Breaking the Code, PBS, Bruce Roe and Francis Collins talk to Ray Suarez, 1999
This interview provides a glimpse of the Human Genome Project, as it was happening.
It captures some of the excitement...
The determination of a DNA Sequence of a whole human chromosome is a tour de force. It provides the first view of a complete chromosome from a completely new vantage point. It's like seeing the surface or the landscape of a new planet for the first time.
... and shows how much things have changed since 1999.
Computers have been enormously helpful to this project. It's rather fortunate that the computer revolution and the genetics revolution are occurring in a nice dovetailed fashion, or we'd be having some trouble. But I will say for the real computer experts, they don't see our problems so far as all that demanding or challenging; even though it's a lot of information, it is fairly straightforward [so far].
Showing posts with label biotech. Show all posts
Showing posts with label biotech. Show all posts
Monday
Biotech/bioinformatics India overview
www.biospectrumindia.com
I just finished scanning a year's worth of BioSpectrum issues. Here's a quick overview (with a severe bias towards bioinformatics). For facts and figures, the magazine's BioData is a good resource.
India isn't among the big players yet in terms of biotech, though it does seem to be positioning itself for a leading role in bioinformatics thanks to its strong IT sector. Nevertheless, there is much excitement about biotech taking off, founded not just on euphoria, but on the availability of natural resources (diverse gene pool and ecosystems) and scientific talent, a pharma sector that is moving from manufacturing generic drugs to drug discovery and providing services (e.g. contract research), a large domestic market for bioagri and traditional medicinal knowledge that provides a unique starting point for drug discovery. Of course there is also the cost advantage of conducting biotech in India rather than the United States.
So far vaccines seems to be the single largest biotech business, including exports (mainly WHO-driven) and development of new vaccines. Bioinformatics is a small business by comparison (one tenth the revenues of vaccines in 2002/2003), but the quickest growing one. However, given that the global market is smaller to begin with and that India is entering the market with proven IT competencies, chances are good for status as a global player. Analysts expect India to capture 5% of the global market by 2005. Another sector that relies on India's established reputation as a global player for ITES (IT enabled services) is the market for contract research opportunities (CRO).
In its early stages, bioinformatics was largely a software services business based on supplying custom-made code for foreign pharma and biotech firms. Increasingly, however, Indian bioinformatics firms are launching proprietary products. A growing niche could be internet applications: 'In contrast to the accelerated growth that the internet has experienced, companies in the biotech sector have just begun to utilize the variety of internet applications available. Although maintaining a web presence and accessibility to research exists for these companies, the industry has relatively overlooked the possibilities of B2B commerce, ASP applications or the ubiquitous wireless domain,' says Aditya M Reddy, CEO of Hyderabad-based DeUS Infotech Private Ltd.
So far the main customer base (80% of data-driven drug discovery) is in the US, and to a small extent in Europe, Australia, Singapore and Japan. The domestic pharma and biotech industries are considered by many to be too young to represent a significant market yet.
Despite this, and Ernst & Young survey showed only 3 Indian cross-border alliances in biotech for 2002.
Industry insiders warn that the service business in biotech is limited and that, for India the real money is in discovering new drugs for ourselves and not in supplying information and data to foreign companies, who would then use this information to discover new molecules.
Various clusters are aggressively marketing their locations, e.g. Hyderabad (Genome Valley) and Bangalore (the biotech city).
The main bioinformatics players are Strand Genomics, CDC Linex, Bigtec, Institute of Bioinformatics, Jubilant Biosys, Ocimum Biosolutions, Mascon Life Sciences, Bilcare, Scinova, SysArris, Molecular Connections, and SERC.
The major software outsourcing companies, such as Infosys, Wipro Health Sciences (or Wipro Healthcare), TCS, Kshema Technologies, and Satyam Computer Services are also exploring opportunities. However, their strength seems to lie in providing management software for biotech and pharma companies (bio-IT), rather than specialized bioinformatics.
International players (in bioinformatics and bio-IT) are IBM/IBM India, Intel, Sun Microsystems, Oracle, and Cognizant Technologies.
I just finished scanning a year's worth of BioSpectrum issues. Here's a quick overview (with a severe bias towards bioinformatics). For facts and figures, the magazine's BioData is a good resource.
