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.

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.

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 ^[1]. 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

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:

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

^[2]

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.

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.

For the qualitative data, 12 past iGEM participants were interviewed, 4 of which founded a business (Founders) and 8 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.

Table 2: List of Founders Interviewed

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

Table 4: Most Prominent Reasons for Founding a Business

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.

Table 5: List of Interviews with Non-Founders

Table 6: Core Questions and Responses from Non-Founders

Table 7: Most Prominent Reasons for Not Founding a Business

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.

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.

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 ^[3]. 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. For those interested, a copy of the survey can be found at the very end of this page.

Before diving into the significant factors, here are some graphs representing the general trends in gender and team size of the iGEM teams that answer the survey. Overall, the respondents were split nearly 50/50 in gender. The most common team sizes had between 6-10 or 11-15 people.

Graph: Team Number

Graph: Gender of Respondents

Table 8: Team Characteristics

Graph: Team Percentage that Joined in Founding

A logit regression analysis was used to analyze the most significant team factors in founding a business from iGEM. In this case, the team entrepreneurial spirit and team functionality were both highly significant with p = 0.00 and 0.076, respectively. Interestingly, while it makes sense that having an entrepreneurial spirit is positively correlated with founding a business, team functionality has a negative effect with a coefficient of -0.445! This is surprising as often team functionality plays a large part in project success. Perhaps this means the team splintered off into different groups, where only some team members founded a business independent of the rest. This is evident from the survey and graph as well, showing only a few people from the original teams founded the business. From the qualitative interviews, some teams did in fact only found with a few members of the original iGEM team. Without more information on this data, however, it is hard to make accurate assumptions on why team functionality does not enable business creation in this case. On the other hand, having an entrepreneurial spirit in the team has an extremely significant relationship of ß = 0.00, with all other variables held constant, meaning the drive and motivation to found a startup enables biotech business creation. Judging from the qualitative interviews, it certainly appears true that entrepreneurial spirit played a role as the founding teams were passionate and worked hard to secure funding and resources to found a business.

Table 9: Product Characteristics and Market Opportunity

Market growth proved the most significant factor in predicting founding in terms of markets and product characteristics, with a p = 0.007 and a positive coefficient of 0.53, with all other variables held constant. This implies the Founders were relatively aware of or stumbled upon a market opportunity with their iGEM project and were able to access the market in time to found a viable business. From the qualitative interviews, some of the founders either knew during their project development that there was market growth, or only after the iGEM competition. Either way, it is clear that market growth related to a business is beneficial to founding a startup and so conducting research on the marketability of an idea could be beneficial when choosing an iGEM project.

Table 10: Academic and Entrepreneurial Mentorship

Entrepreneurship consulting for iGEM projects is highly significant (p = 0.0) with a positive correlation of .644, all other variables held constant. This suggests the iGEM teams that built startups were either highly influenced or attained success partially because of consulting with business/entrepreneurship advisors. Furthermore, it is apparent that founding teams in the interviews had entrepreneurship consulting, either from their mentors or from accelerators and incubators. Therefore, it can be concluded that having an entrepreneurship mentor can highly influence its founding.

Regressing the variables concerning enough resources, enough time and enough advising provided no significant results at the 10% level (p ≤ .10). Although potentially significant, the survey data did not provide a reliable relationship between founding business and these variables. However, taking data from the qualitative interviews, the founding teams in general did not have enough funding/resources for startup creation during iGEM and therefore either 1) received money and resources from accelerators/incubators or 2) took out bank loans 3) gained sponsorship from other companies and universities. Furthermore, some non-founding teams did have decent funding but did not use it for business founding. So while funding, time and resources do not show a reliable relationship from the quantitative data, the qualitative data shows ambitious teams sought out and secured the resources they needed, enabling them to found a business.

