Abstract

Biotechnology entrepreneurship is important for bringing beneficial scientific discoveries to the awareness and use of society. Although iGEM is an open source competition that does not in itself focus on business creation, it begs to question what the possibilities could be if it did. Entrepreneurship uses the market to find a problem and solve it. By using business methods as a scaling method, biotechnology can provide solutions for a larger variety of problems and to a greater number of people. In sum, biotech entrepreneurship is a mechanism for spreading good ideas and making useful products available to those that need them.

Furthermore, understanding enabling factors in biotech entrepreneurship can help bring awareness to biotech and promote entrepreneurship for iGEM participants and scientists everywhere. Therefore, the aim of this research is to establish the most significant enabling factors in relation to biotech and synthetic biology (SynBio). From there, future steps can be made to promote entrepreneurship in the scientific realm.

The analysis will begin with a presentation of the hypothesis, research model and objectives. The next sections provide a qualitative and quantitative analysis of the research. The concluding sections involve a list of suggestions and next-steps on how the data can be used for entrepreneurship.

Research Question, Research Objective and Research Design

Our theory holds that if certain enabling factors exist for biotech business creation and success, then biotech businesses will be founded. If this is true, then further research is needed to understand the enabling factors in biotech entrepreneurship in order to further promote its success. We assume that the factors that facilitate business creation and biotech innovation also extend to the realm of biotech entrepreneurship.

Research Objective 1: Establishing a theoretically grounded framework to understand the enabling factors that facilitate entrepreneurship in biotechnology.

Research Objective 2: Substantiate the theoretical framework and investigate the motives, barriers and decision criteria that leads to business creation in biotechnology and SynBio.

Research Objective 3: Establish the most important factors that lead to or prevent business creation in biotechnology and synthetic biology within the context of iGEM.

Research Model

To answer the objectives, this research draws on a combined multi-method empirical study, linking a qualitative and quantitative approach to understand entrepreneurship in biotechnology and SynBio. By combining qualitative and quantitative data, the research benefits from the advantages of both approaches. Qualitative data can capture the causal process of a certain phenomenon and substantiate the hypothesis derived from literature in order to answer research questions behind the enabling factors in biotechnology entrepreneurship (Eisenhardt 1989, Eisenhardt and Graebner 2007, Miles and Huberman 1994, Yin 1984). On the other hand, quantitative data allows testing on a large scale as a greater spectrum of observations can be tested. This strategic combination will create a better understanding of significant factors in biotech entrepreneurship.

The next sections will establish 1) the background research used to develop the theory and structure the data collection, including literature and advising, 2) a qualitative research approach, 3) a quantitative research approach, 4) an analysis of the combined qualitative and quantitative data, a 5) a conclusion and discussion regarding enabling factors in biotech plus 6) suggestions for the biotech industry and iGEM to enable more scientists to found a company.

- MODEL 1: Research Model**

Literature analysis

A number of papers and books related to entrepreneurship and biotechnology were reviewed to design the survey and interview guidelines. The main literature sources include:

Literature	Description
Engel, Jerome S. Global Clusters of Innovation: Entrepreneurial Engines of Economic Growth around the World. 2014	An in-depth review and description of various entrepreneurship ecosystems around the world, as well as the enabling factors that allow startup success.
Steinmetz, Max. Success Factors of Startups from the Founders Perspective. 2011	Research on success factors of startups from the point of view of business founders.
Kananen, Johannes. Success factors of Start-up companies from the investors’ perspective. 2011	Research on success factors of startups from the point of view of investors.
Journal of Comparative Policy Analysis: Research and Practice: “Where science comes to life: University bioscience, commercial spin‐offs, and regional economic development” 2014	Biotech entrepreneurship, university spin-offs and how they are created.

From these sources, 11 main paradigms were established to distinguish enabling factors relevant to business creation. These paradigms cover most important influences on business creation.

Table 1: Paradigms of Entrepreneurship
Team	Entrepreneurial experience, background, education, team spirit, risk-taking, team functionality
Product/Project	Characteristics of the product/project, prototyping, proof of concept, marketability of product
Academic Mentorship	Mentorship related to project creation, advising in biotech and in entrepreneurship, access to information, knowledge exchange, technology transfer, collaboration
Entrepreneurial Mentorship	Access to personal network of contacts/business angels, venture capitalists
Access to Resources and Product Development	Material and laboratory access, quality of test environment
Access to Customer Feedback	Access to feedback by potential users and customers of the product
Access to Financial Support	Funding via venture capitalists, accelerators, research funds, banks, university support, etc.
Access to Legal Advice	Advising for patenting or legal issues
Unique Market Opportunity and Access	Market characteristics (market competition, industry life cycle), timing of product, partners in the industry, etc.
Environment	Cluster for entrepreneurship and/or biotechnology, political/regulation situation
Founder	Characteristics of entrepreneurs, more specifically, their abilities and skills, personal motivation, vision, gender, education and work experience. *It should be noted that most of our analysis is on a “team” basis with less focus on individual founder characteristic, therefore, enabling factors related to individual characteristics are omitted in this study.

