Vincent Walsh MSc by Research Thesis Sept 2014 (1)

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Analysis of Biotechnology Cluster Drivers with
Emphasis on the Atlantic Region that was
Incorporated within the EU
Interreg ShareBiotech Project
Vincent John Walsh
(BSc. Hons. Toxicology)
A thesis submitted to Athlone Institute of Technology in
accordance with requirements for the award of
Masters of Science by Research
Based on research carried out under the co-supervision of
Dr. Paul Tomkins and Professor Neil J Rowan
September, 2014

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Table of Contents
Chapter 1 INTRODUCTION
1.1. Origins of Biotechnology 16- 20
1.2. The Nature & Scale of Biotechnology Research 20 – 21
1.3. Economics of the Biotech Sector 21– 25
1.4. Biotechnology Promising a Brighter Future 25 – 27
1.5. Collaboration between Universities & Industry 27 – 29
1.6. Research Infrastructure 29 – 30
1.7. Core Facilities 30– 33
1.8. Core Facilities & HEI’s 33 – 35
1.9. Laboratory Informatics 35-
1.10. Biotechnology Development in Europe 36 - 39
1.11. Industry Collaboration 39 – 41
1.12. IP & Tech Transfer 41 –
1.13. Clusters 41 – 45
1.14. The Clustering Concept 45 – 46
1.15. The Importance of Clusters 46 - 48
1.16. Clusters in Ireland 48– 50
1.17. BioPharma Cluster Ireland 50 – 51
1.18. Development of the Indigenous Biotech Sector 51– 52
1.19. Porters Theory on Clusters 52– 53
1.20. Typology of Clusters 53– 56
1.21. The Cluster Life Cycle 56 – 58
1.22. HE Networks & Clustering 58 –
1.23. Social Networking 58 - 59
1.24. Virtual Networking 59 – 60
1.25. Impact of Communication Technology 60 – 61
1.26. Transnational Collaboration ` 61 -
1.27. Tech Translator 61 –
1.28. Key Enabling Technologies 61– 63
1.29. Life Science Research that isn’t Biotech 63 – 67
1.30. Aims and Objectives of this Project 67 – 72

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1.31. Research Justification 72 –
Chapter 2 METHODS
2.1. Research Approach 74 - 75
2.2. Technology Core Facilities 75 –76
2.3. Studies and Action Plan to Reduce the Gap… 76 –
2.4. Summarised Research Surveys 76 –
2.5. ShareBiotech Companies Survey 76 – 78
2.6. ShareBiotech Research Groups Survey 78 – 80
2.7. ShareBiotech Technology Core Facilities Survey 80 – 81
2.8. Presentation of ShareBiotech Needs Report 82 -
2.9. ShareBiotech Life Sciences TCF Booklet 82 – 83
2.10. The ShareBiotech TCF Audit 83 - 86
2.11. Regional Technology Translators (Pilot Action) 87 –
2.12. Organisation of Local Technology Meetings 87 –
2.13. Selection of Local Technology Meeting Domains 87 –
2.14. Natural Products LTM 87– 89
2.15. Towards 21st
Century Toxicology Framework Document 89 – 90
2.16. Expert Interviews 91 –
2.17. Dissemination of Information and Colloquia 91 – 92
2.18. Biotechnology Clusters 92 –
2.19. Transnational TCF Model 92 – 94
2.20. The CIRCA Group Consultants 94 –
2.21. The Darcy Report 95 – 96
2.22. ShareBiotech Report to Support the Growth… 96 - 97
2.23. ShareBiotech Technology and Training Offer… 97 – 98
2.24. Instruments to Foster Technology Transfer… 98 – 99
2.25. Analysis of Life Science TCF’s Business Models… 99 – 101
Chapter 3 RESULTS 103 -
3.1. ShareBiotech Biotechnology Techniques Competencies … 103 –
3.2. Biotechnology Competencies and Regional Needs Survey… 103 – 106

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3.3. Innovation in ShareBiotech Regions 106 – 108
3.4. ShareBiotech Research Groups Survey Results 109 – 131
3.5. ShareBiotech Companies Survey Results… 131 – 154
3.6. ShareBiotech TCF Survey Results 155 –
3.8. ShareBiotech Technology Transfer Survey Results 157 – 159
3.9. Answers to Technology Transfer Survey Questions 159 – 172
3.10. Natural Products Companies Surveyed in Ireland 172 – 181
3.11. Local Technology Meeting Organised in Ireland 181 – 185
3.12. The ShareBiotech Private Company/BRI Audit 185 – 190
3.13. Software for TCF Management 191 –
3.13. Implementation of CIRCA Report Recommendations 191 – 197
3.14. The Darcy Report 197 – 199
3.15. Expert Interviews 200– 203
3.16. Profiles of Experts Interviewed 204 – 209
3.17. Main Points in Expert Interviews 209 – 261
3.18. Recommendations to Strengthen the Biotech… 261 – 265
3.19. Biotechnology Education & Training Needs Offer… 265 – 272
3.20. Recommendations to Improve the Offer of Training… 272 – 274
3.21. Characterisation of ShareBiotech LTM’s 275 –
Chapter 4 DISCUSSIONS
Opening 277 – 278
4.1. INTERREG IV 278 – 280
4.2. Fragmentation of Biotechnology in Europe 280 – 282
4.3. Sustainable Growth for Europe 282 – 283
4.4. ShareBiotech Activity 3 Surveys 283 – 294
4.5. Natural Products Companies in Ireland 295 – 298
4.6. Success Factors in Biotechnology Today 298 – 300
4.7. US versus European Biotechnology 300 – 301
4.8. Technology Core Facilities 301 – 305
4.10. ShareBiotech E&Y TCF Report 307 –

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4.11. Expert Interviews Discussed 307 – 314
4.12. The Circa Report Discussed 314 – 316
4.13. The Darcy Report Discussed 316 – 317
4.14. University –Industry Collaborations 317 – 320
4.15. Biotechnology Education; Training …Discussed 320 – 322
4.16. The Future of Biotechnology 323 –
4.17. The Virtual Biotech Model 324 – 326
4.18. Technologies Supporting Virtual Organisations 326 – 329
4.19. A Sustainable Bio Economy for Europe 329 – 330
4.20. SME’s in Ireland and Europe 330 – 331
4.21. Conclusion 332 – 333
4.22. Future Work – Horizon 2020 333 – 335
Appendices
Appendix 1 ShareBiotech Company Survey
Appendix 2 ShareBiotech Research Groups Survey
Appendix 3 ShareBiotech Technology Core Facilities Survey
Appendix 4 ShareBiotech TCF Audit
Appendix 5 ShareBiotech Education Needs & Offer Questionnaire
Appendix 6 ShareBiotech Deliverables (1 – 15)
Appendix 7 Toxicology 21st
C Agenda
Appendix 8 ShareBiotech Email Contact List

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List of Figures
Fig. Number TITLE PAGE
Figure 1.1 US Biotechnologies year by year 23
Figure 1.2 Innovation capital in the US year by year 24
Figure 1.3 Irelands cluster map shows Biotechnology/Pharmaceutical clusters 49
Figure 1.4 Bio pharma and Bio-chem sector employment projections/past/future 52
Figure 1.5 Michael Porters Diamond Cluster Model. Source 53
Figure 1.6 Hub and Spoke cluster model 54
Figure 1.7 Satellite Platform cluster model 54
Figure 1.8 State Anchored / State cantered cluster model 55
Figure 1.9 The Triple Helix Model 56
Figure 1.10 The Cluster Lifecycle 57
Figure 3.1 Populations of ShareBiotech Regions 104
Figure 3.2 Economic Indicators Index 105
Figure 3.3 Employment Indicators Index in Atlantic Area 106
Figure 3.4 Innovation Indicators Index ShareBiotech Regions 107
Figure 3.5 Summary of Biotech Company Domain & Regional Location 108
Figure 3.6 Summary of Research Centre Domain & Regional Location 108
Figure 3.7 Main Specific domains of the Interviewed RG’s % Total 110
Figure 3.8 Main Scientific domains of the RG’s in ShareBiotech Regions 111
Figure 3.9 Scientist’s & Technicians employed in RG’s 111
Figure 3.10 Number of Scientists and Technicians employed in RG’s in July 2010 112
Figure 3.11 Collaboration of the RGs in 2010 with other institutions/enterprises 113
Figure 3.12 Types of Collaboration of the Research Groups with institutions/enterprises 113
Figure 3.13 Characterization of Collaboration of RGs with institutions/enterprises 114
Figure 3.14 Participation of RG’s in one or several technological networks 114
Figure 3.15 Research groups that hold registered patents 115
Figure 3.16 RG’s that do not have patents but consider patenting in the future 115
Figure 3.17 DNA/RNA Biotechnology Techniques Uses and Needs in RG’s 117
Figure 3.18 Proteins and Other Molecules Biotechnology Techniques Uses and Needs 118
Figure 3.19 Proteins and Other Molecule Techniques Internal and External Use 118
Figure 3.20 Tissue Culture and Engineering Biotechnology Techniques uses & needs 119
Figure 3.21 Tissue Culture and Engineering Biotech Techniques Int/External Use 120
Figure 3.22 Gene and RNA Vectors Biotechnology Techniques Uses and Needs 121
Figure 3.23 Gene/RNA Vector Biotechnology Techniques Internal and External Use 121
Figure 3.24 Biological Resources and Associated Facilities Uses and Needs 122
Figure 3.25 Biological Resources and Associated Facilities Internal and External Use 123
Figure 3.26 Imaging and Related Instrumentation Uses and Needs 124
Figure 3.27 Imaging technologies accessible internally & externally 124
Figure 3.28 Process Biotechnology Uses and Needs 125
Figure 3.29 Process Techniques Internal and External Use 126
Figure 3.30 Nanobiotechnology Techniques Uses and Needs 127
Figure 3.31 Nanobiotechnology Techniques Internal and External Use in the AA 127
Figure 3.32 Bioinformatics Techniques Uses and Needs within the Atlantic Area 128
Figure 3.33 Bioinformatics Techniques Internal and External Use in the RG’s 129
Figure 3.34 Training needs regarding techniques and related skills of the RG’s 130
Figure 3.35 Training needs regarding techniques and skills of the RG’s by region 130
Figure 3.36 Other needs of the research groups for the advance of R&D activities 131
Figure 3.37 Other needs of the research groups for the advance of R&D by region 131

