The Bioinformatics CRO Podcast
Episode 54 with Evan Floden
Transcript of Episode 54: Evan Floden
Disclaimer: Transcripts may contain some errors.
Grant Belgard: [00:00:00] Welcome to The Bioinformatics CRO Podcast. I’m Grant Belgard and joining me today is Evan Floden. Evan, would you like to introduce yourself?
Evan Floden: [00:00:07] Yeah, awesome. Thanks a lot for having me Grant. I’m Evan Floden. I’m the CEO, co-founder of Seqera Labs, previously been building the Nextflow project for the last ten years or so. So I’ve been very interested in following the developments in bioinformatics over that time. It’s great to be on the show.
Grant Belgard: [00:00:23] Thanks for joining us. And I’m sure most of our listeners have heard of Nextflow, but maybe not everyone’s heard of Seqera. Can you tell us about the company and its origins and pulling the strings behind Nextflow?
Evan Floden: [00:00:36] Yeah, absolutely. It’s an exploit was started by myself and co-founder Paolo Di Tommaso. And really the idea around Seqera was really a continuation of the project, but really bringing it to fruition in terms of a commercial sense. So whilst we focused originally on a lot of the work that Nextflow was doing on pipelines, now we’ve expanded out a fair bit from that. So Nextflow we began ten years ago. Seqera has been around for about five years now. We’re really focusing on taking some of the principles that Nextflow has. The idea of empowering scientists with modern software engineering came about from the use of things like containers, the adoption of cloud, really enabling scientists to use those tools and to focus on that. And Seqera is just a continuation of that, but now broader sense. So really making the whole bioinformatics pipelines accessible, but going beyond the pipelines as well.
Grant Belgard: [00:01:25] And what’s your business model?
Evan Floden: [00:01:27] Very much focused on bottom up adoption from the open source. So in terms of Nextflow usage, we’re looking at around 100,000 people in total. So use Nextflow and that gives us obviously a really cool base. In terms of business model, it’s mostly focused on selling to enterprises, to organizations, to folks who are scaling up from single bioinformaticians to running things in production and really providing them the infrastructure, the tools that they need to build the pipelines out. And increasingly so the aspects as well.
Grant Belgard: [00:01:58] Have you seen adoption beyond bioinformatics?
Evan Floden: [00:02:00] Interestingly, in Nextflow, yes. Nextflow doesn’t have anything too specific with regards to bioinformatics in the way that it’s written. However, obviously its application is very much being focused and being used in bioinformatics. So we’ve started to see use cases and things. For example, image analysis, you start to see it. For example, satellite image analysis, also radio astronomy. Anywhere there is scientific workloads that have particularly batch component to them. I think an element of that, the user base has developed a lot of content in Nextflow through things like nf-core, and that obviously lends itself to people picking up Nextflow itself and using it for life sciences. But it’s not to say it’s not being used in other areas and obviously we’re happy to support that and see where the community takes that.
Grant Belgard: [00:02:45] How did Nextflow in Seqera evolve? Can you take us back to the beginning and what your thoughts were then and how that’s played out over time?
Evan Floden: [00:02:53] Absolutely. So Paolo and myself were working in a lab in CRG in Barcelona, and our lab was looking at multiple sequence alignment. Folks in Bioinformatics may be familiar with some software called T-coffee. It’s a very commonly used multiple sequence alignment tool that was developed by our former supervisor, Cedric Notredame. And as part of that, the job in the lab of Paolo was to enable us to run those analysis. And it was, we were particularly interested in high throughput so tens of thousands of sequences and looking at how small variations in those sequences can have an effect on the multiple sequence alignment and the resulting outputs. That was the topic of my PhD and that was what was intended to go and study. Obviously as I got there, I started to spend more and more time on Nextflow and that evolved from there. It was a very small project to begin with. We just published it onto GitHub. It started with I remember, after a year I think we had a list of the ten people who were using it or 30 people who were using it, and it was a very a small start. Over time we were able to just continually evolve and adapt it.