Table 11: Access to Customer Feedback

Graph: Access to Customer Feedback

Access and use of customer feedback is also highly significant with a p-value of 0.001 and a positive coefficient of 0.527, all other variables held constant. This makes sense as customer feedback is very important in business creation as it directly addresses a customer’s problem, which enables the business to then build a product that solves it, developing into a viable business. Furthermore, customer feedback allows project developers to tweak the product according to changes in trends and customer needs, enabling greater product viability. However, judging from the graph, the survey respondents in general had hardly any customer feedback. This could present an area of improvement for iGEM and iGEM teams for making more successful projects and possibly businesses.

Table 12: Access to Financial Support

Interestingly, the factor that proves most significant in business creation related to financing is the awareness of government funding with a p-value of 0.001 and ß = 0.482, all other variables held constant. This can be interpreted to mean founding iGEM teams are 1) aware of government funding and can therefore take the opportunity to secure financial support, 2) are highly motivated and are seeking funding from sources outside of the university/iGEM and/or 3) are provided this information from mentors or other sources to support project development. As previously mentioned, the interviewees were very active in finding funding sources, some of which used accelerators and other sponsors. A team that is active and aware of opportunities certainly has an advantage in business creation.

Table 13: Access to Legal Advice and Patents

Patents are a unique topic in the case of biotechnology entrepreneurship as they can significantly enable or bar a startup from success. The variables represent the need/interest in legal advice, having an interest to patent and the ability to patent during iGEM project development. The need for legal advice and having a patent interest show a positive and significant relationship to founding a business (ß = 0.404 and p = 0.030, ß = 0.411 and p = 0.044, respectively). This signifies that 1) Founders are in need of legal advice because of their interest to found a business, 2) the product could require patenting to be viable and/or 3) understanding how to secure a proper patent is difficult.

On the other hand, patenting during the iGEM project development shows a negative relationship of -0.417 and p = 0.73, all variables being held constant. This negative relationship with founding implies a barrier to patent a product during iGEM. Such a barrier would explain why some teams have difficulty founding businesses during iGEM project development.

Many of the founding teams interviewed did receive legal advising from their accelerators or mentors. Only a few needed to patent, and some are still in the middle of filing for a patent. The qualitative results are mixed on needing patents to have a viable product; however, it is clear that there is a lack of legal understanding and a need to provide iGEM teams with better legal knowledge and training, if the need were to arise.

Table 14: Environment, Clusters and Industry Relationship´

Another significant factor regarding biotechnology clusters and industry support is the variable knowledge exchange with a high significance of p = 0.00 and a positive coefficient of .653, all variables being held constant. This significant and positive relationship implies interaction with biotech clusters and/or industry members is highly influential for biotech business creation, as it likely provides 1) expert insight into problems that need solving, 2) knowledge in scientific processes, 3) knowledge in business processes and/or 4) market information important for successful business creation. From the qualitative data it is clear that most of the founding teams consulted industry experts regarding their projects and business consideration. The non-Founding teams had noticeably less interaction with industry representatives. Although founding has a clear relationship with knowledge exchange, it is clear from the survey respondents that only a few iGEM teams actually collaborated with other entities and exchanged knowledge. Therefore, it appears extremely important for iGEM teams considering founding (or for iGEM success) to have knowledge exchange.

Table 15: Business Model

Graph: Business Plan

In regards to building the business model of an iGEM project, having a business plan is extremely significant with p = 0.00 and a positive coefficient of 3.07, all variables held constant. Clearly, having a business plan greatly improves the chances of an iGEM team founding. However, as seen in the graph, very few teams in iGEM actually make a business plan. The qualitative data also suggests that founding teams created a business plan during iGEM. Therefore, it can be concluded that a business plan enables iGEM teams in business founding.