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Figure 3.38 Main specific domains of the interviewed companies - % Total Answers 132
Figure 3.39 Main Specific domains of the interviewed companies by region 133
Figure 3.40 Number of persons employed in the companies. In July 2010 133
Figure 3.41 Number of persons employed in surveyed companies in July 2010 134
Figure 3.42 Network Membership of Interviewed Companies by Region 135
Figure 3.43 Network membership of companies by region (%) 135
Figure 3.44 Enterprise group membership of companies by region (%) group 135
Figure 3.45 Role of Biotechnology in the companies - % Total Companies 136
Figure 3.46 Role of Biotechnology in the companies- % Total by region 136
Figure 3.47 Role of Biotechnology in the companies - % Total by region 137
Figure 3.48 Geographic markets where companies sold goods/services 2008 to 2010 137
Figure 3.51 Development of R&D activities - % Total Companies 138
Figure 3.52 Means of execution of R&D activities by companies - % Total Answers 139
Figure 3.53 Intellectual Property of the companies - % Total Companies 139
Figure 3.54 Barriers to your R&D capacity - % Total Answers 139
Figure 3.55 DNA/RNA Biotechnology Techniques Uses/Needs companies 141
Figure 3.56 DNA/RNA Biotechnology Techniques Internal/External uses companies 142
Figure 3.57 Proteins and Other Molecules, Techniques, Uses/Needs companies 142
Figure 3.58 Proteins and other molecules Techniques Internal/ External Uses 143
Figure 3.59 Tissue Culture/Engineering Biotechnology Techniques Uses/Needs 144
Figure 3.60 Tissue Culture and Engineering Biotechnology Techniques Int/Ex Uses 144
Figure 3.61 Gene/RNA Vectors Biotechnology Techniques Uses/Needs companies 145
Figure 3.62 Gene and RNA Vectors Biotechnology Techniques and External uses CO 146
Figure 3.63 Biological Resources/Associated Facilities Biotech techniques U/N CO 148
Figure 3.64 Biological Resources/Associated Facilities Biotech Techniques U/N CO 147
Figure 3.65 Imaging & Related Instrumentation Biotechnology Techniques U/N 148
Figure 3.66 Imaging & Related Instrumentation Biotechnology Techniques U/N CO 148
Figure 3.67 Process Biotechnology Techniques U/ N in Interviewed Companies 149
Figure 3.68 Process Biotechnology Techniques Internal and External Uses CO 149
Figure 3.69 Nano-biotechnology Techniques U/N in Interviewed companies 150
Figure 3.70 Nano-biotechnology Techniques Internal & External Uses Companies 150
Figure 3.71 Bioinformatics Techniques Uses and Needs 151
Figure 3.72 External and internal sourcing of Bioinformatics Techniques Companies 152
Figure 3.73 Company Training Needs % 152
Figure 3.74 Company Training Needs 152
Figure 3.75 Other Needs for Advancement of R&D Activities in Companies % 153
Figure 3.76 Other Needs for Advancement of R&D Activities in Companies Region 153
Figure 3.77 Technology Transfer Survey Response by Country 157
Figure 3.78 Regional Response to Technology Transfer Survey 157
Figure 3.79 Number of people working in innovation services and technology transfer 158
Figure 3.80 Type of instruments used to facilitate TT by interviewed organisations 158
Figure 3.81 The structure of TT Survey results analysis 159
Figure 3.82 Technology Transfer through student placement 160
Figure 3.83 Technology Transfer through joint supervision 161
Figure 3.84 Technology Transfer through joint conferences 162
Figure 3.85 TT through training and continued professional development 163
Figure 3.86 TT through secondment results in ShareBiotech partner areas 164
Figure 3.87 % TT through training and continued professional development 165
Figure 3.88 TT through contract research (service supply) & consultancy 167

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Figure 3.89 TT through legislation, communication tools/incentives to support spin-outs 167
Figure 3.90 Technology Transfer through shared facilities 168
Figure 3.91 Technology Transfer through patents 169
Figure 3.92 Technology Transfer through licensing and project maturation 170
Figure 3.93 Spider web graph representing the results of the ShareBiotech audit 186
Figure 3.94 Spider graph representing the BRI AIT audit results 188
Figure 3.95 Bioscience Research Institute AIT analysis in terms of flows 189
Figure 3.96 Projected optimal staff domains for the AIT Microscopy TCF 190
Figure 3.97 BRI Management Organization Chart suggested in the CIRCA Report 195
Figure 3.98 Main organizational relationships of the TCF 197
Figure 3.99 Scope of service provision in relation to the BRI - TCF 198
Figure 3.100 Accreditation Model suggested by CIRCA for BRI compatible to ISO 13485 199
Figure 3.101 Representation of the level of agreement between the 7 core experts
regarding 32 common theme questions
202
regarding Q1 to Q10
202
regarding Q11 to Q21
203
regarding Q22 to Q32
203
Figure 3.105 Represents the number of yes answers agreed by all 7experts interviewed 203
Figure 3.106 Number & Type of Formal Higher Education Biotechnology Degrees AA 266
Figure 3.107 Vocational courses related to Biotechnology identified per region 267
Figure 3.108 Types of vocational training offer per region 268
Figure 3.109 Classification of the Current offer in Biotechnology Courses 268
Figure 3.110 Training needs identified by research groups 269
Figure 3.111 Training needs identified by companies 270
Figure 3.112 Soft skills in the field of biotechnology requiring short-term training 272
Figure 3.113 Analysis of the uptake of ShareBiotech Mobility Grants 274
Figure 3.114 Analysis of ShareBiotech Funded LTM’s 275

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List of Tables
Table
No.
Title Page
Table 1.1 Irish BioPharma Clusters Breakdown of Irish companies per sub-sector 44
Table 2.1 Audit Questions TCF 85 -86
Table 2.2 TCF's interviewed by E&Y 100
Table 3.1 Valid Questionnaires Collected the ShareBiotech project 104
Table 3.2 Number of Students in the research groups in the Atlantic Area in July 2010 112
Table 3.3 Age of Interviewed companies in the Atlantic Area- Descriptive Statistics 134
Table 3.4 Barriers to R&D Capacity of the Interviewed Companies by Region 140
Table 3.5 Access Capacity Ratio (Total Internal and External Accesses by Total
Access)
153 - 154
Table 3.6 Irish organizations interviewed Re. Technology Transfer Survey 156
Table 3.7 Results Synthesis Table of Technology Transfer Survey 171 - 172
Table 3.8 Natural Products companies interviewed in Ireland 173- 175
Table 3.9 Biotechnology SME categories for selection of LTM’s 175- 179
Table 3.10 Brief Analysis Results of N.P. Company Telephone Interviews 180 - 181
Table 3.11 SWOT Analysis of Bioclin resulting from the TCF audit 187
Table 3.12 Audit Recommendations for Bioclin recommended by TechToolNov 188
Table 3.13 SWOT Analysis BRI resulting from the TCF audit 188
Table 3.14 The recommendations of the ShareBiotech audit of the BRI 189
Table 3.15 List of selected laboratory core facility management systems i.e. LIMS 191
Table 3.16 Consensus between Experts answers to questions 1 to 33 249 - 251
Table 3.17 Recommendations to Support the Growth of a Bio-Based Economy 263 - 265

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List of Abbreviation
3D Three Dimensional
AA Atlantic Area
AAP Atlantic Area Program
ACC Access Capacity Ratio
ADA Adenosine Deaminase Deficiency
AFBI Agri Food and Bioscience Institute
AGBR Association of German Bio Regions
Agri Agricultural
AHU’s Air Handling Units
AIT Athlone Institute of Technology
AMDeC F.I.R.S.T. Facilities, Instrumentation, Resources, and Services & Technologies
API Alimentary Pharmabiotic Centre
ARE Applied Research Enhancement
B2B Business to Business
BBSRC Biotechnology and Biological Sciences Research Council
BBT Babraham Bioscience Technologies
BBT Babraham Bioscience Technologies
BI Biotechnology Ireland
BIF Bio Incubator Forum
BMW Border midlands Western
BRC’s Biological Resource Centres
BRI Bioscience Research Institute
BSE Bovine Spongiform Encephalopathy
CAGR Compound Annual Growth Rate
CAMI Centre for Advanced Medical Imaging
CCEB County and City Enterprise Boards
CCMAR Centre for Marine Research (Portugal)
CCR Centre for Commercialization of Research (Ontario)
CCR Centre for commercialisation and Research
cDNA Complementary Deoxy Nucleic Acid
CEBR Council of European Bioregions
CEO Chief Executive Officer
CFMS Core Facility Management System
CIIMAR Interdisciplinary Centre of Marine and Environmental Research
CIT Cork Institute of Technology
CNRS Centre National de la Recherche Scientifique (France)
CO2 Carbon Dioxide
COO Chief Operating Officer
CRIA Centre for Knowledge Transfer (Portugal)
CRITT Innovation et Developpemente de la Sante en BRETAGNE
CRO Commercial Research Organisation
CSIC Consejo Superior de Investigaciones Cientificas (Spain)
CVs Curriculum Vitae’s
DABT Diplomat of the American Board of Toxicology
DBF’s Dedicated Biotechnology Firms
DCU Dublin City University
DDD Drug Discovery & Development
DETE Department of Enterprise, Trade and Employment
DIHK Committee for Industry and Research in the German Chamber of
Commerce and Industry
DNA Deoxy Ribo Nucleic Acid
DOE Department of Energy
DSC Differential Scanning Colourimetry
E&Y Ernst & Young
EC European Commission

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ECO European Cluster Observatory
ECVAM European Centre for the Validation of Alternative Methods
EFPIA European Federation of Pharmaceutical Industries and Associations
EFTA European Free Trade Association
EI Enterprise Ireland
EICFP Enterprise Ireland Commercialisation Fund Programme
EIR Entrepreneur In Residence
EITTS Enterprise Ireland Technology Transfer Supports
EOP’s Equipment Operating Sheets
ERA-IB European Research Area Industrial Biotechnology
ERA-MB European Research Area Marine Biotechnology
ERBI Eastern Region Biotechnology Initiative
ERDF European Regional Development Fund
ES Spain
ESOF Euro Science Open Forum
ETB EuroTrans Bio
EU European Union
F S National Training and Employment Agency
FDA Food and Drug Administration
Fig Figure
FISH Fluorescence in-situ Hybridisation
Forfás Ireland's Policy Advisory Board for Enterprise and Science
FP Framework Project
FR France
GC Gas Chromatography
GCMS Gas Chromatography Mass Spectroscopy
GDP Gross Domestic Product
GE Gene Expression
GLP Good Laboratory Practice
GMC’s Genetically Modified Crops
GMIT Galway-Mayo Institute of Technology
GMO’s Genetically Modified Organisms
GMP Good Management Practice
GPC Gel Permeation Chromatography
GSK Glaxo Smyth Kline
H&E Higher Education
HEA Higher Education Authority
HEI Higher Education Institute
HEIs Higher Education Institutes
HGP Human Genome Project
HIV Human Immunodeficiency Virus
HP Hewlett Packard
HPLC High Performance Liquid Chromatography
HQ Head Quarters
IBA Irish Biotechnology Association
ICT Information and Communications Technology
IDA Industrial Development Agency (for Inward Investment)
IDR Invention Disclosure Reports
IGN Spanish Instituto Geografico Nacional
IGR-IAE Institut D’administration des Enterprises de Rennes – Institut de Gestion de
Rennes
ILab Intelligent Laboratory Management
ILO Industry Liaison Officer
IMI Innovative Medicines Imitative
INMRP Irelands National Marine Biotechnology Programme
INRA Institut national de la recherche agronomique
INTERREG The Cross Border Territorial Co-operation Programme for Northern

