SaaS Interviews with CEOs, Startups, Founders
1544 1 Day After $1.4B Exit He Launches LifeOmic to Tackle Precision Health Using AI and Machine Learning
16 Oct 2019
Chapter 1: What is the background of Dr. Don Brown and his previous ventures?
Don's been through it all. Went through 99, 19 million bucks in revenue, went public. Then it got just unrealistic and just fantasy land. He held on though to the stock, was acquisitive in terms of buying up distribution partners, and then ultimately exited and took that company that was taken private for about 1.4 billion. He didn't even take a break the day after.
launches a company called Lifomic. Why? Because he's passionate about the space convergence of healthcare plus Cal computing and really what he calls, and I think the industry calls, prescriptive health as they look to scale, sorry, precision health as they look to scale. Just signed a big contract with Indiana University as kind of their first paid pilot. Hello, everybody.
My guest today is Don Brown. His first company was acquired by EDS in 1986. He founded Software Artistry in 1988, which became the first software company in Indiana to IPO. He then founded and served as CEO of Interactive Intelligence, which went public in 99 and was acquired in 2016 for $1.4 billion. He then started Lifomic in late 2016.
Chapter 2: Why did Don Brown launch LifeOmic immediately after his exit?
He received a BS in physics, an MS in computer science, and an MD from Indiana University. Also received an MS in biotechnology from John Hopkins University in 2017. Don, are you ready to take us to the top? Yeah, you bet. All right. A lot of history here. You've seen patterns. You've seen trends. You've done a lot here. Talk to me about Lifomic. What's the company doing?
What's your revenue model? How do you make money? Well, we're still trying to figure out the revenue model. We're more concerned right now about...
Chapter 3: What is the vision behind LifeOmic and precision health?
building a cloud-based platform for precision medicine. We all know that in order to treat people better, we've got to utilize all this big data we're accumulating about them. And that's what we're trying to facilitate at Lifomic. And what, you know, educate me here. I don't know what precision, I don't know what that means. What is that?
Well, unfortunately, medicine is a lot of trial and error today. You go in, doctors will try you one medicine, whether it's for hypertension or depression or whatever. If that doesn't work or has side effects, they'll try another medicine. The situation is even worse with serious diseases like cancer, where you may not have the opportunity for multiple trials.
And so we're starting to get better about taking information, your DNA sequence, for example, And using that to more specifically tailor treatments to you. Okay. And who do you envision? I want to talk to you about how you got into this space.
But before I do that, who do you envision really powering you from a resource perspective in terms of paying you as a customer so you can drive future growth? Will it be the end consumer that wants to make smarter decisions like a WebMD almost? Or will it be the other side? Well, we're kind of approaching it from both angles, kind of top down and bottom up.
We're working with large academic medical centers like my alma mater, the Indiana University School of Medicine. They're loading up information about thousands of cancer patients to try to use our machine learning and other techniques to figure out who's going to respond to a particular treatment and who won't. But along the way, we started to get interested in
Kind of the patient side of things. So we've developed a mobile app that we're rolling out for free to end users to try to kind of guide them along toward precision health from an individual standpoint. Yeah. Any platform that's using machine learning or AI is only going to be as strong as the unique inputs you feed it. So what are these inputs? Have you kind of monopolized me?
That's a bad word. You know, we don't want to get in trouble here. But what are these assets? Have you acquired and how are you making sure they really help your machine learn? Well, the great thing about health care is that there's no shortage of data. So what we do is try to combine information from classic electronic medical records.
So what drugs you're on, what diseases you've been diagnosed with, those sorts of things. And then your whole genome sequence. Do I have to opt in for that, though, Don? How do you get that data? Well, I... It depends on whether we're approaching from the top or the bottom. When we're working with a large academic institution like IU, they have this data from patients. I see.
So they're sequencing cancers, for example, and the normal tissue from patients and then feeding that data into our systems.
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Chapter 4: What challenges does Don face in developing a revenue model for LifeOmic?
If you come into us via a web app, then it's up to you to bring that data either from a service like 23andMe or to go out and have your genome sequenced and upload that information. Interesting. Is that really the main input you're using? It's your genome sequence? Really, it's a combination. Your genome sequence tells us about the potential.
So for the most part, there are a few genes where if you've been dealt a bad hand, that's just the luck of the draw. But most genes really are affected by the environment. And so it's that combination of your whole genome sequence and your environmental exposure. Mm-hmm. No, it makes good sense. Pre-revenue today, still exploring pricing?
Chapter 5: How does LifeOmic plan to utilize big data in healthcare?
Well, actually, we just signed our first deal with IU, with the School of Medicine. So we have a subscription model. We're basically charged based upon the amount of data and the sort of computational load that it imposes. Measured by what? I'm sorry? What's the actual metric you're measuring? Computational load based off what metric? Well, I... Basically, it maps onto the underlying AWS model.