[00:03:57] It’s one of the great things about open source is you’re able to get that feedback and people are able to contribute ideas back, issues back, and it allows us to really evolve from there. It’s been a fantastic journey over that time. We got to probably be about five years into the project and realized that there was first a commercial opportunity, but secondly, it’s something that we both love doing. I was getting towards the end of my PhD and I just really wanted to keep working on the technology. I saw a huge potential. Paolo and myself traveling around Europe and doing training courses and just really saw the opportunity to take that to the next level. And that’s the spark for creating Seqera and seeing all the opportunity that there was from that, I should say. So since starting Seqera, Nextflow has increased its usage at least tenfold on that. So I guess there was a slight risk at that time in doing that, but we were pretty convinced on the project and it’s really been the foundation for everything we’ve built so far.
Grant Belgard: [00:04:50] Yeah, it’s gotten very widespread adoption in biotech for sure. I think it’s one of those situations where people will want to use a tool that is nice and robust that a lot of the potential hires they would be looking at have experience with. And I think Nextflow has gotten to that critical mass where it’s not this really niche thing. It’s certainly for people who have been in biotech for a few years, a lot of bioinformaticians have experience with it.
Evan Floden: [00:05:24] Yeah, I think that’s an interesting point on how does something like Nextflow essentially become a de facto standard. It’s an interesting one in that if you look at there’s been many groups or many times that folks have tried to create standards, whether this is in academia or in industry bodies and the like. And if we look into parallels of the areas, things like the Docker container is almost is the standard for containerization. But that was started by a few folks who had an idea and created a company. And now really revolutionized the world of modern software. I think that Nextflow has similar ideas and that it was we were trying to do something a little bit against the grain, not necessarily sanctioned by anybody. And that almost spurred us on in some sense. But then once you get that critical mass has taken off, I think that there’s touching on the aspect of I agree, it’s fantastic that folks can come in, they’ve already got the skills and Nextflow and then there’s that other whole piece to it, which is what I call the content, but it’s really the pipelines and all of that material which enables folks to take take those off the shelf. There’s now things like nf-core, there’s modules. We’re getting up to over a thousand modules there which you can really mix and match the components of your pipeline and obviously use the framework and the tooling to build that there. And that’s really can save organizations so much time just even getting started with that analysis. For example, add their own module in which is specific maybe for their chemistry on some sequencing, but they can use the rest of the pipeline. Those kind of examples were prevalent and it’s something which I think is possible from having this open science approach to things.
Grant Belgard: [00:07:03] And what’s your vision for the company?
Evan Floden: [00:07:05]  at the start we’ve really been focused on the workflow execution piece and I think this is going to continue to be our bread and butter. We still see the challenges exist with regards to scaling generally across bioinformatics, but also across life sciences as well. The volume of data is not decreasing. It’s if anything, it’s increasing the use cases for sequencing as well. And imaging analysis is increasing. The multi-modality of the work which is coming in is requiring almost different approaches. So we focused a lot on that high throughput piece. There’s an element where we have been building up a collection of open products, things like Nextflow. We have MultiQC, which is the most widely used analytic and reporting tool. We also have FusionWAVE, which are two infrastructure tools which allow folks to run these pipelines at scale. And that’s a like a core layer of infrastructure within building on top of that secure platform, which is essentially the main product which our customers purchase. And as part of that, that’s the piece that we’re scaling up beyond the pipelines into things like data management, into things like interactive environments and going from there. There’s a lot of platforms which claim to do the same thing. I think we have a slightly different approach to that and that’s I think kind of the one of the key differentiators here as well.
Grant Belgard: [00:08:19] And who are your competitors and how are you different from them?
Evan Floden: [00:08:24] There’s been genomics in the cloud. It has been around for a while and there’s obviously been some big players there for a fair amount of time. There’s obviously a whole bunch of of newer ones as well who have received funding recently. We still see the biggest competitor in at least the majority of deals is folks building it themselves. They are typically building these systems. You often have people who are, say, familiar with a certain way of doing things and they try and basically do the same thing in the cloud or they want to scale up beyond single users. And we see a lot of customers who purchased the platform. They’ve already tried to build their own thing first. So that’s the core competitor that we see in terms of building that out. The other competitors there are when I think about generic genomics in the cloud. They’re really focused primarily on a lot of simplification. And I think that there is certainly a subset of users who do need that simplification. But one of the things that we think about a lot is when we think about our value that we provide, we’re not necessarily just helping people sort of simplify.
