Garbage In, Garbage Out: Science, Data, Technology with Jonathon Hill

Science isn't just about discovery; it's about doing it right to ensure reliability and validity.

Joining me is Jonathon Hill, an epitome of a scientist, educator, innovator, and the Co-founder and Vice President of Science and Technology at Wasatch Biolabs. Although trained initially as a premed, Jonathon's professional journey took a deep dive into genetics, focusing on genetic regulation and stem cell biology, and now making significant strides in epigenetic diagnostics and treatments. 

We talk about cutting-edge work on DNA targeting and data selection using AI which redefines efficiency and cost-effectiveness in biotechnological applications. We also explore the crucial role of scalability when moving from laboratories to markets and discuss Wasatch Biolabs’ unique partnership with academia to propel future scientific innovations.

If you’re fascinated by how meticulous data handling transforms biotech research and development, tune in to hear Jonathon Hill shed light on these pivotal processes and more.

Specifically, this episode highlights the following themes:

• The critical role of accurate data collection in scientific research
• Integration of technology and traditional biology to enhance research efficiency
• Transitioning academic research techniques to commercial scalability

Links from this episode:

• Get to know more about Steven Swan: https://www.linkedin.com/in/swangroup
• Get to know more about Jonathon Hill: https://www.linkedin.com/in/jonathon-t-hill
• Learn more about Wasatch BioLabs: https://www.wasatchbiolabs.com
• Be a Podcast Guest: https://kitcaster.com/jonathon-hill
  
  

Transcript

Jonathon Hill [00:00:00]:
Modern discovery is done in teams with different people working together, even different organizations working together, all bringing something unique to the table. And that's the kind of environment and kind of company that we've tried to create where we are one of those players working with other people to try to create these cool discoveries and improve the lives of many people.

Steve Swan [00:00:23]:
Hello and welcome to Biotech Bytes, where we speak with it leaders in biotechnology about their thoughts and feelings around technology affecting our industry today. I'm your host, Steve Swan, and today I have the pleasure of speaking with Jonathan Hill from Wasatch Biolabs. Jonathan, thanks for joining me today.

Jonathon Hill [00:00:40]:
Thanks, Steve. Thanks for having me on. I'm glad to be here.

Steve Swan [00:00:43]:
Sure thing, sure thing. And so, before we get going into, really the crux of what we usually talk about is technology, why don't you give me a quick intro into you and your organization.

Jonathon Hill [00:00:53]:
Excellent. Let me tell a little bit about my background, how I got here. Like many people probably listening to this podcast, when I was an undergraduate at university, I was pre med. I wanted to go help people. And to me that meant that I had to be a doctor. One of the fundamental perception changes that I had as an undergraduate was realizing that there are other ways that I could benefit people to help people out. And one of those ways was the research that I was starting to conduct in a lab. And so I totally changed everything, ditched the whole medical route and decided to go get a PhD studying how genetic regulation really can help create people.

Jonathon Hill [00:01:34]:
Right. My initial kind of passion that I was into was this idea that we all start as a single cell, and by turning on and turning off genes in the right order, the right time, the right place, we can create every organ and tissue that we have. So my early work was in stem cell biology, looking at those kinds of things, trying to figure out how we could use that as a treatment option. And at the time, I learned that I had a talent in bioinformatics and computer programming. And so I picked up DNA sequencing very early on. I did my first bioinformatics experiments in 2007, 2008. So right when this was starting out, I got into it, and I've run with that since. My goals have always been, how can I help people? By looking at this fundamental biology and how it works and informing medical treatments or diagnostics or whatever we can do to help people out.

Jonathon Hill [00:02:22]:
Lately, we've been looking at that and thinking one thing we can really do to maximize our impact is to get involved on the translational side, help move these things from the lab into the marketplace and be able to look at those. I've gotten involved in a couple of companies, especially wasatch biolabs, where we are trying to take epigenetics and epigenetic sequencing and use that in various contexts, especially in the diagnostic space.

Steve Swan [00:02:49]:
Very cool. So you're using technology, right? Truth be told, that was also premed as well. That's okay.

Jonathon Hill [00:02:55]:
Yeah. It's a common thing, right?

Steve Swan [00:02:57]:
It is, it is, but, yeah. So technology, is technology the cornerstone of what you've been doing, or. Tell me about that.