India isn't among the big players yet in terms of biotech, though it does seem to be positioning itself for a leading role in bioinformatics thanks to its strong IT sector. Nevertheless, there is much excitement about biotech taking off, founded not just on euphoria, but on the availability of natural resources (diverse gene pool and ecosystems) and scientific talent, a pharma sector that is moving from manufacturing generic drugs to drug discovery and providing services (e.g. contract research), a large domestic market for bioagri and traditional medicinal knowledge that provides a unique starting point for drug discovery. Of course there is also the cost advantage of conducting biotech in India rather than the United States.
So far vaccines seems to be the single largest biotech business, including exports (mainly WHO-driven) and development of new vaccines. Bioinformatics is a small business by comparison (one tenth the revenues of vaccines in 2002/2003), but the quickest growing one. However, given that the global market is smaller to begin with and that India is entering the market with proven IT competencies, chances are good for status as a global player. Analysts expect India to capture 5% of the global market by 2005. Another sector that relies on India's established reputation as a global player for ITES (IT enabled services) is the market for contract research opportunities (CRO).
In its early stages, bioinformatics was largely a software services business based on supplying custom-made code for foreign pharma and biotech firms. Increasingly, however, Indian bioinformatics firms are launching proprietary products. A growing niche could be internet applications: 'In contrast to the accelerated growth that the internet has experienced, companies in the biotech sector have just begun to utilize the variety of internet applications available. Although maintaining a web presence and accessibility to research exists for these companies, the industry has relatively overlooked the possibilities of B2B commerce, ASP applications or the ubiquitous wireless domain,' says Aditya M Reddy, CEO of Hyderabad-based DeUS Infotech Private Ltd.
So far the main customer base (80% of data-driven drug discovery) is in the US, and to a small extent in Europe, Australia, Singapore and Japan. The domestic pharma and biotech industries are considered by many to be too young to represent a significant market yet.
Despite this, and Ernst & Young survey showed only 3 Indian cross-border alliances in biotech for 2002.
Industry insiders warn that the service business in biotech is limited and that, for India the real money is in discovering new drugs for ourselves and not in supplying information and data to foreign companies, who would then use this information to discover new molecules.
Various clusters are aggressively marketing their locations, e.g. Hyderabad (Genome Valley) and Bangalore (the biotech city).
The main bioinformatics players are Strand Genomics, CDC Linex, Bigtec, Institute of Bioinformatics, Jubilant Biosys, Ocimum Biosolutions, Mascon Life Sciences, Bilcare, Scinova, SysArris, Molecular Connections, and SERC.
The major software outsourcing companies, such as Infosys, Wipro Health Sciences (or Wipro Healthcare), TCS, Kshema Technologies, and Satyam Computer Services are also exploring opportunities. However, their strength seems to lie in providing management software for biotech and pharma companies (bio-IT), rather than specialized bioinformatics.
International players (in bioinformatics and bio-IT) are IBM/IBM India, Intel, Sun Microsystems, Oracle, and Cognizant Technologies.
Sunday
Business ecosystems - perfect metaphor for the biotech industry
Strategy as Ecology, Marco Iansiti and Roy Levien, 2004
Another article from the March edition of HBR. Iansiti and Levien compare networks of suppliers, distributors, outsourcing firms, makers of related products or services, technology providers, etc. to ecosystems in nature. Certainly not a new concept for anyone who has read up on networks recently, but they carry the analogy further to derive business strategies and insights. An interesting read.
Like an individual species in a biological ecosystem, each member of a business ecosystem ultimately shares the fate of the network as a whole, regardless of that member’s apparent strength. From their earliest days, Wal-Mart and Microsoft—unlike companies that focus primarily on their internal capabilities—have realized this and pursued strategies that not only aggressively further their own interests but also promote their ecosystems’ overall health.
They have done this by creating “platforms”—services, tools, or technologies—that other members of the ecosystem can use to enhance their own performance. Wal-Mart’s procurement system offers its suppliers invaluable real-time information on customer demand and preferences, while providing the retailer with a significant cost advantage over its competitors. (For a breakdown of how Wal-Mart’s network strategy contributes to this advantage, see the exhibit “The Ecosystem Edge.”) Microsoft’s tools and technologies allow software companies to easily create programs for the widespread Windows operating system—programs that, in turn, provide Microsoft with a steady stream of new Windows applications. In both cases, these symbiotic relationships ultimately have benefited consumers—Wal-Mart’s got quality goods at lower prices, and Microsoft’s got a wide array of new computing features—and gave the firms’ ecosystems a collective advantage over competing networks.
