinrelated technologies High throughput protein identification, quantification and sequencing Protein/peptide synthesis Protein engineering and biocatalysis Consequences, opportunities and challenges of modern biotechnology for Europe Final Report/Deliverable 3 Page 18 of 172

Metaboliterelated technologies High throughput metabolite identification and quantification Metabolic pathway engineering Cellular/ subcellularrelated technologies Cell hybridisation/fusion Cell and tissue culture and engineering Embryo technology Stem cellrelated technologies Gene delivery Fermentation and downstream processing Supporting tools Bioinformatics INDUSTRIAL MANUFACTURING, ENERGY AND ENVIRONMENT Chemicals

Biofuels

Bioreme diation

Nucleic acid (DNA/RNA)related technologies Highthroughput sequencing of genome, gene, DNA DNA synthesis and amplification Genetic engineering Antisense technology Proteinrelated technologies High throughput protein identification, quantification and sequencing Protein/peptide synthesis Protein engineering and biocatalysis Metaboliterelated technologies High throughput metabolite identification and quantification Metabolic pathway engineering Cellular/ subcellularrelated technologies Cell hybridisation/fusion Cell and tissue culture and engineering Embryo technology Stem cellrelated technologies Gene delivery Fermentation and downstream processing Supporting tools Bioinformatics

Table 3.1 provides an overview of the applications of the key technologies presented in chapter 2 in the three sectors. The table shows that the use of key technologies differs very much between sectors and even between subsectors within a sector. The table highlights the multiple uses of key biotechnologies. A prerequisite for biotechnology research for all three sectors are nucleic acidrelated technologies, proteinrelated technologies and supporting tools in the field of bioinformatics; all the corresponding cells are shadowed. Metabolitere lated technologies and cellularrelated technologies are used only for specific application areas. The latter technologies are characterised by an earlier stage of development and thus directly linked to a specific research area. Future impetus for the exploitation of biotechnology could result from the wider integration of these novel technologies in existing processes. The table also shows that some key technologies are less broadly applied, for instance fermenta tion technologies that are applied in some subsectors of medical applications and all sub sectors of the sector Industrial manufacturing, energy and environment. In the following three sections the application of these key technologies and other – more sectorspecific – biotechnologies in the three sectors will be presented in more detail. 3.2 3.2.1

Applications of biotechnology in the medical and pharmaceutical sector Introduction

Biotechnology is increasingly playing a role in conventional drug discovery, both as a tool box in research applications and as a means for the production of biopharmaceuticals. It is Consequences, opportunities and challenges of modern biotechnology for Europe Final Report/Deliverable 3 Page 19 of 172

opening up new possibilities to prevent, treat and cure hitherto incurable diseases using novel methods of treatment and diagnosis. Biotech medicines such as antibodies and enzymes now account for 20 % of all marketed medicines and 50 % of those in clinical trials (EuropaBio 3 2005 ). Many biotechnology applications in health are based on the results of sequencing the human genome, leading to the identification of potential targets for both small and large mole cule therapeutics. The deeper understanding of the genetic prerequisite of humans and ani mals, systems approaches to diseases and advances in the development of diagnostics and therapeutics are transforming current diagnostic and therapeutic approaches to medicine. Together with new technologies such as emedicine, this will enable a predictive and preven tive medicine that will lead to personalized medicine (Hood et al. 2004 4 ; Bolsin et al. 2005 5 ). Through genetic engineering, biotechnology can modify different living organisms – plant and animal cells, bacteria, viruses and yeasts to produce medicines for human use (bio manu facturing). This aspect is further explained in section 3.2. Biotechnology has applications in the discovery and development of medicines, vaccines, diagnostics and emerging cell and gene therapies. All applications apply to the human sector, the veterinary and the animal companion sector. However, some approaches are predomi nantly developed for human applications, as costs are high and an adequate return on in vestment is only expected in human applications. Animal application could follow succes sively. Some of the most promising applications of biotechnology are in the field of animal health and production, especially in areas such as assisted reproduction, increased disease resistance, nanobased diagnostic and ‘smart’ treatment delivery systems, improved vaccines 6 and refined diagnostic techniques (MacKenzie 2005 ). 3.2.2 Therapeutics for Humans 3.2.2.1 Drugs Biotechnology offers different approaches for the development of new drugs: both in respect to the origin of therapeutic agents and in respect to therapeutic principles (Avidor et al. 2003 7 ). An example of the former is the identification and exploitation of new active molecules produced by marine microbiota, using improved microbial cultivation techniques and the ap plication of DNAbased molecular methods (Zhang et al 2005 8 ). Comparative genomics applications such as the comparison of the metabolic pathways of parasites and their hosts 9 facilitate the identification of new drug targets (Chaudhary and Ross 2005 ). Such advances in metabolomics (mapping the entire metabolic pathways) are bound to expedite the de velopment of new drugs for known pathogens. The discovery of novel therapeutic modes of action such as antisense technology favours the development of new medicines for the treat ment of unmet medical needs, as in the field of cancer (AboulFadl 2005 10 ; Coppelli and Grandis 2005 11 ). These applications are in an early developmental stage, i. e. preclinical de velopment and early clinical testing. Advances in drug manufacturing such as improved fer mentation technology, easier establishment of animal cell cultures and improved production methods of monoclonal antibodies (MAB) in transgenic animals (Butler 2005 12 ; Lonberg 3

EuropaBio (2005): http://www.europabio.org/healthcare.htm. Hood L, Heath JR, Phelps ME, Lin B.Science. (2004): Systems biology and new technologies enable predictive and preventative medicine. Oct 22;306(5696):6403. 5 Bolsin S, Patrick A, Colson M, Creatie B, Freestone L. (2005): New technology to enable personal monitoring and incident reporting can transform professional culture: the potential to favourably impact the future of health care. J Eval Clin Pract.Oct;11(5):499506. 6 MacKenzie, A.A. (ed.): Biotechnology applications in animal health and production. Scientific and Technical Review, Volume 24 (1), April 2005. 7 Avidor Y, Mabjeesh NJ, Matzkin H.: Biotechnology and drug discovery: from bench to bedside. South Med J. 2003 Dec;96(12):117486. 8 Zhang L., An R., Wang J., Sun N., Zhang S., Hu J., Kuai J. (2005): Exploring novel bioactive compounds from marine microbes. Curr Opin Microbiol 2005 Jun;8(3):27681. 9 Chaudhary, K.; Ross D.S. (2005): Protozoan genomics for drug discovery. Nat Biotechnol 2005 Sep, 23(9): 1089 1091. 10 AboulFadl T. (2005): Antisense oligonucleotides: the state of the art. Curr Med Chem 2005;12(19):2193214. 11 Coppelli F.M., Grandis J.R. (2005): Oligonucleotides as anticancer agents: from the benchside to the clinic and beyond. Curr Pharm Des 2005;11(22):282540. 12 Butler, M. (2005): Animal cell cultures: recent achievements and perspectives in the production of biopharmaceuticals. Appl Microbiol Biotechnol 2005 Aug;68(3):28391. 4


2005 13 ), could make small market drugs more attractive for investment and reduce the phar maceutical industry’s reliance on developing blockbuster medicines. In this respect, biotech nology can contribute especially in the field of orphan drugs and individualized medicines. Examples for biopharmaceuticals with a large market are erythropoietin, folliculestimulating hormone, hyaluronidase, monoclonal antibodies and tumour necrosis factors. Advances through modern biotechnology are also expected for the development of new antimicrobial agents. Against the background of multi drug resistance in hospital infections the develop ment of novel antibiotics such as peptides and the enhancement of already available antimi crobial drugs is an important R&D area. Products at the boundary between drugs and food are nutraceuticals. Biotechnological methods are used in their development and production. Both probiotic food, containing bacte ria that have health effects and products that are supplemented with biotechnologically pro duced compounds such as phytosterols, that help to regulate blood cholesterol level are examples for products already on the market. Orphan Drugs Between 20 and 30 million Europeans are affected by 5,000 rare diseases. Biotechnology provides several tools to develop diagnostics and treatments for orphan diseases, derived from the identification of new targets from the complete sequencing of the human genome. Since the EU Orphan Drugs Regulation came into force in early 2000, it has covered over 212 applications for an orphan drug designation. Among them are enzymes to treat metabolic dis orders and cancer drugs with small incidence rates (EuropaBio 2005 14 ). Some examples of biotechnology drugs to treat rare diseases are given in table 3.2. Table 3.2:

Source:

Selected examples of biopharmaceuticals for low incidence diseases in the US and European Markets Category Recombinant DNA Products

Product EGF receptor Factor VIII Interferon beta1a Interleukin1 and 2 Somatropin

Enzymes

Algalsidase Algucerase Glucocerebrosidase Glucosidase Galactosidase

MERIT biopharmaceuticals database; Rader 2005 15

Tailormade medicines For patients, finding the right medication with less trial and error is critical. Applications for tailormade medicines rely on developments in pharmacogenetic testing and the knowledge of the individual metabolising situation. Healthcare biotechnology aims to bring tailormade treatments to patients by early detection of the patient's genetic status and his or her indivi dual response to a drug. This allows matching medicine doses and medical treatments to in dividual patients (EuropaBio 2005 14 ). Some application have reached the clinic such as the use of Herceptin (trastuzumab), for treatment of breast cancer patients that overexpress the HER2 protein, or dose adjustment of thiopurines according to the biochemical and genetic 13

Lonberg N. (2005): Human antibodies from transgenic animals. Nat Biotechnol 2005 Sep;23(9):111725. www.europabio.org 15 th Rader, R. A. (2005): Biopharmaceutical Products in the U.S. and Euroepean Markets. BioPlan Associates, Inc. 4 edition, 11207. 14


status of the patient. Widespread application of individualized treatment is still limited due to unclear reimbursement situation and insufficient knowledge of potential applications and the procedures 16 . Finally, drug delivery can be improved through the use of new materials and methods based on new discoveries in bionanotechnology. The incorporation of drugs in nanoparticles facili tates the delivery of the drug to specific sites, reducing adverse side reactions (Kubik et al 2005 17 , Kayser et al. 2005 18 ). Nanoencapsulated drugs have already reached the market. However, their costeffectiveness is controversial. 3.2.2.2 Cellbased therapies In the past few years, cell therapies with stem cells, allogenic and autologous differentiated cells, have expanded greatly as a tool to develop potential therapies for various indications. Though they are still in the stage of clinical development, they offer a way of using a person’s own cells and tissue to create prosthetic, restorative, therapeutic and even cosmetic health care solutions. Under normal conditions, damaged joint cartilage does not – or only poorly regenerate in the body. For several years now, cell therapy for restoring knee cartilage defects has been avail able by growing a patient's own cartilage cells to repair cartilage defects. Other tissue engi neered products include skin and bone replacement (Hüsing et al. 2003a 19 ). Research on human cell and tissuebased products is currently being conducted in the regeneration and repair of bones, tendons, nerves, ligaments, heart valves and blood vessels. The overall, but still distant goal of tissue engineering is to construct in vitro human organs to overcome a scarcity of donor organs and to improve disease treatments. Research has been carried out on the urinary bladder, kidney, heart, liver and pancreas (Oberpenning et al. 1999 20 , Humes 2000 21 ). Products are still far away from clinical use and several scientific and technical hurdles still need to be overcome (e. g. vascularisation, controlled threedimensional structure, and coordinated action of different cell types). Cellbased cancer immunotherapies such as cellbased tumour vaccines are under develop ment to combat cancer. This type of therapy could one day provide new efficient strategies for the treatment of several incurable types of cancer (EuropaBio 2005). Presently, however, such approaches are only in the early clinical development stage. Research into stem cells could result in important cellbased therapies to treat serious dis eases and conditions such as neurodegenerative disease of the central nervous system (Si lani and Corbo 2004 22 ), diabetes, coronary diseases and stroke, spinal cord injuries, autoim mune diseases and skin disorders (Hüsing et al. 2003b 23 ). Researchers are working on three types of human stem cells: adult, foetal and embryonic. The use of human embryonic stem cells is currently at the centre of an ethical and societal debate.

16

Zika et al. (2006): Pharmacogenetics and pharmacogenomics: Stateoftheart and potential socioeconomic impacts in the EU. Report of JRCIPTS 17 Kubik T., BoguniaKubik K., Sugisaka M. (2005): Nanotechnology on duty in medical applications. Curr Pharm Biotechnol 2005 Feb;6(1):1733. 18 Kayser O., Lemke A., HernandezTrejo N. (2005): The impact of nanobiotechnology on the development of new drug delivery systems. Curr Pharm Biotechnol 2005 Feb;6(1):35. 19 Hüsing, B.; Bührlen, B.; Gaisser, S. (2003a): Human Tissue Engineered Products Today's Markets and Future Prospects. Final Report for Work Package 1: Analysis of the actual market situation Mapping of industry and products. Karlsruhe: Fraunhofer Institute for Systems and Innovation Research, 2003, 122 p. 20 Oberpenning, F., Meng, J., Yoo, J. J. & Atala, A. (1999): De novo reconstitution of a functional mammalian urinary bladder by tissue engineering. Nat Biotechnol, 17(2), 14955. 21 Humes, H. D. (1999): Bioartificial kidney for full renal replacement therapy. Semin Nephrol, 2000, 20(1), 7182. 22 Silani V, Corbo M. (2004): Cellreplacement therapy with stem cells in neurodegenerative diseases. Curr Neurovasc Res 2004 Jul;1(3):2839. 23 Hüsing, Bärbel; Engels, EveMarie; Frietsch, Rainer; Gaisser, Sibylle; Menrad, Klaus; Rubin, Beatrix; Schubert, Lilian; Schweizer, Rainer, Zimmer, René (2003b): Menschliche Stammzellen. Abschlussbericht. TA44/2003. Bern: Zentrum für TechnologiefolgenAbschätzung beim Schweizerischen Wissenschafts und Technologierat, 2003 337 p.


