For our first Founded & Funded podcast of the year and Season 4 opener, investor Chris Picardo sat down with co-founder and CEO of Ovation.io on the heels of their Series B fundraise, to talk about the incredible journey that the company has been on in 2020. Ovation is a scientific data company that provides a Laboratory Information System (LIMS) to independent labs. Ovation stood up testing for COVID for these independent genomic labs in just about a week’s time following the early outbreaks in February of 2020. And they saw a 75 fold increase in usage. A growth curve they could not have imagined in early 2020. They discuss growth and also how the incredible amount of genomic data acquired through testing will be a powerful tool for academics, researchers and drug developers into the future. Transcript is below the podcast! Podcast is available on all podcast platforms – Apple, Google, Spotify
Transcript (this is machine driven transcription so expect some typos)
Chris Picardo: So I thought, today, given the big funding news that ovation recently announced, it’d be really fun to talk to the CEO, Barry Wark about the company and where things are going and how innovation is serving the future of precision medicine. So I think to, to give some [00:01:00] background here, I first met Barry probably two and a half years ago in a pre COVID world where we met over breakfast to discuss, this company called ovation.
Which was, trying to revolutionize the software that independent genetic testing labs were using. And I remember leaving the breakfast and coming back to Madrona and being like, man, I’ve got to get as many people as I can to meet there because that was just an incredibly exciting vision.
And I want to be involved in this company. And, it took a little while, is as processes normally do. But I think about two years ago, we made the series a investment is I think one of the first institutional investors. And we’ve been working really closely with Barry and team since to build the company.
And I think it will be really exciting to talk a little bit about where we’ve gone from the initial vision and where we are today. So to give a little background before I jump into, chatting with Barry which is always fun. Ovation, when we first talked to them was, really focused on [00:02:00] empowering independent genetic testing labs who formed the backbone of modern precision medicine with modern software and at the time and this is still true for a lot of them, the kind of best-in-class software that people were using looked a lot like Excel and probably looked a lot like Excel from the nineties. Not an updated version of Excel. Innovation said, Hey, you know what?
There’s a much better way to do this, . To let labs do significantly more and to have modern tools that, grow their businesses and serve patients better. And we’re going to build that. And, I just remember thinking that is such an awesome vision and a market that a lot of people haven’t touched and that needs to be served better.
And, for reasons we can talk about Barry was also a super compelling person to build the company as it solves sort of his own problem from his postdoc days. Since then the company has been on a tear and so I’ll let Barry talk about all of the really interesting things that we’ve accomplished.
First thing, Barry, welcome, welcome to the podcast. And [00:03:00] I think that, it’d be great just to hear from you. Cause we talk about the business all the time, but not too much in this context, hear from you a little bit about why you built ovation. You know where it was two years ago, two and a half years ago when we first started talking and what we’re doing now,
Barry Wark: Yeah. Awesome. Well, let me tell you a little bit about what Ovation is today, just to set the context. Ovation is a scientific data technology company. Our products make it easier for labs to bring innovative tests to patients that need them while at the same time, connecting researchers and academics with the insights required to deliver life-changing medicines faster.
This has been the vision from the very beginning. In fact, I’ve been fascinated by the intersection of biology and technology. Since I was in high school, I loved molecular biology and I was lucky enough to have a biology teacher who let us learn how to sequence DNA by hand using electrophoretic gels.
I mean, this was really early days. I was inspired by the same teacher who [00:04:00] returned from a conference with a story about this amazing new instrument that automated DNA sequencing. And these were the first sequencers that were being used in the human genome project. Obviously our high school lab couldn’t afford an instrument like that.
They cost hundreds of thousands of dollars, but we had a new digital camera and I figured there must be a way to take a picture of the gel and have a computer analyze it which is the beginning of my. Programming career. It was the beginning of my love of life science. And it was the beginning of my love of the two together.
So fast forward, I’m finishing my PhD in neurobiology at the university of Washington. And I was just frustrated by the fact that life science researchers like myself. Collected way more data than we could ever use. And the data that we didn’t use ended up sitting idle on our hard drives on our servers.
