Our last post explained how we are looking at Life Sciences investment this year.
But the challenges of life science demand more than merely appropriate organization. We have to change the way we think about investing to be effective here at the earliest stages. We have to approach deep science companies differently than we do consumer product or digital health companies. The risks of scientific failure are so great, and the differentiation between huge success and zero value is so narrow and specific, that we feel an informed initial screen is essential here.
To do that, our deep science team has developed a new framework for investing in deep science bio startups. Deep science companies must meet all the criteria below to be considered investment opportunities for us:
Focus area. The company’s focus must match our current fund priorities; we are supporting our defined focus areas here, not reaching out.
Need. The market impact of the scientific solution must be great. We are looking for clinical responses to major diseases that currently have no existing meaningful intervention; incremental improvement is not enough.
Stage. We are moment-of-inception investors elsewhere, but in deep science, we carefully engineer our investment point. We never invest at the earliest stage; it is impossible to measure the risk of scientific failure at that point. We will invest at pre-clinical or proof-of-concept stages. We are looking for defined assets in each investment.
Science. We need to see science that has been validated by publication in top-tier scientific journals or otherwise comes thoroughly vetted by the scientific community.
Team. The team must have all of these: Full-time CEO, veteran successful bio entrepreneur, and A-list scientist.
Timeline. We will only invest in companies where we see a 5- year or lower path to Phase II clinical trials, acquisition, or IPO. Total capital requirement for that arc should be $20M (ideal) to $40M (acceptable, if the opportunity is big enough).
IP. Deep science companies we invest in must have at least provisional patents. Granted patents worldwide are better.
Valuations. Investment rounds we enter for deep science companies must be less than $10M pre. We must be able to model an exit valuation of at least $200M before we invest.
Our purpose in this framework is to eliminate companies as early as possible that will not later be attractive acquisition targets, have too high a risk of science failure, or will take too much time or too much money to reach the tipping point for value creation.
What this framework means for us in Bio/Pharma and Therapeutics is a lot of well-digging for few gushers. We can (and must) examine hundreds of science approaches in order to find a single company that has all the right stuff. It will be heavy lifting without much obvious reward, week after week. Our approach here must conform to Winston Churchill’s definition of success: Moving from failure to failure without loss of enthusiasm.
For medical devices, the impact of our framework will be even more severe. In this area, all the science risks are compounded by manufacture, replacement, process change, and a host of other risk factors. Simply put, every medical device startup will arrive to us this year cold and dead on the slab. Application of our frameworks will need to animate the corpse, as it were. Medical device startups that pass our tests will be as singular (like our current investment, Lazarus). But any device company that does rise to our challenge will be a remarkable entity and have the stuff of greatness within it.
We will adhere to this framework for 2020 absolutely. It is our primary method for avoiding face plants in the deep science area.
By Managing Partner Mike Edelhart
@MikeEdelhart