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Ireland, the Border Region of Ireland and Western Scotland
IP Intellectual Property
IPO’s Intellectual Property Owners
IPR Intellectual Property Rights
IRAM Institute of Millimeter Radio Astronomy
IRCSET Irish Research Council for Science, Engineering and Technology
IRL Ireland
ISO International Organisation for Standardisation
IST Irish Society of Toxicology
IT Information Technology
ITB Institute of Technology Blanchardstown
ITEM Institute of Toxicology and Experimental Medicine (Munich)
ITT Institute of Technology Tallaght
JISC Joint Information Systems Committee
JPI Oceans Joint Programing Initiative Healthy and Productive Seas and Oceans
KBE Knowledge Based Economy
KET’s Key Enabling Technology’s
KET’s Key Enabling Technologies
KIC’s Knowledge and Innovation Communities
LBN London Bioscience Network
LBN London Biotechnology Network
LC MS Liquid Chromatography Mass Spectroscopy
LE Large Enterprise
LIMS Laboratory Information Management Systems
LMB Laboratory of Molecular Biology
LTD Limited Company
LTM Local Technology Meeting
MaRS MaRS Discovery District Canada
MD Managing Director
MIRC Midlands Innovation Research Centre
MMI Molecular Medicine Ireland
MRC Medical Research Council (Cambridge)
MRes Masters in Research
MRI Materials Research Institute (AIT)
MS Multiple Sclerosis
MSc. Master of Science
NBP National Biotechnology Programme
NCBES National Centre for Biomedical Engineering Science
NCBI National Centre for Biotechnology Imaging
NCBI National Centre for Biotechnology Imaging
NFWDP New Frontiers Entrepreneur Development Programme
NHGRI National Human Genome Research Institute
NIBRT National Institution for Bioprocessing Research & Training
NMR Nuclear Magnetic Resonance
NMR Nuclear Magnetic Resonamce
NUIG National University of Ireland Galway
NUTS Nomenclature of Territorial Units for Statistics
NYDC New York Development Corporation
OBIO Ontario Bioscience Innovation Organisation
OCE Ontario Centre of Excellence
OCE Ontario Centre of Excellence
OECD Organisation of Economic Co-Operation and Development
ONE Ontario Network of Excellence
OSI Ordinance Survey Ireland
P&G Procter & Gamble
PCR Polymerase Chain Reaction
PET Positron Emission Tomography

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Ph.D. Doctor of Philosophy
PHA Polyhydroxyalkanoates
PI Principle Investigator
PLA Polymer Polylactic Acid
POC Proof of Concept
POI Program in Open Innovation
Post-Grad Postgraduate Course
PT Portugal
qPCR Quantitative Real-Time Polymerase Chain Reaction
R&D Research & Development
RDA Regional Development Agency
REACH Regulation Evaluation Authorisation and Restriction of Chemicals
REF Reference
RG’s Research Groups
RI Research Infrastructure
RNA Ribo Nucleic Acid
RO’s Research Organisations
ROI Return on Investment
RTP Research Triangle Park
RT-PCR Real-Time Polymerase Chain Reaction
S&E Southern & Eastern
S&T Science & Technology
SCC Stockholm Science City
SFI Science Foundation Ireland
SiRNA Small Interfering Ribo Nucleic Acid
SME Small to Medium Sized Enterprise
SNP’s Small Nucleotide Polymorphisms
SOP Standard Operating Procedure
SPECT Single Photon Emission Computed Tomography
STEM Science Technology Engineering and Maths
TA Thermal Analysis
TCD Trinity College Dublin
TCF Technological Core Facility
TCI The Competiveness Institute
TDL Technology Development Laboratory
TOF Time-Of-Flight 9Spectroscopy
TT Technology Translator
TTO Technology Transfer Office
TTP’s Technology Transfer Pathways
UCC University College Cork
UCD University College Dublin
UK United Kingdom
UKBI United Kingdom Business Incubation
UL University of Limerick
UMIC University of Manchester Innovation Company
UniMAP University of Malaysia, Perlis
US United States
USPTO US Patent and Trademark Office
VC Venture Capital
VP Vice President
VREs Virtual Research Environments
WIT Waterford Institute of Technology

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ACKNOWLEDGEMENT
There are a number of people without whom this thesis might not have been written, and to
whom I am greatly indebted. I have had the privilege to work with many talented individuals
who have made contributions to my research experience. My supervisor, Dr. Paul Tomkins
has been, and will always remain an excellent role model for me. Despite his busy schedule,
Paul always found the time to discuss anything and instilled in me the confidence to
continue and maintain belief in the worth of this endeavour. His dedication and commitment
to science and education is truly inspiring and remarkable. Special thanks to Paul’s wife
Collette who welcomed me into their home on many occasions and extended to me
unequalled hospitality, countless dinners and cups of coffee, but most of all, her warm smile
and endless support. I offer my sincere gratitude to my other co-supervisor, Professor Neil
Rowan, for the considerate ways in which you challenged and supported me throughout the
whole of this work – knowing when to push and when to let up.
Thanks to Siobhan, Anita, and Lorna, who played very important roles along the journey, as
I tried to make sense of the various challenges I faced and in providing encouragement at
those times when it seemed impossible to continue.
This dissertation is also dedicated to my brilliant and outrageously loving and
supportive partner, Lorenza Scavino. I extend warm gratitude to my sister Colette and my
three sons, Clive, Mark, and Ian for their belief in my ability.
I wish to thank Professor Horst Domdey, Dr. Martino Picardo, Dr. Claire
Skentelberry, Dr. Mario Thomas, Dr. Tony Jones, Dr. Derek Jones, and Dr. Mary Skelly, for
agreeing to be interviewed by me. Their insight, input, and influence were invaluable to the
writing of this dissertation.
I would like to thank all the members of the ShareBiotech consortium from the four
partner regions (Spain, Portugal, France, and Ireland) whose warm welcoming cultures,
enthusiasm, and professionalism, were a breath of fresh air and made the ShareBiotech
project a pleasure to be part of.
Also, the generous financial support of the EU Interreg Sharebiotech Project and the
Bioscience Research Institute in AIT for giving me the opportunity to carry out this work
and for believing in my ability and trusting me to represent them on the European stage.
Finally and most importantly, I dedicate this work to those who are loved and sadly
missed, but never forgotten, and were pillars of strength to me; my wife Gillian, my mother
Julia, my sister Jacqueline, her loving son Ross, and my father Christopher.
Bealtaine n-anamacha a bheith ina shuí ar dheis Dé.

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Abstract
Analysis of Biotechnology Cluster Drivers identifies successful models and
strategies in Europe and throughout the world that contributed to their success and
development. This constitutes a complex and frontier study that sets out to review,
examine and experiment with factors perceived to limit the development of positive
biotechnology cluster drivers in the life science technology sector of the Alantic
area, which was addressed under the EU Interreg Sharebiotech project. This
collaborative project, in keeping with Interreg structure, was divided into 7 inter-
related activities. Although my studies are framed around specifically activity 3
(addressing studies and action plan to reduce the gap between life science technology
supply and demand) that also encompassed comprehensive interviews with leading
experts in this field (activity 7); this thesis also describes the main outputs of all 7
activities as to view in isolation would both diminish and skew interpretation and
relevance of the former. It is also relevant to convey that this author also contributed
significantly to all 7 activities during the life time of this Sharebiotech Project.
The main intention of this study, through the ShareBiotech project, was to strengthen
the biotechnology sector of the Atlantic Area, through the maximisation of the
benefits of life science research infrastructures and skills, for the economic
development of the partner regions and of the Atlantic Area as a whole. This
research endeavoured to understand the reasons behind a weaker biotechnology
sector in the Atlantic Area; to identify infrastructure gaps and needs and to analyse
the drivers for success in other areas of Europe and the US through the clustering
model. The ShareBiotech project went far beyond just conducting an inventory and
offering existing technologies: it promoted a bottom-up approach and endeavoured
in partnership with stakeholders to find appropriate technological answers by
adapting the technology offerings.
Core aspirations of the project included (a) to facilitate wider sharing of knowledge
and technology within the Atlantic Area, across life science fields (Health, Marine
research, agriculture and food) and related high-tech transversal domains
(bioinformatics, imaging, and nanotechnologies), and between academia and
industry, (b) to reinforce regional service provision of technologies for researchers
(both public and private) in line with the identified needs, (c) to create the basis of a
transnational network of Technological Core Facilities (TCFs), in order to provide
technological services at the transnational level, (d) to foster technology absorption
in the less technology-intensive sectors and companies, in particular through
explaining applications of complex and recent technologies to SMEs and (e) to in
increase the profile and the visibility of the biotechnology sector of the Atlantic
Area, in order to make it an attractive choice for networking, cooperation and
locating business.
Findings showed that collaboration between industry, government, and HEI’s is
vital to the economic future of the EU, and is vital to the recovery of Ireland’s
economy. It is anticipated that this research will elucidate a model that can be
implemented in the Atlantic Area encompassing Ireland. This study also reported on
niche specialist areas of expertise and service provision across the EU Atlantic
region.