Xenotransplantation has been a field of extensive research in the last decade. It uses existing varieties or genetically modified animals (usually pigs) and successive cloning techniques to produce organs that can be transplanted into humans. Technical barriers due to immunogen ity and concerns about human safety through the transfer of possibly dangerous and infec tious viruses into the human population led to a decline in interest in xenotransplantation. According to expert opinion, interest in xenotransplantation will further decline as alternative cell therapies based on human stem cells become reality. 3.2.2.3 Gene therapies Despite the high standard of today's medical treatments, and the number of already available drugs, many of the most debilitating human diseases do not yet have a cure. The molecular basis of many genetic disorders, such as haemophilia, cystic fibrosis and muscular dystrophy, has become better understood, due to the discovery of the affected genes. In some forms of cancer, genetic predisposition could play as important a role as environmental factors in tu mour growth and malignancy. Identifying the genes that play a role in these diseases and combating their effects is one of the most promising ways to treat certain diseases. Gene therapy has entered a phase of active clinical investigation in many areas of medicine. Human clinical trials have been started for the treatment of severe immunodeficiency dis eases, cystic fibrosis, hypercholesterolemia, haemophilia, muscular dystrophy, and many types of cancers (melanoma, prostate, ovarian and lung cancer), AIDS, and cardiovascular 24 25 disorders (Kempten et al. 2004; Gosh et al 2005 ; Ebert and Svendsen 2005 ; Hideshima et 26 27 28 al. 2005 ; BudakAlpdogan et al. 2005 ; CavazzanaCalvo and Fischer 2004 ; EuropaBio 2005). So far, the FDA has not yet approved any human gene therapy product for sale nor did the EMEA. In January 2004, SiBiono GeneTech received approval by the Chinese State Food and Drug Administration (SFDA) to commercially market Gendicine, a genetherapybased treatment for nasopharyngeal cancer. This seems to be the first approved genetherapy treatment in the world (Wilson 2005 29 ). The treatment delivers a healthy copy of the antitu mour p53 gene through a simple adenovirus construct that does not integrate into the ge nome of cells. The cost of a single dose of therapy is expected to be only 360 US$. The amount of generelated research and development occurring worldwide continues to grow rapidly. The FDA has received many requests from medical researchers and manufac turers to study gene therapy and to develop gene therapy products. Such research could lead to genebased treatments for cancer, cystic fibrosis, heart disease, haemophilia, wounds, in fectious diseases such as AIDS, and graftversushost disease (FDA 2005 30 ). Some clinical trials such as the gene therapy of a fouryear old USgirl in the early 1990s, who was born with an adenosinedeaminase deficiency syndrome, resulted in a permanent cure (Budak et al. 2005). However, clinical trials have also shown the risks and scientifictechnical problems associated with gene therapy, for example in the case of the death of Jesse 31 Gelsinger (Smith and Byers 2002 ) and the development of leukaemia in patients treated

24

Ghosh K., Khare A., Shetty S. (2005): Implications of human genome and modern cell biology research in management of cardiovascular diseases. Indian Heart J. 2005 MayJun;57(3):2703. 25 Ebert A.D., Svendsen C.N. (2005): A new tool in the battle against Alzheimer's disease and aging: ex vivo gene therapy. Rejuvenation Res. 2005 Fall;8(3):1314. 26 Hideshima T., Chauhan D., Richardson P., Anderson K.C. (2005): Identification and validation of novel therapeutic targets for multiple myeloma. J Clin Oncol 2005 Sep 10;23(26):634550. 27 BudakAlpdogan T, Banerjee D, Bertino JR. (2005): Hematopoietic stem cell gene therapy with drug resistance genes: an update. Cancer Gene Ther 2005 Nov;12(11):84963. 28 CavazzanaCalvo M., Fischer A. (2004): Efficacy of gene therapy for SCID is being confirmed. Lancet. 2004 Dec 1831;364(9452):21556. 29 Wilson J.M. (2005): Gendicine: The first commercial gene therapy product. Human Gene Therapy. 2005 Sept 16:1014. 30 FDA (2005): Cellular and Gene Therapy. Internet release 11/08/2005. http://www.fda.gov/cber/gene.htm. 31 Smith L. and Byers J.F. (2002): Gene therapy in the postGelsinger era. JONAS Health Law Ethics Regul 2002 Dec; 4(4):10410.


with a retrovirus to cure SCID X1 (severe combined immunodeficiency) (Gaspar and Thrasher 2005 32 ). 3.2.2.4 Therapeutic vaccines Therapeutic vaccines play an important role for the control of infectious diseases in people that are already infected with a virus. The application area with the most experiences is the control of HIV by stimulating the immune system to fight HIV and slow the progression of the disease. More than 20 therapeutic vaccines to stimulate Tcell responses of persons with HIV were under development within the last 20 years, most of them in the USA, but some also in 33 Europe (McMichael and Hanke 2003 ). At present, more than 15 phase I, II or III trials are ongoing involving a variety of different strategies, including more complex subunit vaccines, recombinant viral vectors, primeboost strategies and DNA vaccines, as well as new delivery mechanisms like intranasal application (Smith and Renaud 2003 34 ). There are a number of main challenges ahead to developing an effective HIV vaccine. These lie in protein engi neering, the optimisation of Tcell inducing vaccines, to increase the capacity to carry out phaseIII trials, and to manufacture them in sufficient quantities (McMichael and Hanke 2003). 35 3.2.3

Therapeutics for Animals

Biotechnology plays an important role in many veterinary and companion animal areas such as infectious diseases, animal production and foodsafety. A number of applications are available on the market or are in an advanced status of (clinical) development. Thus far, ge nomics and systems biology have not been largely introduced significantly in typical veteri nary pharmacological and toxicological research programmes. The high costs and complexity connected to these large projects often form major obstacles for research groups with limited budget (Wittkamp 2005) 36. A first example of the utilisation of genomic research in the de velopment of animal drugs is the identification of a specific enzyme, the Babesia bovis Llac tate dehydrogenase as a potential chemotherapeutical target against bovine babesiosis (a parasitic disease; Bork et al 2004) 37 . 3.2.3.1 Recombinant drugs and hormones Although product lists for veterinary drugs including companion animal drugs approved by the United States Department of Agriculture’s Center for Veterinary Biologics and the FDA’s Center for Veterinary Medicine are published regularly it is difficult to distinguish biological and recombinant drugs among the thousands of products approved (Walsh 2003) 38 . Within the EU, the assessment of veterinary biotechnology products falls under the auspices of the EMEA’s Committee for Veterinary Medicinal Products. Among the recombinant products approved for veterinary use in the EU all but one are recombinant vaccines. The recombinant interferoneomega was approved in 2001 for the therapy of canine parvovirosis. In a placebo controlled field trial the drug reduced mortality also both in the vaccinated and unvaccinated cohort of cats when it was applied after clinical signs of canine parvovirosis were observed

32

Gaspar H.B., Thrasher A.J. (2005): Gene therapy for severe combined immunodeficiencies. Expert Open. Biol. There. 2005 Sep;5(9):117582. 33 McMichael A.J., Hanke T. (2003): HIV vaccines 19832003. Nat Med. 2003 Jul;9(7):87480. 34 Smith, R. and Renaud, R. C. (2003): Vaccines of the future. Nat Rev Drug Discov 2003 Oct;2(10):7678. 35 McMichael A, Hanke T. (2003): The quest for an AIDS vaccine: is the CD8+ Tcell approach feasible? Nat Rev Immunol 2002 Apr;2(4):28391. 36 Wittkamp, R.F. (2005): Genomics and systems biology – how relevant are the developments to veterinary pharmacology, toxicology and therapeutics? J. vet. Pharm Therap 28: 235245. 37 Bork, S.; Okamura, M.; Boonchit, S.; Hirata, H.; Yokoyama, N.; Igarashi, I. (2004): Identification of Babesia bovis L lactate dehydrogenase as a potential chemotherapeutical target against bovine babesiosis. Mol Biochem Parasitol 2004 Aug;136(2):16572. 38 Walsh, G. (2003): Biopharmaceutical Benchmarks – 2003. Nature Biotechnology 21(8): 865870


(de Mari et al 2003) 39 . This led to the extended approval of Virbagen Omega for cats in 2004 (Press Release of the Committee of Veterinary Medicinal Products (14/15 March 2004)). Several recombinant drugs are currently in the status of clinical or preclinical trial. One example is the recombinant porcine interferonealpha/gamma. In preclinical trials it could be shown that it inhibits classical swine fever virus and other important viral pathogens in dif ferent cell lines (Xia et al 2005) 40 . Bone healing in dogs and cats was stimulated in a prospective clinical study on a nonglyco sylated recombinant human bone morphogenetic protein2 (nglyrhBMP2)/fibrin composite. It could be shown that it is an efficient alternative to bone autografts in dogs and cats. 41 (Schmoekel et al 2005) . Human recombinant factor VIIIa is discussed to be used in veteri nary medicine under the prerequisite that the two major obstacles: immunogenity and costs can be solved (Kristen et al. 2003) 42 . Efficacy and safety of recombinant feline erythropoietin (rfEPO) was tested in clinical trials with anaemic cats due to chronic kidney diseases (CKD). It could be shown that treatment with rfEPO can reestablish active erythropoiesis in most cats with CKD. However one third of the tested animals developed redcell aplasia (RCA) a type of anaemia which is refractory to 43 additional rfEPO treatment (Randolph et al. 2004) . Erythropoietin is also used in another context in animals. Human recombinant drugs such as erythropoietin (rHuEPO) are used for the (illegal) doping of racehorses by subcutaneous administration. The methods of molecular diagnostics described in the diagnostics paragraph such as enzymelinked immunosorbent assays are suitable to conduct antidoping control (Lasne et al. 2005) 44 . One of the first biotechnological product for animal production was bovine somatotropin (bST) a hormone that increases milk yield by an altered use of nutrients for milk synthesis, (Bauman 1992) 45 . In this case the Council of the European Union decided in 1999 to ban the possible use in the EU for animal welfare reasons. In the US rbST is approved. Other recombinant product such as the equine growth hormone failed for safety issues already in clinical trial. Long term therapy for this recombinant product showed to result in insulin resistance in horses with various disease states (de GraafRoesldema et al 2003). 46 In the context of veterinary drugs novel principles for drug delivery and biomaterials are also discussed in veterinary applications. Senel and McClure (2004) 47 review current applications of chitosan including wound healing, bone regeneration, and drug delivery for antibiotics, an tiparasitics, anaesthetics, painkillers, growth promoters and immunomodulatory agents and vaccines. Biodegradable polymers are also discussed with applications including intravaginal devices, injectables and implantable systems in the animal health market (Winzenburg et al.

39

de Mari, K. Maynard, L. Leun, H.M. Lebreux, B. (2003): Treatment of canine parvoviral enteritis with interferon omega in a placebocontrolled field trial. Vet. Rec. 152(4): 105108. 40 C.Xia, W. Dan, W. WenXue, W. JianQing, W. Li, Y. TianYao, W. Qin , N. YiBao (2005): Cloning and expression of interferonalpha/gamma from a domestic porcine breed and its effect on classical swine fever virus. N. Vet. Immunol Immunopathol 104(12):819. 41 Schmoekel, H.G. Weber, F.E. Hurter, K. Schense, J.C. Seiler, G. Ryrz, U. Spreng, D. Schawalder, P. Hubbell J.J. (2005): Enhancement of bone healing using nonglycosylated rhBMP2 released from a fibrin matrix in dogs and cats. Small Anim Pract 2005 Jan;46(1):1721. 42 Kristen, A.T. Edwars, M.L. Devey, J. (2003): Potential use of recombinant human factor VIIIa in veterinary medicine. Vet Clin North Am Small Anim Pract 33(6): 143751. 43 Randolph, J.E. Scarlett, J.M. Stokol, T. Saunders, K.M. MacLeod, J.N. (2004): Expression, bioactivity, and clinical assessment of recombinant feline erythropoietin. Am J Vet Res.;65(10):135566. 44 Lasne, F. Popot, M.A. VarletMarie, E. Martin, L. Martin, J.A. Bonnaire, Y. Audran, M. de Ceaurriz, J. (2005): Detection of recombinant epoetin and darbepoetin alpha after subcutaneous administration in the horse. J Anal Toxicol 29(8): 835837. 45 Baumann, D.E. (1992): Bovine Somatotropin: Review of an Emerging Animal Technology. J Dairy Sci 75: 3432 3451. 46 de GraafRoelfsema, E. Tharasanit, T. van Dam, K.G. Keizer, H.A. van Breda, E. Wijnberg, I.D. Stout, T.A. van der Kolk, J.H. (2005): Related Articles, Effects of short and longterm recombinant equine growth hormone and short term hydrocortisone administration on tissue sensitivity to insulin in horses. Am J Vet Res. 66(11):190713. 47 Senel, S. McCllure, S.J. (2004): Potential applications of chitosan in veterinary medicine. Adv Drug Deliv Res 56(10): 146780.


2004) 48 . Membrane transporter/receptortargeted prodrug design is another trend currently under development to enhance bioavailability of drugs both in humans and animals (Maju madar et al. 2004). 49 3.2.3.2 Antiinfectious agents Antiinfectious agents, i. e. antibiotics and antifungal products are together with vaccines the most important group of biopharmaceuticals in animal health applications. With most thera peutic antimicrobials used to treat bacterial infection in animals there are related antimicro bials used in human medicine from the same family. Among them are aminoglycosides, amoxicillin and clavunalate, cephalosporins, polyketides, and fluoroquinolones (www.vetgate.ac.uk; release 3 February 2006). Antiinfectious agents were used in the past in the EU with three different intentions · as therapeutic agent after the onset of an infectious disease · as preventive agent when animals are most at risk, and animals are known to be sus ceptible, · as enhancing agents in subtherapeutic concentration that should help growing animals digest their food more efficiently (growth promoters) The application of antibiotics as growth promoters was banned in the EU by 1 January 2006. Feed additives being promoted as possible alternatives to antibiotic growth promoters include amino acids, enzymes, prebiotics, probiotics, organic acids, and immune modulators (Frost&Sullivan Market Insight 24 Nov 2005). Many of these feed additives can be produced by biotechnological fermentation processes, followed by downstream processing. 3.2.4

Molecular Diagnostics

Molecular diagnostics are becoming a driving force in drug development, drug application, surveillance of human and animal health status. Applications have spread from identifying infections to include screening for cancer, hepatitis, a variety of genetic disorders and even tissue screening to minimize the risk of tissue rejection (Dutton 2005 50 ). Improved microarray technology with cheaper process costs and new application areas lead to diversify molecular diagnostics in new directions including in vitro diagnostics. The human health benefits of bio technology detection methodologies go beyond disease diagnosis. For example, biotechnol ogy detection tests can screen donated blood and organs for the pathogens that cause AIDS, hepatitis and a variety of other infectious diseases (EuropaBio 2005). While traditional testing methods are still widely used in veterinary diagnostic laboratories, promising new technologies, such as biosensors and microarray techniques, are being de veloped. Nucleic acid diagnostic techniques such as polymerase chain reaction (PCR) have become routine veterinary diagnostic tools for rapidly screening large numbers of samples during disease outbreaks. In addition, nanotechnologies, although not yet implemented in veterinary laboratories, hold the promise of screening for numerous pathogens in a single assay. Other biotechnologies are likely to be widely used in the future as they can improve diagnostic capabilities while reducing the time and perhaps, the costs, associated with con ventional technologies. Although a lot of developmental work is still required, biotechnology and its applications hold great promise for improving the speed and accuracy of diagnostics 51 for veterinary pathogens (Schmitt and Henderson 2005 ). Protein testing 48

Winzenburg, G. Schmidt, C. Fuchs, S. Kissel, T. (2004): Biodegradable polymers and their potential use in parenteral veterinary drug delivery systems. Adv Drug Deliv Rev 56(10): 145366. 49 Majumadar, S. Duvvuri, S. Mitra, A.K. (2004): Membrane transporter/receptortargeted prodrug design. Adv Drug Deliv Rev. 56(10): 143752. 50 Dutton, G. (2005): Molecular diagnostics as Clinical Tool. Genetic Engineering News 2005; 25(18): 125. 51 Schmitt, B. and Henderson, L.: Diagnostic tools for animal diseases. Rev sci tech Off int Epiz, 2005, 24 (1), 243 250.


