Biotechnology - Genomic and Proteomics/Give an overall picture of the BGP field

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How was this field born and how is it evolving?

Timeline

  • 1953, Crick and Watson discover DNA at Stanford
  • 1973, rDNA (insertion of foreign gene between two ends of an existing gene) produced at Stanford (Acharya pp. 2)
  • 1970's and 1980's – proliferation of private biotech firms
    • 1971, Cetus founded
    • 1976, Genentech founded. First firm to use rDNA technology (Acharya pp. 4)
  • 1982, first rDNA product, human insulin, approved in US (Acharya pp. 4)
  • 1980's firms grow through heavy outside investment
    • easy financing for firms that chose to go public (Acharya pp. 2)
  • 1980's, outside US, pressure to subsidize public-private partnerships for Biotech research (Acharya pp. 3)
  • 1987, stock market crash and larger recession push small biotech firms to merge into larger multinational companies
    • 1990, Genentech merges with Hoffman LaRouch to become largest example of this new sort of firm (Acharya pp. 3)
    • 1993, only 14 biopharmaceutical companies record profits (Acharya pp. 5)
    • 1995, Glaxo-Wellcome merge, forming one of world's largest pharma companies


Causes and Culture

  • Biotech industry emerged from Bay area in 1960's
    • Stanford's biochemistry and virology (later molecular biology) departments expanded aggressively during this time (Penhoet pp. 6)
    • Bill Rutter, chairman of UCSF's Biochemistry and Biophysics department . His work ethic became the model for the industry (Penhoet pp. 7)
  • Herb Boyer, Bob Swanson start Genentech in the mid-1970's
    • first private biotech firm
    • later followed by Cetus, Chiron (Penhoet pp. 8)
  • Venture Capital firms already existed to support emerging Silicon Valley, came in to support Biotech ventures as well (Penhoet pp. 8)
  • Open attitude towards IP: belief early on that innovation would be sustained, so academics continued to publish their findings, even when working with private companies (Penhoet pp. 8-9)


Dynamics of the Biotech field defined by (Pisano pp. 82)

  1. actors (start-ups, established companies, labs, customers)
  2. institutional arrangements
  3. rules

All these have changed over time (Pisano pp. 84)

  • first generation
    • product: large molecules
      • 1973: Herb Boyer and Stan Cohen discover rDNA process
      • 1976: genentech founded
      • using rDNA and Mab to discover new drugs (Pisano pp. 84)
      • Use single genetic engineering technic to develop a variety of products (Pisano pp. 87)
      • Some of these products would be licensed to pharma companies for production. Some hoped to develop their product vertically, from concept to market
    • dynamic: FIPCO
      • smaller projects operated independent of the pharma companies
      • deals with pharma companies to fund large ($300m+) projects (Pisano pp. 86)
      • kept extremely close link to universities (Pisano pp. 85)
      • Amgen (founded 1980), Genentech (1976), Chiron (1981), Gilead Sciences (1987)
  • Second generation
    • product:
      • novel recombinant proteins - proteins never used in clinical testing but suspected to have positive effects (Pisano pp. 88)
      • 1975: monoclonal antibodies (Mab) developed - supposed to be able to bind to specific unhealthy cells without harming healthy cells. Were a clinical and financial disappointment (Pisano pp. 88)
      • more willing than first generation companies to look at individual molecules (Pisano pp. 90)
      • In general, these products would be licensed to pharma companies for production
    • dynamic:
      • Hope that biotech drugs, because formed from natural human proteins, would be less risky than drugs produced in other fields. When did not happen, money began to dry up (Pisano pp. 90)
      • Companies had to focus more narrowly - hopes often rested on a single project
      • Less hope of becoming fully-integrated pharma companies themselves. Increasingly getting their funding from established pharma firms (Pisano pp. 91)
  • Third generation
    • product
      • two groups (Pisano pp. 92):
        (1) developing processes for genomics research, licensing their discoveries to other companies (e.g., Celera, founded 1998)
        (2) working directly on genomics research through government grants (complete list of grant recipients here: http://www.genome.gov/page.cfm?pageID=17015407)
    • dynamic
      • Human Genome Project creates cultural shift: less laborious testing of individual hypotheses, more effort to develop large amounts of data and product (Pisano pp. 92)

What are the main business models?