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1 Introduction
1.1 Origins of Biotechnology
This project embraced a selected analysis of the status of aspects of biotechnology
research and associated industry across elements of the Atlantic Region of the EU,
with novel follow-on research focused on the potential benefits of collaboration
models, knowledge transfer and access to technology facilities. This unique Intereg
project reflected the current and growing importance of biotechnology to the EU in
terms of society, life quality, environment and life sciences and benefits and the
associated industry, economic, technology and knowledge impacts. Before
introducing the formal tasks and objectives of this research, it is necessary to review
aspects of biotechnology and the potential origin of the drivers of this project.
Elements of this review comply with the traditional prior project time period, but
some embrace a parallel time frame and even more recently, when appropriate.
While some basic elements of biological knowledge would inevitably have slowly
accumulated since the origins of Homo sapiens in Africa about 200,000 years ago
and indeed their predecessors, it is inevitably only since the development of human
capacity to record and retain evidence of ideas and activities that a notion of aspects
of scientific history exists. There is nevertheless evidence of oral transfer to
generations of acquired knowledge, about 10,000 years ago. Initial knowledge
drivers as a capability evolved, would have been associated with attempted self-
understanding and basic understanding of surrounding plants and animals. The
literal word ‘biology’ may have originated in the 18th
C, but initiation of the former
can be associated with ancient cultures in Egypt, Mesopotamia, India and China,
although a more structured notion of biology probably derives from the more secular
tradition of ancient Greek philosophy (Magner, 2002). The overview of biology as a
discipline embracing the knowledge of living things progressed in the 19th
C as a
precursor of current terms, such as 20th C life sciences (Agar, 2012). In all
disciplines, the acquisition of information, the analysis of complexities and
pragmatic progression of knowledge and exploitation, accelerates with the passage
of time and consequently the scale, complexity and number of definitive derivatives

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of biology has expanded enormously over the past two decades (Buchwald & Gray
2008).
There are now at least 42 divisions of the biology domain embracing everything
from agriculture to traditional zoology and a minimum of at least 10 further sub-
divisions of some of these (Gum et al., 2004). A key life science division is
biotechnology. There are a number of definitions of biotechnology, but a commonly
cited generic definition is that of the OECD:
"The application of science and technology to living organisms, as well as
parts, products and models thereof, to alter living or non-living materials for the
production of knowledge, goods and services" (OECD, 2009). Biotechnology is
consequently in part, the deployment of biological processes, organisms, or systems
to generate products that influence or enhance life – this tends to imply
commercialisation of research. The origin of the term, ‘biotechnology’ is associated
with Kéroly Ereky in Hungary in 1919, who used it to describe a means of
generating enhanced porcine products.
As part of the history, as far back as 10,000 years, selective breeding of plants and
animals was practiced, and alcohol fermentation has been carried out for at least
6000 years. However, it was not until the middle of the 20th
century, when a number
of fundamental discoveries were made, that the potential of biotechnology to impact
greatly on human health and well-being was recognised.
In a 20th
C context, the beginnings of biotechnology are consequently
associated with farmers and the farming industry of plants and animals. However,
many reviews and discussions of biotechnology tend to reflect the history of the
discipline as originating before this formal title.1
In reality, a crucial period that
influenced the current definition of biotechnology, implying a capacity to change
integral biological systems, occurred in the 1970s and hence a modern interpretation
of the origins of biotechnology is associated with the advent of genetic engineering,
despite the prior discovery of DNA structure in 1953 (Watson & Crick, 1953). This
respected crucial 1970s development was that of recombinant DNA technology by
Cohen & Boyer (Cohen & Boyer, 1973). Recombinant DNA permitted the first
transfer of a selected section of DNA between E. coli bacteria. This effectively
1
The Biotech Industry Organizations website Bio.org, 2014

18
represented a future capacity to bioengineer cells and organisms and subsequent
protein synthesis. The contributory significance of Boyer and the VC Robert
Swanson, to the advent of biotechnology is further evidenced by his founding in
1976 of the world’s first significant and domain associated, biotechnology company,
Genentech. This company ultimately grew to a value of $47b by 2009, was
responsible for the first human gene expressed product in bacteria, somatostatin in
1977 and was eventually taken over by Hoffmann-La Roche in 2009.
While, the biotechnology industry first arose in the United States in the
1980s, subsequently, a combination of creative biologists, venture capitalism, and
the influential support of state and local governments generated a series of major
biotechnology clusters, including San Francisco, Boston, San Diego, Seattle,
Maryland, and North Carolina, although this term was not fully appreciated then.
Conversely, commercial biotechnology took longer to develop in Europe, except for
the UK. The EU emphasis on government support was important, but as per the
USA, it was recognised many years ago that significant other factors were required,
including good relations with academic departments that specialize in the life
sciences, the availability of educated venture capital, and the development of critical
masses of companies involved in biotechnology and related activities.2
Examples of other influential developments would include: field testing of
genetically engineered plants (1985); patenting of genetically modified (transgenic)
animals (1988); Animal cloning (Dolly the sheep, 1997); and the publishing of a
complete human genome sequence (2003). In recent years the five major
interdisciplinary breakthroughs, - (i) gene sequencing; (ii) developments in
recombinant DNA technologies; (iii) advances in imaging techniques; (iv) the
growth and nature of internetwe development; and (v) nanotechnology - have
played a significant role across the biotechnology sector.
Selected, additional important developments include: in 1980 the US Supreme
Court ruled that genetically altered life forms could be patented, a Supreme Court
decision that allowed the Exxon oil company to patent an oil-eating microorganism.
In 1982, Genentech received approval from the Food and Drug Administration
2
Science advertising supplement, May 7, (1999) p989

19
(FDA) to market genetically engineered human insulin. In 1985, genetic finger-
printing was used for the first time in a court room as evidence of an individual’s
presence at a crime scene. In 1990 the first gene therapy took place on a four-year-
old girl with an immune-system disorder called ADA deficiency and the Human
Genome Project (HGP), the international effort to map all the genes in the human
body was launched at an estimated cost of $13 billion between the US & UK. Kary
Mullins won the Nobel Prize in chemistry in 1993, for inventing the technology of
polymerase chain reaction (PCR).
In addition, 1977 researchers at Scotland’s Roslin Institute cloned a sheep called
Dolly from the cell of an adult ewe – the first substantial mammalian clone. 1988
saw a rough draft of the Human Genome map showing the locations of more than
30,000 genes. On 14th
of April 2003, The International Human Genome Consortium,
led in the United States by the National Human Genome Research Institute
(NHGRI), and the Department of Energy (DOE), and the Welcome Trust Sanger
Institute in the UK, announced the successful completion of the Human Genome
Project more than two years ahead of schedule.
On the 20th
of May 2010, Craig Venter created the genome of a bacterium from
fundamentals and incorporated it into a cell to make first partially synthetic life-
form. The new organism was based on an existing bacterium that causes mastitis in
goats, but at its core was an entirely synthetic genome that was constructed in vitro.
However, further advancement in full synthetic organism development has not
progressed significantly since.
To return to more fundamentals regarding this discipline, biotechnology as a
broad discipline embraces sub-disciplines, which have now become labelled as red,
white, green, and blue. Red biotechnology implies medical processes such as
biopharma, or using stem cells to regenerate damaged human tissues and the future
capacity to generate entire organs in vitro. White or grey biotechnology implies
industrial processes such as the production of new chemicals or the development of
new fuels for vehicles. Green biotechnology relates to agriculture and involves such
processes as the development of pest-resistant grains or the accelerated evolution of
disease-resistant animals. Blue biotechnology, encompasses processes in marine and
aquatic environments, including sustainability of oxygen production and control of
hazardous fresh and marine organisms (Marine Biotechnology & Developing

20
Countries, 1999). Bioinformatics is an interdisciplinary domain, which analyses
biological systems via complex computational systems and consequently is
responsible for a huge proportion of bio-data, and significantly contributed to some
of the advanced recent biotech developments, previously cited (Wang, 2012).
There is a tendency to predominantly equate biotechnology with biopharma,
but the average time required to generate a biopharma product, the risk of failure and
the subsequent regulatory process implies significant development costs despite the
potential for subsequent substantial profits and important bio-impacts. This has
reflected a greater recognition that other biotech domains must develop more and
produce commercial outputs in shorter time frames. This has particular relevance to
many elements of the Atlantic Region of Europe, where one might expect that
biotech territories such as marine, energy, food and chemicals to receive specific
focus and motivation.
1.2 The Nature & Scale of Biotechnology Research
An indication of the breadth of biotechnology, would minimally embrace the
following sub-disciplines:
Agricultural Biotechnology
• Plant biotechnology
• Animal biotechnology
• Biofertilisers, biocides, biological additives, microbial pest control, hormones,
pheromones etc
Aquaculture/Marine Biotechnology
• Fish health & nutrition
•Broodstock genetics & breeding
• Bioextraction & marine bioprospecting
Environment
• Biofiltration & treatments
• Bioremediation, waste management, phytoremediation
• Diagnostics
Food Production and Processing
• Food processing
• Functional foods, additives, nutrichemicals
Forest Products
• Silviculture
• Enhanced industrial bioprocessing

21
Human Health
• Diagnostics
• Therapeutics
• Gene therapy
• Genomics/ Proteomics/ Bioinformatics/ Bioprospecting – genomics & molecular
analysis
Industrial Biotech and General Biochemicals
• Custom bio-synthesis of biologicals
• Bioprocessing
• Custom synthesis of fine chemicals
Medical Devices, Equipment/Supplies and Bioengineering
• Equipment manufacture, instruments, consumables, reagents
• Bioengineering, large scale fermentation & contract manufacturing, down-stream
processing
Mining/Energy/Petroleum/Chemicals
• microbiologically enhanced petroleum/mineral recovery – biofuels/bioenergy
• Cleaner industrial bioprocessing
Nanotechnology
• New materials design, therapeutics, manufacturing processes
Specialist Service Provider
• Contract research and development to the biotechnology industry
• Consulting to the biotechnology industry
Agriculture is a major focus for biotechnology predominantly because societies need
to increase food production via lower cost as population density grows. Early
biotech developments to protect the environment led to reduced use of agro-
chemicals like pesticides, fertilizers and rodenticides. More recently it has generated
environmental friendly crops such as insect-resistant, herbicide-tolerant species and
crops that can fix nitrogen. Other elements of agricultural biotech development,
particularly GM crops have of course generated fears and concerns in many
countries – issues which have still not be fully addressed (Soetan, 2011).
Within biotechnology disciplines, there is a substantial portfolio of unique
biotechnology methods as well (Jungbauer, 2013).
1.3 Economics of the biotech sector
Analysing factors and variables that influence the economic growth of the biotech
sector is now routine and indicative of the importance of this domain in many

