Latest / Get Real with Jim Weiss / Ardy Arianpour, Founder and CEO of SEQSTER

Transcript

Ardy Arianpour, Founder and CEO of SEQSTER · Get Real with Jim Weiss

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Speaker 1: I'm Jim Weiss, chairman and founder of Real Chemistry, and
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Speaker 1: this is the Get Reel with the Chairman podcast. My
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Speaker 1: next guest is Arety arienfor CEO and co founder of Seatster,
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Speaker 1: an innovative healthcare tech company that puts patients in control.
0:27
Speaker 2: Of their health data.
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Speaker 1: Arty is an entrepreneurs entrepreneur and doesn't stand still, which
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Speaker 1: is probably why we relate to each other so well.
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Speaker 1: Before Seikster, he launched numerous clinical and consumer genetic tests
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Speaker 1: at Pathway Genomics and Ambry Genetics, which was sold to
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Speaker 1: Konica in twenty seventeen for a billion dollars. He's been
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Speaker 1: recognized as a healthcare transformer, a forty under forty business
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Speaker 1: leader in San Diego, a met Tech brice, and star
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Speaker 1: in one of Pharma Voice's one hundred Most Inspiring Leaders.
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Speaker 1: Thanks for joining us for this fast faced conversation covering
1:02
Speaker 1: everything from his humble beginnings to playing a role in
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Speaker 1: the landmark twenty thirteen Scotis gene patent decisions to a
1:09
Speaker 1: three hour call with Bill Gates to how he and
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Speaker 1: steect Or will change the patient experience and improve outcomes.
1:19
Speaker 1: Hey already great to see him, man, I think you
1:22
Speaker 1: and I are like two ships passing on LinkedIn.
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Speaker 3: Absolutely always great to see you and I hope all
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Speaker 3: is well Jim as always, and I look forward to
1:31
Speaker 3: seeing you in person soon at five other conferences that
1:34
Speaker 3: we missed each other at.
1:35
Speaker 1: Let's just start from the start. You have an incredible story.
1:38
Speaker 1: Your family fled Kran in the early eighties. Tell us
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Speaker 1: that story with just a few bucks in their pocket.
1:45
Speaker 1: You were a refugee. How did those years inform your
1:49
Speaker 1: career steps and keep you going.
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Speaker 3: I'm so thankful for America in San Diego because when
1:57
Speaker 3: we were escaping the war, during the Irani Rock War,
2:01
Speaker 3: I was six years old, and so I didn't get
2:04
Speaker 3: a chance to even go to kindergarten because it was
2:07
Speaker 3: during the time of war and everything was kind of
2:09
Speaker 3: shut down. And we fled to Europe Helsinki, Finland, to
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Speaker 3: be exact, and then we were able to come straight
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Speaker 3: to Lax and then my dad always tells us the
2:22
Speaker 3: story all the time, whether it's a Sunday dinner or
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Speaker 3: cooking kebabs or whatever we're doing during the holidays together.
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Speaker 3: He asked the people at Helsinki, Finland, where's the furthest
2:34
Speaker 3: place I can go? From the Middle East in America
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Speaker 3: and they said, oh, you can go to San Francisco
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Speaker 3: and he's like, no, no, no, no, like somewhere really south.
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Speaker 3: They're like, oh, you can go to La No. Is
2:45
Speaker 3: there anything souther than that. They're like, yeah, there's like
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Speaker 3: this place called San Diego, but it's like close to Tijuana.
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Speaker 3: It's like, okay, I want to go there. I want
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Speaker 3: to be the furthest the way so they can't find me.
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Speaker 3: That's how we landed in San Diego. We were one
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Speaker 3: of the first family in the early eighties to come
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Speaker 3: to San Diego and growing up in San Diego seeing
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Speaker 3: the abundance of biotech. At a young age, I just
3:10
Speaker 3: joined the board of the Fleet Science Center. It was
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Speaker 3: the first time I got to touch science before even
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Speaker 3: knowing English. Had such a profound effect on my upbringing,
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Speaker 3: and everyone around me was either a scientist or there
3:24
Speaker 3: were a doctor or there a PhD. Something. I was
3:28
Speaker 3: able to start my first job at the age of
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Speaker 3: sixteen at the Salt Institute because my neighbor was an
3:34
Speaker 3: engineer for DNA sequencers at the time, and that's how
3:37
Speaker 3: I got into getting into pre med and then I
3:40
Speaker 3: followed through the journey that I'm on, I guess now
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Speaker 3: through an amazing career and it all happened because it
3:48
Speaker 3: was the American dream. My family and I are an
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Speaker 3: example of the American dream actually not only being alive
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Speaker 3: but thriving.
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Speaker 1: What does Sikster do for patients, doctors, and hospitals and
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Speaker 1: the most layman terms, how does seekster help in that
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Speaker 1: complicated process?
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Speaker 2: Yeah?
