Title: Paradoxes and innovation processes in biotechnology
1Paradoxes 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.
2Definition 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)
3Biotech influences many sectors
4Sometimes Biotech bioscience bio-x
Biotech bioscience bio-x
5Definition of biomedicine
Sectors
Medical technology
Instruments
Pharmaceuticals
Knowledge fields
6Paradox 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
7Paradox 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.
8Paradox 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
9Paradox 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?
10CASE Regenerative medicine To help the body
heal itself
Replace - implant new organ Repair - add
new cells to organ Regenerate - stimulate cell
renewal
11Challenges
- 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
12Challenges
- 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
13Challenges
- 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
14CASE 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
15CASE 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
16Biotech 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
17Refuting 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
18Paradox 5 Regulation both costly and wanted
CASE Tissue engineering the regulatory gap
Astrid Szogs Annika Rickne
19Firm 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
20Regulatory 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
21Constructing 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
22Conclusions
- 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
23Paradox 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
24Rickne, Laage-Hellman, McKelvey 2006
25Knowledge 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
26Policy 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
27Policy 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.
28Who 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
29Questions 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?
30Readings
- 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.