Jonathon Hill [00:03:03]:
It is. You know, it's interesting. I like to talk about how I'm the oldest of nine kids. I've got a big, big family, and all of my siblings are engineers or software programmers, things like that. And so we have a strong kind of engineering design bent, and I'm the only one that kind of went more of the science route, the biology route. And yet I think I keep getting pulled in that direction because I find that developing new technologies and new ways of answering scientific questions where I'm good at it and where my passion really lies. And so right now, we're really trying to push sequencing technology and especially adding, you know, methylation sequencing and these other kinds of things on top of that in targeted ways so that we can go in and ask very specific questions and answer those questions that, frankly, we never could answer before, because we just did not have the means to do so.

Steve Swan [00:03:53]:
Jeff, so what you're doing is, are you making us better, or are you making us faster, or are you making us smarter or all the above?

Jonathon Hill [00:04:02]:
I like to think it's all of the above.

Steve Swan [00:04:04]:
Okay.

Jonathon Hill [00:04:04]:
Okay. If I can talk a little bit about what we're trying to accomplish here. First, you think about the basic level here. When I was going through undergraduate and graduate school, that's when the human genome had just come out. And at the time, everybody was excited and was talking about how having the sequence of the human genome would answer all these questions about disease, and we would be able to solve cancer and all these kinds of big promises that they were making. Yet I think one of the biggest things that came out of the human genome project for all the things that he gave us, was how much it did not give us, how many diseases cannot be diagnosed with genetics, etcetera. For example, if you're watching the video, you can see a heart on the wall behind me. It's because one of my major foci of work is congenital heart defects.

Jonathon Hill [00:04:53]:
Well, only 35% of congenital heart defects can be explained by a genetic mutation. So now you've got almost two thirds of disease that has no explanation in the sequence. One of the things we've learned on top of that is that there is the epigenome, these chemical modifications that are being made to the DNA and to the chromatin. These, unlike your DNA sequence, change over time. They change with disease state and they change in response to environmental factors. And so many times it's going to be these changes that are actually linked to the disease, not the DNA sequence itself. Right. And so that's kind of the fundamental thing.

Jonathon Hill [00:05:35]:
That's how I think we're making a smarter and better by looking at these chemical changes that are there. But at the same time, in any given case, you know, you have 3.2 gigabases of DNA, you've got methylation marks across that entire span of DNA of sequence. And yet in any particular case, only a small fraction of those are actually informative. If you're trying to diagnose Alzheimer's, for example, maybe 0.01% of those methylation changes are actually informative. For that, we've invented a technology where we can take and target those regions and do native methylation sequencing on it and get just the informative parts. What that does is greatly reduce the amount of sequencing we have to do. So that makes it cheaper and faster for us to do. Right.

Jonathon Hill [00:06:23]:
And so we're trying to hit both sides of that where we are making us better. We can do things we couldn't do before, but at the same time we're being price conscious and trying to lower the cost of these kinds of experiments and this kind of research. And so, you know, we're trying to have our cake and eat it too.

Steve Swan [00:06:40]:
Well, I mean, and that's where technology is going to come in, or so we're talking about. Right. You know, I mean, all the other folks I've been talking about, these it leaders are talking about how technology and AI, and specifically, right, it can help on the clinical side, it can help on the commercial side, can help on all these different ways to help us become more efficient, right? But on the research side of things, I mean, you know, just to take it down to, you know, Steve Swan terms, right, you see these CEO's that are up in front of Congress, Senate, whoever, right? And they're defending their research cycle, they're defending their ten year period in the hundreds of millions of dollars. I mean if what you're doing can shave off six months, right, a year, anything, even that would be huge. I mean, I don't even want to talk years, because that would just be, you know, that would blow somebody's mind. But you shave any time off, that's huge. That's a huge amount of dollars, and that's a huge benefit for the marketplace, too. Right? So that's what we're talking, right?

Jonathon Hill [00:07:39]:
I mean, there's multiple aspects to this. One is the time, right? Can we reduce the time of research, get things moving into market that's not only better for kind of costs of government research, et cetera, but, you know, more attractive to investment dollars, things like that, if we can increase that turnaround or speed up that turnaround time. But also, I think there's a throughput question. We always are wondering, you know, how many people can we afford to include in our clinical trial, for example? Right? And by reducing those costs, reducing the amount of sequence we have to do on each patient, we can grow those cohorts, which allows us to make sure that we have diverse cohorts or that we're catching all of the different kinds of comorbidities and things like that that might be going on. And so it makes our science better that way by reducing the costs. And I also think as we're developing things, unfortunately, one of the breaks between academic research and the commercial space that I've seen is that we are not very price conscious in academic research. We're like, yeah, I'll just sequence the whole genome. It's a couple thousand dollars per person kind of thing, not a big deal.