[00:09:25] We also are making the science easier and also making it possible to do harder things in some sense. So it’s really about taking modern software engineering, providing those tools to scientists. And it’s a little bit like treating scientists like they are developers and giving them the tools to do harder things than to specifically run things in a more simple way. The other aspect of that is that whilst we have our open source roots, that really means that when customers run an exploit pipeline, they run in their environment, they run in their cloud. If you connect up our platform, you connect it up to your cluster. It could be running in Europe and you could connect it up to your Azure instance, which is running in West Coast. You are moving the workload to where the data is in this case, as opposed to the other way around. So it’s a very much more like an open framework and open platform that allows you to connect that as opposed to more of a walled garden, which you see in the other approaches.
Grant Belgard: [00:10:20] What challenges have you encountered the dramatic growth you’ve had in your user base?
Evan Floden: [00:10:25] I think the challenge is often from an organization side of things is really scaling up, how do you go from a group of people, a small group of people, really building something to be able to replicate that across an org. It’s a lot about investing in folks. Not everyone you hire is going to have a PhD in bioinformatics and being able to translate those skills and to be able to have that customer empathy and that customer understanding and almost like scientific understanding of the problem is a challenge. And I think that that’s kind of applies a lot. You see in some other organizations where bringing folks in maybe without any life sciences background or ability or willingness to learn in that doesn’t necessarily translate so well. So from an organization perspective, it’s a lot about building that context and building that organizational knowledge and memory to be able to do that. On the user base side, I think we haven’t really had too many challenges, I would say on that community growth. We’ve been very fortunate that projects like nf-core really came out of the community. They were organic in the sense there is folks who building their own training courses. There is people who have just built so much content around Nextflow, the plug in systems, the AD pipelines on nf-core. That’s really almost I would say, really happened organically and therefore it hasn’t really involved too much in terms of necessity of resources or work from our side other than really just trying to foster that community and enable those people to solve the problems for themselves.
Grant Belgard: [00:11:55] This is your first company, right? So I guess there have been a lot of new things to learn. What’s surprised you the most?
Evan Floden: [00:12:01] I previously had worked at a startup for 4 or 5 years, which was very interesting. Experience was very small at the time. The company ended up going public, so I spent some time there and doing product development. It was at the bench though, so it was very much a scientific role. I saw that there, that it was very interesting. However, it was just very slow to do things at the bench given to what you could do and my inkling for tech really got the better of me and went into the bioinformatics field. When I think about how that journey has progressed and I think particularly the last three years as you start to hire and work, I was surprised at how important the personal relationships have been. I think as a scientist you often think of the world of business or you think of the world of creating an organization. You think it’s very transactional. And when I think about the folks that we’ve partnered with on the investment side or the people that we’ve hired or the partners that we’ve brought on the customers, those relationships are now, in some cases ten years old. And I’ve just been so surprised at how important and how deep they have been just given my maybe slightly naive view coming from a purely academic perspective so I think it is the key one I always go back to when I think about that.
Grant Belgard: [00:13:17] That’s an interesting observation. I think it aligns with what I’ve maybe seen as a broader perception in academia where actually many things are more transactional in academia than they often are in biotech, although in both contexts those personal relationships are crucial and very, very long lived. Because it’s a very small world. And you often work with the same people for many, many years in many different contexts. I know we very often work with the same people, but at different companies because there’s so much churn, they’ll leave one company and go somewhere else. We work with them there and and then someone else from that new company leaves and goes to another, but it’s actually those personal relationships can play a much larger role than the formal relationships with the companies in some cases.