(Steinmetz 2011, Kananen 2011, Engel 2014)

Advising

Once the paradigms of important factors were established for entrepreneurship, experts in biotech and entrepreneurship were contacted for further consultation. The advisors included academic advisors and professors in synthetic biology, representatives of BioM (the biotech cluster in Munich, Germany), entrepreneurial advisors from the startup accelerator TechFounders and current and past participants of iGEM. All of these advisors contributed to the research methodology as well as the quantitative survey and qualitative interview design.

Research Approach

First, 11 of qualitative interviews were held to better understand the factors that affected Founders and non-Founders from the iGEM population. Second, a quantitative survey was designed to analyze the significance of different variables in business creation in biotech (specifically in iGEM). From the survey a statistical analysis was performed to measure the degree to which the variables affected founding a business.

The survey analyzes current and past iGEM participants, who are working in relatively the same, with similar education levels, time frames and resources.

Potential Limitations of the Data

Although the sample size (n = 140) is decent for data analysis, a larger sample size could potentially provide better results. Furthermore, as there were only a handful of business founded from iGEM (less than 20), the sample size of Founders from iGEM remains small due to this limitation. However, this only strengthens the reasoning for conducting research on this topic, to understand why so few teams have founded businesses and what can be improved to make it more common in the future.

Qualitative Data Approach

For the qualitative data, 11 past iGEM participants were interviewed, 4 of which founded a business (Founders) and 7 who had not (non-Founders). The goal of the interviews was to understand the Founders/non-Founders decision process and the factors that influenced or barred the way to business founding. The chapter is organized 1) a list of interviews with Founders, 2) a table of the core questions and responses from the Founders, 3) a list of interviews with non-Founders and 4) a table of the core questions and responses from the non-Founders.

Founder Interviews

TABLE 2: LIST OF FOUNDERS INTERVIEWED
INTERVIEWEE	COMPANY	UNIVERSITY/IGEM YEAR	INTERVIEW DATE
Cindy Wu	Experiment	U. Washington 2010 and 2011	September 13^th, 2016
Danny Cabrera	BioBots	U. Pennsylvania	September 20th, 2016
David Lloyd	FredSense	U. of Alberta, U. of Calgary	September 20th, 2016
Eva-Maria/	Gene Advisor	Edinburgh 2006	September 15th, 2016

The following table gives a snapshot of the core questions the Founder interviews sought to establish: 1) what are the enabling factors for founding a company, 2) were there adequate resources, including enough time, advising and funding to build a company, and 3) was there any knowledge or technology exchange or support from related industries.

TABLE 3: CORE QUESTIONS AND RESPONSES FROM FOUNDERS
Interviewee	What were the main reasons for founding a company?	Did you have adequate resources? (tools, academic advising, entrepreneurship advising, time, funding)	Did you have knowledge or technology exchange with industry members? Were you in a biotech cluster?	Other comments on entrepreneurship in biotechnology/ synthetic biology?
Cindy Wu	The proof of concept at iGEM and in general was successful Initially the idea was a solution to fix their own problem Accelerators and investors were supportive	Had adequate funding from the university during iGEM After iGEM, had very low funding until joining Y-Combinator, an accelerator in San Francisco Raised money from investors A lot of mentorship, but not business mentorship until after iGEM	Yes. Lots of help with many CEOs, founders, universities Mentors and alumni from Y- Combinator	At the beginning, had no business, website, sales experience. However, they were able to develop and entire project and eventually a startup from scratch and learning everything new. iGEM was definitely an enabling factor Their advantage with earning investors trust was their huge vision for their product Almost did a PhD, but glad she did not so she could do her business
David Lloyd	Grant funding from Deep Starter, a program for SynBio companies Good team, smart people	Yes, enough resources and funding A lot of entrepreneurial/business advising	Yes, a ton of knowledge exchange, less technology exchange	iGEM was definitely an enabling factor
Danny Cabrera	Good business opportunity More influence founding a business than academia – ended up deferring PhD Good mentorship Funding from DreamitHealth accelerator	Yes, very good advising in academia and business	No, not really	Today it is much cheaper to do biotechnology than ever before, and in some ways the barriers are much lower
Eva-Maria/Jelena Aleksic	Research and access to high tech, plus a good idea of a market need Industry knowledge exchange	Not enough funding. Took bank loans to support the project	Yes, from the Accelerate Cambridge program, the industrial community and the academic region	The business did not really take off until finishing their PhD’s. But once they did, they switched to the business side and founded a startup.

