Big pharma experience can be valuable in building a startup from scratch. Just ask Lovisa Afzelius, a former AstraZeneca and Pfizer researcher who now creates companies as an origination partner at Flagship Pioneering.
Afzelius is a co-founder and CEO at three Flagship startups — Apriori Bio and two to-be-named biotechs — and was the founding CEO of Alltrna, which is attempting to make medicines from transfer RNA.
In typical Flagship fashion, the biotechs are focused on developing platform technologies that could be used to make many medicines. Her companies have outsized ambitions, too, claiming the drugs they plan to discover could have a wide range of applications.
During the downturn that’s dogged the biotech sector over the last year, however, investors have become less receptive to platform companies and their typically lengthier development timelines. Some Flagship portfolio companies, like Sana Biotechnology and Rubius Therapeutics, have lost much of their value since going public. Others, like Flagship startup Vesalius Therapeutics, have trimmed their research plans.
Still, Afzelius is optimistic the new startups she’s formed can deliver. Having now spent a decade in company creation — she founded one startup after leaving AstraZeneca in 2012 and then a digital health company after leaving Pfizer in 2017 — she’s familiar with taking bets.
“Finding the ‘perfect storm’ — the apex of where novel technological advances enable an unlock of a previously intractable scientific field,” Afzelius said.
BioPharma Dive spoke with Afzelius about her experience building new biotech companies. This conversation has been lightly edited and condensed for clarity.
BIOPHARMA DIVE: You developed drugs for AstraZeneca and Pfizer before turning to startups. How did that help your career?
LOVISA AFZELIUS: It was really a time when AstraZeneca was at its top. There were a lot of senior people around who were phenomenal mentors, who put you in situations that you may not have been ready for. But with a lot of support, you had the ability to test them out and learn a ton from it.
AstraZeneca closed down its site [in Sweden]. I was asked if I wanted to continue within, but I took a step out to do something different. I joined as a CEO for an early startup within the Karolinska Development there. That was an exciting way of getting to know the Swedish startup scene and investment scene.
After a successful turnaround of that company, I was recruited to Pfizer in the U.S. In 2013, I joined the inflammation/immunology research unit at Pfizer to build their systems immunology function. It’s leveraging computational [science] together with immunology, which at that point of time, given that next-generation sequencing and many other tools had just come up, was the perfect point to start thinking about these two disciplines.
I was also developing drugs as a product leader from early-stage through to late-stage clinical development. As I was doing that, I also did an MBA at MIT. I had my eyes opened to the biotech world in Boston, realizing the immense number of startups, but also specifically got exposure to Flagship, and understood their very unique way of creating new companies.
How has your experience helped you turn an idea or a piece of research into a full-fledged company?
I was in that interface between biology, chemistry and computational [science]. You need to understand all of those different disciplines. You have to understand and be somewhat fluent across the entire space that you're operating in to see those new opportunities that may never have been applied in the area where you are currently. Now may be the perfect time for bringing those two together and making them grow.
What was important during that time was the closeness to mentorship. Having really talented people around me that could mentor and help [me] work through novel situations and be fantastic colleagues and friends.
In the beginning, when computational [science] started to be incorporated into drug development, there was absolutely no infrastructure. We literally had to do everything ourselves. You had to partition your hard drive so that you could run Linux to write the algorithms to build your models. You had to code the graphical interfaces so that you could actually show someone the results that you were getting from those algorithms.
That’s a good learning [experience], because you also see it's possible to build something from scratch. It’s a huge satisfaction to look back at a software you built become something that is actually generally usable now in that field. That's what we're doing now. We're building companies from a white piece of paper, often going into the fields where no one has been before and thinking through what are the biggest problems that we're trying to solve.
In recent months, we’ve seen job cuts at Flagship portfolio companies, among many others in the industry. Is there a change to how the company is approaching its model?
The market today is very different from what it was a couple of years ago. It was also an extraordinary year in 2020 and 2021. In all company building, it's all about building the science. We know that even the best science sometimes does not work. You have to try because that's how the biggest medical unveilings have happened. It’s important that we keep the focus on building these companies in the best possible way. The market will go up and down. Our focus is on the most pressing needs, on the science that needs to be solved.
What are you looking for when you partner with scientific founders to turn their ideas into a company?
A passion about being able to make a difference and solve a problem that eventually will meet an unmet need in patients. I think that's the best motivation you could ever have for working really long [hours], which we do in order to get these things through.
Science will never do exactly as you want it to do. By having optionality in your strategy, it allows you to adapt, to find the best possible way that will also be the best for patients down the line.
Flagship is thinking about starting from the non-adjacencies. We don't go into trying to be in the exact same space as everyone else, we look for where we can make big leaps and we can make big changes to biology.