Paradoxes and innovation processes in biotechnology

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Paradoxes and innovation processes in
biotechnology biomedicinePolicy concerns
Global Competition in High Tech Sectors, Nov.
2007 Lecturer Astrid SzogsIt is gratefully
acknowledged that the slides were provided by
Annika Rickne.
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Definition of biotech

• Biotech as a knowledge field
• The application of knowledge about living
  organisms and their components characteristics
  into industrial products processes
• Included knowledge fields molecular biology,
  genomics, proteomics, bioinformatics, etc.
• What to include in biotech changes over time
• Biotech as an industrial sector
• Firms focusing specifically on these knowledge
  fields Dedicated Biotech Firms (DBF)

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Biotech influences many sectors
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Sometimes Biotech bioscience bio-x
Biotech bioscience bio-x
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Definition of biomedicine
Sectors
Medical technology
Instruments
Pharmaceuticals
Knowledge fields
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Paradox 1

• Different definitions, operationalizations
• DBF vs all types of firms
• Biotech vs biomedicine vs bioscience
• Statistics measurement
• Measuring change within a region/country
• Comparisons between countries
• Causal relations
• Focused field but still lack of facts

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Paradox 2

• Controversies whether commercialization of
  biotech is good or bad
• Ethics sources of stem cells
• Safety use of xeno-material
• Modification of nature GMO
• Public knowledge or appropriation ownership of
  cells
• Equality who to donate to, welfare diseases
• These are balanced against needs and outcome
• User needs Parkinson, Altzheimers
• Economic growth High hopes
• Attracting talent Interesting research
  environments
• There are many concerns that need to be balanced
• Region and countries take different roads
• Policy actors play major role also firms,
  universities, researchers, media, etc.

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Paradox 3 ST vs market as drivers

• Science technology driven
• Knowledge base areas of scientific
  technological knowledge
• Embodied in techniques instruments
• As knowledge evolves borders are blurred
• Driven by possibilities in ST
• Driven by researchers engineers
• User driven
• Societal debates
• Innovations developed in close interaction with
  medical doctors and patients
• Examples
• Nobel Biocare Brånemark implants
• Focal Biodegradable gel
• Innovations emerge from uncertain, complex
  processes involving knowledge and markets.
• Development of science-technology-application-mark
  et intertwined
• Co-evolution

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Paradox 4 High hopes but slow return

• High hopes of meeting user needs and creating
  economic growth
• Most countries have a biotech policy for growth
• India US 5 billion, 1 M jobs by 2010
• Regenerative medicine cure diabetes, increase
  life span
• But not so much realized so far?
• Examples
• Tissue engineering
• Pharma
• How fast and radical change can we expect?

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CASE Regenerative medicine To help the body
heal itself
Replace - implant new organ Repair - add
new cells to organ Regenerate - stimulate cell
renewal
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Challenges

• Research
• Complex multi-disciplinary approach
• In vitro viability versus in vivo function
• Determine primary pharmacology and dosing
• Availability of animal (disease) model
• What constitutes clinical success ?
• Products
• Firm experience of how to get products to the
  market
• Some products on the market
• Production
• Living organisms preservation of viability
• Biodistribution and half-life of cells
• The batch size of one
• What constitutes GMP ?
• Traceability processes
• Sources
• Large scale?

Rickne and Sandström, 2006
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Challenges

• Regulatory issues
• Technology and clinical therapy evolving faster
  than regulation and standardization of processes
• Protect patients
• Quality Safety and Efficacy
• Classification not clear
• A political process
• Collaboration between public health authorities
  and private enterprise
• Will it be too costly?
• Fast reaction needed!!
• One man cannot hold another man down in the
  ditch without remaining down in the ditch with
  him Booker T Washington.
• Ethics/Precautionary Principle
• Media coverage
• Creating debate (Nancy Regan)
• Ethical issues
• Who to donate to?
• Stem cells Which source?

Rickne and Sandström, 2006
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Challenges

• To handle the customer hesitancy the regulatory
  issues
• Gradually introduce the technology
• Reimbursement
• convincing clinical data
• public acceptance
• demand for therapy.
• Firms investors
• Clear route needed regulation, business models,
  reimbursement
• Societal gains
• Who should make money?