22
developed countries (Aggarwal, 2011). In 2009, the bio-based economy in Europe
was estimated to be worth 2 trillion euros in annual turnover derived from
biotechnology related activities alone and provided 20 million jobs.3
The health and industrial sectors that either use biomass or have applications for
biotechnology accounted for 5.6% of GDP in Europe in 2004 (compared to 7.4% for
information and communication technology).
In the decade before the recent economic crisis, the US biotechnology
industry was expanding as expected. According to Ernst & Young’s annual global
biotechnology reports measured in 2008 dollars, US biotechnology revenues
increased from $20 billion in 1996 to $70.1 billion in 2008, while R&D spending in
the industry increased from $10.8 billion to $30.4 billion. In 1996 the industry had
1308 biotech firms, of which 260 were publicly listed; and in 2008, 1754 companies,
of which 371 were publicly listed. Employment in the industry increased from
118,000 in 1996 to a peak of 198,300 in 2003, before declining to 187,500 in 2004
and 170,500 in 2005, and then rising again to 190,400 in 2008 (Lazonick & Tulum
2011). An accurate comparison EU and US biotech economic status based on these
published reports is not simple. In reality, the US hosts the largest biotech sector.
The global biotechnology industry rebounded strongly in 2013, during the
time frame of the ShareBiotech project. Public companies achieved double digit
revenue growth and there was a sharp rise in funds raised. Product successes have
boosted revenues, brought in investors, and large companies have been motivated to
invest strongly in R&D. However, much of the industry’s growth was driven by a
relatively small group of commercial stage companies, which spurred on the rest of
the industry to achieve greater efficiency in their drug development efforts. In an
Ernst & Young report, several findings emerged in their analysis of key performance
indicators.4
These key findings were as follows:
Revenue climbs: Companies in the industries established biotech centres (US,
Europe, Canada, and Australia) generated revenues of US$98.8B, a 10% increase
from 2012. However, virtually all growth came from 17 US based commercial
3
Ernst & Young, 2012, “What has Europe got to offer Biotechnology Companies
4
Ernst & Young report (Beyond Borders, 2014)

23
leaders, defined as companies with revenues in excess of US$500M. European top-
line growth slowed but profits soared.
R&D spending rebounds: R&D spending rebounded forcefully, up 14% from the
previous year, mainly driven by a 20% increase in US spending. This was the first
time since the onset of the global financial crisis that R&D growth outpaced revenue
growth.
Net income slips: Net income was down by US$0.8B, driven in part by the
US$3.7B increase in R&D expenditures during the year.
Market capitalization grew considerably, by 65% to US$791B, catalysed by strong
performances from commercial leaders, which increased overall confidence in the
sector.
Figure 1.1: Funding growth: Biotech companies in North America raised US$31.6b in
2013, a sharp increase from the US$28.7b raised in 2012 and the second highest total since
2003. Fifty biotechs (in the US, Canada and Europe) debuted on the public markets in 2013,
raising US$3.5b, a 300% increase compared to 2012 and the highest one-year total since
2000. (Source: E&Y, Capital IQ, Bio Century and Venture Source)
While, the impact of the financial crisis on the biotech, and in particular, the
biopharma sector was first recognised in 2009, (Lazonick & Tulum 2011), and
despite being a core science and requiring innovative, creative and deliverable
science, as a business it is inevitably driven by money and associated profits, within
a capitalist society.

24
Figure 1.2: Innovation capital; defined as the amount of equity capital raised by companies
with less than $US500M in revenues; increased by 36% and comprised the majority of total
funding for the first time since 2010. Driven by a strong IPO market, US companies raised
US$14.8B in innovation capital in 2013, the largest amount in any year in the last decade,
and 59% of the total capital raised. Meanwhile, the commercial lenders raised US$10.5B in
2013, despite a drop in debt of nearly 50% since 2011. (Source: E&Y, Capital IQ, Bio
Century and Venture Source)
In reviewing biotech start-ups in Finland, the authors after analysis decided,
that a high profitability and low growth biotech firm is more likely to make the
transition to high profitability – effectively higher growth than a firm that starts off
with low profitability. Also, a biotech venture that demonstrates high growth but low
profitability is less likely to become a profitable firm than one that demonstrates both
low growth and low profitability, (Brannback et al., 2009).
This confirms that for biotech companies, previous growth alone is not a
reliable indicator of future performance. Consequently backing fast growing biotech
start-ups does not guarantee business success. Brannback et al., (2009) suggest that
an assessment of the company’s internal resources, capabilities and market potential
could be more useful for prediction.
The global biotech industry is characterized by its requirement for large R&D
investments sometimes associated with uncertain results and infrequent benefits.
This complexity has enforced the belief that governments should positively influence
the sector. The USA as a leader in R&D spending and its consequences, has recently
contributed to its economic recovery by investing in innovation, education and
infrastructure to create future jobs and industries, (Sohn et al., 2013). Strategies to
achieve these objectives include an increase of investment in patent management.

25
The United States has proposed to give the US Patent and Trademark Office
(USPTO) full access to its fee collections and to strengthen USPTO’s efforts to
improve the speed and quality of patent examinations through a temporary fee
surcharge and regulatory and legislative reforms. It should be appreciated as well
that Germany and Austria support SME R&D development and that the majority of
companies, small and large are privately owned, and not dependent on shareholders.
The 2008 global economic crisis has placed far more pressure on government
policies to support economic recovery. However, R&D investments by emerging
economies like China, Brazil and India are expanding at rates often higher than those
in the US, and some European cuts in R&D spending could negatively impact on EU
biotech development as well as determine the number of biotech transfer contracts in
the future. While public sector cuts may improve investor confidence, it accelerates
the decline of science and technology. Biotechnology is one of the sectors most
sensitive to economic investment, implying that it does need government support,
including in the US. A relatively simple model is that public authorities should
facilitate technology transfer from universities and public research organizations to
industry (Sohn et al., 2013).
One nature of technology start-up company change over the past two decades
is that more young and even old people are now involved in the process. A recent
US study showed more University graduates initiating companies than their
academic staff (Åstebroa et al., 2012).
1.4 Biotechnology - Promising a Brighter Future for Europe and the World
Biotechnology contributes to everyday lives, from clothes and how they are washed,
food and the sources it comes from, medicines and even the fuel for transport.
Biotech already plays, and must continue to play, an invaluable role in meeting
people needs.
From new drugs that address medical needs and fight epidemics and rare
diseases, to industrial processes that use renewable feedstock instead of crude oil to
lower the impact on the environment and crops that are able to grow in harsh
climatic conditions and ensure safe and affordable food, biotech can and will
generate economic, social and environmental merits. The development of new
technologies promises a brighter future for the EU and globally. To drive

26
biotechnology forward it needs support from policy makers that supports risk-taking
and the public need to be better informed about how biotech can create a healthier,
greener, more productive, and more sustainable economy.
Healthcare biotech is already benefiting millions of people globally through
treatment of, cardiovascular disease, stroke, multiple sclerosis, breast cancer, cystic
fibrosis, leukaemia, diabetes, hepatitis, and other rare and infectious diseases.
Healthcare biotech is estimated to account for more than 20% of all marketed
medicines and it is predicted that by 2015, 50% of all medicines will be biotech.5
Biotech will ultimately generate more “Personalised Medicine” to diagnose what an
individual patient’s problems are and apply treatment to suit the specific needs of the
patient. The European healthcare biotech comprises in excess of 1,700 companies
and has a market value of more than €17B. The provision of jobs in the healthcare
biotech sector in Europe more than doubled from 2000 to 2008, showing an increase
of 158%.6
Industrial biotech helping to minimise mans impact on the environment while
boosting manufacturing output has generated increased employment. Industrial
biotech or “white biotech” used microorganisms and enzymes in the production of
detergents enabling clothes to be washed at lower temperatures, and in the
production of paper and pulp, clothing, chemicals etc., is done in a more
environmentally, efficient way that uses less energy, less water and produces less
waste. Agricultural products and organic waste can be used to produce biofuels e.g.
bioethanol, bio-diesel.7
In the battle against “climate change”, white biotechnology
can save energy in production processes which lowers the emission of greenhouse
gasses, a reduction of between 1B and 2.5B tonnes of CO2 equivalent per year by
2030.8
Europe is a world leader in the production of enzymes, and produces 75% of
the world’s enzymes.9
5
OECD, 2012: The Bioeconomy to 2030: Designing a Policy Agenda
6
Office of Health Economics, UK
7
Europa Bio, 2008
8
WWF Denmark, 2009
9
EU Commission, 2010

27
Agricultural biotechnology or “Green Biotech” can increase the food yield
from land by 6% to 30% which helps protect biodiversity and wildlife, (Gilbert,
2010). Agricultural biotech offers built-in protection against insect damage,
resulting in a reduction of pesticide spraying. Green biotech reduces fuel use and
CO2 emissions, and less land is required enabling farmers to grow more food,
reliably, in harsher climatic conditions.10
In 2009, this was equivalent to removing
17.7 billion kg of carbon dioxide from the atmosphere or equal to removing 7.8
million cars from the road for one year.
Agro biotech plants protect themselves against weeds and pests, so there is
less soil disturbance and this increased the efficiency of water usage and will also
reduce the risks of flooding as the soil will be better able to maintain water via
absorbance.11
By offering new improved and adapted agricultural crops such as
drought or saline resistant plants, agricultural biotech can contribute to the
Millennium Development Goals on reducing poverty and can help increase food
security for a growing global population estimated to reach 10b by the year 2050.12,13
It is likely that the use of the different sectors in biotechnology as sustainable
technologies will be a major contributor to cater for an ever-growing population.
1.5 Collaboration between Universities & Industry
As expected, industrial firms use a variety of relationships with university research
centres to contribute to development. Large companies have higher intensity
knowledge transfer and research support relationships in order to strengthen skills
and knowledge and gain access to university facilities for advancing non-core
technologies. Conversely, SMEs employ technology transfer and cooperative
research relationships in order to strengthen skills and knowledge and gain access to
university facilities for advancing core technologies (Santoro & Chaktabarti, 2002).
10
www.pgeconomics.co.uk
11
Impact of Genetically Engineered Crops on Farm Sustainability in the US, 2010
12
http://www.gatesfoundation.org
13
WHO, 2010

28
In Germany, specific HEIs, particularly Fraunhofer’s are focused on working with
companies and attract a third of their funding as a consequence.
A recent PwC report14
regarding Regional Biotechnology generated a number of
recommendations, including:
 KBBE Aspects (Knowledge Based Bio-Economy) - ~ 9 recommendations,
including increase funding for SMEs and creating more translational research
centres in specific KBBE domains
 Funding
 Incubators – create new bio-incubators at cluster or regional level
 Technology Transfer (TT)
 Cluster Organisations – 10 recommendations, but does not specifically
identify enhanced HE interaction or Core Facilities as issues, although there
is a previous reference to incubator facilities. A more detailed review of
cluster issues will follow.
 Entrepreneurial Culture
A partial emphasis of this proposal is again linkage, networking and formal clusters,
but rather simplistically does not draw attention to the benefits of accessible
technology facilities and the potential cost savings of HEI connections. While, this
project inevitably supports and promotes the benefits of biotech industry-HEI
connectivity, it is accepted that a large proportion of HEIs in many countries have a
history of slow delivery of industry research requirements, knowledge insecurity and
lack of understanding of business needs and mode of operation.
The formal recognition of the importance of HEI-business collaboration for
innovation and subsequent exploitation did occur many years ago and Germany did
introduce the first Fraunhofer institutes in 1949. Despite the existence of vocational
orientated Polytechnics in the UK from the 1960s, the sector was converted to
standard university in 1992, with a resultant decline in industry interfacing. Other
countries such as Ireland retained its more minor equivalent, the subsequent Institute
of Technology.
The Lambert Review of Business-University Collaboration was a report
by Richard Lambert, published in the UK in 2003, which aimed at improving the
relationships between the HE science base and the business community (Lambert,
2003). The UK Lambert Review recommended significant enhancement of the scale
14
PwC 2012

