AN INTERVIEW WITH ANTTI YLIPÄÄ: cancer RESEARCHER TURNED CEO

In this session, we introduce you to the frontman of Genevia Technologies: our Chief Executive Officer and co-founder Antti Ylipää. We find out what caused him sleepless nights while founding the company, what led to him gaining such a comprehensive view of the field of bioinformatics and his insights into the future of molecular biology.

Venla Kiminki: Good to see you Antti, thanks for meeting me! So, let us get started. You are a bioinformatics scientist, but it would be great if you could tell us more about your studies, as well as some interesting details around your research background.

Antti ylipää: “I have always been interested in science. In elementary school, when I was asked what my dream job was, my answer was to become a brain researcher. Later, though, computers took centre stage, and I ended up combining my fields of interest by studying molecular biology, computer science and statistics at the computational systems biology program. My own research background is mostly in computational cancer research, but as many bioinformaticians, I too had a chance to work on a lot of different topics during my time in academia. Even though the many side projects felt like a burden at the time, working in various fields has brought a surprisingly significant benefit for me in my current position.

My computational biology career got started with computational modelling of a giant squid axon and developing parameter estimation methods for biochemical reaction networks, but then the world of genes and molecular information processing got a permanent hold on me. Through our international collaborations, I became embroiled in all kinds of omics data that cancer researchers were producing independently, and in consortia, such as the Cancer Genome Atlas. I had the opportunity to spend time at our collaborators’ labs too: at the Institute for Systems Biology in Seattle, and at MD Anderson Cancer Center in Houston. Now, after 10 years of meeting up with life science researchers as part of my current job as the CEO of Genevia Technologies, I feel like I know a surprising amount about other molecular biology applications besides just oncology.”

You founded Genevia Technologies together with Professor Matti Nykter as a spin-off from an academic bioinformatics research group in 2011. Tell us what led you down this path?

“Around ten years ago, as microarray technologies became affordable and accessible to experimental biology groups in general, our bioinformatics research groups started receiving a lot of collaboration requests for analyzing microarray data sets. Most experimental biologists had very little experience with scientific computing and algorithms, and bioinformaticians were in short supply, as they still are today incidentally. At that time, I was a PhD student with Prof. Matti Nykter’s bioinformatics group working on my thesis on cancer genomics. Pretty soon there were so many collaboration requests from researchers working in other fields than oncology, and we decided that it would be better if the experimental groups got access to professional data analysis services rather than just assigning yet another side project to a student in our group.

Since the core services at that time were non-existent, we decided to create a “commercial bioinformatics core lab” to help out experimentalists with their omics data, and that’s how Genevia Technologies came to be. With Matti as my scientific support, I learned how to use omics data and bioinformatics methods in many other fields than oncology, I learned how to properly resource multiple overlapping projects, how to recruit competent bioinformaticians and many other key aspects of scientific entrepreneurship that I had not thought of before. As a company in Finland, we naturally started by providing our knowledge to Finnish academia, but soon began venturing out into other Scandinavian countries as well. The real boon for Genevia Technologies was the massive decrease in sequencing costs which enabled so many new research groups to start adopting omics technologies as part of their research. Not too long after, we had academicians and industry clients from small biotech start-ups to well-known multinational companies all over the world.”

It’s no secret that academics are often anxious about transitioning into industry jobs after they earn their PhD. Tell us your story, how did it feel to transition from a university researcher into a science entrepreneur?

“I can definitely attest to the transition anxiety as I had to combat that myself too, and frankly, I probably felt just as anxious and insecure as any academic researcher dipping their toes into the industry. Somehow, I had led myself to believe that bioinformatics and research were going to be different in academia, whereas everything else would be kind of the same. It turned out to be the complete opposite! Our scientific work is very much like academic research, maybe not surprisingly since we work a lot on academic research projects with our clients. However, everything else turned out to be very different: The first thing I noticed was that getting projects required selling them to professors instead of just waiting for them to contact us. Then I found out that all the money goes to the bioinformaticians’ salaries, and of course that I cannot pay them more than what the professors pay me for our services.

Especially the aspect of selling the projects was terrifying to me as a scientist. I had nightmares about working in sales as it was something I had always tried to avoid at all costs. Thankfully, after forcing myself reluctantly into a few sales meetings, I realized that I had mistakenly thought that selling science projects was like selling anything else, say, cars. In reality, our sales meetings turned out to be much more like the meetings we used to have back in academia with our experimentalist colleagues when starting a collaboration project. Now that I think about it, the main difference is that after the science talk, I just estimate how long it will take for us to complete the project, and assign a price from a table based on that estimate. If the clients agree that the work is worth the amount, we sign a contract, and then it’s back to the familiar collaboration mode again. Later on, the anxiety subsided and now I am happy to report that I actually enjoy hearing about our clients’ work and planning the bioinformatics workflows for their studies!

