What is the goal of scientific research? Simply put, it is either discovery, understanding or innovation. Basic scientists are concerned with the first two, discovery and understanding, while applied scientists are focused on innovation. What is innovation then? it is the development and implementation of new products, services or processes that add value to end-users and generate wealth for the organization. Based on that definition, it becomes clear that the mission of applied scientists is to identify real needs and create commercially viable solutions. Innovation = invention x commercialization as Bill Aulet, a professor of entrepreneurship at MIT, would say.
Sounds simple, yet this is not what currently happens in most Canadian universities. A recent report by AUTM showed that the total expenditure on scientific research in Canadian academic institutions was $5.7 billion in 2017. During the same year, Canadian academic institutions generated $75 million in gross income from licensing agreements. That is a mere 1.3% of the research expenditure! The USA is 3.5 times better than Canada in creating wealth from research expenditure at 4.5%. Moreover, Canada’s global ranking in innovation has been dropping! In 2018, Canada came 22nd in the Bloomberg innovation index ranking, and was one of two G7 countries that were not considered “top tier” in innovation. We have not been doing any better in the past either. In 2013, the conference board of Canada ranked Canada 13 out of 16 peer nations when it comes to innovation.
I want to be clear here; fundamental research is critical and should be funded regardless of commercial outcomes. It would be a terrible mistake to repeat what the Conservative government did under Stephen Harper and cut funding to basic research. Moreover, the solution is not to increase overall funding into applied research in order to increase commercialization. The best solution is to increase the commercial viability of funded applied research done in academia; and this is where I believe scientific entrepreneurship can offer some solutions.
So, how can we improve the commercial viability of applied research done in academic institutions?
In this article, I will share 5 lessons I learned about applied science research after completing my PhD and as the CEO of a startup, and I believe these lessons are also viable answers to the question above.
Identify Real Pain Points
At Impactful Health R&D, we dedicated 3 months to interviewing 85 stakeholders in our industry to understand two things: 1) what are the current real pain points in the industry, and 2) who has them. This information helped us identify if our solution was solving a real need, and who was interested enough to pay for it. There is an art to doing customer interviews to capture real data and reduce biases. Steve Blank, an entrepreneur and Adjunct Professor at Stanford, developed the customer discovery methodology and talks about this extensively in his book, The Startup Owner’s Manual, and on Youtube. Another book on conducting good customer interviews is called The Mom Test by Rob Fitzpatrick. The author here describes a methodology to extract reliable data even from the most biased of individuals, such as your mother.
Interviewing real customers, done correctly, leads to real data. You cannot depend on market research reports alone to understand the real market needs. Or to be more relevant to academia, you cannot depend on review papers or a citation of a citation of a market research report to justify the need you are addressing. Moreover, it is not sufficient to have one end-user validate the need for the product. For example, one physician believes that a certain device will solve a big medical issue. That is not enough data for a research scientist to go ahead and start developing the device. We are scientists after all, an n=1 is never sufficient.
Unfortunately, it is uncommon in academia to find applied scientists communicating regularly with multiple industry players or end-users in order to identify real market needs. There has to be more cross-talk between academia and industry, and less silo work.
The National Science Foundation in the US recognized the need to commercialize more research from Academia, and created I-Corps. One of the main objectives was to train academics to become more entrepreneurial and to give them the tools to quickly assess the viability of technologies developed within their labs. Academics had to follow the customer discovery methodology developed by Steve Blank to do customer interviews. The result: more than 50% of the academics ended up creating startups, and those startups attracted private investments that were 3x more than the NSF (tax-payer $) funding given to the teams.
Conduct Market-Informed Research
Identifying real pain points through interviews is great, but what is even better is to keep open channels with interested end users/customers during prototyping. We made sure to maintain very close ties with our potential end users and they provided us with extremely valuable data related to the current market trends, the technical specifications that would allow easy integration of our solution, and a reasonable price range for our product. This data actually pushed us to iterate on our design a few times, either to reduce cost or improve usability. Ultimately, it will lead to a better product-market fit.