And this is pervasive all the way from academic research through commercial R and D. And it became a passion and I wanted to help [00:05:00] fix this. I took it at face value that getting that data to the right person at the right time was good for the world would help us develop new therapies. It would help us bring medicines to market faster and.
It’s valuable. And therefore it might be good business. And that, that became just the passion and Chris, by the time you and I finally got to sit down for breakfast. We had a little bit more idea on what that meant. I’d met my co-founder Winston Brasor, who came from the commercial side of life science.
And we were really starting to understand that diagnostic labs were this amazing nexus of acute need for good software to run their business better. And the ability for those labs to work together, to bring insights to academic and commercial researchers that would help patients down the road.
Chris Picardo: Yeah. I think what was interesting to me is that, talking to Barry. Now we talk about how much data is being created in life science and then lifescience research and what should be done with it and how people are trying to do different things. But [00:06:00] the thing that was so interesting is it’s talking about how these independent testing labs are really on the front line for this end to end process and think, very one of the things you had said initially is like, Hey, if you.
Have a rare disease and you need to be into a trial. Well, where are you going to go? You need to go get tested by one of these labs. And these guys are, on the forefront of meeting patients with this very necessary service. And like you said, they were being served, poorly if more or less non-existent they by the software that was out there.
And so I, I think that’s something that you just said, which is worth talking about it a little bit too, is that, this is, when you think about what is going on in precision medicine and what are life science companies thinking about? Well, one way they need they’re really thinking about is how do we reach the patients and be able to get them the right tests at the right time so that we can give them the right therapy.
Barry Wark: Yeah, that’s absolutely right. Patients with rare diseases often experience that diagnostic Odyssey, they see many [00:07:00] providers they’re tested for a variety of conditions before they get to a diagnosis. And it’s these labs that we’re talking about that are doing, like you said, that, that frontline work of precision medicine, helping patients identify the right therapy at the same time, as you said.
Yeah. Therapeutic development teams are under constant pressure to accelerate the speed with which they can bring discoveries to market, reduce the risk of that R and D process. And one of the big costs, both time and dollars in all of that is running clinical trials. Whether that’s for biomarker discovery or validation.
Or later stage trials and one of the obvious ways to reduce that risk to accelerate that process is to not do the trial at all. You hear a lot today about real-world data and the use of real-world data in the drug discovery research and development process. And that’s really, these labs are sitting at the front line of that.
[00:08:00] The data collected by these labs is data about patients in the real world. And. If you address all of these labs worldwide, what you’re seeing is a picture of real world clinical data. And in far more breadth and far more diversity than you could ever get by running a clinical trial.
Chris Picardo: Before we jump into kind of what, the clinical trial picture and how innovation is playing in that, which I think is super interesting. And it will be the meat of the discussion in a second. I think it would be helpful if you just talked a little bit about real world data versus, data from clinical trials and what do you mean when you say.
Real-world data and who’s collecting it. And why is it different for, pharma companies versus trial data?
Barry Wark: Real-world data is simply data about patients from real world clinical practice rather than a controlled clinical trials. So as a patient, you may get enrolled in [00:09:00] a clinical trial and a doctor who’s not your own may maybe collecting data specifically for that clinical trial.
But every time you visit your provider or get a task that goes into your medical record, that’s potentially real-world data. The huge challenge with using this real-world data is its diversity. It’s often unstructured or poorly structured, and it’s also siloed. Real-world data is collected in millions of places around the world.
And so for a clinical team, a clinical R and D team or a researcher to say, we’d like to go use real world data. They face a myriad of challenges in finding, sourcing, structuring and collecting that data in a useful way. The promise though, is twofold. Maybe most importantly, it’s a chance for patients to contribute to their care and the betterment of care for other patients like them.
Many patients when you ask them, if they would like to have some agency to help use contribute their [00:10:00] data to this effort, many patients say yes and I certainly would be one of them. The other side of it is that data that patients choose to contribute is potentially able to accelerate or replace a clinical trial.
Right.
Chris Picardo: Yeah I think that’s really interesting and it’s a nice segue for maybe, talking about what’s happened in the last year. Because I think in a lot of ways, we’re in the biggest real-world data situation that we’ve been in ever, we’re effectively going to run the largest human trial in history because we’ve got to vaccinate.