Assessing Your Ecosystem’s Health
So what is a healthy business ecosystem? What are the indications that it will continue to create opportunities for each of its domains and for those who depend on it? There are three critical measures of health—for business as well as biological ecosystems.
Productivity. The most important measure of a biological ecosystem’s health is its ability to effectively convert nonbiological inputs, such as sunlight and mineral nutrients, into living outputs—populations of organisms, or biomass. The business equivalent is a network’s ability to consistently transform technology and other raw materials of innovation into lower costs and new products. There are a number of ways to measure this. A relatively simple one is return on invested capital.
Robustness. To provide durable benefits to the species that depend on it, a biological ecosystem must persist in the face of environmental changes. Similarly, a business ecosystem should be capable of surviving disruptions such as unforeseen technological change. The benefits are obvious: A company that is part of a robust ecosystem enjoys relative predictability, and the relationships among members of the ecosystem are buffered against external shocks. Perhaps the simplest, if crude, measure of robustness is the survival rates of ecosystem members, either over time or relative to comparable ecosystems.
Niche Creation. Robustness and productivity do not completely capture the character of a healthy biological ecosystem. The ecological literature indicates that it is also important these systems exhibit variety, the ability to support a diversity of species. There is something about the idea of diversity, in business as well as in biology, that suggests an ability to absorb external shocks and the potential for productive innovation. The best measure of this in a business context is the ecosystem’s capacity to increase meaningful diversity through the creation of valuable new functions, or niches. One way to assess niche creation is to look at the extent to which emerging technologies are actually being applied in the form of a variety of new businesses and products.
Considering the proposition that the biotech industry has entered a phase characterized by many small forms forming alliances/networks with each other, research institutes and pharma multinationals, the analogy seems particularly relevant.
Another article from the March edition of HBR. Iansiti and Levien compare networks of suppliers, distributors, outsourcing firms, makers of related products or services, technology providers, etc. to ecosystems in nature. Certainly not a new concept for anyone who has read up on networks recently, but they carry the analogy further to derive business strategies and insights. An interesting read.
Like an individual species in a biological ecosystem, each member of a business ecosystem ultimately shares the fate of the network as a whole, regardless of that member’s apparent strength. From their earliest days, Wal-Mart and Microsoft—unlike companies that focus primarily on their internal capabilities—have realized this and pursued strategies that not only aggressively further their own interests but also promote their ecosystems’ overall health.
They have done this by creating “platforms”—services, tools, or technologies—that other members of the ecosystem can use to enhance their own performance. Wal-Mart’s procurement system offers its suppliers invaluable real-time information on customer demand and preferences, while providing the retailer with a significant cost advantage over its competitors. (For a breakdown of how Wal-Mart’s network strategy contributes to this advantage, see the exhibit “The Ecosystem Edge.”) Microsoft’s tools and technologies allow software companies to easily create programs for the widespread Windows operating system—programs that, in turn, provide Microsoft with a steady stream of new Windows applications. In both cases, these symbiotic relationships ultimately have benefited consumers—Wal-Mart’s got quality goods at lower prices, and Microsoft’s got a wide array of new computing features—and gave the firms’ ecosystems a collective advantage over competing networks.
Assessing Your Ecosystem’s Health
So what is a healthy business ecosystem? What are the indications that it will continue to create opportunities for each of its domains and for those who depend on it? There are three critical measures of health—for business as well as biological ecosystems.
Productivity. The most important measure of a biological ecosystem’s health is its ability to effectively convert nonbiological inputs, such as sunlight and mineral nutrients, into living outputs—populations of organisms, or biomass. The business equivalent is a network’s ability to consistently transform technology and other raw materials of innovation into lower costs and new products. There are a number of ways to measure this. A relatively simple one is return on invested capital.