29
and quality of business–university collaboration. Since the 2008 crisis, that request
has probably grown further in part associated with funding.
Networking between universities and the business community is a critical
component of an efficient innovation ecosystem (Wilson, 2012). There are several
established networking tools at national and regional levels that create links between
universities, business and research technology organisations.
The loss of manufacturing industry has encouraged countries like the UK to
promote innovation in newer areas such as biotechnology. The emergence of the
‘bioeconomy’, however, has been highly uneven, with concentrations of activity in
certain countries and particular regions in those countries. In the UK, for example,
there are four major concentrations of the bioeconomy, each of which depends on
selected types of knowledge inputs into the innovation process and physical status of
the region (Birch, 2009). These factors include - differences in public science base,
knowledge spill overs and extent and size of biotech firms. Some regions have large
firms that can provide an ‘anchoring’ effect.
Lambert very much concluded that to increase knowledge transfer requires an
increase in research activity and demands amongst the non-academic communities,
rather than increasing the supply of ideas and services from universities. Over the
following decade, the quality, quantity and nature of industry-HEI collaboration in
the UK does appear to have increased (Santoro & Chakrabarti 2002, Hewitt-Dundas
2012, Wilson 2012,). These important points have been considered retrospectively
in the context of the foundation and delivery of this research project.
1.6 Research Infrastructure
Since the advent of microprocessors and subsequent engineering and software
development, research instrumentation and infrastructure have evolved considerably
in all science domains.
It has been predicted that the 21st century will see significant growth of a
bioeconomy based on applications of biotechnology as important and influential as
the IT was at the end of the 20th century (Lex, 2008).
Research infrastructure has become a major theme of EU strategy to grow research
and its economic outputs. The ERA-NET scheme was launched in 2002 as part of
the Sixth Framework Programme (FP6). It was designed “to step up the cooperation

30
and coordination of research activities carried out at national and regional level in
the Member States and Associated States, through the networking of research
activities, including their mutual opening and the development of joint activities”. It
therefore represented one element of progression towards the creation of the
European Research Area (ERA).
Research infrastructures (RIs) are of strategic importance in the context of the
European Research Area. Excellence in research requires excellent infrastructures,
for data collection, management, processing, analysing and archiving; this is the case
in all disciplines. Infrastructures are imperative for the advancement of science and
for scientific communities; they lead scientific development in new directions, create
an attractive research environment, and support international collaboration.15
1.7 Core Facilities
HEIs have long been recognised as a source of skill sets and research technologies,
including core facilities, (Santoro & Chakrabarti, 2002). A core facility is a
centralized, shared resource that provides scientific investigators with access to
instruments, technologies, services and expertise – this is consequently sometimes
now referred to as a technology core facility (TCF), an abbreviation that will be used
in this project.
A recent analysis of selected US TCFs16
explored a number of issues that can
influence their sustainability, organisation and operation of:
1. Cutting services or raising rates
2. Growing institutional use
3. Marketing services outside of the HEI
4. Better managing equipment transactions
5. More proactively managing start-up packages
6. Exploring possible core consolidation or shut-down
7. Sharing core personnel and creating satellites
8. Developing inter-institutional core partnerships
9. Crafting more disciplined core financial arrangements.
A number of these issues arose during the conduct of this project as well, the
consequences of which will be raised in the Discussion.
15
Science Europe (http://www.scienceeurope.org/), ERA Instruments (http://www.era-instruments.eu/)
16
California Nano-Systems Institute, UCLA, 2012

31
All biotech domains within the life sciences require access to core facilities to
resource advanced research, (Janssens et al., 2010).
High throughput screening (HTS) core facilities generate large amounts of data and
it is recognised that they benefit significantly when managed by appropriate
software, (Tolopko et al., 2010). Similarly, microarray core facilities are
commonplace in biological research organizations, and need systems for accurately
tracking various logistical aspects of their operation, particularly concerning the
number of test samples and the handling of data. A simple solution is to use
Microsoft Excel for tracking the transactions, but this often requires redundant data
entry into multiple spreadsheets, and is prone to error. Lab information management
systems (LIMS) software addresses this problem by storing information in
interrelated tables with more rigorous data entry mechanisms in place to prevent
inaccuracies and reduce redundancy charges that researchers incur necessitate a
highly organized and accurate system for managing this information, (Marzolf and
Troisch, 2006)
The cost and scale of core facilities influences the need for shared access,
(Murray 2009). The concept of core facilities is now widely accepted and
increasingly recognised that a management model must be applied to ensure viable
outcomes (Haley, 2009).
Core facilities are a common base model in the design of academic, non-
profit and commercial biological research organizations as well. In this model,
multiple research groups utilize the specialized resources provided by core facilities,
such as cell culture, sequencing, and genotyping and microarray services. Often
there is a mechanism by which these facilities charge the individual research groups
for the products and services they provide to them – in such a HEI model, individual
Departments have to pay the corresponding TCF for access to resources. Managing
a core facility typically involves keeping records of consumables, tracking samples
processed, and recording charges to researchers for products and services provided to
them. The considerable number of samples processed and the substantial charges that
researchers incur necessitate a highly organized and accurate system for managing
this information
Due to the rapid and wide development of laboratory technology, the speed at
which knowledge becomes redundant is increasing, implying regular training up-

32
skill provisions. With each new testing instrument purchased and each new product
to be tested in a laboratory, the gap can be wider. In order to prove its competence
and become accredited, a laboratory must also prove their staffs are competent. In
order to keep up with changes constantly occurring, laboratories have to constantly
manage the competence of their staff. Effective and efficient management of the
staff competence, knowledge, skills, education, and training can be a very
demanding requirement of the standard, especially for those laboratories which
operate in a free market and have little or no external financial support, (Stajdohar-
Paden, 2008).
iLab Solutions Inc., an example of a company that specialises in management of
core facilities, together with some competitors was subject to a review within this
project. The company conducted an annual survey of US TCFs in 2011 to review
structure and progress.17
In total, 246 individual core managers and directors from
over 1001 institutions, representing more than 30 different core types, responded to
the survey. This study shows that business growth and utilization rates increased
from 2009 to 2010 (60% of cores with growing volume, 7% experiencing declines).
The survey also indicated a number of key issues in core operations:
 Most cores charge for services (93% of cores);
 Chargeback income provides the most important revenue stream (49% of
revenues);
 Core managers tend to spend the largest portion of their time directly
providing services to their customers (56 hours per month);
 Labour constitutes the largest area of expense (50% of expenses);
 Most TCFs still rely on basic spreadsheets to manage administrative tasks;
 The most common means of staying at the forefront of the core’s scientific
interest are through word-of-mouth and conference attendance;
 Social media have made only limited inroads in the core community; and
 Most cores do not track the publications which result from their services.
The most recent 2013 iLab survey, was based on only 60 institutions in the US, EU
and Asia Pacific and the results suggest, demand for access to TCFs continues to
rise, but this is reducing the capacity of TCFs to undertake their own research and
17
iLab 2011http://www.ilabsolutions.com/

33
pressure demands consume staff time and require adoption of new tools to manage
the process.18
1.8 Core facilities & Higher Education Institutions
Formal as opposed to traditional informal, location, resourced and managed core-
facilities are becoming a principle component of science parks and physical
interfacing between industry and HE. For example, the Daresbury Science &
Innovation Campus – Innovations Technology Access Centre (I-TAC) provides
access to some core facilities for start-ups, which emphasises the importance of cost
effective access to fundamental and advanced technology and research facilities.19
The notion of networked core facilities has evolved in many countries and the
web is a common mode of connection and interfacing. The Victorian Platform
Technologies Network (VPTN) in Australia has some correlation with ShareBiotech
objectives. The network has currently 111 facilities over 38 different Universities,
Medical Institutes and Government organisations. Monash University was one of
the main organisations involved in setting up and developing the VPTN. The
network primarily focuses on biomedical and nanotechnology facilities. VPTN
focuses on core facility management systems that will bring better access and
awareness of the networks facilities and their efficiencies. In keeping with
ShareBiotech but effectively progressing further as a real network, VPTN also
engaged with EU, US and Israeli IT companies to set-up core facility management
software that will be integrated across the State so that all the facilities in the
network are visible and can be booked from one site. This required the setup of a
web interface on the front of the software where any customer can access the
required facility. The facilities and host organisations have control over their
facilities and who they approve to access, rules and custom configuration, in return
they allow the VPTN to collect high level information (desensitized) about usage and
capacity to give back to the State government to help in planning and future
investment decisions.
In the USA, AMDeC F.I.R.S.T. ™ (Facilities, Instrumentation, Resources, and
18
http://www.ilabsolutions.com/wp-content/uploads/2013/09/20130830-BMS2013.pdf
19
www.stfc.ac.uk/itac

34
Services & Technologies) was established in 1997, as a real-time web resource
hosting up-to-date information about technology and research resources available at
biomedical core laboratories in the New York tri-state area. AMDeC F.R.S.T.
effectively networked 100 Core Facilities, 300 services, and 400 instruments listed
on AMDeC F.I.R.S.T., available for immediate use on a discounted, fee-for-service
basis.
AMDeC definitely contributed to collaborative biomedical research via team science
initiatives, member services focused on cost savings and access to innovative core
facilities, and private sector partnership with the academic biomedical research
community. However, as a not-for-profit virtual TCF, AMDeC closed in 2013 due
to financial problems.
Traditionally, the presence of experienced academics and the generation of
able graduates were always considered obvious benefits for any technology sector.
It is a simple reality that in many advanced countries over the past twenty years, as
the percentage of a population attending third level HE has increased, the standard
and quality of programmes delivered has declined, despite the introduction of greater
regulatory structures and metric records. The poorer laboratory skills of many
graduates and postgraduates can consume more time and cause problems to industry.
It is crucial that a core facility must have experienced staff and provides proper
updated training for users (Piston, 2012).
Core facilities generally as previously indicated, implies relatively advanced,
complex technology that is not easy for small companies and organisations to
procure and manage themselves, hence a need for sub-contraction or collaborative
access. However, the advent of small cheap IT technology such as Arduino and
Raspberry pi may have some positive effect in the future on the design, nature,
access and cost of some selected laboratory tools (Pearce, 2012).
Obviously, HEIs are not just involved in industry collaboration in this
context, but are a major generator directly and indirectly of companies, mainly via
spin-offs. A recent analysis suggests that the local environment where the university
spin-off process is initiated appears to influence the development of other technology
dependent business ventures, (Rasmussena et al., 2014).
The escalating scale of laboratory technology development, the increased
need for access to selected core facilities and the introduction of a variety of