Everybody. And at the same time, testing has actually popped into the forefront in a way that two and a half years ago, we would not have expected and was not part of our investment thesis here with the fact that. With COVID-19, we are testing certainly as many people as we possibly could.
So I think it’ll be interesting and this will be eventually good to talk [00:11:00] about what ovation is thinking about doing in the long-term. Let’s talk about first, how Ovation, helped in the COVID-19 pandemic and what we did for our. But what we do for our labs and then to, just how much data are we talking about and why has COVID, for lack of a better term, been a bit of the catalyst for accelerating, kind of everything that’s going on in this data and precision medicine world.
Barry Wark: There’s no question that. COVID-19 has pushed labs doing molecular testing and those doing infectious disease testing to the forefront. Like you said, in a way that we never would have predicted, but these are the same labs that ovation has been serving from the beginning.
And so we were well positioned to help those labs. Not only get off the sidelines and contribute to the COVID-19 testing effort, but in some cases achieve truly ambitious healthcare objectives. I think one of the things we can say [00:12:00] about the last year is that it has forced the healthcare.
Industry to tackle ambitious objectives at a scale, and certainly at a pace that was almost unheard of previously. And if you’re going to try and dramatically change an industry dramatically change the businesses of these labs. At that pace and at that scale technology is one of the only ways to achieve it.
Very early on we set as one of our company missions making a significant impact on the availability of testing for COVID-19 in the United States. We don’t disclose exact patient numbers, of course, but ovation customer labs have now processed and millions of SARS CoV-2 tests in the US and worldwide. One of the things we’re most proud of is that we’ve helped our customers achieve. Like I said, ambitious healthcare objectives, whether that’s scaling up to meet massive testing demand in their community.
Standing up new, entirely new labs, literally overnight or new complex workflows [00:13:00] for back to campus initiatives, for example we’re also really proud that because we’ve been able to help labs both large and small our customers are providing testing for often traditionally underserved populations all over the country.
Chris Picardo: I, because I’m, I get to take the time to brag about right. Ovation stuff in a way that you wouldn’t, because you’re too humble. Why don’t you just talk a little bit about how fast we were able to help our lab base. Start COVID testing. I think, we’ve heard about this whole testing issue, but I think, take a second to talk about our software, that approach, and just how fast we were able to turn this on for our launch.
Barry Wark: Well, one of our thesis is in working with with you and the Madrona team is that we understood early on that at our core, we’re a technology company and we believe like you do in investing in great technology and great technology teams. With this pandemic, we were able to bring early in the pandemic, new workflows, new [00:14:00] technologies to market really quickly.
We were the first to market with some of the pooled testing workflows. We’ve been able to adapt to the rapid and ongoing changes in both. Test technology and reporting requirements for all of our labs. And we’ve been able to as I said, rapidly, expand the scale of testing in our labs.
We’ve seen a, roughly 75 fold increase in the utilization of our platform in the last nine months. And it’s been a bit of a wild ride.
Chris Picardo: Yeah, it’s, I, again, like COVID was not in our 2020 plans. It was not where we were planning on, focusing a lot of time on the business. But, I remember from the time that you guys said, Hey, we need to get some, we need to get some software, updates going. For lack of a better term so that we can set our labs can test for COVID to the time that your first lab started testing for COVID. I mean, that must’ve been less than 10 days and,
Barry Wark: Yeah, it was just, yeah, just over a week. And we’ve been. Building and deploying [00:15:00] updates continuously since then. We’ve also put a lot of time and effort into making it possible for labs to start or expand infectious disease testing in general. There are a lot of labs that hadn’t been doing infectious disease testing before COVID and now need to.
And we’re able to get these labs up and running in less than 72 hours from signup to first production sample. It’s a huge effort all the way across our engineering and operations teams.
Chris Picardo: yeah, it’s, from being able to talk to you about it on basically a daily basis, it’s been pretty impressive to, be along for the ride on how we’ve done this. We’ve got a pretty front row seat, right? Because of this on just how much testing is going on, not just COVID and how much data is being created. . How much what’s the scale of the life science data that’s out there? I mean, obviously we’re, we’ve, we’re seeing parts of it at companies like flat iron and foundation. I’ve seen parts of it, but that just how much data is out there.
