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O E C D Wo r k s h o p o n G r e e n Te c h n o l o g y a n d I n n o v a t i o n
P o l i c y
P a r i s , 2 5 t h O c t o b e r 2 0 1 0
CONVERGENCE IN ENABLING
TECHNOLOGIES FOR GREEN
GROWTH
Thomas Reiss
Fraunhofer Institute for Systems and
Innovation Research ISI
Karlsruhe, Germany
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Converging technologies – concept an visions
Converging technologies – down to earth
The case of synthetic biology
Challenges and policy approaches
Agenda
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The concept o f converg ing technologies
Info
Cogno
Nano
Bio
Starting point:
Overlapping of
disciplines
and research fields
Bainbridge, William Sims; Roco, Mihail C. (Eds.) (2006):
Managing Nano-Bio-Info-Cogno Innovations. Converging
Technologies in Society. Heidelberg, New York: Springer.
Outgrow of the New York Conference in 2004.
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“The convergence of Nano-Bio-Info-Cogno
technologies will lead to a paradigm shift and would
contribute to a rethinking of current growth patterns”
Converging technologies as generic problem
solver?
Converg ing technologies – the v is ion (1)
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„A combination of advanced technologies, especially information-,
bioengineering-, and nanotechnologies, has the potential to radically
change developed, capitalistic economies. The economy I envision is
highly decentralized and sustainable. In this future, large numbers of
households and small clusters of houses are capable of meeting many of
their basic needs largely independent of the national and global
economies. After the initial purchase of an inexpensive array of capital
equipment, the homes and clustered neighborhoods will be able to
generate their own electricity, recycle their own water, assemble
materials for clothing ,.. possibly manufacture custom-designed
medicines,… custom produce their own...entertainment products, and
even grow a fair portion of their own food, using fast-growing, genetically
modified organisms grown in.. real-time controlled „green“ greenhouses.
People will work cooperatively.. in their homes and neighborhoods to
manage these systems to produce these and other products... “(Tonn
2006, p. 313)
Converg ing technologies – the v is ion (2)
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Converging technologies – concept an visions
Converging technologies – down to earth
The case of synthetic biology
Challenges and policy approaches
Agenda
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Attempt to structure CT
not along abstract convergence
principles or along disciplines but on the
basis of concrete technological
application fields mentioned in the
diverse CT documents
Application
Cluster
A
B
C
D
E
F
Converging
Technologies
Clustering
process
Concrete applications,
products, ideas, methods,
mentioned in the context
of convergence
Structuring CT in 8 application areas
Source: CONTECS Project
www.contecs.fraunhofer.de
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Clustering: 8 appl icat ion areas of CT
Physical
enhancement/
Biomedicine
Computer-
based modelling
of the world
Converging
Technologies
Neuro/ Brain
enhancement
Human-
Machine
Interfaces
Robots and
intelligent
software/
devices
Synthetic
Biology
Pattern
recognition Sensors
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Converging technologies – concept an visions
Converging technologies – down to earth
The case of synthetic biology
Challenges and policy approaches
Agenda
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(1) engineer and study biological systems that do not exist
as such in nature, and
(2) use this approach for
achieving better understanding of life processes,
generating and assembling functional modular components,
developing novel applications or processes.
What is Synthet ic Bio logy ( SynBio)
about?