  • Platform
    • develop technology platform (e.g. research method) and license it to other companies (Phillips, "Biotech Business Models")
    • Most viable model since the Biotech bust of 2001
    • Broad patent protection will help this sort of business model (Pareras, "Biotech Business Models")
  • Product
    • develop a new product (Phillips, "Biotech Business Models")
    • RIPCO (Royalty-Income Pharmaceutical Company) - develop a new product and license to a larger company in exchange for royalty on sales (Pareras, "Biotech Business Models")
      • large potential customer bases and the sooner it can be brought to market, the better
    • FIPCO (Fully Integrated Pharmaceutical Company) - develop new product and bring it to market yourself (Pareras, "Biotech Business Models")
      • much easier to accomplish if you have many products with which to diversify risk
    • NRDO (No Research, Development Only) - buy a 'discarded' drug from a pharmaceutical company and develop it to the point of bringing it to market. Key that you be able to develop the drug in very efficient way, so as to make it profitable (Pareras, "Biotech Business Models")
  • Vertical
    • early concept to market (Phillips, "Biotech Business Models")

What are the innovation dynamics in this field?(inputs/outputs, timing of innovation/ disruptive or incremental innovation?)

  • Innovations come from uncertain processes involving knowledge and markets (McKelvey pp. 45)
    • Biotech involves intersection of several disciplines – increases the amount of uncertainty (McKelvey pp. 45)
    • There is no clear connection between investment made and products brought to market (McKelvey pp. 46)
    • Innovation in Biotech can come from not just new technological processes, but also from basic scientific discoveries (e.g. the discovery of DNA) (McKelvey pp. 46)
    • Total cost of R&D is increasing (McKelvey pp. 48)
  • Biotech creates value in a variety of different ways
    • not usually a direct connection between scientific discovery and industrial application (McKelvey pp. 48)
    • Tendency to form geographic clusters through university centers and tendency towards mergers (McKelvey pp. 49)
  • For innovation biotech firms rely on networks between different kinds of actors
    • collaboration between large firms, small firms, and universities (McKelvey pp. 50)
    • much of the research carried out at universities. Bridge organizations "Technology Transfer Organizations" established between universities and companies (McKelvey pp. 50-51)
    • public criticism can have the effect of slowing down development of products, e.g. Genetically Modified Organisms (GMO) (McKelvey pp. 52)
  • Firms play increasingly important role in R&D (McKelvey pp. 52)
    • Essential that firms be able to establish links both with universities and with venture capitalists (McKelvey pp. 54)

Factors Impacting the amount and speed of knowledge flow

(1) Geography

  • biotech firms, when part of a geographic cluster, will share in informal knowledge spill-over (Owen-Smith and Powell)
  • biotech firms, when central to a geographically dispersed group, will also gain from informal knowledge transfer (e.g., when a firm is in charge of a trade organization)

(2) Relationship with universities

  • New Knowledge flows out of Universities faster than it does out of companies (Jaffe et al. 1993)
  • New knowledge flows out of private firms faster if the initial R&D began at a non-commercial firm (Owen-Smith and Powell p. 7)
  • strong relationships between private firms and universities actually increases knowledge flow between the private firms themselves (Owen-Smith and Powell pp. 12)

(3) Size and age of firms

  • Because young firms have to deal with the fact that they do not have established relationships with suppliers or customers, and that they do not have clear working relationships within the firms, start-ups will often try to make themselves relevant to outsiders and make themselves sturdy within by increasing knowledge flow with other firms. Here's how:
  1. start-ups establish alliances with other firms
  2. start-ups use those alliances as a way to gain new knowledge
  3. start-ups use those alliances to tamp down potential conflicts
  • That young firms do form knowledge alliances as a way to survive and prosper is confirmed empirically in the literature (Renko et. al.)

(4) relationships with VC's

  • further funding from VC's often contingent on meeting certain research benchmarks. In this way, VC's often drive and direct the innovation, not the scientists (Kaiser)

(5) Increased tendency to patent

  • Rapid increase in the amount of knowledge: between 1977 and 1997, the number of patents approved 'annually' increased almost seven-fold (Oliver pp. 56)
  • Has increased disclosure of final products
  • However, has also increased tendency to keep secrets about products in development
Number of Biotech patent approvals (Oliver pp. 59)
Drugs Microbiology Multicellular organisms Recombinant DNA
1977 660 591 0 14
1982 730 711 1 111
1987 958 1099 19 204
1992 1691 1965 52 356
1997 3372 4178 318 506


Further areas of research:

  • find instances knowledge flow created when a company sells off a part of itself, perhaps to realign its strategic interests
  • find instances where marketing departments drive science R&D (Joe McCracken of Genentech said that this is a problem for some firms. But is it? http://ecorner.stanford.edu/authorMaterialInfo.html?mid=1613)

Is this field replicating models from other fields?