Jonathon Hill [00:08:44]:
But that's because we're in a low throughput type environment. Right. But again, if I come back to the Alzheimer's test idea, which we think we can do with epigenetics, yeah, sure, we can do that in the lab, but no way are you going to scale that to the millions of tests you would need to conduct every year and make that cost effective and scalable, period, regardless of the cost to that kind of scale. And so we've tried to flip that around and say, you know, from the very beginning as academic researchers, as we're developing these techniques and looking at it, we need to be price conscious and we need to be thinking about throughput and automation and all these kinds of things from the very beginning. And that's something in my academic lab we've tried to do and are now taking into Wasatch biolabs and translating to the market space is developing these techniques in ways that are highly scalable so they move faster, improving those turnaround time. They cost less, which saves money, but also allows us to do larger cohort studies and can give us better data so that we can get more refined results and better returns as far as accuracy and precision.

Steve Swan [00:09:51]:
Sure. Now, so just as, again, Steve Swan lay midterms. Right. What it feels like we've been talking a lot about is we're actually in the lab, we're doing our experimentation, we're doing the actual work we haven't talked about. And maybe if we have, I missed a little bit of it before that, deciding what we should go after, what we should research so that we don't go further down the line and do experimentation on things that we could have determined wouldn't work, that we could have knocked out earlier. Are you doing that upfront work or is it really all while we're doing our research, making that better, faster, smarter?

Jonathon Hill [00:10:25]:
Well, yeah, I mean, I think that's a hard decision to make.

Steve Swan [00:10:28]:
Right.

Jonathon Hill [00:10:29]:
What should we research? Because so often we don't know. I often tell my students and the people I work with in science, by definition, we don't know what we're doing. If we did, it wouldn't be science. And so we have to do that exploratory analysis. So, again, maybe I need to step back a little bit. What our technology does is it allows us to go into a genome, right? Take some DNA sample and target specific regions of the DNA that we want to look at, the methylation states of, or the sequence of, or the copy number of that. We want to analyze those regions. So you're right, the first thing we have to do is know what are those regions, right.

Jonathon Hill [00:11:10]:
And so the kind of pipeline that I think about is. Yeah, the first step is to do that whole genome sequencing, that expensive, low throughput, upfront pilot study, in order to identify the regions that are informative. But, for example, I know you guys talk a lot about AI, etcetera. AI is going to take that data and it's going to go through and it's going to find the features that are important. And the vast majority of features within that DNA it's going to throw out, because they don't matter. What we're saying is, in a second round, once you've identified those important features, either by direct data analysis or by looking at your AI models, etcetera, now you can go in and say, I'm just going to grab the important parts, right? And so it's kind of a question. Now I'm ready to scale. Now I'm going to go grab just the parts that are actually informative to my model.

Jonathon Hill [00:12:00]:
I'm going to pull those in, and then I'm going to look at the methylation states of each of those. And now I'm only giving my model the things that matter. Right. I'm not giving it all the noise and the junk that it's going to throw out anyway, not do anything. And so I have huge savings with that, and I'm just preventing problems along the way.

Steve Swan [00:12:20]:
Getting rid of the static, right?

Jonathon Hill [00:12:22]:
Yes, exactly.

Steve Swan [00:12:23]:
Good, good. That's what I was looking for. Yeah. Just trying to figure that out.

Jonathon Hill [00:12:27]:
Yeah.

Steve Swan [00:12:28]:
Okay, cool. Good. Now, from a technology perspective, is it AI, is it new kinds of technology? Is it something different that we haven't been using or thinking about? Or is it leaning on the cloud, compute and so on and so forth. Right, right.

Jonathon Hill [00:12:41]:
And that's another savings we can even think about is the fact that these things take compute time and resources. And by focusing on the informative parts, you reduce the complexity of that model. Now, as we've looked at some of the data we've gotten, sometimes AI models are helpful, but it's amazing, actually, that often the signal is so strong and so clear from this kind of data because we target it to the parts that are important that we don't even need them. A simple linear regression will give us exactly what we want as a predictive value, and so we can use those things. But it also just highlights that when you have great data coming in, you can really simplify those models down to their most basic components and just look at them that way and see the signal, and it's there and it's robust.

Steve Swan [00:13:25]:
So now your organization does partners up with these companies. They come to you. You go to them, you think you found something, and you call XYZ organization and say, we think we found something in our research for something that you're doing, or is it the other way around? Do they come to you?

