Economics of Biotechnology Home Page
THE ECONOMICS OF BIOTECHNOLOGY
1.0 Basic
Conditions
© Harry Hillman Chartrand
Compiler Press, 2008
Index
1.1.5 Substitutes & Compliments
1.2.1 Risk Taking, Cost-Benefit Analysis & the Precautionary Principle
1.2.4 Public & Private Infrastructure
1.0 Basic Conditions
Industrial Organization begins with the basic conditions of demand and supply facing an industry, the firms that supply its output and the consumers - final and intermediary - who buy that output. Supply and Demand constitute the two side of the economic equation. They will tend to remain in equilibrium with market clearing prices. If knocked out of equilibrium by a short-term fluctuation market forces will come into play driving the system back to this equilibrium. If government or some other power does not allow the market to find equilibrium then non-market forces come into play including an underground or 'black' economy.
1.1 Demand
Demand in economics refers to the willingness of a consumer to pay a given price for a given quantity of a good or service. Such willingness reflects the taste of the individual consumer, i.e., his or her wants, needs and desires subject to a budget constraint – income and prices – assuming the price of all other goods and services remain fixed. All things being equal the ‘Law of Demand’ is operative – the higher the price the lower the demand and the lower the price the greater the demand, i.e., there is a downward sloping demand curve.
At each price different consumers are willing to buy different quantities of the good or service but at that price the total demanded by all consumers can be calculated. The result is the ‘industry demand curve’. In effect individual consumers enter, participate or exit the industry depending upon price.
This assumes, however, that the good or service is ‘homogenous’, i.e., the output of firms is identical in the eyes of consumers. If they are not homogenous then the industry demand curve will consist of a series of distinct ‘market segments’ or ‘niches’. One critical question in the economics of biotechnology is whether or not consumers view goods and services produced using biotechnology as similar or different than similar goods produced using traditional methods of production.
This analysis applies, with qualifications, to both final consumers – the individual – and intermediate consumers or producers who buy goods and services as inputs in the production of final or consumer goods. Thus we distinguish between final and intermediate or producer demand.
In what follows I will first review the cultural and related constraints that lead final and intermediate consumers to distinguish between goods and services produced using biotechnology from those produced using traditional methods. I will then focus on and distinguish between these two forms of demand.
Consumer demand for biotech products remains limited. BIO in the U.S. lists only nine biotech-produced consumer products including detergent, bread, polyester bedding, vitamin B2, stonewashed jeans, paper bleaching, ethanol fuel, antibiotics and contact lens solution (BIO 2007).
These commodities, however, do not represent actual consumer demand but rather the application of biotechnology in the production of existing products. Thus biotech, to date, is a primarily a ‘process’ or ‘enabling’ technology (Research & Analysis 2000, 7) used by firms to generate new or improved inputs for producers of final or consumer goods and services, i.e., the results of biotech are ‘intermediary goods or services’ used by producers, not by final consumers.
This is, however, changing. For example, scientists at the National University of Singapore’s Department of Biological Sciences developed a zebra fish that glows in the presence of pollutants (NUS 2004). An American company realized that there was a consumer market for novelty glow-in-the-dark fish and now sells them as the first genetically modified pet (GloFish 2007). Similarly, clones of deceased pets including dogs and cats (National Geographic News 2004) are now being marketed. There is, however, to my knowledge, no current estimate of the value of such 'final' biotech consumer goods.
Beyond the 'newness' of biotechnology goods & services final demand by the individual consumer faces additional constraints including selective cultural resistance and what might be called 'calculatory' constraints. Such calculatory constraints - cost/benefit analysis or the precautionary principle - reflect the fact that biotechnology is the first major enabling technology to be subject to ex ante (before the fact) rather than ex poste (after the fact) assessment.
1.1.2
Culture refers inclusively to art, custom, economics, habits, language, law, life ways, religion, science and technology. All organically interact to historically create the Present as ‘an overlapping temporal gestalten” (Emery & Trist 1972). The economic implications of custom have been examined, for example, by German economist Ekkehart Schlicht (1998) who notes that custom exerts, in Alfred Marshall’s words, a “deep and controlling influence over the history of the world” (Schlicht 1998, 1).