35
mechanisms in the US, EU and elsewhere to facilitate this process, particularly for
SMEs, contributed to the generation of an element of this project programme.
A traditional high ranking university engages in teaching and research and
resources and funds both effectively and students engaging in undergraduate degrees
are aware of on-going research. Delivering research for industry within an HEI does
however impose different requirements and nature relative to traditional academic
research. Consequently many universities (and IoTs in Ireland) conduct mainly
teaching, while research is located in specialized institutions where there are no
students or some postgrads/postdocs registered in a traditional university, examples
being CNRS/CSIC/Max–Planck and Fraunhofer in Germany. Because of its similar
work and structure, the Max Planck Society traditionally maintains close institutional
relations with both the French Centre National de la Recherche Scientifique (CNRS)
and the Spanish Consejo Superior de Investigaciones Cientificas (CSIC). There is a
cooperation contract with both organisations to promote collaboration in the form of
cooperation projects and joint research programmes.
The Laboratories Europeens Associes (LEA; currently 6), and the
Groupements de Reserche Europeen (GDRE; currently 8) have been very successful
with work undertaken with the CNRS and the CSIC, also maintain large research
facilities, including the Institute of Millimeter Radio Astronomy (IRAM); jointly
with the CNRS and the Spanish Instituto Geografico Nacional (IGN).
1.9 Laboratory Informatics
Laboratory informatics is defined as the specialized application of information
technology to optimize and extend laboratory operations. It encompasses data
acquisition, lab automation, instrument interfacing, laboratory networking, data
processing, specialized data management systems (such as chromatography data
systems), laboratory information management systems, scientific data management
(including data mining and data warehousing), and knowledge management
(including the use of electronic laboratory notebooks). Laboratory informatics has
risen with the tide of informatics in general and is one of the fastest growing areas of
laboratory-related technology.

36
1.10 Biotechnology Development in Europe
In the late 90s, some EU members did believe that technology policy should have a
model that relates to and supports regions on the basis that many tech sectors,
particularly biotech tend to develop within relatively close geography. The German
Federal Government initiated a contest, in which Germany’s leading Biotech regions
could compete for public funding (Dohse, 2000). This implementation was in
recognition of the fact that the US and UK had developed significant biotech sectors,
while Germany still retained a substantial chemical industry, it had been slow to
progress biotechnology. In the UK, Lord Sainsbury’s 1999 report, Biotechnology
Clusters, the UK held the largest biotech sector in Europe and was 2nd
to the US,
(Sainsbury, 1999). The Report made a number of recommendations to rely on the
cluster model to increase networking and the resultant scale of the bio sector – but in
the next few years the UK biotech sector declined considerably. Despite the loss of
multiple numbers of large biotech companies, most bought up, in recent years, the
UK biotech sector has grown again, with an emphasis on biopharma and clustering.
2013 showed significant recovery by the UK biotech sector in terms of number of
start-ups, number of public companies, and growth in value of company and scale of
anticipated new products, especially drugs (Ledford, 2013).
At the time in Germany, as part of the Federal Government model, a cluster
centre eventually subject to interview by this project (see Methods & Results
sections), was funded under this regional approach. Germany’s federal status tends
to support this approach, while some EU members and Atlantic Region sectors such
as Ireland, UK and France tend to revert more to capital control. However, within
the German federal structure, inevitably selected public and private organisations
may be prevented from initiating certain technologies, if they are considered to be in
conflict with another region.
The State had a major role in 1985-1995 in stimulating the initiation of the
biotech sector in Germany, although substantive private investment was also a key
driver (Champenois et al., 2009)]. Engagement of government in biotech initiation
other than public sector research did occur in a number of EU countries, while the
US might always present as private driven, the State would contribute via policies,
funding and resources.

37
More recently, there has been interest in examining the biotechnology sector
in new EU Member States and prospective candidate countries. Hungary, the Czech
Republic, Poland and Estonia were shown to be the main new members
demonstrating biotech development (De Greef & Frei, 2009). In part, these
countries are attracting outsourced contracts from other EU countries and globally on
the basis of cost and delivery, although sustainable growth on this basis is unlikely
due to competition with China and India.
In the early 2000s, growing EU authority recognised that Europe tended to
underperform in producing globally competitive technology companies and wanted
to implement methods to address this. One such approach was the EuroTrans Bio
(ETB) programme, still in progress (Abbanant, 2004). The overall objective of
EuroTrans-Bio (ETB) is to provide the European biotech industry with a funding
program dedicated to foster cooperation of R&D&I active SMEs (R&D &
Innovation) and their academic partners across European Member States (MS). The
strategic approach towards this program is presented by focusing on two essential
components:
• Increase impact by transferring national resources into the European Research Area
(ERA)
• Leverage of FP/H2020 funds and sustainability of the ERA-NET scheme20
In the mid-2000s, an optimistic EU aimed to achieve a goal of becoming the
foremost knowledge-based economy in the world and a true ‘Innovation Union’, in
which biotech SMEs were considered vital. As is later discussed, this aspiration has
yet to be achieved. Increasing connectivity between SMEs and larger companies and
HEIs as an element of enhanced regulatory and policy framework was part of
EuropaBio’s SME Platform.
The Europa-Bio report, year 2013, 2014 cited a number of issues affecting the
biotech sector, which was defined as largely being based and dependent on SMEs.
1. Biotech is high-cost, high risk and long term. As a result, many biotech
companies remain non-profit for quite some time and this consequently
20
https://www.eurotransbio.eu/lw_resource/datapool/_items/item_71/prague_fiche_eurotrans-bio-
final.pdf

38
implies high risk for external investors compared to other disciplines such as
IT.
2. Most biotech SMEs are funded by capital, rather than by cash flow, so that
when sources of capital decline the company survival is at risk.
3. Biotech products have to undergo long and expensive development and
regulatory approval procedures and funding for these stages has been difficult
in the EU.
4. Many EU biotech companies are not traditional SMEs (less than 250
employees) but are micro-enterprises consisting of <10 staff and their
capacity to deal with administrative burdens is therefore low.
In 2008, a senior EU biotech official, Maurice Lex published a paper confident that
post FP7, and new investments in R&D and business and infrastructure will ensure
that biotech develops significantly in the EU in 21st
C – this is in keeping with the
previously cited earlier 2000 aspiration (Lex, 2008). How and where and the effect
of different political governance of course cannot always be predicted.
A high proportion of European citizens in a 2010 survey were optimistic about
biotechnology (53% optimistic; 20% ‘didn’t know’). They were however even more
optimistic about brain and cognitive enhancement (59%; 20% didn’t know),
computers and information technology (77%; 6% didn’t know), wind energy (84%;
6% didn’t know) and solar energy (87%; 4% didn’t know), but were less optimistic
about space exploration (47%; 12% didn’t know), nanotechnology (41%; 40% didn’t
know) and nuclear energy (39%; 13% didn’t know) (Gaskell et al.,2010).
Time series data on an index of optimism showed that energy technologies – wind
energy, solar energy and nuclear power – are on an upward trend – what is called the
‘Copenhagen Effect’. While both biotechnology and nanotechnology had seen
increasing optimism since 1999 and 2002 respectively, in 2010 both showed a
similar decline – with support holding constant but increases in the percentages of
people saying they ‘make things worse’. With the exception of Austria, the index for
biotechnology was positive in all countries in 2010, implying more optimists than
pessimists – however, Germany joining Austria in being the least optimistic about
biotechnology and in only three countries (Finland, Greece and Cyprus) was there an
increase in the index from 2005 to 2010.21
There is nevertheless, a strong possibility that
21
Europeans & Biotechnology in 2010, EC Survey

39
positive belief in biotechnology has further enhanced since 2010, even if the majority of
citizens are not really aware of the breadth of the discipline and its potential future impact.
Prior to the initiation of ShareBiotech, it was apparent that Europe’s biotech
sector had tripled in size over the previous decade, expanding to include 2,350
companies in 2006 compared with the 700 that only existed in 1996. Post-2008,
cluster development became a major EU issue. Even in 1996, Germany’s Bio-
Regio Initiative program devoted the deutschmark equivalent of $84 million to
finance biotech cluster development with an outcome of a lot of new companies.
Maintaining success and continuous commercial innovation is not however
predictable and according to a 2007 survey conducted by the German Ministry of
Education and Research a proportion of such companies failed. The BioCluster
2021 differs from the original model in that it is specialising to seek to develop
centres of industrial expertise, such as biocatalysis, biopolymers and protein
production, (Nasto 2008).
1.11 Industry Collaboration
An analysis fourteen years ago attempted to determine what issues influenced
industry collaboration in research (Hagedoorn et al.,2000). According to this study,
companies may participate in research partnerships in order to:
 Reduce transaction costs in activities subject to incomplete contracts;
 Broaden the effective range of activities;
 Increase efficiency, synergy, and effectiveness via the creation of networks;
 Access external complementary technologies and capabilities to support new
developments with business benefits;
 Promote organizational learning, internalize core competencies, and enhance
competitiveness;
 Create new investment options in high-opportunity, high-risk activities;
 Internalize knowledge spill-overs and enhance the exploitation of research
results, while increasing information sharing among partners;
 Reduce R&D costs;
 Pool risk and co-operative competition.
This analysis went on to claim that Governments have promoted and supported
research partnerships in order to:
 Correct market failures in R&D investment, particularly in the context of
invalid research;
 Accelerate technological innovation, aiming at increased international
competitiveness; and
 Increase technological information exchange among firms, universities, and
public research institutes.