Evan Floden: [00:14:12] Yeah, absolutely. We’ve had one customer who’s on a company number three, and he’s a buyer number three as well in terms of spreading the word there. So that’s the relationships which you think about. They grow over time. I think the community aspect of Nextflow helps a lot with that. We really think that there’s a lot of value you can add and through that community, through knowledge sharing to solve those problems with those folks and hopefully bringing some software to them which adds that value. And then obviously as part of that, that can help them broaden and strengthen the relationship on the academia side. It’s definitely very important. I think particularly around some of the relationships you form with folks like your supervisors across that time. I think those are very special relationships. They can last a long time. I’m not going to go too controversial and try to think about the order of first author ordering as often happens in some academic papers. Thankfully, I haven’t had too many situations like that, but yeah definitely don’t envy that.
Grant Belgard: [00:15:11] For sure. On a completely different topic, how do you think about on site versus remote versus hybrid at Seqera?
Evan Floden: [00:15:19] Yeah. It’s interesting one for us. We started. We really got our Pre-seed funding in March of 2020. I quit my job at the CRG and I was like, we’re going to do this. In February, I started working at home because we didn’t have an office for about 2 or 3 weeks, and then the rest of the world joined me on that. So that was an interesting transition. It’s like we hired our first people during that. We raised our first money in March of 2020. So that was like being forced into it, particularly in Spain. It was particularly long and strict lockdown. As part of that, it forced us to be essentially distributed team from the beginning. And given the focus of the customer bases, which is primarily in life sciences hubs. So you can think of Boston, Massachusetts area, California, so US East coast and offices, some stuff in Cambridge, UK, that was going to always be the central hub for our customers. And we had to deal with that from the beginning. So that was a reality for us and saying, now we try and build ourselves out from hubs themselves.
[00:16:22] So we believe that it’s great for people to be able to get together, if anything, for the social aspect of it and to get to know each other and to build those relationships more than actual the work of. Because most folks are going to be in Zoom calls for a decent chunk of the day anyway. So that’s our take on it, believe in building those relationships. And it’s not easy, though. And I think it’s particularly not easy if you’re a young company and you start like that in a, I would say, non-intentional way. It was definitely not our intention to do things in a sense. It kind of happened and we’ve tried to do the best that we can in terms of managing that, but it’s something that we would have learned a lot from. And I guess like a lot of the tools and like a lot of folks, that’s become the new norm for many things.
Grant Belgard: [00:17:10] If you hadn’t gone down the Seqera route, what do you think you would be doing now?
Evan Floden: [00:17:15] Interesting. I don’t really think about that stuff too much. I think that I still see myself as a scientist at heart. I really do enjoy the scientific process. I enjoy discovering things and learning in this way. I could definitely see myself tinkering a lot and I would continue to do that whether that’s in more product development roles or scientific method development. So very much like what we were doing and doing a PhD. That’s the thing that I really enjoy doing. I think it’s part of this role though. I’ve been learning a whole lot of new stuff which also excites me as well. Like it’s many different things that I didn’t think that I would be doing. So it’s hard to say. I’m very glad that I’ve kind of gone down this path in terms of what I would be doing. In another sense, struggle a little bit to think about it.
Grant Belgard: [00:18:00] If you could go back in time to give yourself advice in 2018 as you started the company, what would that advice be?
Evan Floden: [00:18:09] The best piece of advice that I give myself in some sense really about the bigger picture sometimes because it’s very easy to get drawn into the day to day and the small things. And I think particularly as a company scales, you can often you find yourself thinking of those little things. And it’s really only when you step back and you see the growth or the success or the things really matter. So being able to zoom in and yes, the small things do matter, like getting those things right is important, but also being able to scale out sometimes. And I guess just getting that balance right is difficult. It’s a very intense job. It’s a lot of hours and it’s a lot of time. I think that trying to get that balance right, I wouldn’t even call it balance. There’s harmony in your life. And by having those different perspectives and also different perspectives on the different elements of your life, that’s the advice I would give myself to try and work on. And I think you can tell from my description something I’m still trying to work on now.