And, what’s the current state of how it’s being used.
Barry Wark: I [00:16:00] don’t think anyone really knows how much is out there. And it’s for the reason that I got into this to begin with what’s available. And what is accessible is quite literally the tip of an enormous iceberg. And that’s for a myriad of reasons because real-world data is poorly or completely unstructured because it’s siloed in. And it is all over the world because none of those entities have the technology either in-house or amongst them to work together. We don’t see most of it. And I think what what this pandemic has forced to the forefront is the recognition that we need, the ability to. Use this data for public health uses for accelerating vaccine rollouts, for understanding how to allocate resources in a public health crisis.
But beyond that, like you said it’s opening a lot of people’s eyes to the [00:17:00] value of technology in healthcare in, in enabling some of these ambitious data-driven initiatives.
Chris Picardo: If there’s an enormous amount of data out there, most of it’s untouched, but it’s created. And we’ve talked a little bit about certainly in the beginning, how important this is, and I think COVID has. Just, shined a nag notifying glass, right on just how important this type of data is from the fact that we were able to sequence the virus so quickly to the fact that, the first couple of vaccines out on the market are directly due to sequencing.
The virus and actually using this data that we’re talking about. As you think about what’s going to happen with this, right? What are the breakthroughs coming? Maybe it’s COVID related. And the fact that, now we have this pile of infectious disease data, and we need to think about how that’s used for future pandemics.
Maybe it’s. Maybe it’s not that, I’m sure a lot of talk about right. Using data to create better therapies, but you know what do you think is the [00:18:00] kind of next set of breakthroughs that’s come in and what are the important things that are going to be enabled by, this sort of proliferation of data, which has really been accelerated in the last year,
Barry Wark: well, I think there’s maybe a couple of lenses that we can use to answer that question. One is a market. View. I think that we would expect even after this pandemic there to be continued interest and continued resources allocated towards infectious disease testing whether that’s surveillance or just maintaining the capacity to handle pandemics like this in the future.
Sadly, this won’t be the last and I think we all realize that the ability to have more elasticity in the. Testing and healthcare infrastructure is something that’s just necessary going forward. That’s an interesting, overall market change and we’re all still trying to understand all of the implications of that.
Secondly, of course, there’s, public health uses, right? We’ve seen a lot more data-driven resource [00:19:00] allocation. We’ve seen the CDC using real-world data to help prioritize and choose amongst the. Various diagnostic tests that have received emergency use authorization, to understand their real-world performance.
And we’re seeing real world data used in planning the vaccine rollout, both in the U S and worldwide beyond that Tragically. There’s a huge population of new patients worldwide, who are suffering from many long-term conditions associated with COVID-19 infection. Those long-term conditions may be biologically or mechanistically related to conditions.
We’re used to treating such as cardiovascular disease. But in other cases, they may be mechanistically relatively new or previously rare diseases such as a multi-system inflammatory syndrome. In either case there’s a huge opportunity to learn quickly about these diseases from this population of patients.
Scientifically we want to do it quickly. We want to do it efficiently because it’s an opportunity that we hope doesn’t come [00:20:00] back again. But also we want to help these patients and future patients. And so there’s a lot of urgency to do something smart and effective with this situation.
So that these patients and others can have a better life.
Chris Picardo: And would you say that software like ours is really the only way that this is going to all come together efficiently to solve this problem?
Barry Wark: Yeah, absolutely. I think all three of those are. Areas where software has a major role to play. There’s no question that modern technology can help healthcare be more elastic, more efficient and more scalable. There’s no question that companies like ovation and many others are contributing significant real-world data to that immediate public health need playing really significant roles in helping.
Leaders respond to crises like this. But I think in the last point it’s perhaps most important that labs and [00:21:00] providers be able to work together efficiently on a technology platform that allows them to bring their, all of their efforts together with life science researchers to accelerate the development of therapeutics and our understanding of these diseases.