Jonathon Hill [00:13:43]:
The way we like to do it is to have companies come to us. The way we got started was some other colleagues of mine here on campus were commercializing some technology, and they had nowhere to be able to run this kind of direct methylation, targeted methylation. I ended up getting involved, and we created this platform to do this targeted methylation sequencing. But then we realized that it wasn't just valuable for what they were doing. It's valuable in a whole host of different kinds of contexts. And so we thought, let's commercialize this and get out there. And biology is extremely broad and complex. I cannot pretend that I'm going to have insights in all the different places that this technology can be used.

Jonathon Hill [00:14:27]:
But that's where having a network of people working together is so valuable, because I can say, look, I have this great platform. Here's what we can do. And then others are coming to us and saying, hey, here's what we're doing. Do you think your platform can work with us? Right? And we partner that with them and work with them. We're not just a kind of core service center where you send your samples and we send back raw data. We actually sit down with you and help design out the experiment or the test that you want to design. We work on validation studies with you. You know what I mean? We view it much more as a partnership that we are working with you every step of the way to help get that.

Jonathon Hill [00:15:06]:
And we've seen people reach out. We have people that have reached out looking at paternity testing, prenatal paternity testing. We've got people reaching out looking at forensics applications. We've got people looking at neurodegenerative disease. We've got people looking at bacterial infections. We've got all these different kinds of applications, most of which I never would have thought of. It's been fun. It's been great to see these kinds of things and learn about these different fields and how our technology can impact those fields and help these people out.

Steve Swan [00:15:37]:
And so your company wasatch. You've mentioned a university a few times. For the folks watching, what university are you affiliated with?

Jonathon Hill [00:15:44]:
I work at BYU. That's my day job. And this spun out of BYU, and it's been really awesome. In fact, we've created a unique kind of tech transfer model where the university is licensing the technology to the company, and then the company is paying, in research grants, the university to continue some of the research and development on it. So we have a really good, tight relationship between the company and the university that we've had. People reach out to us and say, hey, I want to do this with this other university. They're looking at our model and trying to replicate that model as well to help bridge that gap between academia and the marketplace.

Steve Swan [00:16:22]:
Yeah, that's pretty cool. And have they been able to do that or are they still working on it? Probably still working on it, huh?

Jonathon Hill [00:16:27]:
Still working on it. I mean, we ourselves are only about two years old, so we are up and coming, right? Using cutting edge technology, pushing this out and becoming a model for others that are just starting to try to replicate these kinds of things. It does take a certain attitude from the university. Luckily, where I work, the university says, hey, our major goal in tech transfer is to impact the world, right, to benefit the world. And you need to have that kind of attitude because they're willing to give a little bit more to the company side in order to be able to make this work kind of thing. But we think that it's very effective, it's very cost efficient, and at the same time, we have opportunities to train tomorrow's leaders in the field in order to continue this research. Because we have students working on these projects with us, right. And involve them.

Steve Swan [00:17:16]:
And I'm sure that feeds on itself, too, right? Because they hear that you're doing what you're doing, and, you know, there's going to be kids, right. You know, or young, bright minds that say to themselves, boy, I'd really like to get involved with that. And it kind of probably feeds on itself, you know, probably grown.

Jonathon Hill [00:17:32]:
Yeah. I've gotten to the point where there's a couple students in my lab, I have to tell them to go to class because they don't want to go to class anymore. They just want to work on this research and do it. And I'm like, no, no, you got to go to class. Get out there and do it. But also, we've had several students come up with ideas like these partners, right, coming in and saying, hey, here's an application for this technology that I think would be really cool. And they're spinning off their own biotech companies and running with it. And so we're launching companies, putting them as CEO's, kind of helping them get going all through this model that we've been able to create and this platform that we've been able to develop.

Steve Swan [00:18:06]:
That's awesome. And proliferating. Probably the same technologies and the same applications, just going for different, you know, whether it be therapeutic area or whatever it is. Right. You know, so.

Jonathon Hill [00:18:17]:
Exactly.

Steve Swan [00:18:18]:
Yep.

Jonathon Hill [00:18:18]:
And at the same time, we have established players from industry coming in and looking at it as well. So we get to see both sides, and it's a great environment to be in.

Steve Swan [00:18:27]:
So then now my head's going crazy with the players funding you. My head can't even. I just can see seven different angles on that. So, yes, there's a lot of angles.

Jonathon Hill [00:18:38]:
There's a lot of people working together. You know, I think in a lot of ways, we think of the inventor as this person that's kind of a hermit working in his garage on something. He comes up with some great idea. I think those days are long gone.