Grant Belgard: [00:19:06] Are there any practices you’ve adopted over time? Having a protected half day a week or something to focus on that? Or has it been a moving target?
Evan Floden: [00:19:15] Very, very much. For me, it’s about like routine. It’s the way that I’m able to structure my life. That’s typically starts with beginning in the morning, spending some an hour or so with my son before I have to go to work. And then really trying to fit in all the things that I need to do to to feel good around the work. So for me, that involves a cycle to work. I need to get to work. So I cycle there. It takes 45 minutes or so and then I do the work and then maybe at the end of the evening I’ll be able to cycle back and then try and fit in those times just to try and make it work in a way where I don’t feel like I’m going too much in one direction. So being able to pull those things together the way that it works, I do find this is very difficult with travel though. And obviously it makes it very difficult to fit in the routine in that. So I’m trying to be a little bit more structured about that. And one of the things I’m working on to improve as well, I guess a lot of folks have similar challenges there.
Grant Belgard: [00:20:10] Do you have travel system down now? Checklists and things that feel like you’ve optimized?
Evan Floden: [00:20:17] What I’ve been working on now is more around basically having Monday to Friday where I’m trying not to travel during that period. So I will travel on the weekends to different places and I’ll be in a location for a week, even things like staying in an Airbnb if possible, because then you have got a relatively normal house where you can get into those routines, just trying to do that more. That helps me a bit. I’m still not super. I wouldn’t say I wouldn’t call myself having a system down or having particularly a way of doing things. I like to have a set up, a structure. So where I’ve got my laptop with a keyboard mouse guy, so having that set up and structure just helps me a lot as well.
Grant Belgard: [00:20:51] And what things do you find yourself traveling for Seqera these days?
Evan Floden: [00:20:55] Yeah, we’ve got a lot of events that we’re running. And so given the focus in a lot of North America, we’re spending a fair bit of time there. So we have, for example, the Nextflow summit, which is going to be in Barcelona, but also in Boston this year. So we’ll be spending some time there. We also do secure sessions, which are great events for the community to get together. We’ll often have some talks on technology, things that are coming updated, product updates, roundtables, this kind of thing for 3 or 4 hours in an afternoon. Previously done those in San Francisco and in San Diego, Boston as well, the hubs and continuing to build out that. We’ve been doing a few shows around. We’re going to be at ASG this year and going to be traveling a fair bit around that. And those are the most of the areas. We also have, as I said, a distributed team. So being able to spend time with them is really important as well.
Grant Belgard: [00:21:45] Great. We’ll have to have our operations director come say hi. I won’t be going to ASG, but we will have a booth there.
Evan Floden: [00:21:52] Yeah, folks are absolutely welcome to come and say hi. We’ll get you some next swag and always happy to give folks a demo.
Grant Belgard: [00:21:58] Nice. What message would you have for our listeners about Nextflow and Seqera? As I said, I’m sure most of our listeners have heard of Nextflow and probably many our users, but for those who haven’t used it before, how would you recommend they get started?
Evan Floden: [00:22:15] Yeah, absolutely. If you’re thinking about running pipelines in a way where you want to run them in your own infrastructure, where you don’t want to deal with the complexity of setting that infrastructure up, then Seqera platforms are a great way to start out. We have a community showcase where there is collections of pipelines which are available, where you could log in, select those pipelines and run those and get a feel of how it works. We also continue to add in more options around that, which is enabling on the data management side. So by the time this podcast comes out, we’ll have a data explorer which enables you to really browse and search across different buckets, across different object storage that you may have. And we’re also looking to bring out more functionality and interactive space. So that’s a great place to get started. If you go to tower.nf or if you go to seqera.io, you’ll be able to log in there and find that out. It’s absolutely free to go, go work that and give it a go.
Grant Belgard: [00:23:07] Great. And for people who are already casual Nextflow users, how would they best further build their skills?