Table 16: iGEM Enabling Factors

In many ways, iGEM itself is an enabling factor for biotech entrepreneurship. As shown in the data, having a successful Proof of Concept at iGEM is positively related to founding a business, with a p = 0.16 and a positive coefficient of 0.698, all variables held constant. This makes sense, as proving an idea at iGEM means potential for credibility in the real world as well. If the concept is proven and there is a market opportunity, then likely there is startup potential. In general, all of the interviewed founding teams had relatively successful Proofs of Concept. Overall, this means that really having a proven idea could lead to startup creation.

This model represents the variables that are significant at the 10% level (p ≤ .10) when independently regressed with the dependent variable, Founder. The variables represented are 1) having a successful Proof of Concept at iGEM, 2) having a business plan for the iGEM project 3) knowledge exchange with industry members and 4) having access to customer feedback on iGEM projects.

Table 17: Full Model of Significant Variables (p ≤ .10)

These variables represent the most significant factors related to business founding in iGEM when all the variables are regressed together. Having a successful Proof of Concept at iGEM, a business plan, plenty of knowledge exchange with industry as well as enough customer feedback enables iGEM teams to move their project from the academic world to a viable product.

In sum, the significant quantitative variables (p ≤ .10) on iGEM business creation were 1) access to customer feedback, 2) knowledge exchange with industry, 3) a team entrepreneurial spirit, 4) product market growth 5) having entrepreneurship consulting, 6) awareness of government funding, 7) an interest in legal advice 8) an interest in patenting and 9) having a successful Proof of Concept for the iGEM project. The most significant negative variables (p ≤ .10) are 1) team functionality and 2) the inability to patent during iGEM project development.

Similar to the qualitative data, founding teams used much more knowledge exchange and entrepreneurial consulting, and had an entrepreneurial drive that made them more aware of funding opportunities, market growth and legal issues.

The most interesting factors are the degree to which knowledge exchange and mentorship were so crucial in supporting iGEM entrepreneurs. Industry interaction and proper guidance for the project and business played a heavy role in developing a marketable product, securing funding, understanding patents and being aware of market opportunities.

It is surprising that team functionality did not play a larger role in the statistics. Team quality and cohesiveness is often quoted to be one of the most significant factors for startups; however, in the case if iGEM it seems to be a negative influence. This could also stem from the fact that so many teams are very large (e.g. over 20 people), and often startups begin with much fewer people. This means teams likely split up after iGEM and only a few continued the business, as seen in the qualitative interviews.

The following sections will dive a little more deeply on Founder and non-Founder differences, as well as a look at the combined qualitative and quantitative data to better understand biotech entrepreneurship enabling factors.

To further understand the enabling factors in biotech entrepreneurship, independent samples t-tests were conducted to compare population differences between Founders and non-Founders. More specifically, research was done to understand population differences in the degree of 1) entrepreneurship consulting, 2) advising and 3) cluster support. These variables were chosen because of their significance in the previous regressions and the emphasis the interviewees put on these factors. Understanding differences in Founder and non-Founder characteristics provides further insight into enabling factors in biotech.

1. T-Test Entrepreneurship Consulting

The first t-test examined if having more (or any) entrepreneurship consulting was significant in founding a startup from iGEM. Having access to Entrepreneurship consulting proves yet again to be a very influential variable in business creation. There was a significant difference between the Founders (M = 4.07, SD = 2.21) and non-Founder (M = 1.74, SD = 1.33), conditions; t(138) = -5.56 and p = 0.00. This data completely rejects the null hypothesis and suggests Founders are much different than non-Founders in either having access to and/or effectively using entrepreneurship consulting to found.

2. T-Test: Advising

There was a significant difference between Founders having enough advising (M = 5.53, SD = 1.51) and non-Founders having enough advising (M = 4.74, SD = .146), conditions; t(138) = -1.67, p = 0.097. In line with entrepreneurship consulting, having enough advising is significantly more apparent in the Founder population than non-Founder population. This means enough advising (in academia, science, business creation, etc.) enables iGEM teams to found businesses.