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Speaker 3: Absolutely, Jim, so excited to do this with you knowing
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Speaker 3: each other for so long and looking at you from
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Speaker 3: the outside as a mentor. In so many ways, You've
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Speaker 3: had a lot to do with sikstures evolutions, So I
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Speaker 3: want to thank you personally for that. Number One. Seeksers
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Speaker 3: breaks down health data silos at scale. But what we've
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Speaker 3: really been able to pioneer, Jim, as you know, is
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Speaker 3: an enterprise operating system that aggregates that disparate health data
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Speaker 3: sources into a three hundred and sixty degree view of
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Speaker 3: a patient in real time, solving a multitude of challenges
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Speaker 3: for life sciences, patient engagement, and data interoperability. Specifically for patients.
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Speaker 3: We bring all health data in one place. It's the
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Speaker 3: Mint dot Com of healthcare, the same way that you
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Speaker 3: would bring all your finances in one place. We have
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Speaker 3: crack the code on that and build a very intuitive
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Speaker 3: user experience where on the healthcare side, we're able to
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Speaker 3: bring all provider data across the country, plus a lot more,
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Speaker 3: whether it's genomics data, whether it's claims data, whether it's
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Speaker 3: medical device data, fitness data, nutrition data, whatever that may be,
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Speaker 3: and then we create this longitudinal health record in real time.
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Speaker 3: Because that's a moving target for docs, we are able
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Speaker 3: to provide an admin portal where the docs can actually,
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Speaker 3: via the consent of the patients, look and track and
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Speaker 3: monitor a patient's longitudinal health data whether they're getting discharged
5:41
Speaker 3: from MD Anderson and going to let's say UCSD Cancer
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Speaker 3: Morse for more care and DY Anderson doesn't see that
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Speaker 3: data from UCSD Cancer mors Well through our system, if
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Speaker 3: they white label it, they're able to utilize that as
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Speaker 3: a tool. And then for researchers, we fast track clinical trials,
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Speaker 3: clinical trial recruitment, and our patient engagement piece is so critical.
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Speaker 3: The top seven out of the top ten pharma are
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Speaker 3: now customers have seiksterre Let me.
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Speaker 1: Just ask this question and maybe you could get it
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Speaker 1: a lot. Does it epic and my chart kind of
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Speaker 1: do all that already, tell me how does seekster tie
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Speaker 1: into that? Add to that? What's the difference? What are
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Speaker 1: the similarities?
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Speaker 3: Yeah, absolutely, that's one piece of the puzzle. And it's
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Speaker 3: not that doesn't do it or it doesn't do it.
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Speaker 3: It does it, but it doesn't bring cerner data together.
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Speaker 3: It doesn't bring all scripts data together, it doesn't bring
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Speaker 3: HIE data together. It doesn't bring a bunch of non
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Speaker 3: fire data that's not existing within that EPIC portal. It's
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Speaker 3: only specific to that provider number one, number two. Not
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Speaker 3: all EPIC systems talk to one another. Actually most do not.
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Speaker 3: A great example in our state, Jim is Kaiser. There's
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Speaker 3: two different versions of EPIC for Kaiser system for Kaiser
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Speaker 3: North cal and Kaiser Southern California. They do not speak
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Speaker 3: to one another. So if you come down to La
7:11
Speaker 3: Joya where I live, and you get care at the
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Speaker 3: Kaiser in La Joya and then go back to the
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Speaker 3: Bay Area and go want to get care up in
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Speaker 3: your Kaiser in North cal it doesn't speak to one another.
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Speaker 3: And that's still EPIC. Now it gets way more complicated
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Speaker 3: if you're going to a specialist that's running practice fusion,
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Speaker 3: EMR and Athena health data or whatever that data may be,
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Speaker 3: and so we became experts in actually connecting all that
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Speaker 3: data via the patient, not the provider, and creating that
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Speaker 3: user experience from A B to B two C standpoint.
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Speaker 2: Okay, well that's helpful.
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Speaker 1: So your goal for these conversation is to elevate awareness
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Speaker 1: so you can help someone with this tech. So how
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Speaker 1: do you go from sales at McKesson selling and rejectable drugs?
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Speaker 1: Right kind of stuff I launched, So again, you became
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Speaker 1: a commercial shinlea like me.
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Speaker 2: Why did you stick with sales?
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Speaker 1: Ultimately? It made you a lot of money in your
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Speaker 1: early twenties? Why the pivot back?
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Speaker 3: Yeah, when I was twenty two, I landed my first
8:15
Speaker 3: job selling injectable drugs. I was like rookie of the
8:18
Speaker 3: year at the age of twenty two. I made over
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Speaker 3: one hundred thousand dollars and that was back in two
8:23
Speaker 3: thousand and two. That's a lot of money for a
8:25
Speaker 3: twenty two year old. I could say that I probably
8:27
Speaker 3: blew most of it in Vegas because I was stupid
8:29
Speaker 3: and young at the time. I definitely gambled it a
8:31
Speaker 3: little bit on the rolette table, and that's the honest truth,
8:35
Speaker 3: and then I learned how to manage my money a
8:37
Speaker 3: little bit better. And I've only had a resume once
8:41
Speaker 3: and that was once I graduated from UC Irvine with
8:44
Speaker 3: my biological sciences degree, and then I was going part
8:47
Speaker 3: time to go get my MBA and it took me
8:49
Speaker 3: four and a half years to get my MBA. And
8:52
Speaker 3: I was only doing that because I wanted to get
8:53
Speaker 3: out of sales and get into management. And then once
8:56
Speaker 3: that happened in my mid twenties, I landed my first
8:59
Speaker 3: international business development role. And if I didn't have my
9:02
Speaker 3: sales and marketing role, then it wouldn't have stepped into
9:07
Speaker 3: that next role. And then I was on the corporate
9:10
Speaker 3: side for a couple of years, and then I got
9:12
Speaker 3: recruited to my first startup. I was employee number nineteen
9:16
Speaker 3: at the age of twenty eight, and I took that
9:19
Speaker 3: company from nineteen employees to over one thousand, sold it
9:23
Speaker 3: to Konaka Minolta and the Sovereign Fund of Japan for
9:27
Speaker 3: one billion, and it was families and friends that raised
9:30
Speaker 3: like three million dollars total. So I had a pepperoni
9:34
Speaker 3: on the pizza and did really well for myself and
9:36
Speaker 3: my family. Now, remember my family, and I moved here
9:40
Speaker 3: with like a couple thousand dollars back in nineteen eighty six.