Oh, I see. So, yeah, the computational cycles as well as storage. So, it's... kind of one level of abstraction higher, but it's largely the same thing of compute and storage. Yep. Okay, interesting. And so I noticed on your pricing page, you kind of have the opt-in, which means it's going to probably you when you're trying to figure out pricing kind of as you go along here.
How do you, that conversation with IU, is it kind of a pilot thing? Do you go directly to a one-year, two-year, five-year term? How do you structure these early deals? We structured a two-year agreement with them that's renewable, but we've been working with them for about a year already. So it's kind of a special case. We already knew them. They knew us.
But we're doing pilot sorts of programs with other academic institutions, cancer institutes as well. And as you move forward, maybe not with IU, but your ideal kind of target customer you're working with. I mean, are we talking really kind of million dollar ACVs or hundred thousand dollar ACVs? I mean, what scale do you have to be at for your thing to really add value, would you say?
Well, certainly there are small projects that can be in that $100,000 sort of range, but on up into the multimillion dollar sorts of contracts. As I said, we're starting off with these large academic medical institutions. But we really think this whole notion of precision medicine, precision health will filter down into corporate wellness programs.
So we plan to offer kind of a freemium model where organizations can use our mobile app and our cloud platform for free for their needs. uh, employees or, uh, members. Uh, and then, uh, we have more specialized services that we can offer on top of, uh, uh, what comes in the freemium version. Yep. And, uh, so, so was year one kind of officially last year, 2017. Yep. Okay. That's great.
And what's the team size today? Uh, about 50, five, zero. Okay. And have you kind of self-funded this or did you decide to raise capital? No, I've funded it all out of pocket myself so far. It feels good to be able to do that, right? It does. It is nice. Well, someone else might say, Don, why are you risking your own capital? You've had success.
It should be easy for you to go risk other people's capital. What would you respond? I, you know, when it's your own capital at risk, you can do whatever the hell you want and you don't have to answer to anybody. You don't have to be overly concerned about generating revenue.
So what I did was go out and hire cancer researchers, bioinformaticians, really strong cloud software engineers, mobile engineers. Um, and, uh, really just try to tackle a big problem without being overly consumed about how we make money in the short term. Yep. No, that's a good, it's a good place to be in the 50 folks. Where's everybody based?
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Chapter 6: How does LifeOmic acquire and utilize patient data?
And so I always think I can build something better than anybody else. And that makes it kind of hard to do acquisitions, at least for technology. But we acquired distributors in Australia, South Africa, Germany. You know, there were things like that that really made sense that added a lot of value to the company. You're talking like call time in Australia, Agorai in German.
And it's interesting though. So there's a big, actually a lesson there. I think you just said you acquire distributors. Like a lot of people that I had that listened to the show, you know, they don't think they think about building this product. They never think about actually just owning the distribution channels that they're pumping their product through because then you own the channel.
You can put other products through it and it lasts a lifetime. You recognize that early on. Yeah, it made a huge difference. We had an enormous success in Australia, for example. And to acquire our distributor there and build out our own team, it really propelled our business in a major way. Interesting. Okay. And then wrap up the story for us. 2016, what was total revenue?
So we can back into what the multiple was. Oh, God. Uh, no, I, were you active in 2016 or no? Yeah. Uh, we, we were acquired at the end of 2016. I think we were doing roughly a hundred million dollars a quarter. Okay. Okay. So, and you've sold for 1.4 billion. So call it kind of three between three and five X, something like that. Pretty fair. Yeah. Yeah. That's great.
And then, then, then what I'm sure they try to get you to stay on and you just said, I can't do this. I'm a horrible employee. No, they didn't even ask. Oh, wow. Okay. So you said, fine, I'm going to take a break and go relax. And you could only relax for a year before jumping into this. Yeah, I didn't take a break.
I think they thought I would take a break, but I announced Lifomic the day after the deal closed with Genesis. That's so funny. Very good, Don. Let's wrap up here with the famous five. Number one, what's your favorite business book? Exponential Organizations. Number two, is there a CEO you're following or studying right now? I certainly, I'm a Tesla fan, so I follow Elon's antics.
Number three, what's your favorite online tool for building your company? Oh, I guess Jira. Jira, okay. Number four, how many hours of sleep do you get every night? I... I'm a famous insomniac, so probably four or five. Okay, we'll call it five there. And then you said not married any kiddos? I have eight kids. Oh, you have eight? Yes. Holy mackerel. Eight kids. Okay, wow.
All entrepreneurs or no? I'm sorry? Did they get the entrepreneurial bug? Are they all entrepreneurs or no? One so far. Okay, very good. And how old are you? I'm 62. Last question. What do you wish your 20-year-old self knew? Oh, I, you know, you can do far more than what you realize at the time. Guys, there you have it. Set big goals. Don's been through it all.
Went through 99, 19 million bucks in revenue, went public. Then it got just unrealistic and just fantasy land. He held on, though, to the stock, was acquisitive in terms of buying up distribution partners. and then ultimately exited and took that company that was taken private for about $1.4 billion. He didn't even take a break. Day after, launches a company called Lifomic. Why?
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