Evan Floden: [00:23:17] Yeah, I think there’s some interesting courses which have come out recently, which we’ve been developers with the community as well as from folks at Seqera around advanced Nextflow usage. That’s been a really useful set of resources which have been built out. I think being around the nf-core Slack and the Nextflow Slack is always a great place. There’s a lot of people doing very innovative things there, platform and being able to connect it in there. And then of course attending the events is always a great place to see that. We have 50 speakers, I believe across the events of Nextflow summit in Barcelona and Boston this year. It includes sequencing companies. Obviously the large cloud providers are all going to be there presenting the latest things. We have customers and developing kits. We have customers working in population genomics sequencing projects as well as obviously a whole bunch in biopharma. So that range of use cases can give people a really nice understanding of what other folks are doing. And I think that format as well, where you can really interact with people, can go a little bit deeper into the specifics of how they’re solving those problems is a great way to learn.
Grant Belgard: [00:24:23] So in theory, something like Nextflow would be fantastic for scientific reproducibility, right? Which is obviously been a major issue in the life sciences. But what do you think are the major barriers to adoption of Nextflow for those purposes? Because you usually hear about Nextflow in the context of people trying to do analysis on their own data for their own projects and so on. And it still seems pretty uncommon to see papers published where they have single button reproducibility anyway.
Evan Floden: [00:25:00] Yeah. And I would point folks to the Nextflow paper from 2017 that we published, which is really a little bit of inception here, but we published an excellent paper, obviously using Nextflow, which is really describes a lot of that. And from that git repository you can reproduce everything calling Nextflow from notebooks. So the idea is of open science, I think they’re worth exploring because it goes a little bit beyond just what people consider open source. And that open science is really is a key part of that. So if you think about open source, it’s almost like it’s a license. It’s like, okay, you put Nextflow software out there, people can use it. People can do what they want with it, the Apache 2.0, etcetera. Open science goes beyond that, and it goes to that point where, as you say, people are, for the most part still just publishing papers. But we start to see more and more adoption of folks who are not publishing papers, but they want to publish the paper and the analysis or even just the analysis in itself. When you want to run that analysis or even reproduce that result there, if it’s not going to run on your laptop, it’s going to be very difficult to do so you’re 100% right that Nextflow enables that piece. It does it through a couple of ways. One is obviously containerization, so that integration of containers means that the environment that the task runs in is essentially absolutely the same byte for byte. The other piece of it is that you can run those containers then in any infrastructure so you can run them in  or you can go run them in your cluster or you can run them on your laptop.
[00:26:21] That piece then enables people to reproducibly do that and almost validate the result that then has a little bit of a flywheel effect. Because if I publish my analysis in that way or my tool in that way, you can then take it and then you can put your data into there as well. And that’s the real important piece I think that Nextflow has enabled there. If we think about that going further, one thing that we’ve really stressed is this idea of empowering scientists with modern software engineering so you can reproduce the workflow, but how are you going to reproduce the environment that you use to set that up, or how are you going to reproduce the data set that you use in this sense? And that’s really what we’ve been working with Seqera is the whole thing is defined or can be defined from API. There’s a CLI as well. So you can say import this pipeline or define this computer environment in this way, import export from that. And it’s treating the whole research environment in a reproducible sense, not just the individual component. And this is very much in the vein of infrastructure as code like setups where folks have been using things like Terraform for building those environments and just taking it to the next step specifically for bioinformatics.
Grant Belgard: [00:27:32] What do you think it will take to get that to become standard practice? I mean, there are some individuals and a few groups that routinely will do that. But majority of the time, it seems these are done by custom scripts that are available upon reasonable request and nobody ever gets them.