Robustness. To provide durable benefits to the species that depend on it, a biological ecosystem must persist in the face of environmental changes. Similarly, a business ecosystem should be capable of surviving disruptions such as unforeseen technological change. The benefits are obvious: A company that is part of a robust ecosystem enjoys relative predictability, and the relationships among members of the ecosystem are buffered against external shocks. Perhaps the simplest, if crude, measure of robustness is the survival rates of ecosystem members, either over time or relative to comparable ecosystems.
Niche Creation. Robustness and productivity do not completely capture the character of a healthy biological ecosystem. The ecological literature indicates that it is also important these systems exhibit variety, the ability to support a diversity of species. There is something about the idea of diversity, in business as well as in biology, that suggests an ability to absorb external shocks and the potential for productive innovation. The best measure of this in a business context is the ecosystem’s capacity to increase meaningful diversity through the creation of valuable new functions, or niches. One way to assess niche creation is to look at the extent to which emerging technologies are actually being applied in the form of a variety of new businesses and products.
Considering the proposition that the biotech industry has entered a phase characterized by many small forms forming alliances/networks with each other, research institutes and pharma multinationals, the analogy seems particularly relevant.
Saturday
On the European biotech sector
Why does the European biotech sector underperform? Mark Greener, 2004
In its December / January 2004 issue, Eurobusiness (now discontinued) carried a story on the worries of the European biotech sector.
While biotech in Europe shows impressive growth and success, it is definitely underperforming compared to the US industry. The main reason for this, according to Greener is a lack of venture capital.
The European biotech sector is younger and less mature than in the US. Companies are smaller - with market capitalizations that often fall short of investment funds' thresholds; their products are less developed and require more patience from investors; and there are few high-profile success stories yet to encourage vc's.
These drawbacks are exacerbated by risk-averse investors (much funding of European biotech ventures actually comes from US, not European, sources) and a lack of successful, co-ordinated stock exchanges. Most financing comes from partnerships with or acquisitions by large pharma firms.
Also, an aversion to GM food, a difficult regulatory environment, and a lower rate of entrepreneurship don't help.
The problem is, of course, that a lack of funds and success stories can stifle growth and reduce spending on new R&D, thereby endangering the future of the entire biotech - and by extension also pharma - industry.
An aside: There is a vc fund that has adapted it's venturing model to the European market. Instead of investing in 10 firms, hoping that one will be an overwhelming success, it's revenue model is based on, say, 5 out of those 10 companies delivering reasonably solid returns. Now if only I could remember the name of the vc fund and where I read about it...
In its December / January 2004 issue, Eurobusiness (now discontinued) carried a story on the worries of the European biotech sector.
While biotech in Europe shows impressive growth and success, it is definitely underperforming compared to the US industry. The main reason for this, according to Greener is a lack of venture capital.
The European biotech sector is younger and less mature than in the US. Companies are smaller - with market capitalizations that often fall short of investment funds' thresholds; their products are less developed and require more patience from investors; and there are few high-profile success stories yet to encourage vc's.
These drawbacks are exacerbated by risk-averse investors (much funding of European biotech ventures actually comes from US, not European, sources) and a lack of successful, co-ordinated stock exchanges. Most financing comes from partnerships with or acquisitions by large pharma firms.
Also, an aversion to GM food, a difficult regulatory environment, and a lower rate of entrepreneurship don't help.
The problem is, of course, that a lack of funds and success stories can stifle growth and reduce spending on new R&D, thereby endangering the future of the entire biotech - and by extension also pharma - industry.
An aside: There is a vc fund that has adapted it's venturing model to the European market. Instead of investing in 10 firms, hoping that one will be an overwhelming success, it's revenue model is based on, say, 5 out of those 10 companies delivering reasonably solid returns. Now if only I could remember the name of the vc fund and where I read about it...
Thursday
The Bioeconomy and what it means for regional economies
Prospects for a Bioeconomy: The Biomedical Industry and Economic Development, Cinda Herndon-King and Richard S. Seline, 2000
Without many too many facts to fall back on, I have proposed that hi-tech industry industries are moving away from a pure cluster model towards a 'network of competing and cooperating clusters.' This report backs me up as far as the biomedical industry is concerned. There's more on networks of innovation and regions collaborating to compete at the website of New Economy Strategies.
