by Eric Gilliam
The term ‘valley of death’ is often used to describe the massive difficulties that promising research findings have in making it into and out of clinical trials. Only 10-20% of biomedical research projects ever progress to human trials. Translational medicine programs have attempted to make crossing the valley of death less harrowing for startups that are spun out of academic life sciences research.
One of these programs, SPARK at Stanford Medical School, has seen noteworthy success. As of 2017, 62% of SPARK projects were being licensed, transferred to industry, or in clinical trials. Their YCombinator-like roadmap of offering participants a modest amount of capital, close mentoring from industry advisors, access to clinicians to help understand the final users of their research, and weekly check-ins to share progress and meet with advisors provides a fantastic model of how overcoming the non-scientific problems of a new scientific enterprise can help overcome the valley of death.
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Building successful entrepreneurial business ventures out of academic research is tough. And it’s not hard to understand why. There are ‘business risks’ in all new enterprises that arise from the uncertainty of building a business from scratch, finding customers, and many other things. And, in the case of companies that are spun-out from academic research, there is also ‘technical risk.’ Your research may never get to the point where it is commercializable.
Those risks are known and are a cost of doing business in cutting-edge research areas. But risks in these kinds of businesses can still be minimized. Programs have been popping up at top life science research programs that aim to do just that. In this piece, I’ll talk about a program that has been doing exceedingly well at helping researcher-founders bridge the gap between a course of research and a successful technical enterprise. The program, SPARK at Stanford Medical School, is quite straightforward and has experienced fantastic results. And, as shocking as it may be to some, the success of this program may be largely in how it treats world-class scientists not dissimilarly to how an organization like YCombinator treats its technically bright, but new to business, young founders.
The success of this program provides a concrete example of what it can mean to pass on the ‘practice of entrepreneurship’ to help scientific founders not just take the plunge, but also maximize their chances of succeeding.
The ‘idea’ of being an entrepreneur
The ‘ideas’ of innovation and entrepreneurship should not be taken for granted. To many could-be entrepreneurs, the ‘idea’ of innovation simply does not occur to them. As Anton Howes, author of the Age of Invention Substack, wrote:
The more I study the lives of British innovators, the more convinced I am that innovation is not in human nature, but is instead received. People innovate because they are inspired to do so — it is an idea that is transmitted. And when people do not innovate, it is often simply because it never occurs to them to do so.
Incentives matter too, of course. But a person needs to at least have the idea of innovation — an improving mentality — before they can choose to innovate, before they can even take the costs and benefits of innovation into account.
Matt Clancy, also a fan of Howes’ perspective, expanded on these ideas in two of his pieces. The pieces, Entrepreneurship is contagious and The ‘idea’ of being an entrepreneur, build on this concept by surveying empirical work in the area. Clancy observes that it does not just seem to be the idea of entrepreneurship occurring to a person that is important, but, also, that there are substantial effects when it is a person more similar to you. And, also, it seems that the effect is lost when you are a person who has already considered that entrepreneurship is a real possibility for you. Put differently, the idea of entrepreneurship can be most impactful to those who are capable of doing it but don’t fully realize that. And it’s even more impactful when it comes from a person similar to them.
Clancy summarizes the main pieces of evidence arising from the literature in the following way:
- Entrepreneurs are often found in social clusters (workplaces, neighborhoods)
- Quasi-random exposure to entrepreneurs increases the probability of becoming an entrepreneur
- Entrepreneurial influence seems stronger when entrepreneurial peers occupy a more similar social position
- The effect of exposure to entrepreneurs is much weaker for the people most likely to already be considering a career in entrepreneurship
This begs the question: how can we build on this? Can we use these insights to help engineer a system that produces more entrepreneurs?
The valley of death
Translational medicine is hard — hard enough that the term ‘valley of death’ has been coined to describe the massive difficulties that promising basic research findings have in making it into and out of clinical trials. One of the best ways that we can increase entrepreneurship among academics is to get people through this valley.
Many assume that the factors that contribute to these difficulties are almost exclusively scientific. However, Gehr and Garner write that many of the issues scientists run into point to a larger problem: “scientists and clinicians do not fully understand how industry works or what is needed to make their inventions attractive for further development and/or commercialization.”
Even as the NIH began putting emphasis on this area of translational research in the mid-2000s, with the establishment of the National Center for Advancing Translational Sciences (NCATS) and launching the Clinical and Translational Science Award (CTSA) program, translational research has often still felt like a wicked problem. University tech transfer offices putting more financial resources into the problem has, in many cases, been of little use. The attrition rate in the valley of death is still massive, with only about 10-20% of biomedical research projects ever progressing to human trials.
But, it’s not all bad news! Many life sciences research centers have been starting programs that attempt to help researchers overcome this problem. SPARK gives us a fantastic example of the kind of ideas we need to be transmitting to PIs to make the translational research pipeline less daunting.