For my part, since graduation, I have worked mainly in an obscure and only recently recognized sub-discipline, Cultural Economics. Classified as category ‘Z000’ by the American Economics Association, the ‘zoo’ engages the economics of the arts, religion, social norms and economic anthropology. Following Kenneth Boulding’s seminal article “Towards a Cultural Economics” (Boulding 1972), I practice what amounts to interdisciplinary study within economics itself, weaving together findings from agricultural economics, industrial organization, institutional economics, labour economics, legal economics, micro- and macro-economics and public finance, among others, as they relate to the Arts and culture generally. My ideological bottom line is that maximizing, i.e., economic, behaviour takes place within the context of culture and law. If you do not account for culture, you end up in the cannibal’s cooking pot; if you do not account for law, you end up in jail. Neither is a maximizing outcome. Put simply, culture counts!
Marshall is arguably the founder of the Standard Model of neo-classical market economics. He held, however, a much more subtle, complex and biological view of the economy. As with the work of many great economists including Adam Smith, some of Marshall’s work became part of the canon while other parts were forgotten. This includes his “emphasis on the contribution of knowledge to capital, the relationship between various forms of organisation and knowledge and the importance of ‘the tendency to variation’ in generating progress” (Loasby 1990).
Similarly, Canadian Marshall McLuhan answered the question why do we drive on the right-hand side of the road? The answer: Napoleon. Until then everyone drove on the left in order to keep one’s sword hand free to fight oncoming strangers. In his early military campaigns, however, Napoleon discovered that fresh troops going up to the front taunted those returning leading to fights. Often more troops were lost in such fratricidal combat that against the enemy. Accordingly he ordered everyone to drive on the right keeping their sword hands away from each other.
Everywhere Napoleon’s armies marched began to drive on the right. He did not reached England and accordingly they still drive on the left as they do in Japan (McLuhan & Fiore 1968). Similarly he did not reach Sweden where until the 1970s people continued to drive on the left. In the case of the British car industry this has had devastating economic effect. In Japan, of course, they developed a highly successful international trade in right-hand drive vehicles while continuing to drive on the left at home.
Passage and integration of new technologies through the living tissue of a society always face institutional, legal, moral and other inhibitions. In many cases new technologies have been rejected at great subsequent cost. Consider these three historical examples. First, the ancient Indus Valley culture (about 3,000 to 1,500 B.C.E.) rejected a new technology of war - the socket-headed axe - then fell under the blows of invaders who adopted it (Piggott 1950). Second, medieval China had gunpowder and transoceanic sailing ships but repressed them (Eckholm 2000) until European gunboats humiliated and partitioned the Middle Kingdom in the 19th century. Third, medieval Islamic medicine was the best of its time. But the human body, created in God's image, is, in Moslem tradition, a temple not to be violated. When surgery emerged as the next step in medical progress, Islam inhibited its use and rapidly fell behind the West. These societies succeeded in stopping change but at the price of decline and fall.
Biotechnology is similarly exposed to cultural resistance. Consider fetal tissue stem cell research. Sweden has embraced it; Britain regulates it; the United States rejects it; and, figuratively, Canada can’t make up its mind. Similarly genetically modified food stuffs have been accepted in North American but strongly resisted in the European Union. The fact that some forms of medical biotechnology are rejected in the United States which has accepted GM foods while the Europeans have accepted medical biotech but rejected GM foods illustrates the sectoral rather than global nature of resistance to biotechnology.
The source of resistance takes three primary forms – scientific, religious and the 'Veblen effect'. First, scientific resistance focuses on safety. Two principle techniques are used to estimate the safety of biotech products and processes - the cost-benefit and the precautionary principles (see 1.2.1 Risk Taking). Safety is assessed not only with respect to human health but also environmental impact on, for example, biodiversity.