Cinda Herndon-King and Richard Seline analyzed 28 regions in the United States, with a special emphasis on the 4 most important clusters: Boston, San Diego, the Bay Area and Seattle. At the time the report was written, biotech was poised to pick up investments and momentum from the slacking internet bubble economy.
Herndon-King and Seline provide a comprehensive overview of the biomedical industry. They point out the enormous market potential of the health care industry in the U.S., mainly due to a population with a higher life expectancy that is aging overall. However, much of the potential also arises from the fact that genomic pharmaceuticals allow much more personalized healthcare and a much vaster scope of treatments - beginning with highly targeted preventive care.
They cite Mark Dibner and list 7 factors which distinguish the biomedical industry from other high tech sectors:
1. Financing: The start-up costs of business are high, and generally not financed by the entrepreneur
2. Reliance on research base: Most (55%) of biotechnology companies engage in activities which are in the research and development phase only.
3. Time to market: Typically, between five to twelve years is required. Return on investment for early investors is not based on product sales but from increasing valuation of the company, realized upon exit.
4. Regulatory environment: The cost of the the drug development and approval process is estimated at an average of $300 to $500 million per drug. The time required for approvals can be highly variable, and can often depend on factors outside the control of the submitting company.
5. Dependence on patent issues: Attracting investment requires a strong global intellectual property position.
6. Alliances and outsourcing: Due to the high costs of doing business, biotechnology firms extensively leverage outside skills, technology and capital through alliances. Reliance on academic innovation has emerged as the primary factor affecting biotechnology industry cluster devlopment.
7. Influence of public perception and environment.
Two major trends that form a recurring theme throughout the report are:
1. the interrelationship of tools and enabling technology with basic scientific discovery. The distinction between providing equipment or software and conducting basic research is blurred since so much discovery depends on the development of specialized or custom-made new tools.
2. the requirement for interdisciplinary approaches to biomedical research, bioinformatics being a case in point for both trends.
The authors go on to describe 2 phases of the industry:
The first wave business model centered on the 'full integrated pharmaceutical company' that licensed, financed, managed, and fought the federal regulatory labyrinth around (typically) a university patent or paper. This fully-integrated model housed the research, the testing, the manufaturing, and the distribution and sales for all aspects of bringing a drug or product to the market.
The second wave of the biotech industry is best defined by the reliance upon outsourcing and business networks rather than the integration model. Simply, the biotech and life science industry has found alliances, networks among researchers-vendors-suppliers, and a more concentrated and accelerated focus of both the science and the economics to be not just valuable but competitive propositions.
This has implications for regional economies that focus on biotech/biomed:
The Second Wave therefore is permeating regional strategies: proximity is no longer a value proposition in all elements of the lifecycle. Proximity to new ideas, to faculty, to research facilities promises greater innovation (defined as a social process among inputs of the science and outputs of entrepreneurial formation), but as firms mature the proximity demand within a region is challenged. Seattle for instance found in the late 1980s that no strategic marketing firms existed in their region and thus turned to Los Angeles and New York for assistance. Over a three year period, enough demand was created in Seattle that approximately 30 firms were established to serve the growing strategic marketing and sales requirements – many were outpost from Los Angeles and New York, others were home-grown. Currently San Diego has exceeded its manufacturing capacity – land is in short supply and costly; an initiative is underway to partner with border cities in Mexico and communities outside of California for non-essential manufacturing services.
There is a shift from self-contained regional clusters to specialized networked regions (see graph on page 44 of the report).
This is a reflection of changes in the industry itself as it moved from full vertical integration within one firm to a greater reliance on networks and alliances.
Proximity matters but not as it once did - like a fully-integrated company, regions believed that they must manage or control all aspects of the product cycle. With the determination that not every region has all the critical ingredients, more and more expectations arise for networking with other institutions, knowledge, talent and entrepreneurs beyond the local community. Proximity matters because innovation is a social process but not all aspects of the product testing and development must rely on the capacity to 'rub shoulders' with the testing, trials, and manufacturing aspects of the industry.
But the question remains: Which aspects require shoulder rubbing, and which don't?
Without many too many facts to fall back on, I have proposed that hi-tech industry industries are moving away from a pure cluster model towards a 'network of competing and cooperating clusters.' This report backs me up as far as the biomedical industry is concerned. There's more on networks of innovation and regions collaborating to compete at the website of New Economy Strategies.