  • Anatomy of the Biotech industry looks a lot like semi-conductors or software (Pisano pp. 118)
    • Market for knowledge
    • University-spawned start-ups focusing on specific pieces of the value chain
    • Role for VC
  • However, Biotech R&D different from Silicon Valley R&D: (Pisano pp. 118-119)
    • Persistent uncertainty in ability to bring products to market
    • R&D process cannot be broken into discreet bits
    • R&D process is usually much longer for Biotech products (even though funding process for Biotech is about as short at in Silicon Valley) (Pisano pp. 116)
    • Because there a silos of information within the different parts of the R&D process, there is a great deal of tacit, difficult-to-communicate, background information
    • Murky IP rights makes sharing riskier (Pisano pp. 122)
    • Unlike Silicon Valley (exceptions - GE, IBM, and Xerox), Biotech actually performs basic scientific research
  • Results:
    • $300 billion in capital since the industry got started
    • yet only a handful of profitable companies
  • Additional note: though not imitating the model of big pharma, biotech is often parasitic upon it:
    • Almost all Biotech companies have to form contractual relationships with Pharma companies (Pisano pp. 117)

How many companies?

  • 336 publicly traded companies in the US in 2006 ("Beyond Borders" pp. 19)
  • in 2006, 8 largest Biotech companies bring in $35,821,000,000 out of a total market revenue of $55,458,000,000. In other words, eight companies accounted for 65% of the industry's revenue ("Beyond Borders" pp. 18-19)

Company Revenue in 2006 (USD millions) R&D in 2006 (USD millions) Net income/ (loss) in 2006 (USD millions) Employees in 2006 % of US GDP

Company Revenue in 2006 (USD millions) R&D in 2006 (USD millions) Net income/ (loss) in 2006 (USD millions) Employees in 2006 % of US GDP
Amgen 14268 3366 2950 20100 0.00108
Genentech 9284 1773 2113 10533 0.00070
Genzyme 3187 650 (16.8) 9000 0.00024
Gilead Sciences 3026.1 383.9 (1190) 7575 0.00023
Biogen Idec 2683 718.4 217.5 3750 0.00020
Cephalon 1764.1 403.4 144.8 2515 0.00013
MedImmune 1276.8 448.9 48.7 2359 0.00010
Celgene 898.9 258.6 69 1864 0.00007
Abraxis BioScience 765.5 96.9 (46.9) 1734 0.00006
ImClone Systems 677.8 112.1 370.7 1287 0.00005

How much money do they make or how much money do they “move” in the American economy?

  • total market revenue in 2006 was US $55,458,000,000 ("Beyond Borders" pp. 18)

How important is research from universities in this specific field?

  • Past: Universities very important in developing new processes. Three largest innovations in the biotech field all occurred in university settings (Pisano, Science Business, pp. 26-30)
    • rDNA
      • Herb Boyer and Stanley Cohen (Stanford)
    • monoclonal antibodies (MAbs) - can produce large amounts of a specific kind of anitbody
      • Georges Kohler and Cesar Milstein (Cambridge)
    • combinatorial chemistry - create large varieties of chemical compounds by assembling chemical building bocks in every combination.
      • Jonathan Ellman, 1992 (Berkeley)
  • Present: Multiple studies conclude that academic research is the basic driver of innovation in Biotech (Oliver "University Based..." pp. 194)
    • Many industry-university collaborations (Oliver "University Based..." pp. 194)
    • Technology transfer offices have made universities much more ambitious in retaining rents from discoveries (Oliver "University Based..." pp. 194)
    • Several studies show that universities no longer engaged simply in 'pure science' but also specific industrial innovation (Oliver "University Based..." pp. 197)
    • Some universities (e.g., Oxford) build technology-transfer offices with the specific goal of building new spin-off companies (Oliver "University Based..." pp. 198, 203). Possible reason:
      • Potential profits
      • Potential draw for more entrepreneurial professors
    • The strength of the connection between a university and industry depends on the environment fostered by the university. Stanford, which encourages spin-offs and industry collaborations, has greater industry involvement those does Berkeley, a similar institution (Oliver, "University Based..." pp. 204-205)

How important is public funding in this field?

How important is private funding / venture capital in this field?

  • In 2007, VC investments accounted for US $29.6B in capital ("2007 CED North Carolina Venture Report")

Are there any specific public policies (from agencies, federal or state policies) that give incentives for openness or enclosure?