Protein microarrays and immunoassays help to determine the molecular status of a certain disease such as some types of cancer and guide the clinician toward the choice of optimal therapy. About 1500 different proteins have recently been identified in the blood, and a num ber of potential new markers of diseases have been characterized. Thus haematology in combination with microarray technology offers enormous promises of plasma/serum prote omic analysis for diagnostic/prognostic markers and information on disease mechanisms (Thadikkaran et al. 2005 52 ). Currently nearly one hundred companies are active in the field of microarrays (Gershon 2005 53 ). However it is also generally accepted that new insights will not be gained by simply acquiring more and more gene expression data and that it is no longer sufficient to focus on the 25,000 proteincoding genes that make up roughly 2 % of the human genome. Exploring the role and diversity of noncoding DNAs is equally important. Molecular Imaging Molecular imaging (MI) combines new molecular agents with traditional imaging tools to cre ate targeted, tailored therapies with the ability to simultaneously find, diagnose and treat dis ease. Currently being investigated for numerous applications including oncology, cardiology and neurology molecular imaging offers significant benefits over standard diagnostics and treatments (www.micentral.org). For example diagnostic peptides (515 amino acids) can be used to specifically bind to receptors at the surface of tumours. This allows the exact determi nation of solid and metastatic cancers followed by a surgical, chemotherapeutic or radiologi 54 cal therapy (Zitzmann et al. 2005) DNAbased testing DNAbased testing has a long tradition for differential diagnostic of infectious disease. The most prominent technique in this context is PCR technology as described in chapter 1.2. In clinical diagnostics, a specimen of genetic material weighing only onetrillionth of a gram can be repeatedly copied by PCR to provide sufficient material to detect the presence or absence of a virus as well as to quantify its levels in the blood. PCR tests were the first that could accurately measure the amount of HIV in a patient’s blood. This provides reliable information on the disease course and shows when changes are needed in a patient’s medication. DNA based testing opened the horizon to genetic testing. Genetic testing The wealth of genomics information made available by the Human Genome Project is greatly assisting doctors in diagnosing hereditary diseases. There are currently over a thousand hu man hereditary diseases that can be identified using genetic tests (EuropaBio 2005 55 ). The majority of these tests detect the presence of mutations in a single gene that can cause monogenic (single gene) disorders, most of which are relatively rare. These tests can also identify patients with a genetic propensity to develop diseases caused primarily by environ mental factors or diet, giving patients an opportunity to prevent the disease by avoiding the environmental triggers. Genetic testing is also critical to the development of pharmacogene tics, which uses biotechnologybased diagnostics to better diagnose disease and provide new ways to match medicine doses and treatments to the individual (EuropaBio 2005). Up to now only few examples such as the determination of the Herceptin receptor status in breast can cer patients are clinically widespread. Other applications such as the analysis of the TPMT status (thiopurine methyl transferase) are developed and could be used in the clinic. Due to various reasons as discussed into more detail in section 3.1.2.1 the diffusion into daily clinical practice is still missing. 3.2.5

Vaccines

52

Thadikkaran L., Siegenthaler M.A., Crettaz D., Queloz P.A., Schneider P., Tissot J.D. (2005): Recent advances in bloodrelated proteomics. Proteomics. 2005 Aug;5(12):301934. 53 Gershon, D. (2005): More than gene expression. Nature. 2005 Oct 20;437(7062):11958. 54 Zitzmann, S. Knapp, E.M. Mier, W. (2005): Spezifische Darstellung und Therapie von Krebserkrankungen. Laborwelt 6: 2123. 55 www.europabio.org


Immunization is rightly regarded as one of the great medical successes of the 20 th century. Recent outbreaks of West Nile Virus (WNV), severe acute respiratory syndrome (SARS), avian influenza and monkeypox, as well as threats from bioterrorism, have increased the in terest in developing new vaccines. Vaccines can also play a role in eradicating HIV, although this requires overcoming serious problems due to the high degree of antigenic variability among HIV strains (Smith and Renaud 2003). Traditional vaccination employed whole, attenuated infectious agents, with the vaccine prompting an immune response to protein structures. A new approach is the development of vaccines based on the carbohydrates on parasite surfaces instead of proteins. Some patho gens like Trypanosoma brucei, a protozoan that causes sleeping sickness, can change their protein coat every two weeks, which makes it very difficult for the immune system to develop a sufficient immune response. Carbohydrates in the cell walls are changed less frequently, or not at all, and therefore present a much more stable target. An Australian group is currently working on vaccines based on these substances against the cause of malaria, Plasmodium falciparum (Dennis 2003 56 ). A third strategy involves DNA vaccines. Several DNAbased methods of immunization such as pure DNA, DNA conjugated to a protein allergen, and plasmid DNA, have shown promise in animal models of several disorders. Some of these DNAbased therapies have entered phase I/II clinical trials (Liu and Ulmer 2005 57 ). Promising application areas are immunothera 58 59 py for cancer (Choo et al. 2005 ), severe respiratory syndrome (Zhang et al. 2005 ), and 60 allergic disease (Weiss et al. 2005 ). These applications show the close connection between traditional vaccination as a preventive measure and novel therapeutic approaches for vacci nation. Research in vaccine adjuvants has increased in the last years and resulted in promising approaches. The field is moving rapidly. Mucosal vaccine delivery systems are specifically designed to allow vaccines to enter the body through nasal or oral mucosal surfaces, avoiding invasive vaccination techniques. Additional components are necessary to protect antigens from degradation and promote their interaction with the host tissue (O'Hagan and Valiante 2003 61 ). Products in this field of application have already entered the market. Vaccination continues to be the main approach to protecting animals from infectious dis eases. Until recently, all licensed vaccines were developed using conventional technologies. However, the introduction of modern molecular biological tools and genomics, combined with a better understanding of not only which antigens are critical in inducing protection, but an appreciation of host defences that must be stimulated, has created new opportunities to de velop safer and more effective vaccines (Rogan and Babiuk 2005 62 ). The last ten years have seen the development of rDNA vaccines, which, when used in association with appropriate diagnostic kits, make it possible to distinguish vaccinated from infected animals. In this con text it is important to distinguish between DNAbased vaccines and live recombinant vac cines, that are based on a mutant strain (e. g. marker vaccine against Aujeszky’s disease). Proteinbased vaccines and diagnostic systems might be superseded by the DNAbased systems by the middle of the 21st century (McKeever, Rege 1999 63 ). 56

Dennis, C. (2003): Sweet revenge. Nature 2003, Vol. 423, pp. 580582. Liu MA, Ulmer JB.: Human Clinical Trials of Plasmid DNA Vaccines. Adv. Genet. 2005;55C:2540. Choo A.Y., Choo D.K., Kim J.J., Weiner D.B. (2005): DNA vaccination in immunotherapy of cancer. Cancer Treat Res. 2005;123:13756. 59 Zhang D.M., Wang G.L., Lu J.H. (2005): Severe acute respiratory syndrome: vaccine on the way. Chin Med J (Engl). 2005 Sep 5;118(17):146876. 60 Weiss R., Hammerl P., Hartl A., Hochreiter R., Leitner W.W., Scheiblhofer S., Thalhamer J. (2005): Design of protective and therapeutic DNA vaccines for the treatment of allergic diseases. Curr Drug Targets Inflamm Allergy 2005 Oct;4(5):58597. 61 O'Hagan, D.; Valiante, N. (2003): Recent advances in the discovery and delivery of vaccine adjuvants, in: Nature Reviews Drug Discovery 2003, Vol. 2, No. 9, pp. 727735. 62 Rogan, D. and Babiuk, L.A. (2005): Novel vaccines from biotechnology. Rev sci tech Off int Epiz, 2005, 24 (1), 159174. 63 McKeever, D.J. Rege, J.E.O. (1999): Vaccines and diagnostic tools for animal health: the influence of biotechnology. Livestock Prod Sci 59: 257264. 57 58


Different applications include vaccines against Aujeszky’s disease, classical swine fever, ra bies, avian diseases and rinderpest. DNA vaccines constitute a revolution in the concept of vaccination, which was previously based on the injection of a protein or a medium expressing a protein. It is now possible to induce immunisation by direct injection of the gene that codes 64 for the immunogenic antigen (Vannier and Martignat 2005 ). The example of coccidiosis shows how the understanding of the gene functioning can lead to a concerted action of nutritional and vaccination strategy. Coccidiosis is a ubiquitous intestinal protozoan infection of poultry seriously impairing the growth and feed utilization of infected animals. Conventional disease control strategies rely heavily on chemoprophylaxis, which is a tremendous cost to the industry. Existing vaccines consist of live virulent or attenuated Eimeria strains with limited scope of protection against an everevolving and widespread pathogen. Recent progress in functional genomics technology facilitates the identification and characterization of host genes involved in immune responses as well as parasite genes and proteins that elicit protective host responses. This allows the design of nutritional interventions and development of vaccination strategies (live and recombinant vaccines) against coccidio sis (Dalloul and Lillehoj 2005 65 ). Vaccines against veterinary helminths have focussed in the past on identifying protein anti gens. Notable successes have been achieved for some cestode parasites, where recombi nant proteins have been developed into highly effective vaccines. Increasing evidence suggests that parasite glycan moieties may provide an alternative source of vaccine antigens, and increased attention is now being given to this class of compounds. In addition to identi fying candidate protective antigen(s), an increased research effort is needed to develop appropriate strategies for the formulation and delivery of helminth vaccines. (Hein and Harri son 2005) 66 3.2.6

Barriers for the application of biotechnology in the medical and pharmaceutical sector

In contrast to many other application areas, healthcare biotechnology has a broad public acceptance. Scientifictechnical barriers due to a very early stage of development are present in some application areas such as metabolomics and proteomics. According to expert opinion, public research could benefit from greater unification of research efforts and more infrastructure funding. Public research is especially limited in fields that require largescale equipment and high speed computer technology. Stem cell research and gene therapy are both application areas in an early developmental stage. They are characterized by scientifictechnical barriers such as a lack of understanding of differentiation for the rational use of stem cells and tissue engineered products and the nondirected integration of vectors in the case of gene therapy. Both topics are subject to intensive research. A barrier for the development of novel drugs and tailormade medicines lies in the accessi bility of clinical data. Due to data protection laws and commercial confidentiality concerns, clinical data from private and public sector studies is often unavailable for use in applications such pharmacogenetic testing. Fundamental researchers at universities sometimes are unaware of the fact that the basic data they are generating in fundamental research may have potential for applications. Many lack information and knowledge about the innovation change and about global markets rele vant to what they are doing. This could be changed in three ways: (1)

Universities and the relevant units of the university should develop their innovation policy.

64

Vannier, P. Martignat, L. (2005): Nouveaux vaccins et nouvelles perspectives therapeutiques d’intérêt vétérinaire issus des biotechnologies: examples d’applications. Rev Sci tech Off int Epiz 24(1): 215229. 65 Dalloul, R.A. Lillehoj, H.S. (2005): Recent advances in immunomodulation and vaccination strategies against coccidiosis. Avian Dis. 2005 Mar;49(1):18. 66 Hein, W.R. Harrison, G.B. (2005): Vaccines against veterinary helminths. Vet Parasitol Sep 30;132(34):21722.


(2)

(3)

The new generation of researchers, the doctoral students should be offered training in how fundamental research can generate innovations, how to recognize commercial potential and how to protect and take forward the innovation to those who will de velop it further and commercialize it. Fundamental researchers should work in closer proximity (intellectual and physical) with the exploiters. This can be achieved, for example, in so called centres of com petence, where top researchers develop their research plan together with exploiters, making use of shared infrastructure.

A barrier for public sector research is access to skilled staff. In some disciplines, such as bio informatics, systems biology and clinical research, there is a lack of skilled staff, partly be cause the public sector has to compete with the private sector. Another barrier is the limited availability of earlystage and startup venture capital, which can prevent the establishment of new firms. After overinvestment in the late 1990s and 2000, culminating in the collapse of many new technology startups, venture capital has shifted in creasingly into latestage investment. The peak in seed and earlystage venture capital in 2000 has been followed by a continuous decline until 2003. In 2004, startup investments in creased again by 13 %, but still represented a small share of total investments (6 %). Seed investments still fell and represent only 0.4 % of all investments (EVCA 2005 67 ). This trend is impeding the biotech industry as a whole, but has particular relevance for the biomedical sector, given both high investment requirements and high risk. Barriers for commercialisation result from a lack of guidelines and clear regulations and the different attitude related to IPR matters in Europe, Canada and the US such as patentability of higher life forms. Administrative policies are needed to address possible conflicts and ensure research participant safety as cellular therapies progress from research laboratories to the patient's bedside. Several policies are required: to ensure minimum standards of quality for emerging products before human clinical trials, to enforce consistent reporting requirements for private and public cellular research, to minimize financial conflicts of interest and to address identified conflicts, and, in some jurisdictions, to limit private litigation. These policies would help preserve the objectivity of the review process and ultimately increase participant safety (Yim 2005 68 ). In some cases barriers for the use of biotechnological developments can be found in the lack of knowledge of users and multiplicators. As shown in a current EU study 69 on genetic testing efficient biochemical tests are already introduced for many applications. Physicians who have not been trained in genetics are reluctant to use the new methods as they feel unfamiliar with the new technology and lack the knowledge to read the results and draw conclusions. Another barrier is the unclear reimbursement situation for many new products and therapies such as tissue engineered products and pharmacogenetic testing. The extent to which inno vative health technologies are reimbursed by private insurance or national healthcare sys tems is partly a political debate over the cost of health care and partly due to issues of cost effectiveness. Only costefficient health technologies are likely to be reimbursed. 3.3 3.3.1

Biotechnology in primary production and the agrofood sector Introduction

Biotechnology has many applications within the agrofood sector that are largely based on using biotechnology techniques to improve breeding programmes. These include the use of marker assisted selection (MAS) (which involves the use of genomics tools such as marker gene identification, genome mapping etc) to speed up conventional breeding, and genetic modification (GM), in which a gene from one species that codes for a desirable trait is in 67

EVCA (2005): EVCA Final Activity Figures for 2004. Internet release 11/20/2005: http://www.evca.com/images/ attachments/tmpl_8_art_166_att_795.pdf. 68 Yim R. (2005): Administrative and research policies required to bring cellular therapies from the research laboratory to the patient's bedside. Transfusion. 2005 Oct;45(4 Suppl.):144S58S. 69 Zika et al (2006): Pharmacogenetics and pharmacogenomics: Stateoftheart and potential socioeconomic impacts in the EU. Report by JRCIPTS.