Cinda Herndon-King and Richard Seline analyzed 28 regions in the United States, with a special emphasis on the 4 most important clusters: Boston, San Diego, the Bay Area and Seattle. At the time the report was written, biotech was poised to pick up investments and momentum from the slacking internet bubble economy.
Herndon-King and Seline provide a comprehensive overview of the biomedical industry. They point out the enormous market potential of the health care industry in the U.S., mainly due to a population with a higher life expectancy that is aging overall. However, much of the potential also arises from the fact that genomic pharmaceuticals allow much more personalized healthcare and a much vaster scope of treatments - beginning with highly targeted preventive care.
They cite Mark Dibner and list 7 factors which distinguish the biomedical industry from other high tech sectors:
1. Financing: The start-up costs of business are high, and generally not financed by the entrepreneur
2. Reliance on research base: Most (55%) of biotechnology companies engage in activities which are in the research and development phase only.
3. Time to market: Typically, between five to twelve years is required. Return on investment for early investors is not based on product sales but from increasing valuation of the company, realized upon exit.
4. Regulatory environment: The cost of the the drug development and approval process is estimated at an average of $300 to $500 million per drug. The time required for approvals can be highly variable, and can often depend on factors outside the control of the submitting company.
5. Dependence on patent issues: Attracting investment requires a strong global intellectual property position.
6. Alliances and outsourcing: Due to the high costs of doing business, biotechnology firms extensively leverage outside skills, technology and capital through alliances. Reliance on academic innovation has emerged as the primary factor affecting biotechnology industry cluster devlopment.
7. Influence of public perception and environment.
Two major trends that form a recurring theme throughout the report are:
1. the interrelationship of tools and enabling technology with basic scientific discovery. The distinction between providing equipment or software and conducting basic research is blurred since so much discovery depends on the development of specialized or custom-made new tools.
2. the requirement for interdisciplinary approaches to biomedical research, bioinformatics being a case in point for both trends.
The authors go on to describe 2 phases of the industry:
The first wave business model centered on the 'full integrated pharmaceutical company' that licensed, financed, managed, and fought the federal regulatory labyrinth around (typically) a university patent or paper. This fully-integrated model housed the research, the testing, the manufaturing, and the distribution and sales for all aspects of bringing a drug or product to the market.
The second wave of the biotech industry is best defined by the reliance upon outsourcing and business networks rather than the integration model. Simply, the biotech and life science industry has found alliances, networks among researchers-vendors-suppliers, and a more concentrated and accelerated focus of both the science and the economics to be not just valuable but competitive propositions.
This has implications for regional economies that focus on biotech/biomed:
The Second Wave therefore is permeating regional strategies: proximity is no longer a value proposition in all elements of the lifecycle. Proximity to new ideas, to faculty, to research facilities promises greater innovation (defined as a social process among inputs of the science and outputs of entrepreneurial formation), but as firms mature the proximity demand within a region is challenged. Seattle for instance found in the late 1980s that no strategic marketing firms existed in their region and thus turned to Los Angeles and New York for assistance. Over a three year period, enough demand was created in Seattle that approximately 30 firms were established to serve the growing strategic marketing and sales requirements – many were outpost from Los Angeles and New York, others were home-grown. Currently San Diego has exceeded its manufacturing capacity – land is in short supply and costly; an initiative is underway to partner with border cities in Mexico and communities outside of California for non-essential manufacturing services.
There is a shift from self-contained regional clusters to specialized networked regions (see graph on page 44 of the report).
This is a reflection of changes in the industry itself as it moved from full vertical integration within one firm to a greater reliance on networks and alliances.
Proximity matters but not as it once did - like a fully-integrated company, regions believed that they must manage or control all aspects of the product cycle. With the determination that not every region has all the critical ingredients, more and more expectations arise for networking with other institutions, knowledge, talent and entrepreneurs beyond the local community. Proximity matters because innovation is a social process but not all aspects of the product testing and development must rely on the capacity to 'rub shoulders' with the testing, trials, and manufacturing aspects of the industry.
But the question remains: Which aspects require shoulder rubbing, and which don't?