9:45
Speaker 3: So having all this amazing stuff happened in your twenties
9:50
Speaker 3: to early thirties allowed me to take a step back.
9:54
Speaker 3: I retired literally for like two and a half three weeks,
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Speaker 3: and then I called my dad and said, I'm I'm
10:00
Speaker 3: going to go do this thing called Sikster. And at
10:03
Speaker 3: the time I was thirty five.
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Speaker 1: Tell us about your genetics career. I mean, I think
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Speaker 1: you were predicting this shift while even in sales and marketing,
10:11
Speaker 1: and look, you were.
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Speaker 2: In the core market.
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Speaker 1: I mean, if we're Hona, San Diego really is a
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Speaker 1: premier market for that. Like you said, you learned science
10:19
Speaker 1: before English, which I love. So you want to talk
10:21
Speaker 1: a little bit about that.
10:23
Speaker 3: Yeah, absolutely, And that is probably the most critical stage.
10:27
Speaker 3: And that was from the company that I took from
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Speaker 3: nineteen being in plenty nineteen to one thousand, we launched
10:33
Speaker 3: gosh one hundred plus clinical diagnostic tests. I think I
10:38
Speaker 3: was the youngest person to purchase an Illuminus sequencer. At
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Speaker 3: the time, it was called the Genome Analyzer, and that
10:45
Speaker 3: was after Jay Flatley and friends purchased Selexa technology from
10:51
Speaker 3: the Bay Area and made allumina to what it was
10:54
Speaker 3: back then. And I was one of the first fifty
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Speaker 3: people to be whole genome sequenced clinically, and I have
11:01
Speaker 3: those results and they gave me an award and all
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Speaker 3: that for that, and then I didn't share this, but
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Speaker 3: I'll share it on this call. Both my grandparents passed
11:10
Speaker 3: away due to Alzheimer's disease. My dad the callon cancer survivor.
11:14
Speaker 3: My mom's a breast cancer survivor. So my mom got
11:17
Speaker 3: breast cancer in her forties and that had a dramatic effect.
11:21
Speaker 3: And that was when I was an undergrad. It came
11:23
Speaker 3: full circle when I was able to fight Mariad Genetics
11:27
Speaker 3: in federal court, being one of four people in the
11:31
Speaker 3: world to be part of the Scotis decision in twenty
11:34
Speaker 3: thirteen to frame gene patents for all of mankind. It
11:38
Speaker 3: was the biggest thing, and I learned so much about
11:42
Speaker 3: data being siloed at the time because Mariad had the
11:46
Speaker 3: largest database for variants of unknown significance known as VUSS,
11:53
Speaker 3: and we came up with the first next gen sequencing test.
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Speaker 3: Mariad had the patents on this sanger seat when see test,
12:01
Speaker 3: the next gen test was a lot better. It was
12:04
Speaker 3: more coverage, and we were fighting the fact that you
12:07
Speaker 3: can't patent someone's body, and we prevailed, and that's how
12:13
Speaker 3: we had a billion dollar company exits and it flooded
12:18
Speaker 3: the markets opened up the markets within genetic testing that
12:21
Speaker 3: was critical to seeksters inception.
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Speaker 1: And I think if we all kind of knew are
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Speaker 1: genomics and genetics relative to different drugs, Hey, is this
12:31
Speaker 1: going to work for me?
12:32
Speaker 2: What's the likelihood?
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Speaker 3: And you know this because a gene Tech and Herceptin
12:36
Speaker 3: and all the work that you did at Genetech.
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Speaker 1: That was the start, right, that was the start, and
12:40
Speaker 1: then gene Micouse, then Garden. You mentioned one of my
12:43
Speaker 1: wife's on coologists says there are more genomics and genetics
12:47
Speaker 1: companies than there are treatments or patients in the world.
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Speaker 2: I mean, he's a little facetious.
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Speaker 1: I mean, but without that information, right, the signatoria and
12:57
Speaker 1: some of the things that we're seeing over an over
13:00
Speaker 1: again coming out tempest and Boston Jane, that's right. For example,
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Speaker 1: the excitement around cancer vaccines and how you can take
13:08
Speaker 1: that RNA experience with COVID.