serted into the genetic material of another species. In addition, there are many other potential applications of biotechnology, such as the use of DNA fingerprinting and molecular diagnos tics for identification, traceability, and food/feed safety applications. Marker assisted selec tion/breeding may be viewed as a more complex application of diagnostics, where DNA based markers are combined with other tools such as quantitative trait loci (QTL), genetic maps, highthroughput tools etc. in order to increase the response to conventional selection. The boundary between biotechnology applications in agriculture and that in food or industrial processing is unclear. This section is limited to the use of biotechnology to produce feed/food, fibre, or industrial feed stocks for use in foods and in food and industrial processing. It does not discuss the application of biotechnology in food processing itself, such as the use of en zymes produced through GM bacteria in cheese manufacture. Broadly defined, agricultural biotechnology covers all biotechnology applications to food, feed, and fibre. This includes six main areas of application; clustered in three groups. Firstly, crop production, horticulture and silviculture (forestry), secondly, animal husbandry, fisheries and aquaculture and insects and finally molecular farming. Each area of application has distinctive characteristics, is of different relevance to the EU, and faces different barriers to adoption within Europe. 3.3.2 Animal husbandry, fisheries and aquaculture, and insects 3.3.2.1 Animal husbandry Biotechnology has applications in animal breeding, in feed (part of plant biotechnology) and other additives production, molecular pharming, animal health, and DNA fingerprinting for food safety or tracing GM use. Both Marker Assisted Selection (MAS) and GM can be used to improve animal strains and breed animals with greater precision than conventional breeding method alone. Also, the use of genomic technologies to identify genes involved in serious inherited diseases can help animal breeders select the unaffected animals and improve the characteristics of their stock. A possible application of GM breeding (or marker assisted se lection) is to develop dairy cows that produce more nutritious milk. This is currently in the re search stage. One of the first applications of GM technology was the development and production of bovine somatotropin (bST) to increase milk production in the dairy industry. Injections of recombinant bST in dairy cows increases milk yield, productive efficiency (milk/feed), and decreases ani mal waste. rBST is used commercially in 19 countries worldwide, but is not approved for use in Europe. A second development is porcine somatotropin (pST) for the swine industry, which increases muscle growth and reduces body fat deposition, resulting in pigs that are leaner and of greater market value. In the US, pST is undergoing testing for FDA evaluation. pST is currently approved for commercial use in 14 countries. As described in chapter 3, biopharmaceuticals, vaccines, and diagnostics have many appli cations to animal populations, both for disease prevention and for treatment. One example is a monoclonal antibody (MAb)based diagnostic test for brucellosis in cattle, a bacterial dis ease which often causes cows to abort pregnancies and which can infect farmers and people who drink milk from an infected cow. Brucellosis vaccines can protect animals from abortion but vaccinated cows can still carry the disease. The MAb test can distinguish between cattle that carry the brucellosis bacterium and those that have only been vaccinated, whereas con ventional tests cannot distinguish between the diseasecausing microbe and the vaccine. Several technologies are in use for animal breeding, including invitro fertilization (IVF) and embryo transfer. The latter is most frequently used in cattle to increase the production of off spring from cows with desirable traits (it is not cost effective as a means of increasing the size of average stocks). Embryo transfer is largely a traditional biotechnology, with the first successful use in 1890 in rabbits and the first use in cattle in 1949. It requires minimal training, with ranchers being able to use this technology without expert assistance. However, embryo transfer can be combined with more modern biotechnologies to improve outcomes or efficiencies. For example, it can be used with sex selection technologies to improve output of a more economically valuable sex, or combined with embryo bisection to further increase the Consequences, opportunities and challenges of modern biotechnology for Europe Final Report/Deliverable 3 Page 31 of 172

number of offspring. In the future, embryo transfer could be combined with nuclear trans plantation to produce clones, if technical difficulties with cloning are solved. Embryo transfer, by producing multiple offspring, can also be used to identify genetically inferior breed stock 70 . Animal applications of biotechnology are highly relevant to the EU, due to the economic im portance of animal husbandry in European agriculture. These applications provide potentially substantial savings in feed inputs and in healthcare and stock management costs, particularly in intensive dairy, pork, and poultry production. Improved breeding programmes also offer benefits through an improvement in the quality of animal products. 3.3.2.2 Fisheries and aquaculture Three types of biotechnology are currently in use in fisheries and aquaculture: recombinant DNA biotechnology is used to develop GM varieties of fish for aquaculture, marker technology is used to improve breeding programmes in aquaculture, and DNA fingerprinting is used for the management of wild fish stocks (including traceability) 71 . The main applications are for faster growing fish species, controlling pests, and for fish stock management. Pharmaceutical production is a small area that is covered in section 3.2.4. GM methods have been used to increase growth rates and food conversion efficiency in At lantic salmon by inserting a Chinook salmon growth hormone gene that is switched on year round, thereby fostering growth yearround, rather than mainly in the summer. The variety, marketed as AquaAdvantage® salmon, can reduce marketable growth times by half. The product is not yet available within Europe or elsewhere as it is awaiting regulatory approval. A second major application is to increase the immunity of fish and shellfish to pests, such as bacteria and viruses. Research in this area has developed new GM strains of molluscs with improved disease resistance. DNA fingerprinting can also be used to identify fish diseases and parasites in farmed populations and distinguish between harmful and benign diseases. For example, oysters can be affected by diseases that are difficult to distinguish. Some cause high mortality rates and require the closure of the affected oyster farm, while others are rela tively harmless. DNA fingerprinting has several applications for the management of wild fish populations, such as distinguishing between different stocks of migrating fish. A fishery can be closed if an en dangered stock is discovered swimming with another stock. DNA fingerprinting can also be used to determine the factors that improve the survival success of wild species that are re leased from hatcheries. For instance, survival can vary by age, location, and conditions at time of release. There are several potential applications of biotechnology for European aquaculture, particu larly for salmon and molluscs (clams and oysters). The relevance of biotechnology for managing European wild fish stocks partly depends on the economic value of migratory fish stocks that are subject to mixing of different subpopulations. In this context, biotechnology applications also include traceability in terms of distinguishing between farmed and wildhar vested products and the prevention of illegal overfishing. 3.3.2.3 Insects The main use of biotechnology is to develop GM insects, or vectors carried by insects, for pest resistance and pest control. An exception is to develop an insecticide resistance honey bee. All products so far are in the research stage. Research on pest resistance includes breeding programmes to develop medflies (a serious tree fruit pest) that would reduce infes tation levels, either through maleonly strains or strains that pass along a fatal trait to de veloping offspring. Other research involves developing a symbiont of the vector of Pierce’s 70

rd

See Hasler JF. Factors influencing the success of embryo transfer in cattle, 23 World Buiatrics Congress, Quebec City, 2004; Betteridge KJ. A history of farm animal embryo transfer and some associated techniques. Animal Reproduction Sciences 79:203244, 2003. 71 Future Fish: Issues in Science and Regulation of Transgenic Fish, PEW Initiative on Food and Biotechnology, Washington DC, January 2003.


disease to kill the bacteria that cause Pierce’s disease in grapes, and developing GM bacteria to express proteins that block the transmission of rice stripe virus by planthoppers. The relevance within the EU of the application of biotechnology to insects is very high, par ticularly to develop methods of controlling insect pests or insectvectored pests for high value perennial crops such as vineyards and tree fruits and for highvalue horticultural crops. The use of GM insects as a method for controlling insect pests could be an environmentally bene ficial and low cost solution for pest management. 3.3.3

Crop production and forestry

Biotechnology has a large number of applications to both food and nonfood crops and con stitutes one of the largest areas of application of biotechnology to date. There are two main applications: MAS (marker assisted selection) to speed up conventional breeding pro grammes and the development of GM crops. MAS is probably used at this time by all Euro pean seed firms, based on expected adoption rates in 1999. 3.3.3.1 Crop production using genetic modification Globally, the visible commercial use of biotechnology in agriculture is dominated by the appli cation of GM technology to crops, with the use of MAS in conventional crops difficult to iden tify. This is largely due to first generation GM applications based on a single gene insertion that confers either herbicide resistance or pest resistance (Bt varieties). Almost all GM crop use is currently limited to four crop species; soybeans, maize, canola, and cotton. This is partly due to the combination of economic and technical factors. Given the high costs of developing GM varieties, seed firms concentrated their research on major global crops with few technical barriers to GM. These provided the greatest opportunities for earning a return on their investments. Gradually, the cost of GM has declined and the technical barriers to GM modification in other major crops such as rice and wheat have been overcome. Consequently, there are now GM varieties of wheat that should shortly be available and GM has been applied to small market crops such as papayas and some horticultural crops such as lettuce. There are six main types of GM crops: grains, horticulture and vines, oil crops, fruit trees, sugar beets, and nonfood crops (primarily cotton). Second generation GM crops based on improved product quality, or valueenhanced crops (VEC), are also commercially available in canola, carnations, peanuts, soybeans and sun flowers. They account for only a very small percentage of total GM crop acreage. The product quality characteristics that have attracted the most attention concern the characteristics of oils and fats. Other product quality characteristics that are in the research stage involve the iron or betacarotene content of rice, storage and ripening characteristics, and protein content. Many applications of biotechnology to crop production have commercial applications within the EU, particularly for sugar beet, wheat, rapeseed (Canola) and maize. Btmaize was grown in Europe in 2005 commercially in five countries (ES, FR, CZ, PT, DE), however on a very limited area corresponding to about 0.5 % of the total acreage. Soybeans and cotton are not as widely grown within the EU as in other countries such as the United States, South Ameri ca, and China. 3.3.3.2 Silviculture (forestry) Biotechnology applications to forestry (excluding orchard fruits) include the use of MAS and GM in breeding programmes, and micropropagation, particularly using somatic embryogene sis. Most biotechnology applications in tree breeding are still in the research stage and limited to identifying markers or sequencing the genome of a few genera such as populus (aspen and poplar), pinus (pine), eucalyptus and picea (spruce). Compared to breeding programmes for crop plants, tree breeding is in a very early stage, with all plantation trees for wood and fibre largely based on wild varieties. The only commercial GM tree plantation is in China. Research Consequences, opportunities and challenges of modern biotechnology for Europe Final Report/Deliverable 3 Page 33 of 172

on GM trees covers herbicide tolerance, resistance to drought and stress, wood lignin con tent, and pesticide resistance. A potential application of biotechnology in silviculture is to create pest resistance in important wood and fibre tree varieties (pine) and in ornamentals and street trees (elms, chestnuts, California oaks) that have been damaged by introduced pests. For example, the gene coding for Bt has been experimentally introduced into poplar varieties to control leafeating insects. Faster growing species is an important goal, but so far GM for this purpose is in the early ex perimental stages and based on higher efficiency of nitrogen assimilation and modification of gibberellins synthesis. A major use of wood is in paper production and as a source of energy. Biotechnology can potentially reduce costs by producing varieties with modified lignin that is more suitable for paper manufacture, or types of wood that are suited for specialty papers, such as for high quality colour printing. An alternative is to reduce paper costs (both economic and environ mental) by developing better ligninolytic enzymes to break down lignin. For bioenergy, high lignin tree varieties are preferred as they produce more energy per unit weight. Micropropagation covers in vitro methods of vegetative multiplication of large numbers of clones through root cuttings, organogenesis, and somatic embryogenesis. Root cutting tech niques are widely used for angiosperms (broadleaf trees) but are commonly viewed as part of modern biotechnology. It is more difficult to use this technique for conifers, where somatic embryogenesis (SE) has attracted a lot of research attention, although not all technical prob lems have been solved. A major potential use of SE (with or without MAS) is to speed up tree breeding programmes. Tree varieties often need to be grown for six or more years before it is known if desirable traits are expressed, resulting in 15 to 20 years to develop a new variety, compared to about 8 years for an annual crop plant. At six years of age, the tree is too old for use in vegetative propagation. Different varieties developed by SE can be both grown and some clones frozen. The clones for the successful varieties can then be thawed and propa gated, significantly reducing the time required for developing a new tree variety. The relevance of biotechnology to forestry within the EU is limited by several important eco nomic constraints. The main future growth area for wood and fibre is in the tropics and semi tropics, where biomass production is many times greater than in the temperate forest zones of the EU. As an example, one hectare of plantation in the tropics produces 40 cubic metres of wood per year, with a harvest age at six years. In contrast, a hectare of forest in Sweden produces 2 cubic metres per year with a harvestable age of 60 years. Not surprisingly, there is far greater interest in breeding new varieties of fastgrowing short rotation trees for wood and fibre in high growth tropical and subtropical zones. Second, Europe currently has a sur plus of wood, with annual removal only 60 % of annual growth. This reduces incentives to invest now in new plantations, although the balance should turn negative by 2050. The net result is that there has been very little private sector interest in using GM or MAS biotech nology to develop new wood and fibre tree varieties for temperate Europe. It is possible that once current temperate forests have been fully exploited, most production will shift to warmer countries. The main relevance of biotechnology to European silviculture is therefore for product quality rather than quantity and for pest resistance in ornamentals and street trees. 3.3.4

Molecular farming

Plants and animals can be modified to express complex molecules such as spider silk or pharmaceuticals for human and animal use. The most developed application is for pharma ceuticals, where there are three main uses: production of vaccines, diagnostics, and large molecule biopharmaceuticals. In most cases the pharmaceuticals need to be extracted from the plant or animal (such as from goat milk) in order to be useful. A possible exception is transgenic plants that produce vaccines that could be directly consumed by humans. Re search in this area is still in the laboratory stage. For diagnostics, researchers have produced transgenic tobacco plants that express the Hepatitis B core antigen. This antigen is used to screen blood for Hepatitis B. Corn, rice ca nola, tobacco, tilapia, and goats have been genetically modified to produce specific human Consequences, opportunities and challenges of modern biotechnology for Europe Final Report/Deliverable 3 Page 34 of 172

proteins with therapeutic benefits. Examples include the anticoagulant Hirudin, produced in transgenic canola, and human clotting factor VII, produced in the fish species tilapia. 3.3.5

Barriers for the application of biotechnology in the agro food sector

Animal applications of biotechnology within the EU faces serious ethical barriers, especially for GM animals for food uses (GM animals for molecular pharming is less controversial) and for GM supplements, particularly bST, and xenotransplantation. These raise ethical concerns about the impact of biotechnology on animal welfare and rights. Public acceptance of GM animals for food is likely to take much longer to achieve than public acceptance of GM crops. For the foreseeable future, the application of biotechnology to animal breeding is likely to be based on MAS rather than on GM technology. The main barriers to the adoption of biotechnology to European fisheries include environ mental, public health, and economic factors. The major environmental concern is the escape of GM fish from openwater pens into surrounding waters. This could reduce the genetic di versity of the wild population if the farmed fish mate with sexually compatible wild fish, or es caped transgenic fish could become an invasive species that replaces wild fish stocks. Public health concerns include accidental changes to the edibility of GM fish and other marine ani mals due to increases in allergens, toxins, or hormones due to the change in the genetic makeup. The main barriers for the application of GM technology to insects are environmental, techni cal, and economic. Because their additional traits remove some of the biological boundaries that differentiate them from their nonGM counterparts, GM insects could become agricultural or environmental pests. As an example, an insecticide resistant honeybee could be a disaster if the honeybee interbred with aggressive varieties of bees with little agricultural value and if resistance was to a broadspectrum of insecticides. The main technical barriers concern differences between laboratory results and field results, particularly because it is more difficult to control a field release of a GM insect than a GM plant. Consumer resistance to GM crops is the single largest barrier to the adoption of GM crops within Europe. There is no visible opposition to the use of MAS in plant breeding pro grammes, however. The main economic problem raised by consumer resistance is likely to be experienced by the dwindling number of small seed firms that lack subsidiaries in countries such as Argentina, the United States, China, or Canada where GM crops are widely grown. The larger European seed firms (BASF, Bayer, Syngenta, KWS and Limagrain) are less affected because they have extensive research and marketing operations in countries where GM crops are permitted. As long as CAP distorts farm gate prices and as long as the financial benefits of GM crops are low, there are unlikely to be significant economic effects of GM crops on the European agricultural sector. The main barriers to adoption of biotechnology to forestry concern gene flow and tritrophic effects, where GM forest plantations could have a negative impact on the food chain. Gene flow is of greater concern for some forestry species than in agriculture because of the size of forest plantations and the distance where wind spread pollen is viable 600 km for some pinus species. Another environmental concern has economic implications. New tree varieties are likely to be grown in large, monoculture plantations. An error, such as an unknown suscepti bility to a pathogen or an undesirable phenotypic trait, can lead to plantation failure, where the entire tree crop is lost or damaged. Depending on the harvest cycle, this can take many years to show up, increasing economic risk. As noted above, the main economic obstacle is that the future growth area for wood and fibre is in the tropics and semitropics, where biomass pro duction is many times greater than in the temperate forest zones of the EU. The barriers to ‘molecular pharming’ include concerns over biopharmaceuticals entering the food supply (a problem that could be avoided by not using food plants such as canola, corn or rice) and economic competition from alternative methods of producing large molecules. At this time, it is not clear which method of producing biopharmaceuticals will have a cost advantage over the long term. Consequences, opportunities and challenges of modern biotechnology for Europe Final Report/Deliverable 3 Page 35 of 172

Finally, many applications of biotechnology in agriculture, including both GM and nonGM biotechnologies, must compete with alternative technologies to achieve similar ends. Conse quently, a major barrier consists of competitive alternatives, such as the ability to develop conventional crop varieties with desirable traits at less cost than developing varieties using MAS or GM, or using feed additives instead of new varieties of feed crops to provide livestock with trace nutrients. 3.4 3.4.1

Biotechnology in industrial manufacturing, energy and environment Introduction

Industrial biotechnology uses biotechnological processes, mainly based on fermentation and biocatalysis (enzymatic processes), to produce a large variety of products. The distinction between traditional biotechnology and modern biotechnology is especially in this sector hard to make. Natural processes like fermentation are being improved, optimised by all kind of technologies, including new key biotechnologies. Nowadays fermentation has become a fully controlled and highly efficient and modern process; though it is still fermentation. The industrial biotechnological production chain starts with the raw materials. These are crops and/or organic byproducts from agricultural sources and households that are first converted into sugars. During the production process ‘green’ raw materials (or biomass) are converted by tailormade microorganisms, cell lines or isolated enzymes into the desired products: chemicals, biomaterials and biofuels. These are discussed in more detail in section 3.4.2. Enzymes are an important group of products of industrial biotechnology. A number of en zymes are directly available in consumer products such as detergents, but a large number of enzymes are used as biocatalysts in downstream industries. This is also part of the industrial biotechnology chain (see figure 3.1) and is discussed in section 3.4.3. The use of biotechnology in production as discussed in sections 3.4.2 and 3.4.3 can lead to cleaner production processes (less use of chemicals and raw materials, less emissions of chemicals including CO2) and higher energy efficiency. Except for these processintegrated clean biotechnologies, also the socalled ‘endofpipe’ use of biotechnology – i. e. bioreme diation is addressed in this chapter. The treatment of air, effluent gases, soil and land, wastewater and industrial effluents, solid wastes and the use of biosensors for bioremedia tion are presented in section 3.4.4. Biotechnology is often qualified as a sustainable alterna tive for chemical processes. Although, the chemical industry has been very successful in de veloping sustainable chemical solutions, the uptake of biotechnology has met some serious barriers; these are discussed in section 3.4.5.