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11
Based on convergence
© TESSY
Drugs
Biomedicine
Biomaterials
Diagnostics
Biofuels
Vaccines
Food
ingredients
Bioremediation
Computer
Science
Engineering
SciencePhysics
Biosensors
Chemistry Biology
Molecular
Biology
Systems
Biology
Therapeutics
Fine
chemicals
Social
Sciences
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Slide 12
The SynBio roadmap h t t p : / / w w w. t e s s y - e u r o p e . e u / d o c u m e n t s . h t m l
Regulation
Funding
Knowledge transfer
raise public awareness
clarification of ethical issues
coordinated regulation for biorisks/safety/security
One European SB network
support for commercialisation
translational funding
SB integration in existing curricula, postgraduate training
IP clarification and harmonization
risk assesmment mechnisms
in vitro production systems
high throughput synthetic methods
artificial vectors/ delivery systems
modelling (in silico)
funding of blue sky research
apply new perspective to research in the biological sciences
educational initiatives at all levels
implement interdisciplinary training
2008 2010 2012 2014 2016
funding for teaching
funding for socioethical analyses
individual funding
infrastructures (registry, databases, shared production facilities)
clarification open source status
}
}
bioremediation, environ. sensors
sustainable
chemical production
energy supply
biomedical products
new materials
understanding biocomplexity
counter-
bioterrorism
funding for legislative/regulatory analyses
funding for safety/security analyses
collaborative funding
methods and components all – omics approaches standardisation: reporting mathematics
code of conduct development of clear guidance
local SB networks
elaborate education/information material
measures to prevent misuse
Scientific Milestones
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Four interconnected fields:
Regulation
Funding
Knowledge transfer
Scientific milestones with clear chronology, however moving
targets
Progress in one fields depends on advances/changes in other
fields
The SynBio roadmap – main features
(Gaisser, S. Reiss, T. Lunkes. A., Müller, K, Bernauer H. (2009) EMBO rep. 10, Special Issue, S9 – S8)
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Roadmap for scientific milestones
2008 2010 2012 2014 2016 2018 2020
Establish registries of
components/models
Establish high throughput
analytical methods
Establish (l ife) databases of
components
Establish high throughput
synthetic methods
Establish in vitro production
systems (e.g. cell cultures,
Establish cell factories
(broad biotechnological
Set up automation
technologies in analytical
Establish efficient and large
scale synthetic chemistry
Apply engineering
perspective at all scales of
Use of efficient and clean
energy production systems
Produce biomedical
products based on SB
Produce new materials
based on SB
Replace chemical processes
with biological ones n= 121
n= 124
n= 123
n= 125
n= 118
n= 116
n= 122
n= 125
n= 128
n= 125
n= 128
n= 125
n= 129
SynBio l : Assessment o f sc ient i f ic
mi les tones
Relevance
factor 3.26
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Scientific breakthroughs being made
Few first steps towards commercialization
Malaria drug
Enzymatic pathways for degradation of lignocelluloses:
biofuels
Economic perspectives:
Short term: biofuels
Medium term: biomaterials, chemicals
Long term: Medical applications (drug design)
Strong media coverage, high public attention
No guiding framework in place: governance, regulation, policy
Current status of SynBio in summary
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Converging technologies – concept an visions
Converging technologies – down to earth
The case of synthetic biology
Challenges and policy approaches
Agenda
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Codification and protection of knowledge
Social embedding
Policy support
Challenges
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SynBio is based on a research culture of openness
and sharing of results in registries – open innovation type
Sharing and exchange require rules and standards,
knowledge needs to be codified:
DNA formats and functions
Data exchange
Characterization of parts
Algorithms
Models
Reporting
Codif icat ion and protect ion of
knowledge
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Regulatory issues
Self regulation (soft) versus state (hard) regulation?
When to switch from “soft” to “hard”? On what basis?
Regulatory foresight: regulatory impact, relation to innovation?
Governance issues
Adequate governance structures?
Role of collaborative and integrated approaches involving multi-
stakeholder partnerships?
Co-evolution between governance approaches and S&T-
development?
Social embedding (1)
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Public perception, role of
Trust and Information
Affectedness and involvement
Regulation
Governance
Ethics
Social embedding (2)
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When and how to intervene?
Are there typical diffusion patterns of converging
technologies?
How to monitor them, which metrics?
How are they shaped by political intervention?
When are the best windows of opportunity for policy
intervention?
Policy approaches (1)
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Dynamics of science based
technologies
discovery
disillusion
reorientation
rise
diffusion
Time
Activity
euphoria
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? ?
?
?
Example: industrial biotechnology (1)
0
500
1000
1500
2000
2500
3000
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
NU
mb
er
of
pa
ten
t a
pp
lic
ati
on
s (
EP
O)
Source: Fraunhofer ISI
2007
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Example: industrial biotechnology (2)
0
1000
2000
3000
4000
5000
6000
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
Nu
mb
er
wo
rld
wid
e
Publications
Patents
Source: Fraunhofer ISI
2007
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Selection (picking winners) or indirect support (e.g.
providing infrastructure, supporting enabling capabilities)?
Steering of processes and involvement of stakeholders
Evolutionary approaches?
Overcoming the interdisciplinary gap?
Needs for specific structures or incentives?
How are emerging fields anchored in traditional
research areas?
Co-evolution between converging technologies and
learning policies
Policy approaches (2)
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THANK YOU!