Rickne and Sandström, 2006
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CASE Biotech in pharma

• Science genomics, combinatorial chemistry, etc.
• Pharma
• Increasing development cost
• Shift towards blockbuster drugs
• Declining RD productivity
• Biological products therapeutic proteins (partly
  due to fast track approval)
• Role of biotech
• identification of drug targets
• understand human body
• tools for development
• Speed up process?
• new sector created pharma restructured, new
  division of labor
• More drugs in development by DBF Big pharma
• drugs for unmet clinical needs (lt15 since 1980)

Hopkins et al, 2006
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CASE Biotech in pharma

• But
• slower to validate targets
• hard to transfer knowledge from academia to
  industry
• translational process difficult
• targets identified with genomics has so far lower
  success rate
• RD productivity still declining (more difficult
  infectious to cronic diseases?)
• Time lags?
• Pattern of technological change (Rosenberg, 1979,
  von Tunzelmann, 1993)
• Revolutionary science incremental technological
  change
• Technology often primitive when introduced
  require high investment for improvement
• Biotech first process technology
• Complementary innovations
• Large technical change in some parts of DD
  process but not overall

Hopkins et al, 2006
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Biotech in pharma

• Organizational institutional change needed
• Organizational change of drug discovery process
  clinical practice
• New regulation needed
• Adapt to clinical procedure (clinical trials,
  economic assessment, etc.)
• Managerial ability
• Policy
• Funding of public RD yes but not expect fast or
  direct returns
• Much focus on technology transfer, start ups,
  etc.
• Link goals (e.g. improved health) to policy
  instruments
• Understand time scales mechanisms
• The hype as a way to speed up the process
  acquire resources?
• Correct statistics

Hopkins et al, 2006
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Refuting the linear view of innovation
Innovations emerge from uncertain, complex
processes involving knowledge and markets

• Incremental technological change
• Science investment as a crucial ingredient
• Conclusion not to downsize ST investment
• Only indirect link to industrial growth
• Mechanisms labor mobility, informal
  collaboration, etc
• Internal firm university capabilities
• Resources complementary assets ability to
  obtain resources in markets and networks
• Organizational Institutional change needed

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Paradox 5 Regulation both costly and wanted
CASE Tissue engineering the regulatory gap
Astrid Szogs Annika Rickne
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Firm opportunities?

• First firms in artificial skin products
• not strongly regulated
• large freedom,
• first mover advantages,
• communication with regulatory units,
• uncertainty
• betting on the development
• Today firms demand
• clear regulation
• transparency
• converngence between countries

Astrid Szogs Annika Rickne
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Regulatory patchwork in EU

• Innovative medical technologies, including TE
  products do not fit into the existing regulatory
  frameworks
• In EU, there is a lack of a harmonized regulatory
  framework for TE products
• This leads to a regulatory patchwork within EU
• Now in process of harmonization

Astrid Szogs Annika Rickne
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Constructing the TE regulation in Europe

• Dimensions underlying the construction of
  regulation
• Scientific origin of cells
• Industrial production volume and frequency
• Historic Building on existing regulation
• A structure under change
• The division of responsibility between the
  national and the supra-national levels are under
  change
• Choice of legal instrument regulation - set
  framework for the change process new rules
  will have to be implemented in all member states
• A negotiation process
• The double role of policy
• Time spans
• Actors, negotiations and power structures

Astrid Szogs Annika Rickne
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Conclusions

• Institutional change (here ex regulation)
  important for innovation
• constrain or facilitate innovativeness,
• provide stability,
• facilitate and control the emergence of markets
• facilitate exchange at markets,
• empower actors,
• not neutral but different missions,
• different efficiency levels
• Institutions are dynamic
• Developed historically, path-dependent
• Involve social groups, coordination power
  systems

Astrid Szogs Annika Rickne
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Paradox 6 Global knowledge flows very local
clustered CASE Commercialization of human
biobanks

• deCode Genetics, Iceland, Oxagen, UK,
  UmanGenomics, Sweden
• Innovation process as iterative, uncertain and
  complex not linear
• multi-scientific and multi-technological
• only initial stage of innovation process
• various aspects of a drug interdependent and
  shaped interactively and simultaneously
• Process shared over several actors
• SMEs intermediaries, integrating
• High RD costs, VC, large samples
• Regulation directs who can appropriate
• Firms played different roles in networks
• Small firms loose out? Takes time, big pharma
  hesitant