Figure 3.1:

The Industrial Biotechnology Production Chain

Biomaterial (biopolymers, etc) Production and preparation of biofeed stocks (vegetable oils, sugars, etc)

Chemicals (enzymes, vitamins, acids, antibiotics, steroids etc)

Food and Feed

Textile and Consumers Pulp and Paper

Biofuels (bio ethanol, biodiesel)

Others

Specialised and supportive products and services (consultancy, instruments, software, recruitment, etc)

Source:

Enzing and Kern (2004) 72

3.4.2 Biotechnology for fuels, chemicals and materials 3.4.2.1 Biofuels Biodiesel and bioethanol are already on the market in a number of countries around the world, although in most cases tax credits are applied in order to achieve competitive market prices. Growth volumes of 9 to 10 % are expected the coming ten years due to the imple mentation of EU regulations. Biodiesel – an equivalent to petroleum distillate is derived from deesterification and methy lation of plant and animal oils and fats. New sources like algae are under investigation. Bio ethanol is mostly made from sugar cane, corn and other starch crops. Biogas or methane is produced by the fermentation of organic matter including manure, wastewater sludge, munici pal solid waste. Large research programs are running in order to develop highyield lowcost biofuel crops, to improve the capacity of bacteria to transform sugars to ethanol, to enhance ethanol tolerant microorganisms to speed up the fermentation process of sugars into ethanol, to develop effi cient and lowcost bioprocessing technology for ethanol recovery, and to degrade trace amounts of toxic organic compounds into harmless compounds. The advent of high through put genome mapping and microarray analysis of gene/protein expression has provided scien tific breakthroughs in the understanding in plant biotechnology, and of structure and function in plant systems for biofuels and chemicals production. A specific problem that has to be tackled deals with the plant cellulose. By weight, plants consist of 7080 % of cellulose (cell 72

Enzing, C.M. and S. Kern (2004): Industrial Biotechnology in the Netherlands. Economic Impact and Future Developments (in Dutch), Delft.


walls). It is very expensive (partly due to the cost of the enzymes used in this process) to make the plant cellulose especially the lignocellulose and hemicellulose available for fer mentation processes. Biotechnological research is currently developing cheaper enzymes and new bacterial strains in order to make the cellulose sugars better available. Bioconversion technologies are under development for the production of liquid fuels such as ethanol from synthetic gas. Synthetic gas is produced through partial oxidation of carbon containing materials and contains CO, H2 and CO2. Traditionally, wood was the main source of synthetic gas, but agricultural, municipal, and paper waste are now being used. Some types of biomass are also specially grown for this purpose. The application of biotechnology in the fuels sector also includes the microbial desulphurisa tion of fossil fuels. Sulphur has to be removed from fossil fuels because the combustion of sulphur molecules in coal and petroleum leads to the production of sulphur oxides, which have a very negative environmental impact. Through genetic and metabolic engineering, new microbial strains have been produced that have a desulphurisation activity 100 times higher than wild strains. Biotechnology is being used for recovering additional oils from inground crude oilformations. This includes the use of biosurfactants: bacteria injected in the crude oil formations secrete surfactants that solubilise oil that was not released in the initial pumping operation. Other applications of more traditional biotechnology are the decentral biogas powerplants and the application of bacteria for purifying oil and coal for more efficient power generation will not be addressed. 3.4.2.2 Chemicals Biotechnology is increasingly penetrating the chemical industry as some chemical processes are replaced by bioconversion processes (fermentation through microorganisms or cell lines) and as biocatalysts (enzymes) replace chemical catalysts. However, a large number of products of the chemical industry traditionally always have been produced through bioconver sion processes, including enzymes, antibiotics, amino acids, vitamins and fine chemicals such as chiral building blocks for the pharmaceutical industry 73 . The microorganisms (e. g. bacteria, moulds, fungi, and yeasts) or cell lines from animal or human origin that perform the bioconversion processes in the chemical industry can be con sidered as miniproduction plants based on the metabolism of the microorganism or cell. Re search is constantly focussed on improving these processes by upgrading the enzymes in volved in the metabolic reactions. The genomes of most industrial organisms that are used for a wide range of biotechnological production processes in the chemical industry have already been sequenced. Genomicsbased research strategies will lead to indepth knowledge of the microbial activity of these organisms. On the basis of this knowledge, genetic, protein and metabolic pathway engineering tools are and will be used to optimise the industrial organisms in order to achieve more efficient, cheaper production processes with higher yields and to develop production processes for new enzymes and other products. New enzymes can also be found in microorganisms that live in difficult environments (extre mophiles living in the deep sea, on geothermal vents, or on heavily polluted sites). As some of the features of the novel natural enzymes are undesired when removed from their natural habitats into the industrial context, engineers use the ‘directed evolution’ technique in combi nation with the ‘DNA shuffling’ technique for modifying the properties of natural enzymes or proteins in order to create desirable properties. Examples of production processes in the chemical industry in which one or more chemical production steps have been replaced by bioconversion steps and biocatalysis are the produc tion of Vitamin B2 (riboflavin) and of Cephalexin and Amoxicillin (both antibiotics). In the Vi tamin B2 production process, the eightstep chemical process has been replaced by a one step fermentation process (moulds and yeast are used). The 10step (bio)chemical synthesis process of Cephalexin has been replaced by a biotechnological process including fermenta 73

Gavrilescu, M. and Y. Chisti (2005): Biotechnology – a sustainable alternative for Chemical Industry. A research review paper. Biotechnology Advances 23, pp 471499.


tion and enzymatic reactions. The new allenzymatic production process of Amoxicillin has replaced a partly chemical synthesis process that created problems (colouring of product) 74 . A somewhat different application of bioconversion in the chemical sector is the use of bacteria in the mining process of medium and highvalue chemicals, such as copper, zinc and cobalt. Bioleaching (with bacteria) and extraction from sulphide ores through biooxidation are being used in this sector. 3.4.2.3 Biobased polymers A separate category of chemicals consists of biomaterials. This includes the production of bioplastics from starch (corn, potatoes). Biotechnology research is focussed on the develop ment of new metabolic pathways in microorganisms that produce polymers or polymer building blocks with specific characteristics. Cahill and Scapolo (1999) 75 expect that in 2010 10 to 20 % of the world production of chemical materials will be replaced by biomaterials. However, a more recent study states that the future markets share of biobased polymers in Europe will stay relatively small: 1 to 4 % in 2020 (IPTS, 2004) 76 . Polylactic acids (PLA) have been synthesised for more then 150 years from biomass, but it had some major disadvantages: unstable under humid conditions. In 2002, a bioconversion process using a bacterium was developed that converted corn sugar into monolactic acid molecules. By heating these monolactic acid molecules, a biodegradable PLA for use in a large variety of plastics, including polyesters, was developed. The polymers are used for clothing, packaging materials and electronic goods. Other developments in this field include the development of fibres on the basis of 1,3pro panediol, with properties better than polyesters and nylon. A pilot plant for the production of 1,3propanediol will come into production in 2006. On the basis of a rational design strategy, eight genes (from yeast and from Klebsiella sp) were inserted into E.coli bacteria; additionally eighteen chromosomal genes were altered. In the final process glucose was converted through a number of steps into 1,3propanediol. Each step produces intermediate products (1,2propanediol, DHAP, DHA, glycerol, reuterin) that can also be used as intermediates for other products 77 . 3.4.3

Use of biocatalysts in down stream sectors

The enzymes produced by the chemical industry are used in consumer products and in in dustrial production processes in a number of down stream industries. The most important are food and feed, textile and leather, and pulp and paper. Enzymes are also used in the produc tion of intermediates for the pharmaceutical industry (see above) and on a much smaller scale in a number of other sectors, including the degreasing of galvanised metal 78 . 3.4.3.1 Food and feed industry Biotechnology is an important tool in the food industry and one of the most important are en zymes. Enzymes in food processing are used for enhancing processing characteristics (such as higher yields, more specific conversions, shorter production cycles), enhancing product characteristics (flavour and colour) and enhancing product qualities (better digestibility). The most commonly used enzymes in food production are amylases (hydrolyses of starch), prote ases (processing of cheese and meat), pectinases (clarification of juices), lipases (modifica tion of fats) and glucose isomerase (production of fructose). The latter represents the most important in terms of volume and is used in the production of High Fructose Corn Syrup 74

OECD (2001): The Application of Biotechnology to Industrial Sustainability, Paris. Cahill, E., Scapolo, F. (1999) Technology Map, Futures Report Series 11, EUR19031EN, Dec 1999. Published online at: http://futures.jrc.es/menupageb.htm 76 IPTS (2005): Technoeconomic feasibility of largescale production of biobased polymers in Europe, EUJRC IPTS, Seville. 77 Sasson, A. (2005): Industrial and Environmental Biotechnology. Achievements, Prospects and Perceptions, UNU IAS Report. 78 For an overview see: IPTS (1998): Biocatalysis: state of the art in Europe, EUJRCIPTS Seville. 75


HFCS. Then there is also the use of enzymes for cheese making. Chymosin, or rennet, is the milk clotting enzyme used to make cheese. It was traditionally extracted from calf stomachs, but the gene for the enzyme was cloned in microbes so that it could be produced by fermen tation. The main food industries that use enzymes are the bakery sector, dairy industry, beer, wine and soft drinks industry, olive and edible oils industry, and the meat and fish sector. Enzymes are increasingly used to improve animal feed. They are used for the enhancement of general nutrient availability, for the degradation of nonstarch polysaccharides (found in cereals and vegetable proteins), for the increased availability of dietary energy in feed and for the improvement of nutrient availability of cellwall carbohydrates. 3.4.3.2 Textile and leather Biotechnology, in this case the use of enzymes, is becoming increasingly important in the tex tile and leather industry. Enzymes are used in the pretreatment of textiles (including desizing, degreasing, scouring and bleaching) and finishing (including biostoning of denim, bio polishing, fibre modification such as antifelting, depilling, improved dye uptake and sof tening). Such as pectinases and hemicellulases for removing pectins and hemicelluloses associated with flax; pectinases, hemicellulases, proteases and lipases for cleaning raw cotton; oxidoreductases and peroxidases for bleaching fibres; catalases for removing residual hydrogen peroxide associated with the fibre bleaching process, etc. The leather industry uses enzymes for soaking, bating (improve pliability), degreasing and enzymeassisted dehairing of skins. However, biotechnology also offers the opportunity to produce fibres with improved or novel features such as new breeds of genetically modified cotton that contains a bacterial gene that makes a polyester like substance. Other applications are the microbially based fermentation process for the production of fibres which is discussed in the biopolymer section 3.4.3.3 Pulp and paper Traditionally in this sector biotechnologies were mainly applied in the waste treatment pro cess. Nowadays cleaner production is achieved also by processintegrated water treatment using biologically treated process water. Application of enzymes in the pulp and paper indus try include biopulping, deinking, biobleaching, reduction of fibre coarseness, improving the drainage rate of water out of the pulp material, increasing paper density and smoothness, and improving the appearance of paper products. The application of enzymes contributes to better availability of wood raw material, savings in the consumption of white carbon, surface active chemicals and chlorine; and decreases in chemical costs, cleaning frequency and the number of stops. For the latter the microbial reduction of pitch (the extractives that cause negative effects in the paper making process) is carried out by microbes or by an enzymatic method (using lipases) on refined fibres before papermaking. The lipase treatment also allows for savings in the consumption of white carbon, surface active chemicals. 3.4.4

Bioremediation

Bioremediation consists of processes that use microorganisms or their enzymes to clean waste streams of industrial processes or contaminated sites from specific contaminants. Generally, bioremediation technologies can be classified as in situ or ex situ. In situ bioreme diation involves treating the contaminated material at the site while ex situ involves the removal of the contaminated material to be treated elsewhere. A specific application of biotechnology is the use of biosensors for in situ monitoring of bioremediation processes. The role of modern biotechnologies in bioremediation is rather small and can be found mainly in 79 biosensors .

79

BIO (2004): New Biotech Tools for a Cleaner Environment. Industrial Biotechnology for pollution prevention, Resource Conservation and Cost Reduction, Biotechnology Industry Organization, USA, OECD (1998)


3.3.4.1 Water Bioremediation technologies have to compete, on the basis of costbenefit analysis, with other technologies. They have proven to be the most attractive techniques for treatment of waste water containing the more common organic pollutants, and for domestic and industrial waste water. Biological treatment techniques include both anaerobic and aerobic treatment with mi croorganisms, depending on the type of water to be processed. Effective and controlled bio removal of nitrate and phosphate contamination from wastewater has become possible. 3.4.4.2 Air and effluent gases Bioremediation technologies that remove contaminants from air and effluent gases (odorous gases, toxic pollutants) primarily consist of biofiltration, followed by bioscrubbing and biotrick ling filtration. These techniques are widely applied, but compete with other technologies, as they are not able to treat all types and concentrations of pollutants. 3.4.4.3 Soil The use of biotechnologies in soil treatment is still rather limited. Land farming is the use of bacteria to clean in situ contaminated sites, with minimal disruption and the degradation of pollutants to harmless substances. Old industrial sites (former refineries, and gas works, petrol filing stations) can especially benefit from biotechnological treatment methods. 3.4.4.4 Solid waste Bioremediation is used in organic waste management in a large number of countries, but it is largely limited to wastes with a high proportion of organic materials. Other applications could be the detoxification of solid waste and digestion of waste with organic content (oil, solvents). 3.4.4.5 Biosensors Biosensors are used for continuous and in situ applications in bioremediation processes, but also in groundwater surveillance. They monitoring contaminated organic media or process streams that contain mixed organic wastes. They measure the interaction of pollutants with biological systems through a biomolecular recognition capability attached to a signal trans ducer. The sensing element can be enzymes, antibodies (as in immunosensors), DNA, or (genetically modified) microorganisms. 3.4.5

Barriers for the application of biotechnology in industrial manufacturing, ener gy and environment

Cost of raw materials One of the main barriers in the first stages of the industrial biotechnology business chain is the price of raw materials. Sugars are currently the preferable renewable raw material for in dustrial bioprocesses, but sugar prices are relatively high, especially in Europe where they are kept high to protect European farmers from foreign competition. The competitive edge may come from tax credits, but also from government support for R&Dprogrammes that lead to new bioprocesses that use cheap feedstock, such as agricultural waste streams. The cost of producing biofuels has to compete with the lower cost of fossil fuels. The oil price has increased considerably in the last two years, which brings the break even point for bio fuels closer to the cost of fossil fuels. Because of the important contribution of biofuels in de creasing CO2 emissions, some governments have recently implemented tax credits and regulations to stimulate the use of biofuels.

