Transitioning from academia to industry: Interview with Prachee Avasthi


The following is a conversation with Prachee Avasthi, PhD., a co-founder of Arcadia Sciences, about her transition from academia to industry. The interview has been condensed and edited for clarity.

You have many professional roles, including the co-founder and CSO at Arcadia and a PI at Dartmouth studying cilia. You’re also on the board of directors at eLIFE and ASAPbio. In general, you seem enthusiastic about both conducting research and improving the enterprise of science itself. Can you tell us a little about yourself and your career trajectory, and what got you started in and excited about science in the first place?

I got interested in biology as an undergraduate, where I conducted research in many different areas, from ecology to neuroscience. The process of discovery was really exciting to me, and I realized it didn’t really matter what area of science I was studying; I loved all of it. My trajectory was mostly linear except that I did switch graduate labs four and a half years into my doctorate. That was a transformative experience for me and seeded the kind of science I do today. Another key experience for me was the summer I spent doing an internship at Genentech. I wasn’t particularly interested in going into industry, but it taught me a lot of things about the process of science and how to think about money in science, which informs how I run my own research lab. In the 10 weeks at Genentech, I think I got about 10 months of work done. This really transformed my own thinking about research in relation to our educational mission in academia. Sometimes it is intentional to not necessarily do science in the most efficient way if we are providing the most educational experience for students. However, this experience certainly changed my decision-making around resources.

How did you know you needed to switch labs?

Many of us think we have to stick with something. My first graduate lab wasn’t a great fit for me scientifically. At the time I thought this was a huge loss, but one of the biggest tasks in graduate school is learning how to learn. While I didn’t finish my PhD in that lab, I did the bulk of developing skills and maturing my thinking there and took that with me for the rest of my graduate career and beyond. My second graduate lab almost felt to me like a postdoc that I felt really well equipped for.

When did you get interested in non-model organisms?

What we call a “model” organism is highly research area dependent. Model organisms are simpler ways of studying conserved structures, physiology, or behavior that are more tractable to study than humans. The algae I work on is a great way to study the structure known as the cilium, a microtubule-based structure that behaves as cellular antennae. It’s well-conserved in the tree of life from the last eukaryotic common ancestor all the way to human cells. In trying to understand the mechanisms that give rise to these structures, I landed in a different field. Even though this algae is a model system for cilia assembly and function, it has a very interesting actin cytoskeleton that’s highly divergent from other eukaryotes. Understanding this difference felt to me like the key to unlocking the biggest secrets in how fundamental biology works.

Is it harder to get funding for non-model organisms and, if so, did that lead to your drive to found Arcadia?

When you run a lab in academia, you get really creative about finding ways to fund the science you want to do. If all we study are humans and models that are very similar to humans, it becomes very limiting. Nature has found different solutions to similar problems. While we can’t do every experiment, evolution has found so many ways to accomplish a diversity of tasks. At Arcadia, we think we can solve many of those problems and find common solutions to open up the tree of life. We’re hoping this leads to a broader shift in how all science gets funded so that researchers in academic labs don’t get declined funding based on the model they’re using and where the tools are. We want to make those tools and data accessible so everyone can answer their questions in the right systems.

Is Arcadia’s funding tied to current leadership?

We have a runway of 12-15 years that will fund ~120 scientists. We’re not looking for other investors or outside grants; we want to protect the mission of Arcadia, which is ultimately an experiment on what science we do, how we communicate that work, and how we fund that work. We want to do high-risk science in the sense that we want to pursue what could be possible, not just what is possible today. In fact, if it can already be done elsewhere we want to promote and encourage that. Because we have different constraints, we want to ask, what kind of science can we do that no one else can? One thing I’m focusing on is maximizing our impact per knowledge gains from our input of resources, in terms of both money, people, and concerted effort. I don’t just want to have a building that does cool science, we want to change the way we do science so all researchers can reimagine what is possible for them.

How did you decide to structure Arcadia? Is it modeled after other biotech companies?

We’re in a gray space where we’re not an academic institute, but we’re also not a biotech company. Everyone bristles when they hear we are for-profit, but the reason is we want to demonstrate value in the multitude of ways of doing science. You shouldn’t have to have a large endowment to do a venture like ours. We want to show potential investors there is value at pushing the boundaries of what and how science is pursued so there can be more companies like Arcadia, not just one. To prove it has value, we have to show the feasibility in that commercialization. But we’re not making drugs or selling a product. What we’re doing is saying, yes there’s a long distance between basic science and commercialization, but that kind of science has value from an investor standpoint. We’re going to invest so that other investors will follow our lead.

Were there any big learning curves to starting Arcadia?

The whole thing has been one big learning curve! What didn’t we learn to do as academic scientists? Project management is a big one. One question that comes up all the time is what does advancement in our company look like? We are really pushing against automatic hierarchy. In academia, the trajectory is that management is the inevitable result of success, but we don’t think everyone wants to be a manager nor are they necessarily good at it. We don’t want to import the hierarchical research lab structure into Arcadia. However, you can’t have a flat structure either, so small teams seem to be really efficient. With smaller teams, we can be more agile with where we put our resources and energy. If a project is going really well, we can always grow that team. We also want to get rid of hierarchical data authorship so that everyone is collaborating on the basis of their expertise. Ultimately, though, everything we are doing is an experiment. We are approaching running the company like scientists and trying to figure out the right way to do it and iterate on it.

How does this mean the research culture is different?

It’s different in a number of ways, including publishing and open science. In my opinion, open science is better science, but it also has to be useful. An excel spreadsheet in a supplement of a preprint is open data, but not necessarily useful. One question we’ve structured our organization around is: How can we make sure people use our data so we help facilitate the most knowledge gains for our input? Early on, we drew a line in the sand and said we aren’t submitting our work to traditional scientific publishers, but we aren’t getting rid of peer review: our goal is public peer review and feedback. We want to get out of our own way, we aren’t going to hold on to our data, we are going to publish early and often. Our data and our protocols are going straight into public repositories. We want to show open science and commercialization aren’t at odds with each other.

As someone who has done both, do you have any advice for current trainees trying to figure out their own career trajectories and trying to figure out whether to pursue a path of academia or industry?

Definitely do your own exploration! Many of us are familiar with an academic job description, but it is unknown as to what a career in industry actually looks like; they’re all very different. Do informational interviews. Set up meetings and ask people what their job entails, what expertise they have and what qualifications they needed to get that job. Importantly, what does their day-to-day look like to actually work at that place? But most importantly, don’t over-value individual opinions. In my experience, what others say is impossible is more a reflection of their capacity and abilities than your own. Most opinions do not take into account your specific talents, circumstances, challenges, and ingenuity. Only you can take the wealth of opinions and put it through your own filter to decide what’s right for you.

Keep an eye out for job postings at Arcadia!

Want to know more? Watch ASCB’s webinar, Transitioning from Academia to Industry. [ASCB Member-only content]

About the Author:

Kristen Skruber is a member of the ASCB Committee for Postdocs and Students (COMPASS) and a postdoc in the lab of R. Dyche Mullins at the University of California, San Francisco studying the membrane-cytoskeletal interface. Twitter: @kskruber1