Data

  • IP - raw data has to be put into the public domain
  • National Center for Biotechnology (NCBI, "Our Mission") - human genomic sequence put into GenBank. Three methods for maintaining openness:
  1. Storing public databases. First among these is the GenBank, but also the "Online Mendelian Inheritance in Man (OMIM), the Molecular Modeling Database (MMDB) of 3D protein structures, the Unique Human Gene Sequence Collection (UniGene), a Gene Map of the Human Genome, the Taxonomy Browser, and the Cancer Genome Anatomy Project (CGAP)" (NCBI, "Programs and Activities"). Complete list of online databases and search tools available here: http://www.ncbi.nlm.nih.gov/genome/guide/human/ (NCBI, "Human Genome Resources")
  2. Developing search tools for databases, e.g., the Entrez program for searching the human genome (NCBI, "Programs and Activities"). Complete list of tools available here: http://www.ncbi.nlm.nih.gov/Tools/ (NIH, "National Institutes of Health Public Access")
  3. Developing standards for databases. If you publish a gene to GenBank, you have to assign it an NCBI identifying sequence. This makes it publicly searchable (Bownas, "Accessing records in NCBI's sequence databases", and NCBI, "Sequence Identifiers: A Historical Note")

Narratives

Tools


NIH EFFORTS

  • Overall effects

NIH efforts facilitated access to research inputs, avoiding problems such as "upstream IP tickets" and "in academic settings where control rights over research direction are in the hands of researchers, increased openness has at least as large an effect on enhancing the scope and diversity of horizontal exploration as it does on inducing vertical exploitation along well-defined research lines."(Murray et all, 2009)


  • Access to Genetic Engineered Mice:
    • Trans-NIH Mouse Genomics and Genetics Resources Coordinating Group (Trans-NIH Mouse Initiatives, "Frequently Asked Questions (FAQs) and Answers")
      • Mouse resources (those pertaining to genetically modified mice) created with the help of NIH funding must be distributed publicly
    • NIH-Firms MOU regarding access and use of essential mice
      • NIH/DuPont OncoMouse Memorandum of Understanding
        • Parties: DuPOnt + NIH + Jax Labs
        • Date: July, 1998
        • Object: "allowed JAX or universities to distribute and share Cre-lox mice with a simple license (essentially a standardized one-page material transfer agreement and an institution-wide license). In addition, JAX announced its commitment to acquire, breed, and distribute Cre-Lox mice on an open-access basis." (pg 14) (Murray et all 2009)
        • Result: high impact, since mice were not available through the Jax Labs before
      • NIH/DuPont Crelox Memorandum of Understanding
      • "Prior to the NIH-MoUs, DuPont had adopted stringent restrictions on use of the mice for academic research. However, the MoUs lifted these restrictions by implementing a simple contract, providing a royalty-free and costless license that specifically removed any claims to reach-through rights on downstream research, and ensuring that the mice covered under the patents would be made available through the Jackson Laboratory (the world's single largest non-proprietary repository for research mice). The NIH-MoUs constitute an openness shock for the mouse genetics research community: Prior to the MoUs research tools covered by the patents - hundreds of varieties of Cre-lox or Onco mice developed in the early 1990s - were subject to stringent restrictions in openness. After the MoUs they suddenly became widely accessible to the entire academic research community." (Murray et all, 2009)
      • "these agreements both reduced downstream expropriation of follow-on innovators (in the case of Cre-lox and Onco) by decreasing the reach-through rights available to DuPont, and increased access for follow-on innovators to the mice themselves (particularly in the case of Cre-lox mice)" (pg 22) (Murray et all, 2009)


FEDERAL LEGISLATION

  • Bay-Dhole: Patents have increased markedly, requiring disclosure of discoveries

Further Products

What is the cost structure of the field?

All numbers here are for the industry as a whole

Inputs

  • VC's: USD$5.5 billion in 2007
  • IPOs: USD$1.2 Billion (largest IPO of the year: Nanosphere raised $113 million in November)
  • Follow-on public financing: USD$2.5 Billion
  • Other Financing (e.g., debt financing): USD$12.2 Billion
  • M&A USD$15.6 Billion, mostly from AstraZeneca's acquisition of MedImmune

Output:

  • Product Sales: USD$55.6 billion
  • Revenues: USD$68.4 Billion (interesting - not as much revenue from outside product sales as I expected)
  • R&D Expenses: USD$30.0Billion

R&D as a percentage of revenue: 39.6%

(All findings from Ernst & Young's 2006 report)

Who are the producers, the buyers, and the users?

What is the structure of power from the production side and what is the structure of power in the demand side? (E.g., who has the power to control production and demand? How is the control distributed?)

Navigation

Bibliography for Item 2 in BGP
Biotechnology_-_Genomic_and_Proteomics