3. T-Test: Cluster Support

There was a significant difference between the Founder cluster support (M = 3.61, SD = .55) and the non-Founder cluster support (M = 2.77, SD = .146) conditions; t(138) = -1.71, p = 0.089. This implies Founders had greater support from their region and/or industry members regarding their iGEM projects, leading to startup founding success.

The t-tests represent differences in Founder and non-Founder population resources that could partially explain why some teams founded and others did not. The Founders had clear advantages in entrepreneurship consulting, general advising and cluster support. This implies that the interaction with advisors and industry experts provided the knowledge Founders needed to found their businesses. Therefore, proper advising and cluster support is highly influential in iGEM team business creation.

The following section presents the open questions asked in the survey. The goal of the questions was to discover what other factors might enable or inhibit entrepreneurship that had not already been addressed in the survey. The respondents were given the option to answer freely on 1) What were other reasons for founding a business and 2) What were other reasons for not founding a business? In addition, the respondents were asked to provide suggestions on how entrepreneurship might be encouraged in biotech/SynBio/iGEM; however, for simplicity this topic will not be presented here but discussed in the “Conclusion and Suggestions” section. After discussion of the open questions, this section will then close with unique quotes from the respondents and a summary of the open responses. For the sake of focus and brevity, each topic will summarize the most common and distinguished responses gathered from the survey.

1) What were other reasons for founding a business?

1. To impact society and bring change
2. To solve a problem
3. For research
4. To gain experience
5. To earn money
6. A lack of biotech jobs in the region, so founded their own venture
7. Passion for the project
8. For Personal development

2) What were other reasons for not founding a business?

1. Lack of experience and “know-how” in business creation
2. Idea/project is unappealing to society
3. The patent rights go to the university, not the team
4. iGEM is open source, thus patenting and/or business creation is not the focus
5. Lack of interest in business opportunities
6. Lack of legality in certain countries
7. The idea is at a very early stage
8. Lack of functional prototype
9. Founding is too risky
10. Regulation barriers
11. Laziness

List of Quotes from Survey Respondents

The following section presents a selection of interesting quotes from the survey respondents. In general, the respondents expressed a real passion for their projects and iGEM, as well as opportunities to further develop their projects as businesses or research (or both) post-iGEM. These quotes provide a more in-depth view of the iGEM participants, their motives and passions.

“I found the purpose of the survey very interesting. Science isn't just discovering or creating things. We must notice the relevance of technology transfer. Discovering a drug that cures cancer, a bacterium that cleans CO2 or a tool that improves crops means nothing if it never reaches the market. Hopefully, iGEM will listen and try to make some changes to more directly encourage entrepreneurship during and after their competition.” – iGEM Participant, October 15th 2016

“If IGEM was all year, constantly distributing new source from different labs, constantly sequence verifying, constantly awarding parts that help a wide variety of people, how much more could get done? I think that the answer is a lot more.” – iGEM Participant, October 10th 2016

“There are many projects that could greatly improve society related to medicine, the environment, and do not go further because of the lack of support or assessment.” – iGEM Participant, October 10th 2016

Summary of Open Responses

To summarize, it appears the extra factors listed from the open responses involve the willingness and passion to solve a problem, impact society, gain experience, personal development and potential to earn money. The barriers against founding range from not having enough experience, not having a good enough idea, inability/lack of knowledge about legal issues, regulation barriers and laziness.

The quotes from iGEM participants provide a more human touch for the research objective, showing a passion and drive for progressing iGEM projects through entrepreneurship but also frustration with the barriers that prevent them. In the following section these extra factors will be discussed in parallel to the established qualitative and quantitative data.

Combing the quantitative and qualitative data brings a clearer picture of what exactly influences biotech startup creation from iGEM participants. Table 18 summary of the most significant enabling factors from the quantitative and qualitative data. The “X” and “O” represent in which data the factor was significant.