Chris Picardo: I want to dig in a little bit to that last point you made and it relates to something that you brought up earlier about clinical trials and, What’s going on. And how innovation is it’s poised, but you know, to start with we’re in, we just seen the probably fastest, most decentralized clinical trial happen.
In our lifetime, someone might call me on that for not being totally accurate, but I’m willing to bet that’s close to accurate with the vaccine trials that happened. They managed to do trials in a really tight timeline at decentralized locations with tons of patients and in order to do they took a ton of data along the way, to To sort of speed up the traditional process. And now that was obviously done out of necessity. But it’s, it’s proved a bit, right? That there is a different model here that can [00:22:00] be used to do trials and are in a really interesting new way. And I think, let’s dig in a little bit on how ovation as part of our longer term vision is really going to enable what we might call virtual trials or decentralized trials to progress them in a faster and more efficient way than what’s historically been done.
Barry Wark: absolutely. I think it’s important to distinguish. There’s a couple of types of trials that, that therapeutic development team might want to do. There are interventional trials, like the vaccine trials where we’re going to give a patient. A therapy and measure the outcome. There is a ton of pressure that’s been created on those kinds of trials by the COVID pandemic.
It’s much harder to convince patients to come into a central site. If that site has capacity at all in order to perform the test, it’s much harder to retain patients in this environment as well. It’s been a lot of pressure on what you’re describing virtual or distributed trials for interventional studies.
There is a growing, but still young industry in [00:23:00] enabling that kind of trial. And this pandemic has accelerated by decades. The progress in that side of things, The other type of trial or non-interventional trials where a researcher may be trying to understand what are the biomarkers, what are the signals that help us understand which patients are.
The right patients for a particular therapy or which patients are the right cohort for a study and understanding that kind of biomarker early in the life cycle of a therapy before clinical trials, de-risks the entire rest of the program accelerates the rest of the program. And so there’s a ton of value on those biomarker style studies as well.
And that’s that’s an area that’s seen a lot less. Attention. But where we think that the diagnostic labs that are our customers have an incredibly important role to play because they are one of the main sources for that kind of biomarker measurement. That’s available in the real world.
Chris Picardo: Yeah. So how does ovation? Sit in the middle there, right? How are [00:24:00] we thinking about sort of the software layer, that’s sitting in between labs and potential customers or users to, to speed up this process.
Barry Wark: Our approach is relatively simple. So our goal is to allow patients. They are doctors, providers, diagnostic labs, and life science researchers to work together on a unified technology platform towards solutions for more efficient therapeutic development. So at its heart, this means using technology in our labs to help those labs collect data more effectively and to match researchers with the right data from the right lab.
In ways that are faster than traditional methods. So we’ve been able to prove the value of this approach in some early projects, right? This is basically enabling labs to use the data that they have available to connect with the right researchers and provide some insight again, from the real world, rather than having to start a new trial doing all of this to help patients, and that’s why I’m so excited about the approach we’re taking. There are diagnostic labs all over [00:25:00] the world, of course, because they’re treating patients all over the world. And so we have an opportunity to do this at really unprecedented scale. That means solving some big challenges, right?
How do we de-identify harmonize and structure this data across thousands of labs worldwide. And how do we allow those labs and researchers to work together effectively? And of course, how do we do all of this while supporting our patients and their privacy and supporting our current and future customers through this massive challenging global health crisis.
Chris Picardo: I want to talk a little bit about company building based on what you just said and how you’ve thought about. Building what is a software company, but it’s really sitting at this intersection of biological science and software.
So how have you thought about the challenges. And company building needs with building a software company in this space. It’s, it’s not an enterprise SAS company and the way that you would be if you’re selling to other software companies.
And so [00:26:00] what’s been the biggest challenge, what are the things that you felt like the most important from a company building perspective here?
Barry Wark: Well, you hit on the biggest challenge. It’s exactly what you described that none of us knows everything we need to make this company successful. There are a lot. Of life science researchers who have been forced to learn some software engineering to do their job but are not. Enterprise software engineers by training.
And likewise, there’s a lot of software engineers that have built software for life scientists, but it’s really hard to get in, in, in the mode of understanding what it’s like to be working at the bench in a lab where the day-to-day work is so different from your own. And we thought a lot about this I’m from one of those camps.