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Speaker 3: Oh, Maderno would not exist if it wasn't for the
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Speaker 3: genomic revolution, right because of the mr Anda stuff. Obviously covid,
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Speaker 3: but the now on the cancer vaccine stuff absolutely, and
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Speaker 3: I think people forget. I think that's another thing. I
13:25
Speaker 3: was very lucky, like you said, because of the timing,
13:29
Speaker 3: but also when you are part of the genomic genetic field,
13:35
Speaker 3: you are very forward thinking, and health It is not
13:39
Speaker 3: really forward thinking. So when I was able to create
13:43
Speaker 3: this health It type of company because of my genomic thinking,
13:48
Speaker 3: and I brought all of my bioinformatics folks, my CTO
13:53
Speaker 3: that looked over five million DNA samples, We're like, oh
13:57
Speaker 3: my god, this is going to be easy. But we
13:59
Speaker 3: didn't know how how dirty the EMR data was because
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Speaker 3: ATCGS interoperable no matter what machine it comes out of,
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Speaker 3: whether it's a Thermoe Fisher machine, Applied Biosciences, Ion, torrent Alumina, Oxford,
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Speaker 3: Nanopore pack, bio it's just the readlink that differs. But
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Speaker 3: the actual data that comes off is pretty much the same.
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Speaker 1: That is so variable given whatever system, as you said,
14:26
Speaker 1: it's coming from for our health information and data, but
14:30
Speaker 1: that's going to be critical. Seeks Star helped your dad's
14:34
Speaker 1: experience after his call and cancer diagnosis. So how did
14:37
Speaker 1: you bring together all that you needed to quickly to
14:41
Speaker 1: achieve an outcome.
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Speaker 3: I think you and your family understand this better than anyone,
14:46
Speaker 3: probably as good as myself and my father's use case.
14:49
Speaker 3: And that was a complete accident. I never thought I
14:52
Speaker 3: would create a technology with my team that would actually
14:55
Speaker 3: save his life. That is not an exaggeration. And you've
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Speaker 3: seen the data Jim personally yourself, so you can attest
15:02
Speaker 3: to the truth of this. But a lot of people
15:04
Speaker 3: think that it's a lie when I say this. But
15:06
Speaker 3: the reason why I get it up and do Seekster
15:08
Speaker 3: every day is because of the mission of actually the
15:11
Speaker 3: fact that I found out that health data is medicine
15:14
Speaker 3: through my dad's use case. He had rectal bleeding on
15:18
Speaker 3: Christmas Eve about two and a half three years ago,
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Speaker 3: and then next thing you know, me and my wife
15:25
Speaker 3: go on vacation in Paris, and then I get a
15:27
Speaker 3: call a day after New Year's where my mom tells
15:30
Speaker 3: me that, hey, look, you remember Christmas Eve dinner time
15:33
Speaker 3: your dad kept going to the bathroom and you're asking
15:35
Speaker 3: why it was rectal bleeding. What should we do? So
15:38
Speaker 3: I told him to go get the col of guard test.
15:41
Speaker 3: He gets the col of guard test by exact sciences,
15:43
Speaker 3: which you are very well aware of, and then the
15:46
Speaker 3: result came back abnormal. He gets rushed to a colonoscopy.
15:51
Speaker 3: He gets a colonoscopy done. By the time that data
15:55
Speaker 3: hits the EMRs, my team of data scientists had his
16:00
Speaker 3: data six days before his GI called to give his
16:05
Speaker 3: colonoscopy results in all his stand results and blood results
16:10
Speaker 3: and everything else. So we were able to run a
16:12
Speaker 3: tumor board with Dan van Hawes at a TGen who's
16:16
Speaker 3: probably one of the top pathologists in the country as
16:19
Speaker 3: you know, and we were able to bring together six
16:22
Speaker 3: different providers. Is genomic data as well as his GRAIL
16:28
Speaker 3: screening data is guarded non invasive liquid biopsy data because
16:32
Speaker 3: I had n't do every single test that you can
16:34
Speaker 3: think of. As you know, I spent fifteen years in
16:36
Speaker 3: genomics before starting Seekster. And what was amazing about it
16:41
Speaker 3: is I got second opinion letters on the Saturday telling
16:44
Speaker 3: us to rush into surgery, and he had an appointment
16:48
Speaker 3: like six weeks out. We got him in surgery that week.
16:51
Speaker 3: I think it was within five business days. And if
16:54
Speaker 3: it wasn't the fact that I was the CEO of Seekster,
16:58
Speaker 3: a hot startup that people knew in San Diego at
17:01
Speaker 3: the time, and we had real data on this patient
17:05
Speaker 3: and it happened to be my father, he probably would
17:08
Speaker 3: not be alive today. Because time to intervention with cancer,
17:13
Speaker 3: as you know better than anyone, is key. And just
17:16
Speaker 3: in this discussion on this podcast with me and you
17:20
Speaker 3: about my dad, about you, about your family, how many
17:23
Speaker 3: people died because they weren't able to get complete care
17:27
Speaker 3: coordination quick enough to get to surgery just to get
17:31
Speaker 3: a cut out fifty two millimeter tumor, ladies and gentlemen,
17:35
Speaker 3: stage two A colon cancer and my dad so lucky
17:39
Speaker 3: dodged the bullets.