Rickne, Laage-Hellman, McKelvey 2006
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Rickne, Laage-Hellman, McKelvey 2006
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Knowledge sharing in networks

• Various linkages exist among diverse actors in
  innovation processes, where the firm plays a
  particularly important role
• Multitude of diverse actors compete and interact
• The firm as an organisational form is crucial to
  assemble the capabilities needed for exploiting
  knowledge within biotech, engaging in research as
  well as commercialising over time in an iterative
  fashion.
• Science-driven scientists, universities and
  industrial RD labs key actors.
• User inputs crucial.
• Resource flows knowledge sharing in networks
  crucial
• Organization of knowledge sharing
• Geographically close relations important
• Institutional structure set frame
  regions/countries differ in propensity to share
  diffuse
• However not always delimited by geography
• Embedded in professional networks and global
  knowledge pipelines
• Global industry knowledge markets
• Policy move from cluster focus to understanding
  of mechanisms of knowledge sharing in each
  specific instance

Rickne, Laage-Hellman, McKelvey 2006
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Policy needs to handle the paradoxes

• Clear comparable definitions,
  operationalizations, indicators and statistics
• The triple role of policy Societal concerns vs.
  patient needs vs. economic growth
• ST vs market as drivers of innovation
• High hopes but slow return
• Regulation costly and wanted
• Global knowledge flows very local clustered

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Policy concerns

• Who takes care of policy?
• Definition of policy role of government
• What level?
• Global-supranational -national- regional -local
• Specific vs. general?
• Policy instruments
• investment in basic and applied sciences
• stimulation of (academic) entrepreneurship
• support of regional clusters
• Etc.

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Who has the recipe?

• US leader Europe lagging?
• In comparison with the USA more biotech firms in
  EU but smaller firms and less revenues
• USA (2001) 1453 firms, 141000 empl, 25 billon
  revenues
• EU 1879 firms, 34000 empl, 7,5 billon revenues
• Main market is US (e.g. 80 of biomedical
  products)
• The evolution of the biotech sector in the USA
• In rich resource environment (California)
• Key scientists
• Funding of science
• Breakthroughs Scientific competition
  collaboration
• Large firms Knowledge flows between new firms
  scientists
• University policy attitudes
• Dominating user industries Close contact with
  both science and users
• Financing through VC and stock market
• Cooperation networking crucial

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Questions raised

• Are these true facts ? Definitions and
  statistics?
• Does US generate more higher quality research?
  Why?
• Is US better at commercializing? Why?
• Does the US have a well functioning institutional
  set-up?
• Should EU imitate the leader? Is there a best
  practice model?

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Readings

• Hopkins, M., Martin, P., Nightingale, P., Kraft,
  A., Mahdi, S. (2006) The myth of the biotech
  revolution An assessment of technological,
  clinical and organisational change, WP, SPRU.
• McMeekin, A., Harvey, M. and Gee, S. (2004)
  Emergent bioinformatics and newly distributed
  innovation processes, in McKelvey, M., A. Rickne
  and J. Laage-Hellman (Eds), The Economic Dynamics
  of Modern Biotechnologies Europe in Global
  Trends, Edward Elgar Publishing Co.
• McKelvey, M., Rickne, A. and Laage-Hellman, J.
  (2004) Stylized facts about innovation processes
  in modern biotechnology, WP.
• Orsenigo, L., Pammolli, F., Riccaboni, M.,
  Bonnaccorsi, A. and Turchetti, G. (1998) The
  evolution of knowledge and the dynamics of an
  industry network, Journal of Management and
  Governance, 1, 147-175.
• Powell, W W., K. W. Koput, L. Smith-Doerr (1996)
  Interorganizational Collaboration and the Locus
  of Innovation Networks of Learning in
  Biotechnology, Administrative Science Quarterly,
  Vol. 41, No. 1.
• Prevezer, M. (2001) Ingredients in the Early
  Development of the U.S. Biotechnology Industry,
  Small Business Economics, 17, 17-29.
• Szogs, A. and Rickne, A. (2006) Institutional
  change as a process of negotiation The case of
  European regulation for tissue engineering,
  Globelics India 2006 Innovation Systems for
  Competitiveness and Shared Prosperity in
  Developing Countries, Trivandrum, India, Oct 4-7.