My, my co-founder is from another one of those camps. And we recognized early on that it takes a lot of curiosity. People have to want to learn something complicated, complex, [00:27:00] different from anything they’ve experienced and a lot of humility to understand where your limitations are and where you need to trust your colleagues.
And so we put a lot of thought into, of course building a team of people that have those qualities and fostering that sense of curiosity and learning and humility that that we need to maintain as a team, as we bring in people. And as we now go into more of a scaling mode, we think a lot about how do you bring in those domain experts and help them?
Teach their knowledge and their skills to a broader team, right? Whether that’s in sales or engineering or operations. It’s really the core of a lot of what we do from a team building perspective.
Chris Picardo: I have a couple more company building questions, cause I just think they are interesting and useful for general people who might be listening, who aren’t building in the intersections of innovation base.
And then I’m gonna put you on the spot. But I think one thing that’s really interesting is, there’s been so much talk this year about distributed companies. And people leaving, the [00:28:00] cities where they may have been and and, moving to other places that still work with their companies.
We were pretty ahead of the curve on that one in terms o, I think Ovation, has been distributed since day one. And at the moment we now have offices and Boston Maine, and Seattle and maybe Spokane,
and so we, and we have team members who also don’t live in any of those places, and yet you’ve been able to build a team that just seems operates so well. And pretty seamlessly that is been distributed. And now, especially it does not get together very often. And so
what’s your biggest learning? I think this is something that founders think about a ton and you guys have really done it from the beginning.
Barry Wark: Well, thanks for the vote of confidence. I would say that we did it by necessity from the beginning. And because we were in this, like you said, this small intersection space between life science and technology, we knew that we were going to need to recruit great talent across. A [00:29:00] really broad spectrum of skills and experiences.
And we just couldn’t pick a place on the map that had all of those. And as a really early stage company, even before you and I met, that’s a big leap for someone to take and building a distributed team becomes a huge recruiting advantage in those early days. So we built a distributed team, from the foundation up I think.
Like you said two years ago that may have been viewed as a potential risk. I think in the last nine months it’s been viewed as a big win. And the reality is probably somewhere in between for, the rest. It forced us to get good at a couple of. Things early on documenting our decisions.
So the team members who weren’t in the room could understand what we were doing and for us to think a lot about how you build culture and connection and engagement, even if you’re not sitting together which has served us well in the last couple of months, our team, more than doubled in size since we went into pandemic lockdown and [00:30:00] we’ve.
Leaned heavily on those skills that we, and those muscle, that, that muscle that we built early on. It’s not all easy though, even for distributed teams. So we used to use a lot of travel. We got on a lot of airplanes to go sit with people face-to-face when we needed to. And obviously we can’t do that now either.
And that’s put pressure on our team as well. There’s no, I think. Secret recipe to this except a lot of hard work and fortunately, some good advice I got from founders that other distributed teams that are, a couple of stages in front of us, really focusing on the hygiene of documentation and information management, you can slide on a lot of that when you’re all in an office together.
But when you’re distributed it becomes really crucial that you get it right early.
Chris Picardo: In the last couple of years, certainly since we’ve been working together can you point to a couple of examples of things where what we really screwed that up. And then what you did fix that or learn from that, or. Or, use that to build a better company.
Barry Wark: Well, I don’t think we’ve got enough time for all of the [00:31:00] stories there. But we’ve learned from all of them. One of the, one of the interesting ones in this in the COVID era is related to team engagement and. Individuals engagement with what we’re doing. We are an incredibly mission-driven company and we were handed a really important mission by this pandemic.
And and early in the in the course of that pandemic, We were, we were all hands on deck. Like we’ve talked about to get technology in the hands of labs to do what they needed to do to address this pandemic. And we didn’t realize how easy it was for all of us to get sucked into a really unsustainable pace.
Lot of people dealt with this, working from home for the first time, it’s easy to lose some work life balance. It was even easier for us in some ways, because we were so passionate about what we were doing every day, every night, every free moment there was work to [00:32:00] do. So I think one of the things we missed on was anticipating , that situation.