17:40
Speaker 1: Right, that's when you can impact early, right, Yeah, let's
17:43
Speaker 1: move from cancer to Alzheimer's. The purple line over the
17:46
Speaker 1: eat and Seekster is for Alzheimer's disease. And of course
17:50
Speaker 1: that's even more timely since there's so much advancement now.
17:54
Speaker 3: Both my grandmothers on maternal and paternal side, one had
17:59
Speaker 3: A three and one had APO four. So I am
18:04
Speaker 3: the worst case for Alzheimer's disease. I want to dedicate
18:07
Speaker 3: all my funding to cheering Alzheimer's or ending Alzheimer's. That's
18:12
Speaker 3: why the E has the purple line in Seikster, because
18:16
Speaker 3: I wanted to never forget number one, my grandmother's passing
18:19
Speaker 3: away from Alzheimer's. Number two. Once Sikster got big enough,
18:23
Speaker 3: I always wanted to somehow help the community of Alzheimer's
18:29
Speaker 3: because that data just doesn't exist because folks like my
18:32
Speaker 3: grandmothers pass away and then their data dies with them
18:36
Speaker 3: and no one collects it. But now I am so
18:39
Speaker 3: proud to share with you that Sikster has been chosen
18:44
Speaker 3: for one of the largest clinical trials within Alzheimer's. And
18:47
Speaker 3: it's taken me almost nine years to get there, but
18:51
Speaker 3: that happened this year. We're super excited about it. I
18:55
Speaker 3: couldn't tell you how excited I am personally how excited
18:59
Speaker 3: my family is, but I feel like, you know, it's
19:01
Speaker 3: coming full circle. And the purple on the E was
19:04
Speaker 3: a reminder every day to keep knocking on that door,
19:09
Speaker 3: trying to let people know that Seekster is a solution.
19:14
Speaker 1: Given all that's happening in this space, we're going to
19:17
Speaker 1: need that coordination of the diagnostic plus the therapeutic and
19:22
Speaker 1: do you think you can facilitate that through becoming a
19:26
Speaker 1: commercial solution for pharma? For example, in and around this
19:31
Speaker 1: space as Lily launches, as Asi has already got a
19:35
Speaker 1: product out there working with Biogen. What role will seeks
19:38
Speaker 1: to play in the evolution of treatment in this Oh?
19:42
Speaker 3: I think you said that on there. The fact that
19:45
Speaker 3: the data is siloed within these individuals like our grandmother's
19:49
Speaker 3: parents or whoever, and we're all aging, We're going to
19:53
Speaker 3: die either of something, and Alzheimer's is growing faster than
19:57
Speaker 3: any rate because of the aging population, or what people
20:00
Speaker 3: call SilverTech. Seekstor plays the pivotal role of really bringing
20:06
Speaker 3: together that longitudinal health record and patient reported outcomes based
20:11
Speaker 3: off of those new blood and diagnostic tests and drugs
20:18
Speaker 3: that those pharma companies that you mentioned are working on,
20:22
Speaker 3: and whether they're in a clinical trial, how do you
20:26
Speaker 3: know if that drug is working for a specific population
20:30
Speaker 3: or not. Our operating system for healthcare is the solution
20:36
Speaker 3: for connecting the dots of not just data together, but
20:40
Speaker 3: also running the analysis and providing those insights on those
20:45
Speaker 3: subpopulations by age, group, by stage, as well as the
20:51
Speaker 3: disease itself.
20:52
Speaker 1: The former situation was the pepperoni on the pizza.
20:57
Speaker 2: Now you wanted to be the pizza.
20:58
Speaker 1: Why you started seeks start but invested your own money,
21:01
Speaker 1: which will make sense, But why'd you bet on this
21:04
Speaker 1: particular field versus going back into genemics and genetics knowing
21:10
Speaker 1: that's next.
21:11
Speaker 2: And I couldn't.
21:12
Speaker 1: Agree more frankly going through this experience myself. If we
21:16
Speaker 1: want to personalize our treatment, we want to give it
21:18
Speaker 1: the best chance of working getting this other part of
21:22
Speaker 1: the system cleaned up, this digital data equation cleaned up
21:26
Speaker 1: because we talk about AI, but AI won't be successful
21:29
Speaker 1: if the data is not good.
21:30
Speaker 2: Right.
21:30
Speaker 3: Look, Yeah, during my fifteen or sixteen years within genetics, genomics, sequencing,
21:36
Speaker 3: clinical diagnostics, dealing with pharma, dealing with the life science enterprises,
21:42
Speaker 3: I saw how costly it was to set up a lab.
21:47
Speaker 3: You would have to raise hundreds of millions of dollars
21:51
Speaker 3: to set up a lab after I would say, oh,
21:55
Speaker 3: twenty ten era. Before that, it was a lot cheaper.