Sunday
Biotech knowledge and market exchange
Inter-institutional spillover effects in the commercialization of bioscience, Lynne Zucker, Michael Darby and Jeff Armstrong, ISSR Working Paper, vol. 6, no. 3, 1994.
In this study, Zucker, Darby and Armstrong lay out a proposition that partly contradicts a study on knowledge networks by Liebeskind et al. Both studies try to answer the question of how scientific knowledge flows into biotech firms.
Summary
Liebeskind et al. propose that firms source their knowledge through social networks to overcome the problems of market failure and inefficiencies involved in internalizing knowledge. On the other hand, Zucker et al. propose that there is a market exchange at work, especially for knowledge that is successfully commercialized. They work from the observation that much work in rDNA research is characterized by natural excludability, e.g. acquiring it requires working together with someone in a lab and/or a time-consuming effort to learn new skills. This results in intellectual capital for the discovering scientists. This intellectual capital diminishes as the new skills and knowledge diffuse throughout the industry. However, during an initial phase, companies that want to commercialize the intellectual capital must employ the services of the scientist who embody it. Scientists can be formally employed or hired as consultants. Links can also be less evident: full or partial ownership, membership in a scientific advisory board, etc.
Zucker, Darby and Armstrong find that formal affiliation or less formal links (joint publications and various forms of compensation) with 'star' scientists are a significant success factor for biotechnology enterprises. This, together with the presence of scientific and financial links, suggests that there is a market exchange at work.
Market or social network and hierarchy?
Which is true? Do biotech firms source their knowledge primarily through market exchange or primarily through social networks and the internal hierarchy?
Both seem to be relevant to some extent. Many of the market exchange mechanisms described above seem designed to bring a 'star' scientist within the firm boundaries, so that knowledge can then be transferred through the hierarchy. Social networks become relevant when scientific knowledge embodied in leading scientists is scarce and human mobility is limited (e.g. limits on the amount of time professors can spend consulting or formal full-time employment of scientists in a firm ). Where lack of mobility hinders market exchanges, social networks become more important. Also, Liebeskind et al. point out that it is very difficult for firms to evaluate newly available knowledge. Social networks play an important role in assessing knowledge before formal evaluations have ascertained its value or relevance to a specific firm.
Finally, social networks and market exchange are not entirely independent in this case. In both cases a great deal of trust is necessary for successful cooperation between a 'star' scientist and a biotech firm. This trust is probably established to a large degree through the social network: the norms and values of the scientific community provide a basis for cooperation; the reputation of the cooperating partners and initial informal contacts will likely be established through the network. A great deal of knowledge exchange mediated through the social network will probably precede a market exchange, which involves closer cooperation and knowledge, which has greater direct commercial benefits.
Apparently, the market only comes into play where factors such as tacitness and absorptive capacity reduce the market failure generally encountered in trading knowledge (Arrow).
Questions of location
Liebeskind et al. found that most successful partnerships involved a 'star' scientist who lived in the same region as the participating biotech enterprise was located. They mention that a few stars have been affiliated with NBEs (new biotechnology enterprises) outside California or published with NBEs outside of their region. Though they seem to be few cases, it would be interesting to see whether they were as successful as cases of local cooperation. Data may be available at the ISSR site...
New rules of work
A few days ago I wrote about Frances Cairncross's book 'The death of distance'. One of the chapters that I didn't mention dealt with new forms of work in the networked economy. Traditional lifetime employment has been disappearing for a long time now. In a continuation of this development, more and more people are engaging in non-traditional employment: freelancing, entrepreneurship, personnel "leasing" and many others.
Cairncross specifically mentioned that firms will pay a high premium for top talent, especially since the most highly qualified knowledge workers will be scarce and demand for them will be worldwide. 'Star' scientists fall squarely in this category. Zucker, Darby and Armstrong mention a study finding that bioscientists act as individual actors, as opposed to acting as agents of their primary ties, whether to the university or the firm (Zucker, Brewer, Oliver, and Liebeskind, 1993). These bioscientists can exercise their expertise independently primarily because they are recognized as having excellent "scientific taste" in the selection of rescues problems and using exceptional care and expertise in exuding that research. They use their 'scientific taste' to advise firms on the relative merit of different lines of research - certainly an example of intellectual capital that has characteristics of excludability, since this 'scientific taste' is highly tacit, embodied knowledge based to a large extent on personal experience.