Analysis and Discussion of Founder Interviews

Table 4: Most Prominent Reasons for Founding a Business

Knowledge Exchange with Industry Members

Entrepreneurship consulting

Funding from external parties (accelerators, banks, sponsors)

Passion to solve a problem

Having a Quality Team

Deferring or Finishing Academic Studies

The Founder interviews had many similarities and differences in their stories behind business creation. While none of the reasons mentioned in Table 4 are not necessarily more significant than others, there is a general trend. First, the teams all shared a similarity of being highly ambitious in finding funding through external sources (accelerators, banks, sponsors), as well as having a large passion for their projects, sometimes even deferring their studies. Second, the teams expressed having a quality team was useful for a successful business. Third, the teams differed slightly on how much knowledge exchange they had with industry partners during their iGEM; however, once business creation became an idea the teams heavily sought out expert advising in entrepreneurship and from industry experts. Interestingly, some of the teams were not aware of their product’s advantage until later in iGEM and many had no idea about the market characteristics until they sought out industry/entrepreneurship consulting. Overall, the storyline seems that the iGEM teams found a useful idea, developed it during iGEM with quality mentorship, came to find that they required more funding and business advising to make the product viable and worked hard to secure resources to found a startup.

The Founders also gave their thoughts in regards to entrepreneurship in biotech, suggesting that 1) today it is easier than ever before to found a biotech company, because funding and resources are much more accessible and 2) iGEM is definitely an enabling factor. These suggestions will be discussed later on in the “Suggestions and Conclusion” section.

It is important to have both sides of the story. Therefore, the next section is a list of the interviews with non-Founders and the reasons they did not found a business from their iGEM projects.

Non-Founder Interviews

TABLE 5: LIST OF INTERVIEWS WITH NONFOUNDERS

INTERVIEWEE	UNIVERSITY/YEAR AT IGEM	DATE INTERVIEWED
Axel Uran	EPFL 2015	September 20th, 2016
Nikolaus Huwiler	EPFL 2014	September 20^th, 2016
Linnea Österber	KTH Royal Institute of Technology 2015	October 4th, 2016
Fernando Contreras	IGEM Sand Diego 2014	October 5th, 2016
Fabian Rohden	TU Darmstadt 2014 and 2015	October 4th, 2016
Fernando Contreras	U. of California San Diego, 2014 and 2015	October 5, 2016
Nicolas Krink	iGEM Paris 2013, iGEM Freiburg iGEM 2014, Marbough 2015, iGEM Dusseldorf 2016	October 4th, 2016

TABLE 6: CORE QUESTIONS AND RESPONSES FROM NONFOUNDERS

Interviewee	What were the main reasons for not founding a company?	Did you have adequate resources? (tools, advising, time, funding)	Did you have knowledge or technology exchange with industry members?	Other comments on entrepreneurship in biotechnology/ synthetic biology?
Axel Uran	Lack of time Studies were in the way Lack of motivation Lack of advising for a startup	Adequate advising Adequate funding Adequate tools and lab space	No, not really	Many investors would love to fund great ideas, and there is so much opportunity in biotech/SynBio Establish an entrepreneurship incentive/track in iGEM iGEM could invite investors to the Jamboree Studies get in the way of founding a business
Niklaus Huwiler	Lack of time Studies Not a priority	Lack of time Lack of advising	No, not really More interaction with laboratories	iGEM is great for networking Too short on time for founding a business
Linnea Österber	Did not have any interest Research oriented Probably not even applicable as a business	No, lack of resources and funding Borrowed lab equipment	No, not really	There was a lack of business spirit and interest
Fernando Contreras	Lack of time Studies in the way There was not a lot of effort put into the business side	Yes, enough funding Decent resources and advising	Yes, there was monetary and material support, as well as sponsorship from industry members	There needs to be more interaction with the industry, either for startup possibilities and/or even potential job opportunities Have iGEM participants focus on solving a real need, fewer “flimsy” projects
Fabian Rohden	Did not have a viable business concept The project was already being done essentially by companies No incentive to patent	Yes, a lot of support for funding and mentorship	Yes, a lot of knowledge exchange	Some of the iGEM ideas are not possible to market iGEM participants should focus on solving real problems
Nicolas Krink	Studies were in the way Lack of time	Yes, we had adequate funding and resources throughout all the teams. Occasional lack of good advising Lack of incentive for many advisors to help in iGEM	No	Germany is lacking a hotspot for biotech and Synbio. There is a lack of resources and lab space with adequate advising to realize projects Biology and life science students are not trained to think entrepreneurially