While it is true that there are academics that collaborate with industry, few of those are meaningful long term strategic partnerships. Many of the current academia-industry collaborations in Canada are initiated to win government grants. However, due to the lack of strategic alignment between the companies and academics, these collaborations tend to be short-lived (usually a few years) and seldom result in a licensing agreement. Creating meaningful partnerships with industry early on can inform the research from the beginning, to ensure that the innovation solves a real need and is commercially viable.
It is about Time
Time is the biggest foe for a Deep tech startup. Having a strong value proposition that is well communicated, a strong team, and a big enough market will usually attract investments, grants and awards; but time is always scarce. As a Deep tech company our product development cycle is longer than other startups; this is, and will continue to be, our biggest challenge. On the flip side, scarcity of time drives us to conduct well-designed experiments to test different solutions in parallel and quickly eliminate non-viable solutions. It also forces the R&D team to work in synergy to accomplish results within a short period of time.
In academia, however, the clock ticks more slowly. This is partly due to the learning curve of new graduate students, partly to the turnover of students working on any given project. Moreover, projects get slowed down due to the course load graduate students have to fulfill in their first year or two. That being said, the professors that I have seen progress quickly are those with 3 or 4 overarching projects who have multiple graduate students working on complimentary aspects within each project. It is like having 2 or 3 people working on different parts of one puzzle, rather than having each graduate student working on a whole puzzle alone.
There are also practices in academia that consume time without adding real value to developing a commercially viable innovation: 1) Conducting various “secondary” or “indirect” experiments that do not add new information, but are there to beef up a publication or a thesis; 2) Publishing multiple papers while changing one or two variables just to increase the number of publications, and 3) Pushing graduate students to publish “dead-end” projects, just so that they can ‘have an extra publication’. All these practices consume time and are a hindrance to developing true innovation.
Research with Scale-up in Mind
One of the things we have tried to do at Impactful Health R&D is to think about scaling up from the very beginning. We always try to minimize the number of steps required for any development, minimize reagents needed, use green chemistry when applicable, and reduce the overall time of fabrication. We also do all of this in collaboration with an expert from the chemical industry. We believe by doing this early on, we will save a lot of time and effort in the future.
Another important aspect of planning for scale up is considering costs well ahead of time. We are very mindful of the cost of our product and the sources of our reagents. When our technology is manufactured in large scale, we need to make sure that the price is reasonable for the market, and that we have reliable suppliers who can scale up with us.
Academics doing applied research should also aim to think about scaling up ahead of time. The one key element here is to source the different components going into the innovation from reliable suppliers. Doing biomaterials science research during my PhD, for example, required buying the bulk of our components from Sigma Aldrich or Fisher Scientific. This is not sustainable on the long run since most of the time Sigma and Fisher are re-sellers of someone else’s product, and as I experienced in the past, they don’t tell you who the actual suppliers are. As such, they are free to add their own margin to drive up the price of the product. So once a proof of concept is developed using one of the R&D suppliers (Sigma, Fisher, etc…), it is best to re-do the prototype with materials/reagents sourced directly from suppliers who are reliable, can scale up and can offer competitive prices.
Protect Intellectual Property or Perish
‘Publish or Perish’, as they say in Academia. In the startup world, it is ‘Protect IP or Perish’. IP takes precedence over publications. I dare even say that if possible, it is preferable not to publish the exact design/composition/process related to the innovation. Competitive advantage is key in the success of deep tech companies. At Impactful Health R&D we always talk about what our technology does, but never about how it does it.
Dissemination of scientific findings is one of the cornerstones of academia. However, in the case of applied science research, academics should first get in touch with the technology transfer offices at their universities to assess the novelty of their research and file a provisional patent if applicable, prior to publication. Moreover, if this research was done to solve a real pain point, as I mentioned earlier, then perhaps forming a partnership with industry or spinning off a startup should be the next move, before publishing the research. Granting agencies and university tenure committees should reward academics who are pursuing commercialization of their technologies, and not just publishing papers.
It is in everyone’s interest for Canadian universities to become powerhouses for applied science innovations, and for Canada to become a global leader in innovation. To do that we have to change the way things are done. More applied science academics should be thinking about commercialization as the ultimate goal, and not publications or even patents. I personally know academics who have licensed their technology, or spun off startups to commercialize their research, and I am inspired by them. We need more academics with this mindset, and we need them NOW.