21:58
Speaker 3: Clear licenses were cheaper, Getting KAPA credited was cheaper. I
22:03
Speaker 3: knew that business and I still know that business like
22:05
Speaker 3: the back of my hand, and I was very successful
22:07
Speaker 3: at it. But it was very costly. What I saw
22:11
Speaker 3: was the digital health revolution coming, and I was always
22:17
Speaker 3: thinking what is next and if my past is an
22:21
Speaker 3: example of the success of the future. I was like,
22:24
Speaker 3: you know what, I'm going to bet on myself. I
22:26
Speaker 3: haven't done that yet. All I've done is bet on
22:29
Speaker 3: other folks and it's great. I've picked the right companies
22:32
Speaker 3: to be part of I've helped with the strategy, the
22:35
Speaker 3: commercial launch, building the teams. Let me try this myself,
22:38
Speaker 3: and let me try it with doing it with just
22:41
Speaker 3: the website. Can I connect all the data on a
22:45
Speaker 3: website and then like three the people of their health problems?
22:49
Speaker 3: How do we make that world a healthier place? I
22:53
Speaker 3: was thinking very big on the consumer side, but that
22:56
Speaker 3: was also a mistake to Jim. That took me kind
22:59
Speaker 3: of years, yes, to learn. And then that was when
23:02
Speaker 3: Bill Gates found out about me and then invested through
23:06
Speaker 3: Boston University because of the Alzheimer's use case and told us, hey,
23:10
Speaker 3: you got something way better than Google Health or Microsoft
23:13
Speaker 3: Health Vault, and we spent eight billion on that stuff.
23:16
Speaker 3: You need to go B to B and that's when
23:18
Speaker 3: we pivoted to a white label churn Key solution, and
23:22
Speaker 3: then pharma came in, patient registries came in, United Healthcare
23:27
Speaker 3: Group came in, payers came in, and all these amazing
23:30
Speaker 3: customers that we have.
23:31
Speaker 1: Now, all that's happened, but we're only in Series I mean,
23:35
Speaker 1: why aren't we in Series B and public and all
23:37
Speaker 1: that kind of stuff if we're so deep in and
23:40
Speaker 1: you have access to every hospital in the US with
23:42
Speaker 1: one click and some of the stuff we've talked about.
23:45
Speaker 3: Yeah, So look, I put the first million in because
23:48
Speaker 3: no one believed that in twenty sixteen running around JP
23:51
Speaker 3: Morgan Healthcare conference with my little green too me back
23:54
Speaker 3: back that I thought was bulletproof. After that, raised a
23:57
Speaker 3: couple million bucks from just friends and family and folks
24:01
Speaker 3: that you were in healthcare like yourself, that knew in
24:04
Speaker 3: the team and believed in what we were doing. And
24:07
Speaker 3: then Taketa and United Healthcare Group investors came and let
24:12
Speaker 3: our Series A along with Anwijicki with a twelve million round.
24:17
Speaker 3: And we only did a Series A so far, and
24:20
Speaker 3: the reason being is because we striked profitability and we
24:24
Speaker 3: didn't need to raise more. We're that diamond in the rough.
24:28
Speaker 3: We're not a huge company, but I've been able to
24:31
Speaker 3: create a lean, mean fighting machine for healthcare. And you know,
24:37
Speaker 3: I probably churned down, as you know, more money than
24:40
Speaker 3: most people, because money doesn't solve the problem. What solves
24:44
Speaker 3: a problem is finding that next use case, helping that
24:47
Speaker 3: next family like yours, helping folks like my dad. That
24:51
Speaker 3: solves real problems. And so I wanted to see how
24:55
Speaker 3: long can I go by just solving the problems. And
24:59
Speaker 3: then once we want to scale out into a whole
25:02
Speaker 3: new market, okay, then we will be in a better position,
25:06
Speaker 3: and markets will be in a better position to talk
25:08
Speaker 3: to folks that are interested, and all options are always
25:13
Speaker 3: on the table. I love seeks here, as you know,
25:15
Speaker 3: it's my life. I love it. You have more experience
25:19
Speaker 3: as an entrepreneur doing this with your enterprises. You know
25:22
Speaker 3: how personal they are. But at the same time, what
25:25
Speaker 3: I don't want it to get in the wrong hands
25:28
Speaker 3: and it gets siloed. I'm looking for the right folks
25:32
Speaker 3: that understand disease, that have been maybe hit by disease
25:36
Speaker 3: unfortunately or their families have been hit by disease, and
25:39
Speaker 3: understand what we are actually doing, what we actually have solved.
25:46
Speaker 3: A lot of people talk about it, but we got it.
25:56
Speaker 1: Now, I want to shift into a section I'm calling
25:59
Speaker 1: so what's it all mean? Where we hear about your
26:01
Speaker 1: work and action and how it's playing out in the
26:04
Speaker 1: real world.
26:11
Speaker 2: What's next here?
26:13
Speaker 1: I think when you think of use cases, what do
26:16
Speaker 1: you think some of those are taking us now into
26:19
Speaker 1: the current environment. And we just saw a little bit
26:22
Speaker 1: of discussion about the potential for the GLP ones and
26:26
Speaker 1: early cancer screening becoming covered by HHS Medicare Medicaid important
26:33
Speaker 1: because I don't know that the world was caught up
26:36
Speaker 1: with this preventive medicine mindset, which is somewhat critical to
26:42
Speaker 1: your success too, because once we have that mindset, we.
26:47
Speaker 2: Can really think about the.
26:49
Speaker 1: Data and the digital health solutions coming first.
26:54
Speaker 2: That will guide the therapy. Isn't that where we ultimately
26:58
Speaker 2: want to go live?