Second, with respect to religion, consider the example of xenogenetic transplants of organs into human beings particularly from pigs. It is unlikely that Islamic or orthodox Jewish cultures will accept, let alone support, this line of genomic research. More generally the world’s three major monotheistic religions – Judaism, Christianity and Islam or ‘the People of the Book’ so-called by Islamic scholars – share, among other things, the First Book of Moses: Genesis. There is therein what has been interpreted by some as a general prohibition against tampering with the Tree of Life (Genesis 3.22 -24). In fact Adam and Eve were expelled from the Garden to stop them from reaching the Tree of Life which arguably today is represented by the DNA helix. (See my "Knowledge & Death: Return to the Garden", 2007
Third, the 'Veblen effect' refers to what is called 'conspicuous consumption', i.e., consumption based on raising social status. As DeGregori and Taverne have pointed out with respect to GM food, a class divide exists. There are those with wealth who argue in favour of 'organic' food even though scientific evidence clearly indicates that GM food is, in many ways, safer than 'natural' (DeGregori 2003; Taverne 2007). Then there are the poor of the world whose only long term hope for sustenance lays in a second 'Green Revolution' based on the superior yields and quality of GM food crops and animal produce. DeGregori links this effect to the upper class fetish for 'hand-made' or unique products such as works of art and crafts. Limited supply and uneven quality of such products is the opposite of what industrial biotechnology provides.
Nonetheless, whether for religious, cultural, economic or scientific reasons acceptance or rejection of a new technology always represents an opportunity cost. The long-run implications of such ‘cultural specialization’ can be significant for the competitiveness of nations.
1.1.4
Intermediate or Producer Demand
The major demand for biotechnology products and processes thus comes from producers who use them as inputs in production. In agriculture, for example, firms use biotechnology to produce new or improved seeds, e.g., herbicide-tolerant or insect-resistant seeds, for use by farmers. Thus demand is from farmers not final consumers. Similarly in the pharmaceutical industry, firms use biotech to produce new or improved drugs for use by doctors in treating patients, i.e., demand is generated by physicians as an input to a treatment regime for patients. Thus demand is from physicians not final consumers. Another example is a Canadian company that has genetically modified goats to produce spider silk in their milk. “Stronger and more flexible than steel, spider silk offers a lightweight alternative to carbon fibre” (BBC 2000).
The best estimate of overall demand for biotech products comes from the first comprehensive survey of the biotechnology industry in the United States conducted in 2003 (U.S. Department of Commerce 2003). The survey involved some 3,200 companies doing $US 272.8 billion worth of business, or 2.7 percent, of U.S. gross domestic product. Their biotech business lines accounted for $33.5 billion, or 0.33 percent of GDP. In Canada, what are called 'innovative biotechnology companies had sales of some $Cdn 3.8 billion (Canadian Trends in Biotechnology, 2005).
There are a number of measures used to determine growth in the biotechnology industry including growth in revenue, venture capital investment, patents, etc. For Canada. I direct your attention to the Government of Canada’s BioPortal and specifically to Canadian Trends in Biotechnology, 2nd edition, Government of Canada, 2005.
1.1.5
Substitutes & Compliments
Complements are goods or services that are used together. In consumption or production the marginal benefit of one is increased by use of the other. In consumption a hamburger and French fries are traditionally consider complements. In advertising the slogan ‘things go better with Coke’ catches the concept. More technically goods and services are complements if an increase in demand for one leads to an increase in demand for the other.
In production nuts and bolts are an example of complements. The effectiveness of a bolt, as a fastener, is increased significantly when a nut is applied and tightened. The elasticity of complementarity can be calculated, i.e., the change in demand for one to a one per cent increase in demand for the other.
By contrast, substitutes in consumption or production are goods and services that can be used as alternatives to one another. Thus in consumption hotdogs are traditionally considered substitutes for hamburgers. Similarly Coca Cola is a substitute for Pepsi Cola. And in production a nail can be considered a substitute for a bolt as a fastener. The elasticity of substitutability can be calculated, i.e., the change in demand for one to a one per cent increase in demand for the other.