Evan Floden: [00:27:55] It definitely is changing as depending on where you are. So if you are developing a new tool, it’s kind of by default. It has to be there. If you consider it was going to be in a paper, the reviewers would essentially have to run the tool and try it out. I think the more you go down like two different areas, then you’ll see I agree it gets less and less in terms of that compliance. I think it’s probably very much like carrot and stick in this sense. Carrot in the way that if you consider yourself, like when you write something in Nextflow or you write a pipeline or an analysis in a reproducible way, you’re really just doing it for yourself in three months time. Because if you’re anything like me, in three months after you’ve done an analysis, you come back to it and then you have to rerun it because you’ve got a new sample or you’ve got some new parameter. It’s just absolutely impossible to remember how you did it, what you did it like, exactly that. So that reproducibility piece is almost like for yourself in a very selfish way. That implies the carrot. The stick bit is coming from this publishers. So as our former supervisors, Cedric Notredame, he has one of the journals and as part of that, it’s really about publishing pipelines, publishing things in this way. And it is using standards like nf-core to do that. So you have to publish in a completely reproducible way, you can define exactly what you are publishing, and I can really see us moving towards a situation where the paper is just one artifact of the actual output. However, it’s not the main output. The actual main output is often the case is like the actual analysis in the tool and say this is particularly relevant for tool development, which is obviously very, very widely used in bioinformatics.
Grant Belgard: [00:29:31] Nice. So maybe changing gears a bit. Can you take us back to your childhood? What got you interested in science?
Evan Floden: [00:29:40] Yeah. So I was originally born in New Zealand. I spent probably the first nine years there and then got the opportunity with my family. We lived in Malaysia and Sweden growing up for some years. I think in New Zealand it was a very kind of natural environment in some senses. It’s obviously a lot less people and a lot more nature, got me interested in bio. And I vividly remember thinking about biology in the sense during high school. I got a little bit obsessed with scientific nonfiction and saw myself really wanting to go into biotech. Bioinformatics at that time was much less prevalent. I guess it was very early for bioinformatics. So that’s what led me to study biotech and then to spend time going into molecular biology. I had a really interesting opportunity for a couple of years as an undergrad working in a yeast laboratory, and what we were doing was essentially had a knock out set of yeast. So it’s you can imagine very large agar plates. Each one of those plates has got really a couple thousand samples on it and each sample has got one different gene removed. And you can treat this with different chemicals or you can make these yeast together and you can look at chemical interactions or genetic interactions and understand what’s happening there at a genetic level and how it integrates with those pieces. There was obviously a bit of robotics, obviously a lot of yeast culturing and a touch of bioinformatics as well. And I think that’s one of the things that sparked my interest into bioinformatics later on. Although to be fair, I didn’t do that until I went to Italy to study a master’s there. Bioinformatics wasn’t available in New Zealand at the time, so it was my opportunity to jump into the field.
Grant Belgard: [00:31:20] So you finished your degree in New Zealand in 2010 and what did you do then?
Evan Floden: [00:31:27] I joined the start-up. It was a very interesting startup. It was about five people at the time were developing a medical device, which sounds nice and clean, but the medical device itself was coming from the fourth stomach of sheep, so I’m not sure if the listeners are familiar with haggis is essentially one of the stomachs of the sheep. It’s a very interesting material. We were trying out lots of different materials and the idea was to see if we could create a bio scaffold. So essentially a tissue which could be used for soft tissue repair in surgery, you would remove the different layers on the top, decellularized it, freeze dry it and essentially end up with a shelf stable product which could then be used in different applications. So the first few years there did a lot of product development. We got FDA approval for the basics of the platform and really ended up developing several other products, for example, creating multiple layers of this for breast reconstruction or hernia repair. And this was really just involved in that whole start up phase. It was really exciting. It was really interesting. I saw how I saw the determination which was required to create a startup, but I also saw how interesting it could be to work on many different topics and many different things. And that change I really liked and I just was just enthralled by that. And I got my, I guess if I  place the seed, let’s say, for what was happening with Seqera later on.
Grant Belgard: [00:32:48] And what brought you to Italy then?
Evan Floden: [00:32:50] I really wanted to get into bioinformatics. I think it was something I’d been pushing for and that’s where I got an opportunity. I got a scholarship to do a master’s there. It was a very interesting time. I got to fully focus on that and I knew some basics of programming, but I really got to fully hunker down and spend a good 18 months or two years just purely focused on that. The bioinformatics program in Bologna is quite widely known. We got to do fantastic things. For example, we would build a Markov models from scratch, from the individual components really got exposed to how machine learning was working in sequence analysis itself. It’s quite a mathematical program, but it really gave me the basis for many of the things that came later on. It’s actually where I met my supervisor, Cedric, and that’s what started the journey into Seqera. I had a little bit of time in Cambridge in between in the UK working at RFM, but that was what got me started in that.