40
Despite the multiple reasons and drivers identified in this 2000 review, it also
confirmed that there can be negative effects associated with collaboration. Despite
the range of benefits, partnerships and collaborations can potentially block
competition and create various kinds of static and dynamic monopolies.
Nevertheless, this relatively early analysis states a predominant benefit that
associates with a basis for many, collaborations and networks, the desire to reduce
R&D costs. Access to advanced technology facilities and the necessary skills to
generate viable outcomes, is an increasingly accepted issue and became core
exploratory task of this project.
There is a tendency in a number of EU countries including Atlantic Region,
such as, Portugal, Italy, Austria and France, for their universities to preferentially
recruit former graduates. This model, while no doubt creates a positive internal
environment, automatically reduces connectivity with global institutions and
associated networks, and the attraction of different knowledge and experience (Niosi,
2011). Conversely, the US encourages interregional university networks and
collaborations with R&D companies and public laboratories – this culture developed
in the UK as well and more recently aspects of it were applied in Ireland. A
common language across the US is no doubt another obvious advantage to facilitate
linkage and communication. Despite, a tendency of the EU to utilise English as a
leader language, in reality it has more than 20 major languages plus many regional
ones, which accounts for basic communication difficulties and reduces mobility and
as a result, interaction between HEIs and companies across the EU (Niosi, 2011).
The fact that the majority of important global science and technology publications
are in English, imposes an information need on practising scientists, but inevitably
language and HE and business culture differences across the EU reduce
communication and mobility relative to similar scale regions in the US – this is an
issue that will decline with the passage of time. Formal EU policy to encourage
cross-country collaboration and web technologies have accelerated research and
business interactions across the EU significantly, but most European researchers still
tend to live in a region within a single European country (Eurobarometer, 2008).
In reality, bringing the best researchers, developers and resources together ultimately
benefits from global rather than just national or regional links, and this of course is a

41
practice being pursued by some key companies and HEIs. The ShareBiotech project
explored some innovative Atlantic Region mechanisms for mapping and enhancing
cross-regional networks.
1.12 IP & Tech Transfer
Patenting became a larger and more important exercise for US universities by the
early 2000s and this different strategy also occurred in the UK but probably to a
lesser extent in EU universities (Owen-Smith, 2003). By 2014, the situation is
extended in most nations. Certainly, IP is now global and biotech is a major section
of patents (Singh et al., 2009).
In recent years while the demand for patenting in biotech has increased,
achieving it has become more complex despite the actual numbers increasing
significantly in most countries. A biotech patent not only needs to be innovative, but
also highly effective and specialised (Simon and Scott, 2011). Registering a patent
usually supports the attraction of more funding and investment to progress the
commercialisation and for biotech products that require considerable development
time, this is a traditional requirement.
The biotech industry reflecting the time and cost of product development and
the fact that the latter goes through multiple stages, is prone to the generation of
many patents to secure protection and enhance company value. This has been a core
biotech model for many years (Taylor et al., 2000). In the US, where multiple
alliances with partners will be set-up by a company to secure funding and support, a
greater scale of specialist research inevitably follows (Zidorn and Wagner, 2012).
As the company progresses, more specialist research will occur (Kim, 2011).
1.13 Clusters
Biotech firms obviously have to develop new products to create business value,
(Deeds et al., 1999). The exchange of ideas across industries, when it occurs depends
on a number of activities, individuals and resources, but physical location is a
contributory factor, (Desrochers & Leppälä, 2011). Physical location maybe
facilitated by participation in a cluster structure as indicated in the previous account
of cluster evolvement and issues.

42
A cluster typically assumes a group of interconnected companies and other
institutions embracing amongst other, services, manufacturing, suppliers and HEIs
within a region (Su and Hung, 2009). Clusters are probably a common structure for
biotech, because, the time, costs and resources required for biotech product
development are frequently so large, that independent start-ups would typically have
difficulty progressing a development. Key individuals, economics and dynamic
networking no doubt influence the initiation and growth of a cluster. While,
referencing to clusters tends to cite the historical classics, Boston, Cambridge, Bay
Area (etc.), as defined by Porter (Porter 1998), there are numerous new,
‘spontaneous’ biotech clusters developing in designated areas across the world.
More extensive geographical linkages are an element of this project.
W.W. Powell of Stanford University believes three elements are critical to the
formation of productive business clusters (Powell, 2010):
•Multiple types of organizations
•A catalytic anchor tenant that protects the openness of the community and allows
multiple views to be heard.
•Cross-cutting local networks
The first and third of these are highlighted by many other analyses as well and
represent a basis of an aspect of the ShareBiotech approach.
Since 2008 there has been expanded EU emphasise on the importance of clusters and
networks for development of the biotech sector, (NetBioCluE 2008). While initial
clusters such as Cambridge, which commenced in the early 70s were occurring long
before the impact of modern networking, networking is considered an important
element and as previously stated, the EU has for some years been convinced that
clustering has positive impacts on economic development, (Ketels 2012). Ketels
report defined four network programmes with potential for economic growth and
these emphasise networking and formal cluster creation:
1. Support of networks in emerging industries and clusters
2. Establishment of national cluster platforms to provide shared services and
connect firms across regions
3. Support for networks of SMEs active in areas with positive externalities, like
innovation and exporting to new markets
4. Networks as part of more comprehensive efforts to enhance regional
competitiveness

43
The nature of networking has of course changed since the advent of the web. For
example, social networks initially linked to career mobility emerged and became an
important element of skills and idea sourcing within the San Diego biotechnology
cluster, and formal government drivers in Southern Germany (Casper, 2007). The
nature of communication in virtually all elements of human society has obviously
changed dramatically since the development and progression of internet technology
and the generation of the web. With multiple aspects of communication being
critical to the delivery and success of clusters, all standard techniques are
implemented, and not surprisingly, a cluster in Scandinavia, devoted to wireless
communication technology, employs and exploits these current and emerging
systems to facilitate the cluster (Richter & Park, 2012). This also supports the view
that a cluster must innately be a promoter, disseminator and user of new
technologies.
Since Porter’s work, there have been numerous analyses and proposed
models regarding cluster development, most of which, distinguish,: (i) spontaneous
clusters, that are the result of the spontaneous co-presence of key factors; (ii) policy
driven clusters, that are initiated and driven by the strong commitment of key
government leaders in an attempt to address industrial decline or as a deliberate
decision to generate a biotech sector. In some regions or countries, both forms of
cluster creation may exist. Biotech clusters in EU, except the UK is largely
government policy driven. The Heidelberg cluster in Germany, largely biotech had
to inevitably address survival and growth when the public funding subsequently
declined (Chiaroni & Chiesa, 2006). A decline in public funding, supportive of
cluster management and development has not since been uniformly addressed across
the entire EU.
A recent Irish report devoted to innovation did not fully embrace the funding
issues. It embraced amongst other basic topics, Knowledge Transfer, Skills Strategy,
Innovation through public procurement, regional innovation through networks,
clusters and gateways, IP. The ‘gateways’ referred to a government intention to
bring networks of towns together. The Gateway model was never implemented and
has now effectively disappeared. The report, despite the title is not innovative and
probably indicative of government knowledge deficits regarding the real world of

44
science/tech and transfer that generates innovative companies, (Innovation in Ireland
– Policy Report 2011).
The 2009 EI summary of aspects of the Irish biopharma and biotech sectors
implied the existence of clusters. Table 1 is evidence of collaboration between
selected companies, but is not indicative of a traditional cluster; evidence of
connection with HEIs not present. A number of the cited companies are SMEs and
their collaboration in effect reflects sub-contraction of work. Within the EU,
promotion of particular models tends to persuade many members to claim their
commitment to them, even if real evidence is limited.
Table 1.1: Breakdown of Irish companies per sub-sector
Source: Enterprise Ireland; Irish Bio pharma Clusters 2009
Ireland’s national biotechnology program is driven from its government’s significant
emphasis on the sector through dedicated funds targeting technology

45
commercialization, R&D infrastructure development and enhancement, and
marketing efforts looking to bring international talent and facilities in-country.
Almost every major university has resources focused on biotechnology studies due
to commitment of the government’s program for research in Third Level Institutions.
However, post “Celtic Tiger” the government embarked on a program of austerity
which saw reduced funding for research to HEI’s research projects which has done
little for Ireland to position itself as a leading European-based location for several
industries, including biotech. Among Ireland’s challenges, it must maintain its focus
in life science fields to grow and retain its related commercial base, and ensure that
academic/industry collaboration, technology transfer and commercialisation efforts
maximise investment in the biotech area. Addition efforts to gain critical mass and
clusters within the sector are needed to ensure that key portions of the R&D and
commercialization activities remain located within Ireland to develop a domestic
expertise to encourage future development, thereby creating a virtual cycle of
innovation; Department of Trade & Enterprise, (DETE, 2008).
The 2011 OBN BioCluster Report review of the Oxford biotech cluster
presents and raises some interesting points in terms of people and finance:
The scale and success of the clusters around Boston, the Bay Area and San Diego
reflects that the companies access the resources and networks that the clusters offer.
This translates into remarkable statistics; nearly 17% of residents in the State of
Massachusetts are now employed in the life sciences sector. Despite a very long
cluster history, some years ago it was pronounced that the UK would need to
stimulate innovation in biotech clusters to have a significant impact, (Rees 2011).
The Oxford cluster relative to Cambridge does appear to be interesting. The amount
of investment in the bioscience industry in Oxford increased between 2008 and 2011
from $108 million to $168 million and from $433 million to $874 million in the UK
from 2007 to 2010, respectively, despite the global financial crisis. However, in
Oxford and the UK overall, the primary biotech sector for investment continues to be
the traditional DDD (Drug Discovery & Development), rather than newer sectors.
1.14 The Clustering Concept
Cluster development also referred to as “cluster initiative or Economic Clustering “is
the economic development of business clusters. Since the cluster model was first

46
proposed by Michael Porter in 1990, it has attracted attention from governments,
consultants and academics. The cluster concept has been adopted globally by many
governments and industry and has been recognised as a means to stimulate urban and
regional economic growth. A continuing trend of cluster initiatives was adopted in
the 1990s globally. The first comprehensive global study of cluster initiatives was
reported in the “Cluster Initiative Greenbook” which was published by Orjan Sovell,
Christian Ketels and Goran Lindgvist (2003), with a foreword by Michael Porter.
The report was presented at the annual meeting of” The Competiveness Institute”
(TCI) in Gothenburg in 2003 and a follow up study in 2005 covered more than 1400
cluster initiative organisations globally.
SMEs, public or private companies and multinational organisations represent
the core of the cluster, the evolution of these elements and the relationships they
form between them shape the cluster development model; regardless of its size,
complexity and specialisation of production processes, the complexity of the cluster
is given by the number of firms that form it.
1.15 The importance of clusters
Economic agglomerations, or clusters, have captured the attention of policy advisors
worldwide. Many countries (e.g., Canada, Australia, Germany and the United
Kingdom) have adopted clustering as a preferred economic strategy for generating
higher rates of invention, innovation and economic growth (Ryan & Phillips, 2003).
Porter (1998: 197) defines clusters “as geographic concentrations of interconnected
companies, specialised suppliers, service providers, firms in related industries, and
associated institutions” (Porter, 1998). A successful or potentially successful cluster
commonly has a strong base of university and government labs and production
facilities, which provide access to expensive specialised skills and machinery, as
well as a significant amount of informational knowledge that is not visible is
embedded in the larger community – also known as tacit knowledge. The
development of a cluster is more than just co-location; it provides an environment
for relationships. As a result, the organisations that are active within a cluster both
compete and collaborate, thereby facilitating the growth of the local economy.
The analogy of the cluster ‘jig-saw’ puzzle (Martin & Sunley, 2002) may be
used to characterise a successful cluster, as it contains all the necessary ‘pieces’ –

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