Biotechnology for Clean Industrial Products and Processes, Paris and OECD (1994) Biotechnology for a Clean Environment. Prevention, Detection, Remediation, Paris.


Economic and environmental competitiveness of industrial bioprocesses The barriers that prevent an increased uptake of bioconversion processes in industrial pro cesses have been analysed thoroughly. This has been done from an economic perspective, through comparative costbenefit analysis of bioconversion technologies with competing chemical and physical technologies. Research has also included the public good benefits of bioconversion from its environmental advantages. These are due to lower operating tem peratures and pressures and biocatalysts are biodegradable, whereas inorganic catalysts are not. One of the main conclusions of these studies was that without external pressure, en vironmental improvements alone are unlikely to lead companies to change their production processes. Governmental legislation, for instance by offering financial incentives for improved sustainability, as is already the case in the use of biofuels, can be a main driver for this 80 change . Consumers’ acceptance of GM produced enzymes Consumers’ acceptance hardly plays a role in this sector as most products are inputs for pro duction processes, i. e. they operate in a businesstobusiness market. An exception is the use of enzymes in food production that are produced by genetically modified organisms. In the past, in some countries consumers and consumers organisations have expressed their resistance to this use of specific enzymes, for instance in cheese making. Also, the produc tion of food additives such as vitamins by GM organisms is a controversial topic for some consumers. A Commission supported survey of public attitudes in Europe showed that GM enzymes for the production of environmentally friendly soaps and detergents is seen as use ful and is supported by a majority of Europeans (France is an exception) 81 . Bioremediation As bioremediation takes place at the lowvalue, endofpipe part of the industrial production chain, fewer resources are available to develop bacteria or enzymes that have higher cleaning capacity or that can treat more substances then now is possible, for instance heavy metals or toxic substances. Government policies (regulations, taxes, R&D programmes) can provide incentives to increase the development and use of endofpipe biotechnologies. Sunk investments and sunk cultures A general barrier for all sectors covered in this chapter is that high investments have to be made in new biobased production facilities. Notwithstanding the promises of biotechnology as a cleaner technology, the sunk investments in existing processes are a serious barrier for the introduction of biobased processes. Introduction of biotechnology implies considerable investments in the building of new or pilot plants and equipment for treating waste water, soil or air. Optimisation of existing processes seems to be the main costsaving strategy. Another related barrier deals with the cultural differences between chemical and petrol based disciplines and biological disciplines. As most companies that use or can use bioconversion technologies are traditionally chemical companies or chemicalmechanical engineering com panies (in the case of remediation), it is difficult to persuade chemical engineers of the ad vantages of bioconversion techniques. So, not only sunk investments but also sunk ex periences and cultures work against the adoption of biobased principles in industrial produc tion processes 82 . This is one of the reasons why there is a lack of awareness within chemical companies of the pro’s and con’s of introducing biobased productions processes.

80

Ast, van J. et al (2004) Industrial Biotechnology Sustainable Tested. An investigation into the contribution of industrial applications of biotechnology to sustainable development (in Dutch), in order of the Dutch Ministry of Housing, Spatial Planning and the Environment, Den Haag. 81 Gaskell et al. (2003): Europeans and Biotechnology in 2002. Eurobarometer 58.0, A report to the EC Directorate General for Research from the project 'Life Sciences in European Society', Brussels. 82 Enzing, C.M., B.F. Filius and R. van der Meijden (1993): Midterm Evaluation of the Innovation Research Programme on Catalysis Research (in Dutch), TNOSTB, Apeldoorn.


4. Concept for elaborating indicators 4.1

General approach

The key objective of Task 1 is to identify appropriate indicators for assessing the conse quences of biotechnology applications in Europe. This requires a conceptual framework for differentiating biotechnology into several stages that can be measured through indicators. Figure 4.1 summarises these stages and identifies three main types of indicators. Figure 4.1:

Conceptual framework for biotechnology indicators Policy goals

impact

Products output Application fields

Services Processes

input

Biotechnology

The focus of the analysis is on identifying indicators that can capture the development, diffu sion and impacts of biotechnology in specific application fields. Therefore, indicators are classified into three main categories (figure 4.1). Input indicators describe capabilities and capacities in researching and developing biotech nologies. They include the necessary knowledge to develop biotechnology applications and to apply them in various economic sectors. Output indicators evaluate the extent of adoption and use of biotechnology products, services and processes within each application field. Impact indicators assess the economic, social and environmental impacts of modern biotech nology applications. Biotechnology inputs such as R&D can also directly affect policy goals, as indicated by the arrow on the right hand of figure 4.1, independently from its adoption by various industry sectors. The general approach to developing suitable indicators according to this framework com prises three steps: first, to describe the phenomena to be measured by each indicator cate gory; second, to propose suitable indicators for these phenomena; and third, to assess data availability and quality for the proposed indicators. This threestepprocedure is followed in chapters 5 to 9. 4.2

Generic, applicationgeneric, and applicationspecific indicators Consequences, opportunities and challenges of modern biotechnology for Europe Final Report/Deliverable 3 Page 43 of 172

In addition to the typology of input, output and impact indicators noted in figure 4.1, there are also generic, applicationgeneric, and applicationspecific indicators. Generic indicators use comparable numerators and denominators common to all applications. An example is total R&D spending on biotechnology, or the share of biotechnology patents out of all patents. Many generic indicators can also be created for specific applications (appli cationgeneric), such as total R&D spending in health biotechnology or biotechnology patents for industrial applications. Applicationspecific indicators are only available for a specific appli cation and have no equivalent for other applications. An example is the share of crop hec tares planted to GM varieties. Generic indicators are essential for assessing the main economic consequences of biotech nology. However, the focus on the consequences of biotechnology means that it is essential to be able to construct applicationgeneric and applicationspecific input, output and impact indicators. Applicationspecific indicators are required because many of the expected eco nomic and social benefits of biotechnology are due to conditions that cannot be generalized across sectors. The use of GM crops, for example, should reduce employment in the agro food chain whereas biotechnology applications in therapeutics could increase employment in the pharmaceutical sector. Many applicationspecific indicators are also of relevance to the social and environmental consequences of biotechnology. Table 4.1 gives examples of the types of biotechnology indicators used in this report. Of note, three of the nine cells are largely empty, with very few relevant indicators. Table 4.1:

Typology of biotechnology indicators with examples Generic

Inputs

Total biotechnology R&D/ total R&D 2

Outputs

Impacts

Applicationgeneric Total biotechnology health R&D / total bio technology R&D 2

Total valueadded of Total valueadded of biotechnology goods health biotechnology and services / total GDP goods and services / health sector value added

Applicationspecific 1

Hectares planted with GM maize / total hec tares planted with maize Number of DALYs gained per year from biotherapeutics per capita

1: There are few, if any inputs that are only application specific (financial inputs, researcher FTEs, publications, patents, etc). 2: Largely empty cells, as most outputs are applicationspecific. Two examples of generic output indicators are the number of biotechnology products on the market, which has very poor comparability across application fields, and the number of firms using at least one biotechnology in production.

4.3

Data evaluation

Four main criteria are used to evaluate data availability and comparability across countries or application fields: · Data coverage (share of countries and/or application fields for which data are available at a reasonable cost and effort) · Data source Consequences, opportunities and challenges of modern biotechnology for Europe Final Report/Deliverable 3 Page 44 of 172

· Definition (how biotechnology is defined) · Timeliness (latest available year, period covered) Data availability can be determined after the data gathering exercise by evaluating data avail ability by country or application field. An assessment of comparability requires information on the data source, definition, and timeliness. For all indicators, metadata 83 on these criteria need to be collected for each country. As an example, the metadata on business R&D expenditures would need to include, for each country, the source of the data, the definition of both biotechnology and a biotechnology firm, and the reference date for the indicator. All three characteristics can affect the comparability of data across countries. Of note, full comparability across countries is an unrealistic goal at this time. In most cases, data for the denominator for indicators will come from highly reliable, official sources, such as population data (per capita, working population, number of researchers). In a few cases data for the denominator will be obtained from a survey and will require meta data. An example is the indicator biotech revenues/total revenues. The data on total revenues of biotechnology firms will also come from a survey. Data source: The most reliable indicators are obtained from complete population data, such as for patents, field trials, or the number of biopharmaceuticals with marketing approval; followed by data from official national surveys based on samples (such as R&D data), data from public research groups and consortia 84 , and lastly from data from surveys run by con sulting firms 85 (number of core biotechnology firms or biotechnology venture capital). Wher ever possible, official national data and data from public research groups are preferred over data from consulting firms. However, some types of indicators are only available from con sulting firms or from a range of eclectic sources. Definition of biotechnology: The OECD listbased definition of biotechnology (see chap ter 2) has been adopted by several countries and will therefore improve comparability for these countries. Other definitions are also in use. For example, Japan includes traditional food fermentation in biotechnology, although the OECD listbased definition excludes this form of traditional biotechnology. An issue that is particularly relevant to biotechnology statistics is differences in the definition 86 of the population of ‘biotechnology’ firms, excluding public research organisations (PROs) . Three main definitions are in use: 1) all firms with some biotechnology activities, 2) dedicated or ‘core’ biotechnology firms where biotechnology is central to the firm’s activities or business strategies, and 3) small core or dedicated biotechnology firms with less than 250 or 500 em ployees (the size cutoff varies by country). The second and third definitions are more widely used than the first definition because of diffi culties in identifying the biotechnology activities of large firms. Studies based on the third definition of dedicated biotechnology firms usually assume that all employment or R&D is ‘biotechnology related’. This is already a heroic assumption for small firms, but it is completely untenable for large multinational firms for which biotechnology could be only a small part of 83

Metadata refers to all information on the data source, such as survey quality, plus other relevant information, such as differences in the wording of a survey question. 84 See for instance, Reiss et al. (2005), Enzing et al. (2005). 85 The main disadvantage of data from consulting firms is that the data provider rarely gives details on the size of surveys and response rates and the data sources. This makes it impossible to assess the quality of the data. In addition, consulting firms are usually in the business of promoting the biotechnology sector. This could be one reason why consulting firm estimates for employment or revenues are often higher than estimates obtained from official surveys. 86 A PRO is an organisation performing research of which the main source of funds comes from other public organisations, and which is in public ownership or control. Research organisations of officially recognised charities or foundations, which raise the majority of their funds from the general public, are also considered as PROs. (Definition from EU funded BioPolis project).


their total R&D, employment, or sales. For this reason, it is crucially important that metadata on the definition of biotechnology firms be collected with all data on biotechnology inputs (employment, R&D, revenues etc). Furthermore, input indicators for the business sector can only be compared across countries when based on the same definition of biotechnology firms. Reference date: Biotechnology is a rapidly changing field. Therefore, the latest available reference date for each indicator is very important and will influence comparability across countries. For example, biotechnology R&D data for 2000 in country x is unlikely to be com parable with biotechnology R&D data for 2003 for country y. In order to evaluate trends, in formation should also be collected on the number of years for which comparable data are available. Time series: Time series data are very useful for many purposes, such as determining the rate of adoption of biotechnology, extrapolating trends into the future, or evaluating changes over time in research fields (for instance using patent data). Consequently, information on time series data should be gathered. This includes the first year of data availability and infor mation on breaks in time series, such as a change in the definition of an indicator. Unfortu nately, many useful indicators, such as R&D investment, are only available for a few years, with frequent changes to the indicator definition. 4.4

Indicator construction

Constructing indicators first requires collecting statistics on biotechnology. A statistic is a simple data point, such as the number of biotechnology firms, or the total amount of public sector expenditures on biotechnology R&D. An indicator places a statistic in context, such as the share of all public R&D expenditures spent on biotechnology. Each statistic can be used to construct a number of indicators by varying the denominator. For example, a statistic on the number of biotechnology patents can be used to construct indicators for biotechnology patents per capita, per 1,000 researchers, or per 1,000 employees. Traditional science and technology indicators are based on national data. For example, data on business expenditures on R&D are obtained from national surveys of firms and patent data are based on an analysis of patent records by the nationality of the applicant or inventor. Similarly, national data sources are required for many biotechnology input indicators, such as for R&D, patenting, or revenues from the sales of biotechnology products. In contrast, many biotechnology indicators for outputs and impacts can be constructed from a mix of national and nonnational data sources (Arundel 2002 87 ). The latter can include oneoff surveys or the results of scientific studies in a single country. As an example, many large molecule biopharmaceuticals have been approved for the treat ment of orphan diseases, with evidence on efficacy or improvements in disability adjusted life years (DALY) based on a limited number of epidemiological studies in a few countries. This data can be combined with national estimates of the affected population to estimate the health benefits in terms of DALYs at the national level. It is also possible to estimate health benefits without national data on the size of the affected population by using data on disease prevalence rates in countries with a similar genetic population. A second example is to combine field study data on the effect of different types of GM crops on pesticide use, yields and farm income 88 with national level data on the number of hectares under cultivation with nonGM varieties of the same crop. In the absence of national data, the benefits (or costs) from switching to GM varieties can be estimated by assuming similar changes in pesticide use and yields as observed in other countries after nonGM varieties were replaced with GM varieties. 4.4.1

Composite indicators

87

Arundel, A. (2002): Agrobiotechnology, innovation and employment. Science and Public Policy 29: 297306. Brookes and Barfoot (2005a, 2005b) have summarized the results of studies on the effect of GM crops on pesticide use, farm incomes, and yields for four crops (soybeans, maize, cotton and canola) in the United States, Canada, South America, Mexico India, China, and Australia. 88


There are three main types of composite indicators. First, several composite indicators are constructed from aggregating data measured in the same units. National GDP is an excellent example. Given data availability, it might be possible to construct a composite indicator for total valueadded from biotechnology by adding estimates of biotechnology valueadded in each application area. This type of composite indicator is discussed in chapter 9. The second type of composite indicator evaluates data measured in different units. The classic example is costbenefit analysis, where the costs are measured in economic units but the benefits are measured in other units, such as DALYs (in health applications) or a reduc tion in tonnes of greenhouse gases (in environmental applications). Similar indicators are in cluded in chapter 6 on health applications of biotechnology and in chapter 7 on agricultural applications. The third type of composite indicator produces an index that summarizes a range of data measured in different units. These are widely used in comparing national performance across countries. For example, it would be possible to construct a ‘biotechnology impacts per formance index’ for the EU, the United States, and for other countries. The construction of these types of indicators is beyond the remit of this report. 4.5

Input indicators

To date, the majority of available biotechnology indicators cover inputs such as R&D invest ments, employees active in biotechnology firms, scientific publications, and patents. Patents measure inventions, but as many of these will never be directly commercialized, they are closer to an input than to an output measure. Input indicators can be grouped into the following categories: R&D, industryfirm knowledge transfer (a secondary R&D measure), knowledge transfer from universities (a secondary R&D measure), employment, education, venture capital, firm counts, publications, and patents (see chapter 5). Many of these are only available as generic indicators that aggregate across application fields. The number of employees active in biotechnology research is one of the best available input indicators, but it is often not completely available due to difficulties in obtaining employee counts from large firms. A widely used alternative is firm count data, but this suffers from poor comparability across countries, due to potentially large differences in average firm size. 4.6

Output and impact indicators

There are two classification issues: the boundary between input and output/impact indicators, and the boundary between output and impact indicators. A problem for defining the boundary between input and output indicators concerns biotech nology adoption. Indicators of the adoption of biotechnology research methods or capabilities in developing biotechnology uses are defined as input indicators. Conversely, indicators for the actual use of biotechnology to produce products or in production processes are defined as output indicators. The outputs and impacts of biotechnology are often closely linked and difficult to classify. Al most all useful (see footnote 2 to table 4.1) output statistics and indicators are application specific rather than generic. They include, at the national level, indicators such as the number of biopharmaceuticals developed by national firms, the percentage of all agricultural land planted with GM crops, and the percentage of paper produced using biotechnologybased processes. In industrial biotechnology, this could include indicators for the number of bioen zymes produced and, because these enzymes are used in downstream industries, the num ber of products of these industries. Generic impact indicators are based on employment, valueadded, or revenues that allow comparisons across application fields. They measure the economic impacts from the use of Consequences, opportunities and challenges of modern biotechnology for Europe Final Report/Deliverable 3 Page 47 of 172

biotechnology. Examples include the retail sales value of biopharmaceuticals, GM seeds, industrial bioenzymes, biodetergents, or bioremediation services. Many impact indicators for the benefits and costs of biotechnology for the environment and for the qualityoflife are application specific. Many of these can be transformed into generic indi cators with the same denominator, as when the environmental costs or benefits of a change in pesticide use, or the benefits of improved quality of life due to biopharmaceuticals, are assigned economic values. However, these types of indicators require intensive analysis and many assumptions that are often specific to particular countries and circumstances 89 , which defeats the purpose of developing internationally comparable indicators. The alternative is to develop firstlevel environmental and qualityoflife impact indicators that are sector specific. Examples include the effect of a GM versus nonGM crop on pesticide use (in toxic equivalents) per hectare, the share of national morbidity days treatable with bio pharmaceuticals, the additional DALYs due to biopharmaceuticals (either for diseasespecific treatment or for all biopharmaceuticals as a class), or the annual change in greenhouse gases from biofuels. Most output and impact indicators are not collected by national statistical offices 90 and will need to be developed using an eclectic range of data sources.