In this study, Zucker, Darby and Armstrong lay out a proposition that partly contradicts a study on knowledge networks by Liebeskind et al. Both studies try to answer the question of how scientific knowledge flows into biotech firms.
Summary
Liebeskind et al. propose that firms source their knowledge through social networks to overcome the problems of market failure and inefficiencies involved in internalizing knowledge. On the other hand, Zucker et al. propose that there is a market exchange at work, especially for knowledge that is successfully commercialized. They work from the observation that much work in rDNA research is characterized by natural excludability, e.g. acquiring it requires working together with someone in a lab and/or a time-consuming effort to learn new skills. This results in intellectual capital for the discovering scientists. This intellectual capital diminishes as the new skills and knowledge diffuse throughout the industry. However, during an initial phase, companies that want to commercialize the intellectual capital must employ the services of the scientist who embody it. Scientists can be formally employed or hired as consultants. Links can also be less evident: full or partial ownership, membership in a scientific advisory board, etc.
Zucker, Darby and Armstrong find that formal affiliation or less formal links (joint publications and various forms of compensation) with 'star' scientists are a significant success factor for biotechnology enterprises. This, together with the presence of scientific and financial links, suggests that there is a market exchange at work.
Market or social network and hierarchy?
Which is true? Do biotech firms source their knowledge primarily through market exchange or primarily through social networks and the internal hierarchy?
Both seem to be relevant to some extent. Many of the market exchange mechanisms described above seem designed to bring a 'star' scientist within the firm boundaries, so that knowledge can then be transferred through the hierarchy. Social networks become relevant when scientific knowledge embodied in leading scientists is scarce and human mobility is limited (e.g. limits on the amount of time professors can spend consulting or formal full-time employment of scientists in a firm ). Where lack of mobility hinders market exchanges, social networks become more important. Also, Liebeskind et al. point out that it is very difficult for firms to evaluate newly available knowledge. Social networks play an important role in assessing knowledge before formal evaluations have ascertained its value or relevance to a specific firm.
Finally, social networks and market exchange are not entirely independent in this case. In both cases a great deal of trust is necessary for successful cooperation between a 'star' scientist and a biotech firm. This trust is probably established to a large degree through the social network: the norms and values of the scientific community provide a basis for cooperation; the reputation of the cooperating partners and initial informal contacts will likely be established through the network. A great deal of knowledge exchange mediated through the social network will probably precede a market exchange, which involves closer cooperation and knowledge, which has greater direct commercial benefits.
Apparently, the market only comes into play where factors such as tacitness and absorptive capacity reduce the market failure generally encountered in trading knowledge (Arrow).
Questions of location
Liebeskind et al. found that most successful partnerships involved a 'star' scientist who lived in the same region as the participating biotech enterprise was located. They mention that a few stars have been affiliated with NBEs (new biotechnology enterprises) outside California or published with NBEs outside of their region. Though they seem to be few cases, it would be interesting to see whether they were as successful as cases of local cooperation. Data may be available at the ISSR site...
New rules of work
A few days ago I wrote about Frances Cairncross's book 'The death of distance'. One of the chapters that I didn't mention dealt with new forms of work in the networked economy. Traditional lifetime employment has been disappearing for a long time now. In a continuation of this development, more and more people are engaging in non-traditional employment: freelancing, entrepreneurship, personnel "leasing" and many others.
Cairncross specifically mentioned that firms will pay a high premium for top talent, especially since the most highly qualified knowledge workers will be scarce and demand for them will be worldwide. 'Star' scientists fall squarely in this category. Zucker, Darby and Armstrong mention a study finding that bioscientists act as individual actors, as opposed to acting as agents of their primary ties, whether to the university or the firm (Zucker, Brewer, Oliver, and Liebeskind, 1993). These bioscientists can exercise their expertise independently primarily because they are recognized as having excellent "scientific taste" in the selection of rescues problems and using exceptional care and expertise in exuding that research. They use their 'scientific taste' to advise firms on the relative merit of different lines of research - certainly an example of intellectual capital that has characteristics of excludability, since this 'scientific taste' is highly tacit, embodied knowledge based to a large extent on personal experience.
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