As a CEO, meeting our clients is only one part of what I do. Roughly, I would say that many of the skills needed and many of the tasks I do, would apply to any PI at a university. I recruit and supervise scientists, write grant applications, make budgets and spending decisions, meet other scientists to talk about science, make plans for increasing the science output of my group and generally take care of my researchers. In contrast, I do not have teaching duties, but instead, I have business duties. In a company setting, we need to plan, structure and manage our work very carefully so that we use the money our clients invested into working with us in such a way that they get the maximum benefit – and come back with their next project.”

The scope of your work seems to be quite versatile, tell us how a science entrepreneur’s typical day at work looks like?

“You’re right, it is indeed versatile. Around half of my time, I invest in meeting professors and research leaders in life science companies. We usually talk about their future or ongoing research projects, and how they can optimally use omics experimentation and bioinformatics methods, as that is generally the value I can bring to the table. Based on these discussions I end up reading papers to understand their application areas, I draft analysis plans and quotations to bring discussions onto a concrete level, and I consult our clients on various issues, such as where to send samples for sequencing for the best prices and quality. Not all of this is strictly business since we do participate in select grant applications too. We are fortunate enough to receive quite a lot of requests to join these kinds of projects, so I do end up spending some time reviewing project proposals and grant applications to find the ones that can best drive our business forward. Not too long ago these tasks required quite a bit of traveling to meet people around Europe, but recently I find myself hopping from one teleconference to another.

I have a lot of management tasks as well, like recruiting new bioinformatics scientists to our team, teaching and supervising them as they learn their new roles, developing new data analysis service products based on what our clients tell me, drafting plans and strategy for the company, overseeing our marketing, and leading my senior managers. Most of these responsibilities require me to stay on top of new technologies, public projects that we leverage in our work, and research papers in the field of life sciences – this suits my personality very well; the engineer in me is excited about new technologies, and the researcher in me enjoys reading about new scientific discoveries quite broadly across biomedicine and life sciences in general.“

Alright, so as a scientist running a company, what makes you tick?

“I feel my current role is very privileged in the sense that I get to be at the forefront of life science by meeting the best scientists in the world and working on their projects. This lets me learn things that interest me and allows me to create an impact on science and technology. Another upside of my job is the chance to execute my own vision on how to run an efficient bioinformatics (core) laboratory and a team of scientists. The computer scientist in me enjoys following how biology is turning into data science before our eyes. This means that in the near future, we get to benefit even more from the application of hot information technology tools – like cloud computing, software automation, and artificial intelligence – as they are adopted into everyday use in biological research.”

Let’s dig a bit deeper into the topic of the near future; what kind of changes do you see happening in molecular biology research over the next five years?

“Molecular biology research will turn into a data science as high-throughput experimentation, like sequencing and mass spectrometry, become ever more affordable and accessible, and the amount of publicly available data increases exponentially. This will undoubtedly weave more computer science like high-performance computing and dedicated hardware solutions into biology research. To be able to keep up with increasing demand of data, robotics and automation –like high-throughput screening– will be leveraged further in order to be able to complete more and more experiments at a lower cost and in a shorter period of time.

The resolution and accuracy of experimental methods will increase. We will be able to probe the molecular contents of individual cells with single-cell technologies and use that information to classify the cells accurately with regards to their type, somatic mutations, and disease status. Furthermore, we will be able to study tissues and organs by mapping molecular properties spatially as opposed to just taking averages. I also see full molecule sequencing technologies just around the corner. Taken together, bioinformatics will not be a separate field of algorithm scientists and computer-support people for experimental biologists, but rather an inseparable part of all molecular biology research.”

Thank you, Antti! Before we go, what would be your message to fellow experimental scientists?

“We work practically exclusively with experimental scientists that are struggling, to a varying degree, with omics data and application of statistics and bioinformatics tools to discover new insights in their particular fields. This is to be expected since not all bioscientists were educated with this sort of research in mind. We founded Genevia Technologies with the aim of helping our fellow experimentalists exactly with these issues. I would encourage experimentalists who really want to focus on their field to think of bioinformatics as just another part of research they regularly outsource: companies already build your PCR machines, mix your reagents and sequence your samples just to name a few. You create the research plan, prepare the samples, validate the findings and report your findings to other scientists; why not let specialized companies help you focus on your strengths rather than trying to do everything with limited resources?”