5. Input statistics and indicators The main inputs to the development of biotechnology products and processes include R&D investments, research collaboration, skilled employees, capital investment in new biotechnol ogy firms, including venture capital, and specialized knowledge, as measured by scientific publications, and patents. Patents also measure inventions, but as many of these will never be directly commercialized, they are closer to an input than to an output measure. Since most generic indicators are obtained from national surveys, it is a comparatively simple task to link them to a wide range of denominators. For this reason, this chapter focuses on the availability of biotechnology input statistics by country. For each statistic, it is possible to con struct several indicators using denominator data from publicly available sources such as the OECD MSTI database or Eurostat’s NewCronos database. For example, statistics on business expenditures on biotechnology R&D can be turned into indicators for the biotechnol ogy share of total business expenditures on R&D (using Eurostat data on total BERD), bio technology R&D expenditures per capita (using population data), or the share of all biotech nology R&D performed by businesses (using data on private sector R&D). Almost all available biotechnology input data are limited to generic indicators, with only a few applicationgeneric indicators available. The best coverage by country is for generic biotech nology inputs in the private sector. An example is the total number of firms with biotechnology activities. There are far fewer input statistics and indicators by field of application and very few input indicators for public sector activities. For both generic and applicationgeneric statistics, we evaluate the types of data available from four sources: 1. 2. 3. 4.

Business sector statistics from official surveys or reports. Public sector statistics from official surveys or reports. Database statistics (patents, publications, and citations). Consulting firm statistics (Ernst and Young reports, venture capital associations, etc).

Comparability is a serious problem for many of the input indicators derived from firm surveys, such as for employment and R&D investment, due to differences in how biotechnology is de fined and how a biotechnology firm is defined. For this reason, information on data sources for input indicators are given in this chapter in table 5.1 through table 5.3, along with a dis 89

For instance, the estimated value of one additional DALY depends on expected income levels and retirement ages, which vary by country, whether or not health care costs are covered by the state or the individual, etc. 90 An exception is Canada, where the Government collects data on revenues from biotechnology products.


cussion of the problems. (In contrast, the data sources for many application indicators identi fied in chapters 69 are given in an annex.) 5.1

Generic input statistics

In contrast to many applicationspecific indicators, generic indicators are largely available from a variety of national surveys, either from official sources or by consulting firms. To date, this information has not been assembled in one publication 91 , which makes it very difficult to determine sources, data availability and the latest year and time period. Due to the complexity of input data, detailed information for specific countries is given in tables 5.1 through 5.3. 5.1.1

Business sector statistics

Table 5.1 gives data availability for generic input statistics on the business sector, derived from official surveys or reports for 15 countries: four nonEU countries and eleven EU coun tries. The results are limited to statistics after 2001. Given the rapid rate of change in biotech nology, statistics from before 2001 will not be comparable with more recent statistics. The most recent national data are for 2003, with some countries reporting results for 2004. The indicators presented in table 5.1 are given without denominations because most of them are obvious (such as total number of firms, total R&D expenditure, total employment) and pro vided by official statistics. To the best of our knowledge, comparable national data are not available for fourteen EU countries: Austria, Czech Republic (some data should be available in 2006), Cyprus, Estonia, Greece, Hungary, Luxembourg, Latvia, Lithuania, Malta, Poland, Portugal, Slovakia, and Slo venia. The statistics for four countries, the UK, Ireland, Netherlands, and Spain, are from con sulting firms. Government surveys were conducted in 2004 in Ireland, Spain, and Poland, but the results were of very poor quality and therefore unusable 92 . There are few problems of comparability based on the definition of biotechnology. Eleven of the 14 countries use the OECD definition of biotechnology, three use another definition limited to modern biotechnology (OTM), and biotechnology is undefined in Spain and Sweden (UD), although in both cases the definition is likely to be limited to modern biotechnology. In most countries, biotechnology firms are also limited to those that perform biotechnology R&D and exclude equipment suppliers. An exception is Ireland, which includes both suppliers and firms that do not perform R&D. It is not clear if suppliers are included in the results for Spain. The German survey also provides separate data for equipment suppliers. There is greater variation in the definition of a biotechnology firm. A major comparability problem is between studies that are limited to dedicated or ‘ core’ biotechnology firms (DBFs), which are almost always limited to SMEs, and studies that include all firms with biotechnology activities, both DBFs and large firms (DBF + L). Seven countries obtain data from R&D sur veys that will capture all firms, of any size, that perform some R&D on biotechnology, while another seven countries use a range of data sources to identify both DBFs and large firms active in biotechnology. These results should be comparable. In contrast, the results for the UK, Finland (with the exception of the R&D statistics), and Sweden (which excludes large pharmaceutical firms) are mostly limited to DBFs. Comparisons of basic statistics on R&D and employment between these two groups will be unreliable, because the first group includes the activities of very large firms, while the latter will not. For example, table 5.1 shows that data on the number of R&D employees in biotech nology for Canada and the United States includes both employment by both DBFs and large firms, while the R&D employee results for the UK are limited to DBFs. This makes cross country comparisons between the UK and Canada and the United States unreliable, with the UK results underestimating R&D employment. In some countries, as in Spain, the R&D and 91

A forthcoming OECD publication will provide biotechnology indicators for the OECD member countries. Data for Japan are not comparable while there are no relevant data for Singapore and South Korea as of February th 20 , 2006 92


employment of a few large firms is several times greater than the combined R&D and em ployment of all DBFs, which highlights the size of potential comparability problems. The best data coverage is for the number of firms, the size distribution of firms, biotechnology R&D, biotechnology R&D employees, and total employment among biotechnology firms. When biotechnology employment data are missing (either R&D or biotechnology active em ployees), firm count data by size can be used to estimate total employment in biotech firms. Firm count data alone is not very useful because of differences in the average firm size. For example, the average American biotechnology firm has 1,100 employees, versus 18 em ployees in Denmark. The number of ‘biotechnology active’ employees, which includes research, production, mar keting, and other employees with biotechnologyrelated responsibilities, provides a measure of the impacts of biotechnology on employment. However, in most countries with data on both biotechnology active and biotechnology R&D employment, a substantial share of all biotech nology employees are involved in R&D. For this reason, the biotechnology employment data are better suited as an input indicator than as an output indicator, particularly because only a few countries collect data on biotechnology active employees. Five countries collect data on collaborative activities, particularly for R&D, but there is little consistency in the types of collaboration indicators across countries. There is very little data on the amount of capital raised, and slightly more on the contribution of venture capital (VC). Consequently, data on the ability of biotechnology firms, particularly DBFs, to raise capital must rely on venture capital associations. The main disadvantage is that this data does not give a measure of the importance of venture capital compared to other funding sources. The venture capital share of all capital raised was 13 % in Denmark, 22.5 % in Canada, and 44.5 % in the UK.


Table 5.1:

Business sector input indicators from government surveys (consulting firms when no official data)

Country

Latest year

Definition of: Biotech Biotech firm 10

Canada Switzerland 3 United States Iceland 4 Belgium Denmark Finland 2 France 7 Germany Italy 1,5 Ireland 8 Netherlands 1 Spain Sweden UK 1

2003 2003 2002 2004 2003 2003 2003 2003 2004 2003 2003 2005 2003 2003 2003

OECD 11 OECD OECD OECD OECD OECD OECD OECD OECD OECD 12 OTM OTM UD 13 UD OTM

DBFs + L R&D DBFs + L R&D DBFs + L R&D DBFs + (L) R&D DBFs R&D DBFs + L 9 DBFs (+L) DBFs + L DBFs + (L) DBFs

# Firms

# Total Firms R&D by size

ü

ü

ü

ü

ü

ü

ü ü ü ü ü

ü ü ü ü

ü ü ü

ü ü ü ü ü

ü ü

ü ü

Available indicators Biotech Employment Collabora Capital R&D tion raised $ Empl. Total empl. Biotech active empl. ü ü ü ü ü ü ü ü ü ü ü ü 6 ü ü ü ü ü ü ü ü ü ü ü ü ü ü ü ü ü ü ü ü ü ü ü ü ü

ü

ü ü

ü ü ü

ü

VC

ü ü ü

ü

ü

ü

1: Survey or data collection by a consulting firm. 2: Large Finnish firms are included for R&D data only, otherwise results limited to 181 DBFs with less than 250 employees. 3: Results for Switzerland are expected in Spring 2006, so it is not clear what data will be provided, other than total biotech R&D. 4: Results for Iceland should be available in spring 2006. 5: Onethird of the Irish firms are not active in R&D, but as the report combines data for Northern Ireland and the Republic of Ireland, we don’t know if this ratio holds for the Republic. Some results, such as firm counts, can be identified for the Republic of Ireland only. 6. Ernst and Young provides estimates for the United States. 7. Data for large firms active in biotechnology are provided separately. 8. Data were collected under the responsibility of BioPartner, an organisation set up by the Dutch Ministry of Economic Affairs, with a mission to set up 75 new DBFs in 5 years (20002004). The data were collected by the staff of BioPartner Network. 9. Data about large firms active in biotech (diversified firms) have been collected for 2002 only. 10: DBF = dedicated biotech (or ‘core’) firm, L = large firm, R&D = firm that performs biotech R&D, as identified in an R&D survey. All indicators in the row refer to the definition of the biotech firm. For example, ‘total employees’ for Canada refers to the total employees among biotech firms, defined as DBFs plus large firms active in biotechnology. For the UK, total employees only refers to employment in DBFs. For further details, see section 5.1.1. 11. OECD: OECD definition of biotechnology 12 OTM: Other definition of modern biotechnology 13. UD: Biotechnology undefined Consequences, opportunities and challenges of modern biotechnology for Europe Final Report/Deliverable 3 Page 51 of 172

Table 5.1 data sources: Canada Switzerland United States Iceland Belgium

Denmark

Finland

Canadian Trends in Biotechnology, biotech.gc.ca, 2005 France Van Beuzekom, B. Biotechnology in OECD Member Countries: An Germany inventory. STI Working Papers 2004/8, OECD, Paris. Survey of the use of biotechnology in US Industry, Dept of Italy Commerce, Nov 2003 Van Beuzekom, B. Biotechnology in OECD Member Countries: An Ireland inventory. STI Working Papers 2004/8, OECD, Paris. The biotech industry in Belgium: National Report to the OECD TIP Nether case study on biotechnology, April 2005 lands

Biotechnology in Denmark: A preliminary report, Carter Bloch, Spain Danish Centre for Studies in Research and Researcy Policy, Working Paper 2004/1, April 2004. Uses results of R&D survey and various sources on biotech firms. Hermans R, Kulvik M, Tahvanainen AJ. ETLA 2004 survey on the Sweden Finnish Biotechnology Industry. ETLA Discussion Paper 978, April 22, 2005 (ETLA); Biotechnology, Ch 13 in Science and Technol ogy in Finland 2004, Statistics Finland March 2005 (SF). UK

Unpublished preliminary data DE Statistics: Unternehmen der Biotechnologie in Deutschland, 2005 Van Beuzekom, B. Biotechnology in OECD Member Countries: An inventory. STI Working Papers 2004/8, OECD, Paris. InterTradeIreland. Mapping the BioIsland, Newry, 2005. The Netherlands Life Sciences Sector reports 2001, 2002, 2003, 2004, 2005 Enzing, C.M. and S. Kern (2004) Industrial Biotechnology in the Netherlands. Economic Impact and Future De velopments (in Dutch), in order of the Dutch Ministry of economic Affairs, TNOreport, STB0436, Delft., Enzing C.M., A.M. van der Giessen en S.J. Kern (2002) Life Sciences in Nederland: Economische betekenis, tech nologische trends en Scenario’s voor de Toekomst, TNO, Delft. Genoma Espana, Spanish biotechnology: Economic im pacts, trends and perspectives, June 2005.

VINNOVA, Nationella och regional klusterprofiler, 2004; Unpublished preliminary data

DTI, Comparative statistics for the UK, European and US biotechnology sectors, analysis year 2003. February 2005.


5.1.2

Public sector statistics

Table 5.2 summarizes the available data on public sector inputs for biotechnology. Data are only available for seven countries, including five EU Member States. Six of the seven countries collect ex penditure data on biotechnology R&D in the public sector. This can be combined with public data on total public sector R&D to produce an indicator on the share of all public sector R&D spent on biotech nology. This equals 12.6 % in Canada and 6.7 % in Finland. Only Spain and Denmark provide count data on the number of researchers in the public sector that are working in biotechnology. As an addi tional input measure the number of PhD graduates in biotechnology could be used. However, such data is only available for life sciences in general and not for biotechnology. The life sciences data are provided by the OECD Education database and covers most EU countries as well as the USA and Japan. Table 5.2:

Public sector input indicators

Canada

Biotech R&D

Public sector spinoffs

ü

ü

Biotech researchers

ü

United States Denmark

ü

Finland

ü

UK

ü ü

Spain 1

Sweden

Subsidies of private sector biotech R&D (US$)

ü ü ü

ü

(ü)

1: Higher education sector only. Table 5.2 data sources: Canada

Canadian Trends in Biotechnology, biotech.gc.ca, 2005

Denmark

Biotechnology in Denmark: A preliminary report, Carter Bloch, Danish Centre for Studies in Research and Researcy Policy, Working Paper 2004/1, April 2004

Finland

Science and Technology in Finland, 2004, p 280281

UK

Personal communication from Steve Churchill

Spain

Genoma Espana, Spanish biotechnology: Economic impacts, trends and perspec tives, June 2005

Sweden

Unpublished data

Canada and Finland also provide data on the number of biotechnology firms that were created as spinoffs from public universities or research institutes. This is a very good indicator for measuring the commercialisation of public research – one of the main goals of the Lisbon Council. A second measure of the contribution of public support for the commercialisation process is the amount of business R&D expenditures financed by the public sector (subsidies of private sector R&D). We have only found relevant data for this for Spain and the United States. Table 5.2 shows that coverage of public sector biotechnology activities is generally very poor. This is basically due to the fact that existing statistical systems are not designed to capture public sector in vestments in biotechnology, which would require a specialised survey. Budget allocations to public 93 94 sector R&D are divided into different fields of science categories using 13 NABS categories, but these do not contain enough detail to separate out biotechnology R&D within each of many different categories that contribute to biotechnology.

