Biotech Lecture Astrid Szogs

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Annika Rickne, CIRCLE Paradoxes and innovation Paradoxes and innovation processes in biotechnology & processes in biotechnology & biomedicine biomedicine Policy concerns Policy concerns Global Competition in High Tech Global Competition in High Tech Sectors, Nov. 2007 Lecturer: Sectors, Nov. 2007 Lecturer: Astrid Szogs Astrid Szogs It is gratefully acknowledged that the slides It is gratefully acknowledged that the slides were provided by Annika Rickne. were provided by Annika Rickne.

Transcript of Biotech Lecture Astrid Szogs

Page 1: Biotech Lecture Astrid Szogs

Annika Rickne, CIRCLE

Paradoxes and innovation processes Paradoxes and innovation processes in biotechnology & biomedicinein biotechnology & biomedicine

Policy concernsPolicy concerns

Global Competition in High Tech Global Competition in High Tech Sectors, Nov. 2007 Lecturer: Sectors, Nov. 2007 Lecturer:

Astrid SzogsAstrid Szogs

It is gratefully acknowledged that the slides were provided by It is gratefully acknowledged that the slides were provided by

Annika Rickne.Annika Rickne.

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Definition of biotechDefinition 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

Medical technology

Instruments

Pulp & paper Food

Chemistry

Agriculture

Pharmaceuticals

Environment Materials

Biotech influences many sectors

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Sometimes Biotech = bioscience = bio-xSometimes Biotech = bioscience = bio-x

Biotech

Bioinformatics

Biomedical engineering

BioMaterials

Bioinformatics

Biotech = bioscience = bio-xBiotech = bioscience = bio-x

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Definition of biomedicine Definition of biomedicine

Medical technologyInstruments Pharmaceuticals

Biotech

Bioinformatics

Biomedical engineering

BioMaterials

BioinformaticsKnowledge fields

Sectors

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Paradox 1Paradox 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 2Paradox 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: S&T vs market as driversParadox 3: S&T vs market as driversScience & technology driven– Knowledge base: areas of scientific & technological knowledge – Embodied in techniques & instruments – As knowledge evolves borders are blurred– Driven by possibilities in S&T– 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-market intertwined• Co-evolution

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Paradox 4: Paradox 4: High hopes but slow returnHigh 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 engineeringPharma

• 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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ChallengesChallenges

• 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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ChallengesChallenges

• 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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ChallengesChallenges

• 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 pharmaCASE: Biotech in pharma• Science: genomics, combinatorial chemistry, etc.• Pharma:

• Increasing development cost• Shift towards blockbuster drugs• Declining R&D 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 (<15 since 1980)

Hopkins et al, 2006

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CASE: Biotech in pharmaCASE: Biotech in pharmaBut

• 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• R&D 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 pharmaBiotech 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 R&D: 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 : Refuting the linear view of innovation : Innovations emerge from uncertain, complex processes Innovations emerge from uncertain, complex processes

involving knowledge and marketsinvolving knowledge and markets

• Incremental technological change• Science investment as a crucial ingredient

• Conclusion not to downsize S&T 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 Regulation both costly and wanted

CASE: Tissue engineering & the regulatory gapCASE: 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 EURegulatory 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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ConclusionsConclusions• 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 & clusteredParadox 6: Global knowledge flows & very local & clustered

CASE: CASE: CCommercialization of human biobanksommercialization 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 R&D 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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Clinicalgenomicscompany

Universities Hospitals

Sample donors

Researchethics

committees

Biotech supplyfirms

Governmentagencies

Pharmaceutical anddiagnostics firms

Researchfinanciers

Venture capitalfims

Other biotechfirms

Rickne, Laage-Hellman, McKelvey 2006

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Knowledge sharing in networksVarious 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 R&D 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

1. Clear & comparable definitions, operationalizations, indicators and statistics

2. The triple role of policy: Societal concerns vs. patient needs vs. economic growth

3. S&T vs market as drivers of innovation

4. High hopes but slow return

5. Regulation costly and wanted

6. Global knowledge flows & very local & clustered

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Policy concernsPolicy 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 revenuesEU: 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 raisedQuestions 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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ReadingsReadings• 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.