How Lifeomic CEO Don Brown grew Lifeomic to $3.5M revenue and 1 customers in 2024.

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 required in 2016 for 1.4 billion he then started life omic in late 2016. he received a bs in physics in ms in computer science and an md from indiana university also received an msn biotechnology from john hopkins university in 2017. don are you ready to take us to the top no 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 life will make what's the company do and what's your revenue model how do you make money uh well we're still trying to figure out the revenue model we're more concerned right now about uh building a cloud-based platform for precision medicine uh we all know that uh 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 lyfomic and what it you know educate me here i don't know what precision i don't know what that means what what is that well unfortunately medicine is a lot of trial and error today you go in doctors will try you one one medicine whether it's a for hypertension or depression or whatever if that doesn't work or has side effects they'll try uh another uh the situation is even worse with serious diseases like cancer uh you know where you may not uh have the opportunity for uh multiple trials uh and so um we're starting to get better about taking information uh your uh dna sequence for example and uh using that to more uh specifically tailor treatments to you mm-hmm okay and 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 that really powering you from a resource perspective in terms of paying you as a customer so you can drive future growth will it be will be the end consumer that wants to make smarter decisions like a webmd almost or will be the other side well we're kind of approaching it from both angles kind of uh top down and bottom up we're working with large academic medical centers like at my alma mater the indiana university school of medicine they're 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 uh we're rolling out for free to uh end users to try to kind of guide them along toward uh precision health from an individual standpoint 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 of these inputs have you kind of monopolized maybe 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 your machine learn well the great thing about uh healthcare is that there's no shortage of data i so what we do is try to combine information from uh classic electronic medical records so what drugs you're on what diseases you've been diagnosed with uh those sorts of things um and then uh 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 kind of uh whether it's we're approaching from the top or the bottom when uh 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 uh if you come into us via a web app then uh it's up to you to bring that data either from a service like 23 and me or to go out and have your genome sequenced and uh upload that uh information interesting is that really the main input you're using it's your genome sequence i'm really it's a combination your your uh genome sequence uh tells us about the potential uh so for the most part um there are a few genes where you've been dealt a bad hand you know uh that's just uh the the luck of the draw but most genes uh really are affected by the environment and so it's that combination of your whole genome sequence and uh your uh environmental exposure mm-hmm no it makes makes good sense um pre-revenue today still exploring pricing well actually we just uh signed our first deal with iu with the school of medicine so uh we have a subscription model we basically charge based upon uh the amount of data and the sort of computational load that it 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 uh the computational cycles as well as storage uh so uh it's uh kind of a one level of abstraction higher but it's largely the same thing of 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 um how do you uh that conversation with iu um is it 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 well we structured a two-year agreement with them that's renewable uh but we've been working with them for uh about a year already uh so that it's kind of a special case we already knew them they uh knew us uh but uh we're doing pilot uh sorts of programs with other academic uh 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 100 000 acvs i mean where what scale do you have to be at for your thing to really add value would you say uh well certainly there are small projects that can be in that hundred thousand dollar uh sort of range but on up into the multi-million dollar sorts of contracts i 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 uh so uh we plan to offer uh kind of a freemium model where uh uh organizations can use our mobile app and our cloud platform for free for their 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 it was year one kind of officially last year 2017 yep okay that's great and what's the team size today uh about 50 5-0 okay yeah and have you kind of self-funded this or did you decide to raise capital no i've uh 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 you know 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 uh you don't have to be overly concerned about uh generating revenue uh so what i did was go out and hire cancer researchers bioinformaticians really strong cloud software engineers mobile engineers and 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 place a good place to be and the 50 folks where is everybody based oh roughly a third across indianapolis research triangle park and the salt lake city area okay very good so three separate spots there and uh and help me understand kind of why get into this space it sounds like you've had some exits in your past you had some success what prompted you to jump into the space just intellectual interest i went through medical school a long time ago and uh i went over to the dark side of business you know started a little software company while i was finishing up med school you're talking interactive intelligence well there was two companies before that uh yeah interactive was uh my most recent one um and i i just always had a love for the life sciences i i i got involved you know did a master's program at johns hopkins and kind of re went back through biochemistry and cell biology all the cool stuff and you know just an opportunity to get in into a field super exciting because there's this convergence of cloud technologies ai and then all we've learned about how the body works and you know sequencing the human genome all those sorts of things that uh i think is going to usher in uh a revolution in health care mm-hmm now interactive intelligence i you know i want to spend a little bit of time on this because there's i'm sure there's some lessons here this was the kind of telecommunications right in cloud computing yes yeah so and you founded 1994 uh yeah somewhere somewhere in there that's right so so it's very rare you see a founder that goes from day one i think you and david launched it back then all the way you know up to ipo to the point where you were i believe taken private in 2016 by genesis um how did you have to change and adapt and learn through that what was...