And we didn’t invest enough as a team in supporting each other and making sure that people were finding a sustainable rhythm. Even though we were already a distributed team, it was just different on top of what we were used to. So we definitely missed on that. And I think now we’ve been able to recover in a couple of really interesting ways.
One of the challenges of distributed teams overall is this balance between synchronous and asynchronous interaction, right? If everyone’s in an office at the same time all of your interactions are synchronous. You sit together, you talk together, you have a conversation when you’re a fully distributed team, it’s really easy to use asynchronous communication, whether that’s email or other kinds of documentation is as the mode of information transfer and finding that balance, right?
Sometimes you want to get on a phone with someone. Sometimes you want to write something to them. Finding that balance is always challenging in distributed teams. And it’s been actually really crucial in understanding this work [00:33:00] life balance for us. We do something synchronously. One of our engineers started a five minute abs class every day, every afternoon.
It’s exactly five minutes. It’s a chance for everyone to take a break and just spend some time together doing something that hasn’t. Nothing to do with work, but it’s really rewarding and we all get a laugh out of it. And it’s okay. If you want to just sit and eat your lunch with everyone while they grunt and do sit-ups.
But it’s an incredibly successful he just finished his 200th class. It’s an unbelievable thing that he’s done for this company in that synchronous mode.
Chris Picardo: Every single person that ovation has six back apps now.
Barry Wark: I wish. But we’re happy to see each other and that’s maybe even more important. The other thing we’ve done actually, from that same group came a totally asynchronous thing. We had a running competition. We split the company in half and we came up with.
Ways to map every possible kind of exercise to a distance in running. This was a really geeky session that everyone had a good time in. And then, regardless of abilities or [00:34:00] fitness or physical constraints, everyone was able to participate in some way. We spent a month, we went out and people just did something active in whatever way they could.
And we brought it together, as a group and it was a really nice way to keep connected with people without working 24 seven.
Chris Picardo: Yeah, I think that’s so impressive to hear how you’ve managed to keep your team, doing all the connectivity stuff. And those really have been, frankly, it’s just such a difficult time to, to run a company and to have a distributed team and have this kind of only remote contact.
And I know I’m going to suggest to Madrona that we do a five minute abs class every day.
Barry Wark: It turns out you have to lead it, which is the
Chris Picardo: Wow to lead it but, I think that’s been a good learning for me from this conversation. Well, I want to end this back, just on, a little bit about what we were first talking about and what’s the future of innovation look like.
And, I do think about 20, 21 and beyond, and I think it would just be a nice place to end to talk a little bit about [00:35:00] what you want to do in the next couple of years.
Barry Wark: sure. Well, I used to get out in the mountains more than I do today, but I’ve climbed a fair number of mountains and the way you climb a mountain is a one step at a time. So a lot of the, what are we thinking about now is. Just that. What are the next steps? Obviously with this recent fundraise we’re able to invest in sales, marketing, and R and D to grow our ability to help more of our diagnostic labs, serve patients and providers with the best software in the world.
Helping them bring, cutting edge molecular diagnostic workflows to market, it’s the foundation of everything we do. We’re also expanding our life science business. So we’re enabling our lab customers to combine their insights together and to help life science companies bring new therapies and new diagnostics to patients faster.
We’ve got some really exciting. Progress in that area. And we’ll have a little bit more to say about that hopefully in the near future. But I think we can confidently say we’re going to be able to rewrite some of the rules and [00:36:00] timelines of therapeutic research and development. And my big prediction is that somewhere down the road everyone in the world who needs precision diagnosis gets it.
And we’ll be pretty happy when that day comes.
Chris Picardo: Well, Barry, this is as always, it’s been super enjoyable conversation. I know we could talk for hours more, but appreciate you coming on the podcast and chatting. And I know I’m personally just super excited to, watch and help the next couple of years of Ovation and see how we can achieve these big goals.
So thanks.
Barry Wark: Yeah. Thank you, Chris. Really, I appreciate the invitation and it’s always great chatting with you. And we’re incredibly grateful for the guidance that you and the rest of the mature on the team have given us on this journey.
Thanks for joining us for founded and funded. If you have any questions or want to get in touch, please email [email protected] and stay tuned for more episodes in the coming weeks.
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