A Revolution of the Boring
“Oh, you are a picks and shovels fund?”
Like most labels, it is challenging to determine whether this was a useful categorization, a slight, or both. Doesn’t matter anyway.
Also, Thielsen is not a fund – its a network of operators, investors, scientists, and doctors all committed to accelerating research for the benefit of patients.
We are ALL ABOUT “picks and shovels.” So, what does that mean?
When you read about investing in “life science,” and you see the record funding in biotech (which we will discuss), what is all this really referring to? The lion’s share of the attention and capital is dedicated to therapeutic and diagnostic companies. They are capital intensive thanks to a long regulatory process and thus open an opportunity for large amounts of capital to be deployed into them. Many of my friends work as scientists in these companies and have brought amazing cures and diagnostics to market.
Sweet, let’s help these folks out to do their job better, faster, cheaper. Let’s catalyze their work.
Our job is arm life scientists with the very best tools – the picks and shovels - to find that metaphorical gold. I love this analogy as we see life science research and biotech manufacturing undergoing the same evolution from picks and shovels to explosives and mining equipment (“A brief history of mining” General Kinematics, link). We actively look for and invest in companies that take us from:
technicians and Ph.D. scientists carrying pipettes (yes, even multichannels) for time-intensive sample preparation and movement of reagents
to these same scientists being able to perform discovery at scale and focus on the real value creating work on data interpretation, analysis, and integration.
The enormous pressure that has been put into the system is not that there is widely available, cheap automation that can replace this pipette labor or that the entire research enterprise can be virtualized (in both cases – these are tailwinds that are just on the horizon in terms of scale). The pressure has been from the job market, and the war for talent (McKinsey’s 1997 prescient phrase) is on in biotech.
The job market for life science talent is white hot, and this puts enormous pressure and focus on how time is spent in the laboratory.
Since 2016, average Series A-D rounds for early stage biopharma have nearly doubled in funding amount (i.e. capital deployed, in 2020 – 426 deals with an average of $53M up from 2016 302 and $32M), and many “traditional” tech funds have entered the scene. In addition, large cap pharma ($50B+) has been in-licensing earlier, with a focus on discovery platforms and an increasing share devoted to cell therapy (3X since 2018, “Biopharma and Medtech Deals and Funding” JP Morgan. Oct 2021. link)
This is an awesome time to be in the space and the pace of innovation and in turn, this funding, is fueling a heated and competitive job market. When I graduated with my Ph.D., I was incredibly lucky to get a job offer from a biotech company and a software company, now graduates can expect several offers at graduation or after a handful of months as a postdoc (“A sizzling biotech job market is streamlining the course to a career in chemistry” September 12, 2021 link).
As we would expect, in correlation, technician salaries and job openings are at all time highs. As a proxy, we can look at data for clinical laboratory technologists. I have never seen a government site be this exuberant but here we go –
“Employment of clinical laboratory technologists and technicians is projected to grow 11 percent from 2020 to 2030, faster than the average for all occupations.” (emphasis mine, “Clinical Laboratory Technologists and Technicians” U.S. Bureau of Labor Statistics, September 8, 2021, link)
So, what does this mean for how time is spent in the lab?
Put yourself in the research leader’s role for a moment – the majority of your operating expenses as a biotech leader are going to recruit, employ, and retain the very best researchers. The pressure is on you to remove, scale, or automate the rote, the boring, the not-value adding steps of an experiment for everyone in the laboratory. It's just too expensive not to from both a time and a talent retention perspective. This is why are are very actively investing in a space we refer to as a “revolution of the boring.”
In other words, we love differentiated solutions that make orders of magnitude improvements in the mundane and time-consuming tasks e.g. sample preparation with commodity automation, paired with consumables, as well as virtualization of experiments (screening, animal studies, etc.) to maximize this expensive scientist time.