Table 18: Highly Significant Enabling Factors in Biotech Entrepreneurship (iGEM)

This data shows that the most significant variables enabling entrepreneurship in iGEM are having knowledge exchange, a problem to solve, funding (either from accelerators/incubators/loans), studies out of the way, access to customer feedback, a team entrepreneurial spirit, a successful iGEM Proof of Concept, awareness of government funding, having a business plan, consulting legal advice and entrepreneurship consulting. In addition, survey respondents noted that the passion to solve a problem, the experience and personal development and money opportunities influenced participants to found. The next steps are to establish how this information can be used to benefit iGEM participants and biotech/Synbio entrepreneurs in the future.

There are many factors that influence business creation in the science realm and it is difficult to capture and quantify each variable. However, with this data it is clear that some factors highly influence business creators and further development of these variables can aid in startup founding. The following table is a list of suggestions with the first column, Enabling Factors, listing the paradigms addressed in this paper, the second column, General Suggestions, listing possibilities for biotech entrepreneurship in general and the third column, iGEM Suggestions, listing recommendations from iGEM participants to encourage entrepreneurship from iGEM.

Table 19: Enabling Factors and Suggestions for Enabling Entrepreneurship

The next steps for future research should involve determining how these suggestions can be realized. For example, it would be useful to investigate VCs and accelerators interested in SynBio and incorporate them into the iGEM environment. Perhaps partnerships with established companies could be made to increase knowledge and technology exchange. Entrepreneurship consultants could provide training and advising for iGEM teams. Additionally, scientists need to be inspired and aware of the possibilities of founding companies from their research. These initiatives could be simultaneously progressed as the interest and knowledge in SynBio grows and innovation clusters are formed.

Helmut Schönenberger, CEO of UnternehmerTUM center of Innovation and Entrepreneurship in Munich, is an expert on building a clusters of innovation and believes it would highly benefit SynBio initiatives. According to the seasoned entrepreneur, building an ecosystem of partnerships, mentorships and inspiration for startups creates synergies that push startup potential. Today, clusters of entrepreneurship for Synbio are just at their beginnings, therefore these ecosystems need to be fostered by connecting large companies, startups, VCs and every interested party to build an effective support system for SynBio innovation. Furthermore, teaching entrepreneurship already has established methods - the problem is reaching scientists and showing them the possibilities in entrepreneurship. By creating a SynBio entrepreneurial ecosystem, which iGEM is partially doing, you create a wealth of synergies that promote SynBio startup creation and the SynBio industry overall (Schönenberger 2016).

Promoting these enabling factors and webbing a supportive ecosystem for Synbio is key to entrepreneurship and the SynBio community. Many improvements need to be made to provide scientists with the tools, mentorship, encouragement and business opportunities. The possibilities are there and growing, iGEM and scientists around the globe need only to seize the opportunity.

If you would like to see the survey we used to collect the quantitative data, check it out here: https://static.igem.org/mediawiki/2016/5/53/Muc16_Survey_Entrepreneurship.pdf

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Regional Entrepreneurial Opportunities in the Biotech Industry: Exploring the Transition from Award-winning Nascent Entrepreneurs to Real Start-ups. Accessed on June 25^th, 2016 from: http://www.iwh-halle.de/d/publik/disc/25-10.pdf

Factors Influencing Small Business Startups. International Journal of Entrepreneurial Behavior and Research. Accessed on June 25^th from

https://www.researchgate.net/publication/230600351_Factors_Influencing_Sma

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Schwarzkopf, Christian. "Entrepreneurial Ecosystem and Entrepreneurial Fundamentals in the USA and Germany" 

Fostering Innovation and Entrepreneurship (2016). Springer Gabler 2016

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Eisenhardt 1989, Eisenhardt and Graebner 2007, Miles and Huberman 1994, Yin 1984. “Theory building from cases: Opportunities and Challenges.” Accessed on October 1, 2016 from https://aom.org/uploadedFiles/Publications/AMJ/Eisenhart.Graebner.2007.pdf

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Helmut Schönenberger, personal communication, October 14^th, 2016