For our purposes the question is the role of biotechnology in generating complements and substitutes for existing goods and services. An example of complementarity is genetically modified crops such as ‘Roundup Ready Canola’. Roundup is a herbicide produced by Monsanto. Its effectiveness in eliminating weeds and fostering higher yields is complemented when canola is genetically modified to resist the effects of Roundup. Thus the herbicide used in combination with genetically modified seed generates higher yields. An example of substitutability is found in household detergents where phosphorous was traditionally added as a brightener and cleaning agent. Today, due to environmental concerns about phosphorous, biotechnologically produced enzymes are used as a substitute (BIO 2007).
Beyond the question of the role of biotechnology in producing complements or substitutes for existing goods and services there is another question now being addressed by findings flowing from the Genomics Revolution. Stuart Kauffman, a noted molecular biologist/chemist, is critical of contemporary economics for its treatment of compliments and substitutes. Quite simply, the Standard Model offers no explanation for the emergence of compliments or substitutes or for the increasing diversity and complexity of new goods and services, e.g., the book versus the DVD player. More particularly it has no current theory of how economic and technological webs are produced:
There is a profound reason why economics has had a difficult time building a theory of the evolution of technological webs. They lack a theory of technological complementarity and substitutability without which no such web theory can be built… Economists call nut and bolt, ham and eggs, “complements”. That is, complements are goods and services which are used together for some purpose. Screw and nail are “substitutes”, each can replace the other for most purposes. But the growth of technological niches rests on which goods and services are complements and substitutes for one another. Thus, the introduction of the computer led to software companies because software and hardware are complements. Without a theory of which goods and services are complements and substitutes for one another, one cannot build a decent account of the way technological webs grow autocatalytically. (Kauffman 1990, 315)
Kauffman uses the classic example of the automobile replacing not just the horse but also the network of goods and services associated with it. He points out the new web of compliments that followed innovation or emergence of the automobile. These included paved roads, garages, gasoline stations, parking lots, car insurance, the drive-in, then the drive-thru, etc. Such ‘Kauffman webs’ are, at least in part, commensurate with Paul David’s “network externalities effects” in economics (David 1990, 356).
Kauffman’s work in genomics provides a series of alternative analytic techniques that may offer economics and business new ways of determining the webs produced by new complements and substitutes, e.g., the web of complements that has developed around the IPod. Thus noted economist Paul Romer is using some of these findings to study the evolution of technological webs.
The trick is to calculate, at each period, which of the goods currently produced, or now rendered possible by innovation based on the current goods, are produced in the next period and which current goods are no longer produced. This allows studies of avalanches of technological change. (Kauffman 1990, 314)
Supply in economics refer to the willingness of producers to provide a given quantity of output at a given price. Such willingness reflects the production function of each firm including available technology, the cost constraint of input prices and the price it can get for its output. All things being equal 'The Law of Supply' is operative, i.e., the higher the price the greater the supply, the lower the price lower the supply. There is therefore an upward sloping supply curve.
At each price different producers are willing to supply different quantities of the good or service but at any given price the total supplied by all producers can be calculated. The result is the ‘industry supply curve’. In effect individual firms enter, participate or exit the industry depending upon price.
This assumes, however, that the good or service is ‘homogenous’. If they are not homogenous then the industry supply curve will consist of a series of distinct ‘market segments’ or ‘niches’. One critical question in the economics of biotechnology is whether goods and services produced using biotechnology are similar or different than goods produced using traditional methods of production.
In what follows I will review some basic conditions of the supply of biotechnology goods and services. This will include the whether such goods are complements or substitutes for existing products; the role of instrumentation in the production of biotech goods and services; the source of knowledge that leads to new biotech products and the 'knowledge workers' involved in their invention and innovation; the public and private infrastructure that supports their production; the rate of growth in their production; and, the raw materials from which they are made.