26:59
Speaker 3: And I think it's so important with what you said,
27:01
Speaker 3: Jim is, I'll give you a really clear example with
27:04
Speaker 3: the use case and a company. All this information is
27:07
Speaker 3: public obviously, so ABBY came to us. We won the
27:10
Speaker 3: ABVI contract. We built their ABVY research collaborative, and we
27:15
Speaker 3: started out with migraine patients. They wanted fifty patients in
27:18
Speaker 3: six months, we got them five four hundred and thirty
27:22
Speaker 3: three or so. I think it was just astronomical in
27:26
Speaker 3: two months with data. But that's not the crazy part.
27:30
Speaker 3: The crazy part is this what I call transverse longitudinal
27:34
Speaker 3: health records. It's the first time I'm actually talking about this.
27:38
Speaker 3: People talk about the individualized health record or the longitudinal
27:42
Speaker 3: health record, but no one's ever talked about the transverse
27:46
Speaker 3: longitudinal health record.
27:48
Speaker 2: Sounds like a prequel to a Disney Marvel movie.
27:52
Speaker 3: Well, you could probably get Spielberg to direct something for
27:55
Speaker 3: us on this health side right right with like I
27:58
Speaker 3: don't know, Pixar and AI or something. Look with the
28:01
Speaker 3: AVI stuff on the migraine. Out of that five thousand
28:04
Speaker 3: something we saw, twenty two percent had endometriosis. They add
28:09
Speaker 3: an endometriosis study that they were budgeting eighty million dollars
28:13
Speaker 3: for for twenty twenty six. Instead of waiting trying to
28:17
Speaker 3: get the recruitment going all this stuff, they were able
28:20
Speaker 3: to launch that in twenty twenty three with a click
28:23
Speaker 3: of a button because of our technology. And that in
28:27
Speaker 3: itself is a great example use case to what you
28:31
Speaker 3: were saying on It's all about getting the right therapy
28:34
Speaker 3: and treatments just because you're running a migraine study doesn't
28:37
Speaker 3: mean that the Seikster data can't help someone with cancer
28:42
Speaker 3: or endometriosis or something else. And that's what's so amazing
28:47
Speaker 3: about Sikster. We're able to bring a three hundred and
28:52
Speaker 3: sixty degree view on a patient in real time, longitudinally
28:59
Speaker 3: with all the other data too, and that is a
29:02
Speaker 3: total game changer for healthcare. So for those innovators leaders
29:07
Speaker 3: that are listening to this podcast, to you and I,
29:11
Speaker 3: please just let us know how we can help, because
29:14
Speaker 3: our stuff is in the market and it helps folks
29:18
Speaker 3: like my dad, folks like you and your family, folks
29:21
Speaker 3: at scale. It's not just the disease management software, it's
29:26
Speaker 3: way beyond that.
29:27
Speaker 1: We really have two real world themes to dial into
29:30
Speaker 1: that you've been involved in. Right, So, the Landmarks gotus
29:34
Speaker 1: decision you mentioned, which eliminates this gene patent problem. Now
29:39
Speaker 1: we're in an era of so much data. It led
29:43
Speaker 1: to the launch of the Braka test and so many
29:45
Speaker 1: other things that I think are important to not significantly
29:49
Speaker 1: benefit patients. You had that meeting with Bill Gates that
29:53
Speaker 1: changed your life, but I think the conversation got even
29:56
Speaker 1: more I would say urgent with the COVID nineteen epidemic
30:01
Speaker 1: and issues and now where that's going, and how quickly
30:05
Speaker 1: vaccines and drugs are getting made and come to market,
30:09
Speaker 1: and all the AI discussion and drug discovery and target discovery.
30:14
Speaker 2: And all the rest. Tell me where you think we are.
30:17
Speaker 1: And then of course this evolution and revolution in digital
30:21
Speaker 1: data and health, how do those come together to change
30:24
Speaker 1: it all?
30:25
Speaker 3: Yeah, I think where we are. We're at an inflection
30:28
Speaker 3: point where you're going to see monumental shifts in healthcare
30:33
Speaker 3: in the next five years because of AI, and not
30:36
Speaker 3: because of all the hype and AI, because there's I
30:39
Speaker 3: think a lot of hype and AI and you said
30:41
Speaker 3: it before me, but I believe AI is worthless without
30:46
Speaker 3: right quality and fidelity data. The data is the food
30:51
Speaker 3: for the AI and all the LMS and everything that
30:54
Speaker 3: you can do, and that in itself is going to
30:56
Speaker 3: help fast track trials, fast track the management, fast tracked therapies,
31:03
Speaker 3: and a lot of those companies that are driven in
31:07
Speaker 3: this space are going to need the right data to
31:11
Speaker 3: train those models so that they can be more accurate.
31:16
Speaker 3: We're at a very exciting time. I would compare it
31:20
Speaker 3: to the same time in nineteen ninety nine when the
31:23
Speaker 3: Internet boom happened and the dot com era happened. You
31:27
Speaker 3: can see that with Nvidia. You can see that with
31:30
Speaker 3: all the tempest stuff and the IPOs that are starting
31:34
Speaker 3: to kind of go back. I think you're going to
31:36
Speaker 3: see a lot of consolidation in this space. You're going
31:39
Speaker 3: to see MNA activity just get on fire, because it
31:43
Speaker 3: has to get Everyone's been sitting on the sidelines with
31:47
Speaker 3: cash or data, and once that gets mixed, this is
31:51
Speaker 3: where big change is going to happen.