What is SPARK?
Andrew Lo, Paige Omura, and Esther Kim have a fantastic, simple paper that outlines what goes into the translational research program at Stanford Medical School, SPARK, and the outcomes of the program. The program helps make the leap from researcher to technical entrepreneur feel smaller and more gradual. This process is a bit of a black box to many academics, even those who theoretically know they could be an entrepreneur. What prevents many from taking the entrepreneurial leap is a feeling of not understanding how to be an entrepreneur. The program does not just make it easier for a researcher to become an entrepreneur, but to make it through the so-called ‘valley of death’ with flying colors.
The program was started in 2006 by Dr. Daria Mochly-Rosen to help educate, mentor, connect, and partially fund Stanford scholars working on unmet clinical needs who had dreams of their work crossing the valley of death. Mochly-Rosen had just taken a leave of absence to found her own company, KAI Pharmaceuticals. While KAI was very successful, Mochley-Rosen found bridging the translational research gap to be extremely unintuitive in spite of her extensive research experience. With that in mind, she founded SPARK and began to build the program along with her co-Director, Dr. Kevin Grimes.
SPARK aims to establish partnerships between academics and experts from industry who are interested in overcoming the hurdles involved in translating academic discoveries into deployable drugs and diagnostics. Every year, a new cohort of scholars, primarily working on unmet clinical needs, is selected. To give some perspective: as of Lo et. al’s writing, 30% of projects addressed orphan diseases and 32% were related to child or maternal health issues. These are far from the easiest areas to succeed in from a business perspective, but their social good implications are obvious.
While the science is complex, the inputs that go into running the program are quite simple. As of Lo et. al’s writing, the cohort of Stanford researchers received:
- $50,000 annually for two years (a meager amount by life science’s standards)
- Access to clinicians
- Educational mentoring from SPARK-affiliated advisors
- A requirement to attend weekly Wednesday cohort meetings along with advisors
Funding was distributed as project milestones were met. Once they were met, additional funds could be requested for further stages of development. And researchers were able to make these relatively modest amounts of money go a long way, having access to Stanford’s facilities and resources.
Access to clinicians
Very likely, a massive factor in the program’s success is the scholars’ access to and encouragement to speak with clinicians to better think through the clinical implications of their research. As any entrepreneur will tell you, this customer interview-like process is absolutely vital to building products that are useful to end-users. Anecdotally, it seems like this is exactly the kind of process that academic researchers taking the translational plunge often don’t fully appreciate and emphasize, possibly even de-prioritizing it to the point that it never gets done.
In SPARK, scholars learn not to work on parts of a problem just because they are the most interesting or fill the biggest hole in the literature. As Lo et. al write:
A key element of the SPARK training is teaching investigators to think using a translational approach. The scholars learn to identify the unmet clinical need of the patient and to understand the problem in tandem with product development. In other words, they are trained to ‘keep the end in mind’ throughout the process. SPARK uses project management tools such as target product profiles and project timelines to help teams plan and identify key milestones, necessary endpoints and crucial decision points.
The SPARK advisor network
The SPARK advisor network helps fill large holes in most researchers’ knowledge and networks. These advisors come from the industry-end of the translational pipeline and understand what it takes to attract follow-on investments into a course of research. Lo et. al describe the advisors:
As of 2016, SPARK had over 100 advisors with significant entrepreneurial or industry expertise in drug development, generally in a specific therapeutic area. On occasion, advisors are organized into working groups, focused on areas such as medicinal chemistry, biologics, financing and venture capital, business development and clinical trial design.
These advisors do not possess ownership rights to any inventions or IP from the program. They volunteer their time to work with SPARK projects, attend weekly meetings, and evaluate projects because of their interest in the research areas behind the projects and for the opportunity to be a part of a high-level network of industry and academic experts. In addition, mentoring also allows the advisors to deploy their knowledge to further drug development in a mission-driven environment which may be more focused on social good than many industry employers.
The weekly meetings
The final component is the Wednesday meetings. SPARK scholars are required to attend these weekly meetings which include lectures from industry experts and project updates that occur on alternating weeks. In addition to the obvious information-sharing and question-asking roles of the meeting, I’d imagine these meetings in which scholars update the group on their progress serve as a valuable accountability mechanism in making sure they keep a reasonable pace on their projects.
Analogous founder meet-up groups, in which groups of early stage founders meet regularly to update one another on their respective progress and challenges, have sprung up around Silicon Valley for exactly these reasons. Sometimes the group can answer your questions, but it is ALWAYS embarrassing to show up and tell the group that you haven’t made progress on tasks which you obviously should have made progress.