1.2.1 Risk Taking, Cost-Benefit Analysis & the Precautionary Principle
The biotech industry with respect to 'business attitudes' is a risk-taking industry. This can be contrasted with risk-averting and 'actuarial' industries. These types are defined by reference to calculation of probability of loss times the cost of loss and the probability of gain times the magnitude of gain. In an actuarial industry the two are equated, i.e., only projects that provide at least equality will be undertaken. A risk-taking industry tends to minimize the probability and/or magnitude of loss and maximize those of gain. By contrast a risk-averting industry maximizes loss and minimizes gain. That biotech is a risk taking industry is demonstrated by the critical role played by venture capital, e.g., see Fierce Biotech.
Risk in biotech, however, involves not just private but also public choice by Governments. For example, in the case of GM foods consider the use of cost-benefit analysis in the Anglosphere versus application of the ‘precautionary principle’ in the European Union. In this regard it is important to note that unlike previous enabling technologies such as electricity or atomic power, biotechnology is being subjected to ex ante (before the fact) rather than ex poste (after the fact) public assessment. Cost-benefit analysis involves calculation of the probability and magnitude of costs and benefits associated with a new technology. If benefits outweigh probable costs it is allowed; if not it is rejected.
In the case of the ‘precautionary principle’ if a new technology has any chance of generating irreversible harm, no matter its short-term benefits, it is rejected (Environment Canada 2001). In fact, the precautionary principle is both an economic and a moral criterion. Thus while the scientific community is primarily concerned with generating new knowledge and producers are primarily concerned about efficiency and profits, consumers harbour deep-seated cultural and moral concerns about the manipulation of living things for human purposes. Living things have ‘natural purpose’ including the urge to survive and reproduce. This feeds the fear that genetically modified products may turn on their creator, e.g., as ‘frankenfoods’ referring to Mary Shelley’s 1818 book: Frankenstein; or, The Modern Prometheus. At least one observer has noted the insensitivity of producers even in press releases announcing new biotech products and processes that feeds this deep seated ‘value conflict’ of consumers (Katz 2001).
Since the beginning of Western civilization, logic has been accepted as the preferred path to knowledge (Dorter 1990, 37). It distances us from our passions; it frees us from the distracting world of sensation and emotion. In the hands of the Romans the Greek logos – logic - became ‘reason’ derived from the Latin ‘ratio’ as in to calculate (OED, reason, n 1). In this sense one can speak of ‘calculatory rationalism’. And from the Romans we derive Science from the Latin scire “to know” which, in turn, derives from scindere “to split” (MWO). Science today is accepted as the epitome of reason deriving knowledge by splitting or reducing a question into smaller and smaller parts or elements until a fundamental unit or force is revealed, e.g., Newton’s gravity.
Until innovation of the experimental instrumental scientific method in the 17th century, however, such splitting and reducing was restricted to words. The critical epistemological difference between ancient and modern Science, leaving aside for the moment mathematics, is the scientific instrument forcing Nature to reveal her secrets. Epistemologically Idhe calls this ‘instrumental realism’ (Idhe 1991). It is the design, development and operation of instruments of ever increasing sensitivity that has allowed humanity to pierce the veil of Nature, of appearances, and establish human dominion. Such instruments are not verbal constructs; they are tangible works of technological intelligence (tooled knowledge) that measure and manipulate Matter/Energy.
To the degree such instruments measure above and below the threshold of our natural senses, they realize a Platonic ideal: “belief in a realm of entities, access to which requires mental powers that transcend sense perception” (Fuller 2000, 69). Furthermore, the ‘language’ of what I call sensors [1] realizes the Pythagorean ideal by reporting Nature by the numbers.
With respect to production of new biotech knowledge, a contrast can be drawn between the capital cost requirements of biotechnology and high energy physics. In high energy physics, the rising cost and scale of equipment, e.g., synchrotrons and particle accelerators, required to generate new knowledge and test hypotheses increasingly limits experimentation and the generation of new knowledge. In biotechnology, by contrast, the cost of equipment, e.g., gene synthesizers, is relatively modest. The contrast may reflect the different stages of development of the science involved. Thus biotechnology is a relatively recent and revolutionary development (30 years old) while high energy physics is a well-established discipline dating back to the late 19th century.