31:53
Speaker 2: It's getting mixed.
31:54
Speaker 1: I feel like you're seeing absolute breakthrough, evolution and revolution
32:00
Speaker 1: coming faster than ever. And I thought the biggest example
32:04
Speaker 1: of that, and you can tell me if you agree
32:06
Speaker 1: or disagree, but going from the vaccines for COVID now
32:10
Speaker 1: to vaccines for cancer, what do you think Seekster's role
32:15
Speaker 1: in accelerating that can be?
32:17
Speaker 3: Yeah, I think it's technology and data.
32:20
Speaker 2: Right.
32:21
Speaker 3: Without technology and data, that pivot or trajectory from COVID
32:27
Speaker 3: to the mRNA stuff to the cancer mRNA stuff couldn't happen.
32:33
Speaker 3: And the faster we can get results on those tests,
32:39
Speaker 3: on those treatments, this is where we can sit on
32:42
Speaker 3: so many different levels, and then the right reimbursements can
32:46
Speaker 3: come in so that it can be affordable for healthcare
32:50
Speaker 3: as well, because one thing we didn't cover is how
32:53
Speaker 3: much gets wasted in not only time, but also prescribing
32:59
Speaker 3: the drugs and what drug works for you doesn't mean
33:02
Speaker 3: it works for me. And seeks you can play a
33:05
Speaker 3: very large role in that overall spectrum.
33:09
Speaker 2: Well.
33:09
Speaker 1: I think one of the reasons I like working with
33:12
Speaker 1: you is that I don't think there's a lot of
33:14
Speaker 1: benefit to spending time telling everybody what's wrong with the
33:18
Speaker 1: healthcare system because we kind of know.
33:20
Speaker 2: I mean, let's not worry about that.
33:22
Speaker 1: I actually feel in just a few years I've been
33:25
Speaker 1: more involved in the digital health world. Not one that
33:28
Speaker 1: I've been and is involved. It's dramatic the change. I
33:31
Speaker 1: think it's put power in the hands of the patient.
33:34
Speaker 1: I know that was the big theme at ASCO this year.
33:37
Speaker 1: I think you're going to keep doing that now. It's
33:40
Speaker 1: really about empowering patients, doctorates' health systems to put the
33:46
Speaker 1: seek and Seeks to right. I mean, that's what you
33:48
Speaker 1: guys are doing. Let's seek and find and solve. I
33:51
Speaker 1: think that's really what Seekster is designed to do.
33:54
Speaker 2: Right.
33:55
Speaker 3: Everyone is seeking health data. It doesn't matter if you're
33:58
Speaker 3: a patient, a farm, a company, a payer, of parents.
34:03
Speaker 3: Everyone is seeking health data. And that's why you've always
34:05
Speaker 3: been a Seikster, and that's why we love.
34:08
Speaker 2: You, Jim.
34:08
Speaker 1: Well, so, how can your audience and our audience learn
34:11
Speaker 1: more of Yeah?
34:12
Speaker 3: Absolutely so. You can send an email info at Seekster
34:16
Speaker 3: that's seq s t er dot com and just it's
34:21
Speaker 3: a request for a demo or request for capabilities or
34:24
Speaker 3: whatever your inquiry is. Or you can go to our websites.
34:28
Speaker 3: Obviously we're on all the social media channels, but you
34:31
Speaker 3: can reach out to me personally on LinkedIn and I'll
34:33
Speaker 3: connect whoever to the team.
34:36
Speaker 2: We got to get seeking, brother, all right, I love it.
34:38
Speaker 2: Get seek Let's seek.
34:39
Speaker 1: Let's find our health solutions, right, I think that's key.
34:42
Speaker 1: We want to make the world a healthier place. We
34:44
Speaker 1: got to get calling.
34:45
Speaker 3: I love it.
34:46
Speaker 2: Well, thank you.
34:47
Speaker 1: I really appreciate you spending time with us on the podcast,
34:50
Speaker 1: and I think we're going to see a lot more
34:52
Speaker 1: progress in just the next couple of years.
34:55
Speaker 3: Thank you so much, Jim for having me a pleasure.
34:57
Speaker 4: As always, Hey, everyone, thanks for listening in today The
35:05
Speaker 4: Get Real with the Chairman podcast is a production of
35:08
Speaker 4: Real Chemistry. I want to thank my team led by
35:11
Speaker 4: executive producer Kate Boss, audio engineer Nick Murphy, and composer
35:16
Speaker 4: Matt Lipkins, and special thanks to Danielle Clark Brown and
35:19
Speaker 4: the amazing team of Real Chemistry. If you like where
35:22
Speaker 4: you're hear, don't forget to review our podcast on Apple, Spotify,
35:26
Speaker 4: or wherever you listen. Also, please subscribe to the podcast
35:29
Speaker 4: so you don't miss an episode.
35:31
Speaker 2: Again.
35:32
Speaker 1: Thanks for listening and we'll see you on the road.