In the academic context where deadlines have become quite loose, these meetings may be a shockingly effective accountability mechanism.
Does SPARK work?
Lo et. al write in their 2017 analysis of the program:
The SPARK program has a unique and rigorous success metric. A project is deemed successful only if it enters a clinical trial, is licensed or transferred to an existing biopharmaceutical company, or leads to the founding of a new startup. In the 10 years since SPARK was founded, 74 projects have graduated from the program. Of these, 24 were licensed to startup companies, eight were licensed to existing companies, four have been transferred to industry without licenses and 31 are in clinical trials (ten without licenses). Together, this amounts to a success rate of 62%.
The SPARK scholars’ projects generated sizable follow-on grants as well. The program invested a total of $7.1 million in 74 projects and these projects generated $38.7 million in additional grant funding. SPARK projects, which largely attack areas of unmet clinical needs, are proving very attractive to investors and are surviving the valley of death with flying colors.
What SPARK failures can tell us about why the program succeeds
62% is a remarkable success rate given the high baseline attrition rate in the field. Surely, many readers will believe that this success is at least partially due to selection effects — because the success rate was far too high above baseline to not have been substantially impacted by project selection. Even if that is true, I think there is still reason to believe this program (and ones like it) can have substantial impacts, selection effects or not.
Lo et. al’s failure analysis looking at those 28 projects that were not successful provides us a lot to learn from. 6 of the 28 failed projects, 21.4%, were simply unable to obtain commercial funding, scooped by industry, or the researcher left before the program was completed. In those cases, the scholars took advisor advice, did what they needed to do operationally, and did not fail due to inability to overcome scientific obstacles. 12 of the projects, 42.9%, failed for scientific or technical reasons, such as failing to develop an acceptable drug candidate or to demonstrate benefit in preclinical models. Lastly, 10 of the projects, 35.7%, simply failed to execute.
What does ‘failure of team to execute’ mean in this context? As Lo et. al explain the category, “In
these cases, the SPARK scholars became disengaged from their project, had inadequate primary investigator engagement or personal conflicts, or ignored advisor input and misused funds.”
Even amongst the minority of failures from the cohort of SPARK scholars, the reason for failure was almost as likely to be basic operational reasons as it was technical/scientific ones. This should leave one remarkably optimistic. While tackling technical and scientific obstacles can be a wicked problem, overcoming operational and networking problems is almost mundane in comparison.
The concept of providing a small amount of funding, a network of industry advisors, regular project check-ins, and access to potential customers is not a foreign model. In fact, that is generally YCombinator’s model. YC was built to help batches of young, technically skilled entrepreneurs make headway in starting a company even if they had minimal business experience, and there is little reason to think the model shouldn’t apply to professors as well.
While professors may be world-class experts in their particular fields of research, many also have little to no work experience outside of academic labs. And, when put in that light, one should not have the expectation that they should know far more about building a business than the bright young people who enter an accelerator like YCombinator. Even the brightest people need a crash course in how to do things the right way. And that is okay, because those are lessons that a program like YC has had success teaching at scale.
The concept of transmitting the idea of effective entrepreneurship should not be overlooked as a pivotal lever that can be used to overcome problems in the innovation pipeline. SPARK is just one great example of a program doing just that to overcome the famous ‘valley of death’ in translational medicine.
For those who are curious.
This piece drew heavily on Lo et. al’s analysis of SPARK, Mochly-Rosen and Grimes (the SPARK directors) short book on the program, and Gehr and Garner’s paper on the larger space of translational research programs.
Other programs like SPARK/SPARK spinoffs have been popping up at other institutions around the world. If any readers come across a similar analysis of any of these SPARK-like programs, please send them along! I’d love to do a follow-up looking at successes and difficulties in replicating the program. Replicating the winning habits of a successful organization is never easy, so I’d be very curious to do some research on how similar programs have held up.
Additonal reading on these other efforts and the area in general can be done at the following links:
Baseline success rates of translational life sciences projects
I have seen estimates in the literature that the industry standard success rate for projects like these is as low as 5% compared to SPARK’s 62%. An example can be found in the literature here and on SPARK’s website here. However, since I was not able to successfully find the source of this lower number in the literature, I chose to use the statistic stating that 10-20% of biomedical research projects never progress to human trials as the baseline statistic instead. If anyone can locate the paper that is the source of the 5% statistic, please reach out to me on twitter and I’ll update the article.
For those curious, Lo et. al briefly described the management and funding structure of SPARK as follows:
The SPARK program, currently led by Drs Mochly-Rosen and Grimes, operates with a management team of five individuals that oversees communications with project teams, runs its weekly meetings, oversees SPARK funds and otherwise manages operations. Although the majority of the funds for SPARK comes from the Dean’s Office, the program operates independently within Stanford University and is managed solely by the SPARK team.