Analysis and Discussion of Non-Founder Interviews

Table 7: Most Prominent Reasons for Not Founding a Business

Lack of Knowledge Exchange with Industry Members

Lack of Entrepreneurial Advising

Lack of time

Lack of motivation and interest

Project was not competitive/viable

Studies Got in the Way

From these interviews it is clear that there are similarities and differences among the non-founding teams. In general, the teams had a lack of knowledge exchange and consulting with mentors. If there was industry consultation, it was primarily in the form of sponsorship. Furthermore, teams had hardly any entrepreneurial consulting and many of the teams did not even consider a business, either due to not having the skills or experience, a marketable product, time and motivation, and/or the encouragement to further their project/consider a business. A common theme was the lack of time due to the need to finish academics or continue into a research-oriented position.

One notable difference among the non-founding teams was the amount of funding and resources. Some teams had quite a lot of funding/resources while others had to get by with less. They also had mixed responses regarding the quality/quantity of academic mentors.

In general, it seems that the teams varied on funding/resources/academic mentorship but were very similar in lacking knowledge exchange with industry experts and entrepreneurship mentors. A definite theme was having a lack of time and motivation with academics in the way.

The non-Founders provided very interesting ideas to encourage entrepreneurship in biotech, including 1) increasing interaction and knowledge exchange with industry members 2) providing incentive for business creation, including a) inviting investors/accelerators/incubators to iGEM, b) creating an entrepreneurship track, c) providing job opportunities with industry members, d) encouraging entrepreneurship in the life sciences, 3) encouraging iGEM participants to solve a real-world problem/seek market opportunities and 4) establish more incubators that provide the resources and advising for people to realize their projects. These suggestions will be further discussed further in the “Suggestions and Conclusion” section later on.

Summary and Discussion of Qualitative Data

The founding and non-founding teams had many differences and a few similarities between them. First, there is a large difference between the two groups and the amount of knowledge exchange and consultation that occurred. The Founding teams had far more knowledge exchange with experts and entrepreneurship advisors than the non-founding teams.

Second, the time and motivation between teams was highly varied. Some teams did not think the project was worth the time and/or their studies were in the way. Although finishing studies was a concern for both groups, the founding teams had either finished their studies or deferred them to make time for a startup. Some of the founders even went into business studies after finishing their science degrees to help their businesses.

Third, the founding teams’ ambitions pushed them to secure funding/consulting for their projects and business aspirations. Although some of the non-Founding teams did have decent funding, they did not use the resources for business creation.

One similarity among the founders and non-founders was the general lack of business experience or skills. Hardly any of the teams had previous experience in business and only a few had dabbled in the idea of founding before iGEM. This shows that not having previous business skills does not have to be a barrier to business creation. The founding teams sought out entrepreneurship consulting and learned on the way while building their products.

In conclusion, the results of the Founder and non-Founder interviews provide interesting insights into the factors that enable biotechnology entrepreneurship in iGEM. The next section uses a quantitative method approach to assess to which degree these factors truly influence founding a business.

Quantitative Data Approach

The quantitative data survey is based upon the 11 established paradigms of business creation, plus added questions to address the specifics of biotech and iGEM. The survey has 60 questions with 140 responses and was conducted between August 26th, 2016 and October 20th, 2016 with SurveyMonkey via social media and contacting current/past iGEMers via email. The majority of the questions were structured as likert scales (1-7 rating) as well as optional open answer questions.

The survey was pretested in order to check for understandability, clarification needs, and accuracy of the questions as well as the comprehensiveness of the survey and the time needed to answer its questions (Bortz and Döring 1996, Schnell et al. 1988). The pretest was conducted with academic peers, interview partners of the case study, biotechnology clusters/companies, professors and entrepreneurship consultants. The reviews from academic peers, biotech professionals and consultants also included feedback on phrasing, presentation, and the structure of the questions.

From the survey data, logistic regression analyses were conducted to examine the relationship of the established enabling variables in biotech business creation. The following sections will begin with 1) regressions based upon the established paradigms of business creation and biotechnology/iGEM, 2) a full model regression containing variables that had a 10% significance in direct relation to our dependent variable (dependent variable = Founder), 3) t-tests to analyze differences between the Founder population and non-Founder population, 4) a summary of the open answer responses and finally 5) a discussion and summary of the data.