Grant Belgard: [00:33:47] Nice. And then after your stint at Cambridge, you went back to Italy, right?
Evan Floden: [00:33:52] It is Barcelona. Yes. Sorry, it’s Barcelona. That’s where I started my PhD, and that’s where I met Paolo. And the story kicked off.
Grant Belgard: [00:33:59] Nice. And then afterwards you stuck around in Barcelona at the CRG. Were you working at all with the CRG during your PhD?
Evan Floden: [00:34:07] Yeah, so my PhD was at the CRG. It’s a research organization, but I mean technically you’re part of a university as well. Although you spend the whole time in the research organization, it’s more of an affiliation so that they can provide you with an academic degree. Yeah, really interesting place. And there’s a lot of the leading biomedical research center in Southern Europe, fantastic location as well, very international. And it provided a fantastic opportunity to learn there and be surrounded by smart people. And obviously it’s what we’re doing.
Grant Belgard: [00:34:39] And this Seqera Avenue formal relationship with CRG or is it kind of just another institute where there are a lot of Nextflow users?
Evan Floden: [00:34:49] Obviously, CRG being home of Nextflow, let’s say the original home of Nextflow, there’s always a special relationship there. The usage of Nextflow is obviously very wide in the organization there. We consider ourselves like a spinoff of the organization. And so the relationship stays special in that way.
Grant Belgard: [00:35:09] That’s great. And do you have any advice for our listeners who might be scientists who are considering the entrepreneurship journey?
Evan Floden: [00:35:19] Yeah, it’s hard one in the sense that, like, you don’t know until you really jump off the diving board in that sense. I found it personally to be very rewarding and very fulfilling. As I said related to your question before, I can’t really imagine myself having not done this or doing something else. At the same time, I fully admit it’s not for everybody. There’s a lot of sacrifices you make in other aspects which are difficult. It’s a way that you can have a very fulfilling role, very fulfilling job. And for me, being driven by the impact of it, I think it’s just the way that I felt that I would best be able to build something that would scale and that would have the most impact on it. I think that one of the reasons behind Seqera at the beginning is really just to spread that I was one of the first couple of uses of Nextflow. It really changed how I was working and I wanted to put that into as many people as possible. I feel the same way about what we’re building in Seqera. There’s great technology which we just want to put into the hands of scientists to help them work. That entrepreneurial journey is for me, it’s really much it’s just the way to get that done. And it’s that the way that it can manifest, I would say.
Grant Belgard: [00:36:26] So if you look forward ten years from now, what would you consider a success for Seqera?
Evan Floden: [00:36:33] We really want to see ourselves as first and foremost, having helped thousand biotech biopharma organizations really reach their own goals. And for that, that’s usually outcome in patients. We want to see biotech continue to grow. We want to see the adoption of those technologies. We want to see things like personalized medicine become available to people. We want to see the promise of genomics technology become a reality in that. That’s the first, I think, that we can play a really important role in making the analysis part of this data analysis, part of this accessible, available, open and build the bioinformatics tool framework that in the world that we want to see in there. From an organization perspective, one of the things I really would love to see is that from Seqera, we almost create our own ecosystem as well. So whether that means of employees who create their own things or really new projects which sprout from the Nextflow ecosystem, really seeing that gives me a lot of satisfaction because it shows that you can start one thing and it can really flower into a whole bunch of other areas. Just myself personally, just really ten years would just love to be obviously healthy, still enjoying the job and really hopefully having made as much impact as possible on those areas.
Grant Belgard: [00:37:49] Well Evan, thank you so much for joining us today. It’s been a nice conversation.
Evan Floden: [00:37:53] Awesome. Thanks a lot, Grant. [See anytime] and folks, if you do want to join us at Nextflow summit, both Barcelona and Boston are still open. We’d love to see you there and thanks so much for the time.