93

Part of government budget appropriations or outlays for R&D (GBOARD), which can include both funding of private sector and public sector research. 94 Nomenclature for the analysis and comparison of scientific programmes and budgets.


In 2006 the results of the BioPolis project will be published 95 . The report will include public expendi tures on biotechnology research, technology transfer and commercialisation for all 25 EU Member States, four candidate countries and Iceland, Norway and Switzerland, through government programs (dedicated biotechnology programmes and general programmes that also address biotechnology). Expenditures will be broken down by main subareas of biotechnology (including plant biotechnology, animal biotechnology, healthrelated biotechnology and industrial biotechnology). Data will be pro vided for the period 20022005. 5.1.3

Database statistics

Public and private databases provide statistics on biotechnology patents and bibliometrics (publica tions and citations to publications). Patent data are available free of charge from the EPO, the USPTO, and other jurisdictions. Bibliometric data are available, usually at a fee, from private firms, such as the ISI database, managed by Thomson. The OECD publishes data on biotechnology patents in its Main Science and Technology Indicators (MSTI) series. The most recent data includes biotechnology patent applications at the EPO for 2001 and patent grants at the USPTO for 1999. Both are becoming increasingly outofdate, although they should be updated in the Spring of 2006. The biotechnology patent counts are based on a validated list of patent classes that consist of a substantial proportion of biotechnology patents. Nevertheless, the classification system includes an unknown level of error, from biotechnology patents assigned to nonbiotechnology classes and from nonbiotechnology patents within the biotechnology classes. To the best of our knowledge, there are no regularly produced, comparable international bibliometric statistics. This work is usually done by academics or consultants on a oneoff basis 96 . The most common national indicators are the absolute number of biotechnology publications, the share of global publications, and the mean citation rate. Patents are more relevant than bibliometrics for research on the social and economic effects of bio technology because they measure activities that are closer to the market than publications. Biblio metric data, on the other hand, provide good information on scientific activities in biotechnology or re lated to biotechnology, thereby measuring an important facet of biotechnology capacities at the re search end. 5.1.4

Consulting firm statistics

As shown in table 5.1, the only available national statistics for several EU countries are from con sulting firms. In some cases, these reports are funded by government offices, such as the report for the UK. Ernst and Young (E&Y) provides near global coverage of biotechnology inputs, although not all results 97 are broken down to individual countries, but are combined into regions (Europe, AsiaPacific) . The main E&Y indicators cover the activities of "biotechnology firms" and include: revenues (plus net profit or loss by region), R&D expenses, number of employees, number of publiclytraded firms, number of privatelyowned firms, cash flow, and equity financing. There are two main disadvantages with using private consulting reports to measure biotechnology inputs: little or no information is given on sampling methods or how firms are identified, and the defini tion of a ‘biotechnology firm’ is unclear. In E&Y reports, a biotech firm is usually defined as a DBF with less than 500 employees. But, the biotechnology activity itself is undefined, which means that the firms could be included because they claim to be active in biotechnology.

95

Enzing, C.M. et al. (2006): Inventory and analysis of national public policies that stimulate research in life sciences and biotechnology, its exploitation and commercialisation by industry in Europe in the period 20022005. 96 Recent examples include Campbell et al., Scan of Canadian Strengths in Biotechnology, ScienceMatrix, Montreal, 2005, Genoma Espana for Spain; Reiss et al. Performance of European Member States in biotechnology, Science and Public Policy 31, 344358, 2004; and the ongoing EUBIOPOLIS project. This project aims at gathering public sectorspecific biotechnology R&D expenditure data for all Member States. We are in the process of determining if the NSF of the United States obtains comparable bibliometric statistics for biotechnology. 97 Ernst and Young (2005): Gaining Momentum.


As an illustration of the problems, the number of identified biotechnology firms in E&Y publications can differ substantially from official data. For instance, E&Y reports 278 biotechnology firms in France, 98 versus official statistics that identify 755 firms with R&D activities in biotechnology . These differences could have large impacts on the estimated amount of private sector biotechnology R&D, since the E&Y reports do not capture R&D spending in biotechnology by large firms or firms that do not report that biotechnology is their core business. For these reasons, E&Y reports (plus other consulting re ports using a similar methodology) provide a poor estimate of total biotechnology inputs and should only be used when official survey data are unavailable 99 . Venture capital associations such as EVCA in Europe provide data on biotechnology venture capital, but this is mixed with venture capital in health fields, so it is more accurately ‘health/biotechnology’ venture capital. The OECD’s 2005 Science, Technology and Industry Scoreboard gives results for many target countries for 2003. 5.2

Generic application statistics for inputs

Generic input statistics by application field are available from official data sources for the private and public sectors. Some statistics are also available from private consulting firms (not discussed here). To date, there are very few applicationgeneric statistics for patents and bibliometrics because of the diffi culties in determining the application for biotechnologies that are relevant to many different fields 100 , but it is possible to tailor patent and bibliometric analyses specifically to different applications. Such 101 work has been done or is underway by academic groups within specific research projects . 5.2.1

Business sector statistics

Table 5.3 replicates table 5.1 for generic input indicators that are available by application field 102 . Table 5.3:

Availability of business sector input indicators by application field. # of Firms

Canada Switzerland United States Belgium 1 Denmark Finland France 2 Italy Ireland Netherlands Spain Sweden UK

Total R&D expenditures

ü ü

ü

ü ü (ü) ü ü

Biotech R&D expenditures

Total employees

ü

Biotech R&D employees ü

ü ü

ü (ü)

ü

Biotech active employees

Capital raised ü

ü (ü)

(ü) ü

ü ü

ü ü

ü

Notes: see table 5.1 for definitions and sources. 1: Application fields in Belgium for R&D employees and biotech active employees limited to pharmaceutical/ non pharmaceutical. 2: Application fields in France limited to NACE sectors.

98

Other differences are as follows, with the E&Y estimate given first: Sweden (178 versus 154), Denmark (80 versus 267), Finland (69 versus 123), Belgium (70 versus 73). 99 This is not a criticism of E&Y reports, which are written to meet the needs of investors in biotechnology firms. These investors are largely interested in small DBFs and not in large firms with some biotechnology activities. 100 An exception is by King J and Schimmelpfennig D, Mergers, acquisitions and stocks of agricultural biotechnology intellectual property, AgBioForum 8:6388, 2005. They give the total number of USTPO agricultural patents between 19762000. 101 e. g. Reiss et al. (2004): Performance of European Member States in biotechnology, Science and Public Policy 31, 344358, 2004; and the ongoing EUBIOPOLIS project. 102 For the latest year, definitions, and source, see table 5.1.


Unless marked otherwise, all application data in table 5.3 are available for health, agrofood, and in dustrial fields. International comparability is generally good, although there are small variations in how each application is defined, particularly in agrofood. Some countries include silviculture and acqua culture in this field, while others do not. The main problem is that the number of internationally comparable input indicators by application field is limited, both by the number of countries for which such data are available and the number of indi cators that can be disaggregated by application. Two key input variables are employees and R&D, but these are not consistent across countries. In particular there are three different measures of R&D: total R&D in biotech firms, biotech R&D, and biotechnology R&D employment. None of these three indica tors are consistently available. The most consistent option is biotechnology R&D expenditures by application field, which is available for four countries. 5.2.2

Public sector generic input statistics by application field

Only Canada and Spain provide R&D expenditures in biotechnology in the public sector by field of application. No other disaggregated indicators are available for inputs. The BioPolis report to be published in early 2007, will also provide figures on public R&D spending through governments pro grams on the sectoral level (plant, animal, food, health, industrial, environmental). 5.3

Recommendations for future data collection

The availability of input indicators is almost inversely proportional to the value of the indicator for assessing inputs into biotechnology and potential outputs. Availability is greatest for basic firm counts, which is a highly misleading indicator, and lowest for biotechnology R&D investment and biotechnol ogy employment by field of application, which are possibly the two most useful indicators for inputs. With the exception of input indicators using patent or bibliometric data, all of these indicators are based on surveys of firms or public sector organisations and are consequently difficult, expensive, and timeconsuming to collect. It will therefore be necessary to focus future data gathering exercises on a few highvalue indicators. As part of this process, table 5.4 summarizes the strengths and weaknesses of 23 input indicators, in 7 categories, for evaluating inputs. The 23 indicators are drawn from both the examples of data sources given in tables 5.1, 5.2, and 5.3 and include additional indicators, for example on patents and bibliometrics. The most valuable indicators in table 5.4, and which should be included in a future survey of European biotechnology firms, are R&D expenditures in biotechnology and the number of employees active in biotechnology (the latter can also serve as an indicator for economic impacts). Of course, collecting these indicators should automatically provide other low value data, such as on firm counts. In both cases, the most useful data would be expenditures on biotechnology R&D and biotechnology active employment by field of application. Both can usually be estimated by the firm’s major area of biotech nology activity, rather than asking for a breakdown of biotechnology R&D or employment into specific fields. Data on total R&D or employment is only worth collecting if the survey also collects data on biotechnology R&D and biotechnology active employment.


Table 5.4:

Value of input indicators for assessing investments in biotechnology and future potential outputs

Description of indicator

Strengths & limitations

Value

Last year

Data Avail ability

Data Quality

Strengths: None, unless no other data on biotechnology activity is avail able. Limits: Large differences in how a biotechnology firm is defined, plus a highly misleading measure of impacts. Strengths: Gives an idea of commercial opportunities plus availability of start up capital. Limits: New firms and spinoffs could more closely reflect availability of risk capital than commercial opportunities. Strengths: Can estimate total employment. Limits: Crude estimate, cannot estimate biotechnology active employ ment.

VL

2003

H

M

L

L

L

L

2003

M

M

Strengths: Combined with biotech R&D, can estimate the share of firm research for biotech. Limits: By itself, without additional data on biotech R&D, it can be mis leading, but easy to collect. Strengths: Good indicator for private sector investment in biotech R&D. Limits: R&D is not a measure of potential outputs, long lag between re search and commercial results Strengths: Best indicator for private sector investment in biotech R&D. Limits: R&D is not a measure of potential outputs, long lag between re search and commercial results. Strengths: Good indicator for public sector investment in biotech re search. Limits: Very difficult to obtain from existing data collection methods. Strengths: Best indicator for private sector investment in biotech R&D. Limits: Extremely difficult to obtain from existing data collection methods. Needs detailed followthrough study to pinpoint specific technologies; long lag between research and commercial results.

H

2003

M

H

H

2003

H

M

M

2003

L

M

I

2003

L

M

I

2003

L

L

1. Firm counts 1a

Number of firms active in biotech nology.

1b

Number of spinoffs or recently created firms.

1c

Counts of firms by size.

2. R&D 2a

Total R&D by biotech firms.

2b

Biotech R&D by biotech firms.

2c

Biotech R&D by biotech firms by application field.

2d

Public sector investments in bio tech R&D.

2e

Public sector investments in bio tech R&D by application field

Table 5.4 continued Consequences, opportunities and challenges of modern biotechnology for Europe Final Report/Deliverable 3 Page 57 of 172



Value

Public sector subsidies of business Strengths: Measures dependence of firms on public support, particularly R&D. if there is a lack of private capital sources. Limits: Long way from commercialisation. 3. Employment

M

3a

Total biotech firm employment.

M

3b

Total biotech employment by application.

3c

PhD graduates in biotechnology, including by application field Biotech active employees

2f

3d

3e

Biotech active employees by application.

3f

New biotechnology active em ployee hires as a percentage of total hiring

Strengths: Combined with biotech employment, can estimate the share of firm effort in biotech. Limits: By itself, without additional data on biotech employment, it can be misleading, but easy to collect. Strengths: Combined with biotech employment, can estimate the share of firm effort in biotech and disaggregation by application provides better information on consequences. Limits: By itself, without additional data on biotech employment, it can be misleading, but more difficult to collect than disaggregated total em ployment. Strengths: Good indicator for capacity of the education system. Limits: Presently only available for life sciences, not for biotechnology. Strengths: Good indicator for employee inputs into biotechnology and can also serve as an impact measure. Limits: Requires careful question design to collect. Strengths: Best indicator for employee inputs into biotechnology and can also serve as an impact measure. Limits: Only feasible to collect if all employees in a firm are assigned to a specific application. Strengths: Medium term plans of the industry, especially when data available by sector. Limits: Need data on the expected job function of new hires, i. e. In re search, production etc.

Last year

Data Avail ability L

Data Quality

2003

H

M

H

2003

H

L

M

2004

H

H

H

2003

L

M

H

2003

L

L

M

L

L

L




Value

Last year

Data Avail ability

Data Quality

L

2004

M

L

M

M

L

M

M

L

Strengths: Measures ability of firms, particularly SMEs, to raise capital. Limits: To be useful, would need data on the purpose of the capital, i. e. for research or to take a product to the market.

LI

2003

L

L

Strengths: Intermediate measure between inputs in terms of R&D and outputs in terms of commercial inventions, also a measure of knowledge base in biotechnology and national research capabilities. Can be tailored specifically to application fields. Limits: Data will both over and underestimate biotechnology patents, probably the majority of biotechnology patents will never be commer cialised. Time lag in data availability. As above.

HNS

2002

H

H

HNS

2002

H

H

4. Collaboration 4a

Can refer to R&D, marketing, or other types of collaboration.

2c

Number of collaborations between large firms and DBFs by applica tion field. 2d Number of collaborations between large firms/DBFs and public re search organisations. 5. Capital raised 5a

Total capital raised in the previous year.

Strengths: Can serve as an indicator of knowledge inputs or of pre paredness for commercialisation. Limits: No consistency in how collaboration is defined. Strengths: Flow of knowledge between small and large firms, particularly useful if for late stage product development and marketing. Limits: Data quality, not all collaborations can be identified. Strengths: Flows of knowledge between public research sector and firms. Limits: Often far from commercialisation.

6. Patents 6a

Number of patents in defined bio technology patent classes.

6b

Number of patents by field of application.




Value

Last year

Data Avail ability

Data Quality

Strengths: Indicator for early stage research, also a measure of knowledge base in biotechnology and national research capabilities. Limits: Far from commercialisation. Strengths: As above, also early stage efficiency indicator. Limits: Far from commercialisation.

HNS

2004

M

H

HNS

2004

M

H

7. Bibliometrics 7a

7b

Number of biotechnology publica tions or citations to biotechnology publications. Biotechnology publications or cita tions by application field (per million inhabitants or thousand researchers)

Value: H = high, priority for future data collection, M = moderate, only worth collecting if existing availability is High or Moderate in order to complete data sets, L = low, VL = very low, I = data collection difficult so indicator value is impractical. Last year: Last year for which comparable data are available for several countries. Data availability: Complete = all countries covered in study; high = 10 or more countries, medium = 59 countries, low =