In this regard, major information technology companies have made significant commitments (IBM to MDS Proteomics, Hitachi to Myriad Genetics, Compaq to Celera Genomics) in the belief that the huge data-crunching needs of nascent biotechnology firms will grow into a multi-billion dollar market for IT equipment and consulting services over the next decade (Reuters January 11, 2002). These developments also include joint ventures (e.g. Hitachi and DoubleTwist, Motorola and TissueInformatics Inc., to develop information processing hardware tailored to biotech research reflecting a belief that the next generation (Reuters January 16, 2002). This state of affairs may represent the beginning of a shift away from physics (especially nuclear physics and weapons production) as the most complex (and financially rewarding) information processing task towards biotechnology.
The current state of development of biotechnological instrumentation has been characterized as being from magic to art to science (Cambrosio & Keating 1988). This transition has been more recently documented by Hood (2002) with respect to experimental techniques or protocols. Such protocols generally begin as the unique personal & tacit knowledge of a single researcher. This is called ‘magic’ by Cambrosio & Keating in their study of hybridomass technology. Over time, this personal & tacit knowledge becomes embodied in an experimental piece of equipment, i.e., tooled knowledge. This stage they call ‘art’ because operation of the prototype requires a high level of tacit knowledge or skill. In turn, the prototype may be commercially transformed into a standardized instrument requiring less skill of its operator who, in effect, transforms from a scientist into technician (Rosenberg 1994, 257-258). This, according to Cambrosio & Keating, is the ‘science’ stage when the now standardized instrument can be routinely used in the ongoing search for new knowledge. The original protocol, however, becomes effectively embodied in the now standardized, calibrated scientific instrument. Put another way:
In the language of technology studies, these instruments “de-skill” the job of making these measurements. They do this by encapsulating in the instrument the skills previously employed by the analyst or their functional equivalents.” (Baird 2004, 69)
Focal knowledge about biotechnology is therefore a form of instrumental realism with machine-readings feeding iconic representation of results cum Heidegger (1938). The role of visual representation in Science should not be underestimated. Consider the “artificial revelation” (Price 1984, 9) provided by the telescope (macroscope) and microscope taking us beyond the ken of our mesoscopic native senses. As noted by Heidegger (1938), scientific ‘observation’ and ‘visual thinking’ [2] were born out of Renaissance perspective:
Observation, from the seventeenth century onward was a perceptible knowledge furnished with a series of systematically negative conditions. Hearsay is excluded, that goes without saying but so are taste and smell, because their lack of certainty and their variability render impossible any analysis into distinct elements that could be universally acceptable. The sense of touch is very narrowly limited to the designation of a few fairly evident distinctions (such as that between smooth and rough); which leaves sight with an almost exclusive privilege, being the sense by which we perceive extent and establish proof, and in consequence, the means to an analysis partes extra partes acceptable to everyone. (Foucault quoted in Idhe 1991, 41)
In my terms, tooled knowledge extends the human reach and grasp far beyond its natural limits. To see and touch such unseen, unreachable spaces our tools must go where no human can. They report back in numbers (digital) converted into graphic (analogue) representations – a form of codified knowledge – to be ‘read’ by the human eye. [3] Observation today involves, in effect, a cyborg-like relationship between a Natural Person and a machine, i.e., Instrumental Realism (Idhe 1991).
With respect to knowledge, Hans-Jorg
Rheinberger (1997), a molecular biologist and philosopher of biology, has
proposed that what scientists in fact discover using “experimental systems”
involving such instruments are not facts or truth but rather “epistemic
objects” whose meaning changes between experimental situations. In a
rather long but convincing quote he demonstrates his point with respect to the
term ‘gene’:
For a biophysicist working with a crystalline DNA fiber, a gene might be sufficiently characterized by a particular conformation of a DNA double helix. If asked, he or she might define a gene in terms of the atomic coordinates of a nucleic acid. For a biochemist working with isolated DNA in the test tube, genes might be sufficiently defined as stretches of nucleic acids exhibiting certain stereochemical features and sequence recognition patterns. The biochemist can reasonably try to give a macromolecular, DNA-based definition of the gene. For a molecular geneticist, genes might be defined as instructive elements of chromosomes that eventually give rise to defined functional or structural products: transfer RNAs, ribosomal RNAs, enzymes, and proteins serving other purposes. Molecular geneticists certainly will insist on considering issues in terms of replication, transcription, and translation and will require examination of the products of hereditary units when speaking of genes. For evolutionary molecular biologists, genes might be the products of mutating, reshuffling, duplicating, transposing, and rearranging bits of DNA within a complex chromosomal environment that has evolved through differential reproduction and selection. Therefore, they will rely on concepts such as transmission, lineage, and history. For developmental biologists, genes might be sufficiently described, on the one hand, as hierarchically ordered switches that, when turned on or off, induce differentiation, and on the other hand, as patches of instructions that are realized in synchrony through the action of these switches. Thus, developmental biologists are likely to refer to the regulatory aspect of genetic circuitry when defining a gene or a larger transcriptional unit such as an operon. We could go on and add more items to the list. (Rheinberger 1997, S248)
On the labour-side, in the past it was physicist and chemists (as well as engineers) who were most sought after by commercial enterprise. Today, however, the increasingly pervasive nature of biotechnology has created significant new employment and entrepreneurial opportunities for biological researchers and scientists (Zucker et al 1998). Audretsch and Stephan found that 50% of ‘scientific founders’ of new biotech pharmaceutical firms had followed a traditional academic career trajectory while only 12.5% had established their careers exclusively with large pharmaceutical companies like SmithKline or Beckman (Audretsch and Stephan 1999, 103). It is important to appreciate that such 'talent' is a rare and precious commodity to firms and its treatment is a matter of great concern. In addition there is the question of what is called 'tacit' and 'local' knowledge which cannot be easily transferred to another firm or agency (Cowan, David & Foray 2000).
Beyond increasing division & specialization of labour in the science of biotechnology, as suggested by Rheinberger above, a similar process is at work in the business of biotechnology. Mercer Human Resource Consultants identify almost 100 different occupational classifications in the biotechnology industry (Mercer 2007). As we will see below, under 2.0 Structure, such jobs are available in a number of distinct NAIC industries whose number, however, varying according to the analyst.
1.2.3 Public
& Private Infrastructure
Public and private infrastructure in biotechnology includes public, for-profit and non-profit institutions and organizations. These include: university departments and their undergraduate, graduate and post-graduate programs as well as their laboratories and semi-independent research centres; government departments, laboratories and research councils, for-profit companies and corporations together with their laboratories and research centres; non-profit foundations such as India’s Foundation for Biotechnology Awareness and Education; and, quasi-public/private grant-giving agencies such as Genome Canada. These widely varied components are increasingly organized into what is called the ‘National Innovation System’ (OECD 1997) to be examined under 2.0 Structure. To my knowledge, no comprehensive survey has been conducted on the public and private infrastructure supporting the biotechnology industry.
The raw material of biotechnology is the vast array of living things on planet Earth and the different proteins developed and coded by each in its evolutionary struggle for survival. There exists therefore a veritable cornucopia of possible protein codes that may be transferred from one organism to another and/or between types of organisms (transgenetic). Human ingenuity may also introduce novel variations not existing in nature. This implies the ability to adapt every evolutionary success of every life form on the planet to the benefit of humanity.
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[1] My term ‘sensor’ corresponds to Baird’s ‘measuring
instruments’ (Baird 2004).
[1] “This visualism is … an essential part of scientific (perceptual) praxis. Even more strongly, … such visualism within science occurs in gestalt and often intuitional ways with respect to insight. What may be called ‘visual thinking’ plays a much larger role than is recognized in most philosophy of science.” (Idhe 1991, 109)
[2] At the experimental level, both touch and smell are in the process of being codified to then be played back to a human ‘reader’.