Steve Swan [00:18:50]:
Yeah. Yeah.

Jonathon Hill [00:18:51]:
Modern discovery is done in teams with different people working together even different organizations working together, all bringing something unique to the table. And that's the kind of environment and kind of company that we've tried to create where we are one of those players working with other people to try to create these cool discoveries and improve the lives of many people.

Steve Swan [00:19:10]:
Well, like you said, I mean, in your garage, that's got to be. That's gone because, you know, just to even get the genome data. Right. I mean.

Jonathon Hill [00:19:18]:
Yes.

Steve Swan [00:19:18]:
Yeah, you're getting that, right. You're not doing that in your garage. Right. You know, and you're not. You're not googling that, you know?

Jonathon Hill [00:19:24]:
So, yes, I always tell people during COVID I still came into the lab every day because it was illegal to take my work home.

Steve Swan [00:19:31]:
Yeah.

Jonathon Hill [00:19:31]:
Right. I couldn't do it at home.

Steve Swan [00:19:33]:
I remember reading a story, I think it was about, uh, Roche had some lab in here in New Jersey. Uh, had some labs, an old abandoned site, I think, kind of near northern New Jersey. So folks were going into the labs because, again, they can't take their work home and do it in their kitchen sink. Right. So.

Jonathon Hill [00:19:49]:
Right.

Steve Swan [00:19:50]:
That's. That's. That's what we're talking.

Jonathon Hill [00:19:51]:
You can't do it. We need lab space. And, you know, just beyond that, though, just the technology is so complex and the skill sets are so specialized that you have to work together.

Steve Swan [00:20:00]:
You do. Yeah.

Jonathon Hill [00:20:02]:
There's no other way to do it. And we want to be one of those partners for people.

Steve Swan [00:20:05]:
Well, you need that funding, like you said, you know, the guy in the garage that's, you know, stirring something in his. In his garbage can is not going to work. You need the funding, you need the technology, you need the databases, you need all that stuff.

Jonathon Hill [00:20:16]:
Right?

Steve Swan [00:20:16]:
You know, all that.

Jonathon Hill [00:20:18]:
And then you need somebody that's a bioinformatician and someone else that's really good on the bench and. Right. You need all those pieces as well.

Steve Swan [00:20:25]:
Yeah. Yeah. So now, what else within your world haven't we hit on that, that we haven't talked about, right. That you think would be informative for folks to. To hear about? You know, in your world, from a technology intersection of technology and science perspective, is there anything that we haven't talked about that we should hit on, do you think?

Jonathon Hill [00:20:43]:
I don't know. I think we've hit on most things. I mean, one thing that I'm always thinking about is that, you know, when we talk about technology and science and that kind of meshing of the bioinformatics and the computers with the actual bench biology, that's something I do. I work at the bench. I also program my own programs, right. So I am at that junction. And one thing we always have to think about is we got to think about the data that's coming into our algorithms. Right? Right.

Jonathon Hill [00:21:11]:
Sometimes I think these worlds are a little too separated. And, you know, we just. On the bioinformatics side, we're just like, well, give me what data you have, and then I'm going to make it work kind of thing. Right? And on the bench side, we're like, I'm just going to generate a bunch of data. But really, if we could integrate those two more and have the binary permutation saying, hey, here's the data that's important for me and the bench people saying, here's why that data is noisy for this reason, et cetera. Right. And how can we reduce the noise of that data? That kind of back and forth play really can improve the outcomes that we see. And so, just like we need to think about cost and scalability from the beginning, we also have to think about the data that's coming in, not just the data that's coming out of our algorithms.

Steve Swan [00:21:55]:
I got to tell you, I mean, again, talking to what I do, right, in these podcasts, talking to all these technology leaders in all shapes and sizes and walks, right? There hasn't been one that hasn't said it comes down to the data. Junk in, junk out, right? You got to make sure your data's ready. Your data's right. Your data's got to work for you. I mean, every single person said, make sure your data is ready. If your data is not ready, you're not going to get anywhere anyway. You could build the greatest technology. You could get the coolest stuff and have the best people working for you.

Steve Swan [00:22:27]:
Bad data, you're sunk. You're done.

Jonathon Hill [00:22:30]:
You're sunk. Yeah. And when you do have noise that you can't take care of, right. That's just inherent in it. You have to make sure that you have a large enough data set to capture all of that noise and have the model be able to see the. The signal and the noise.

Steve Swan [00:22:45]:
To tune it out.

Jonathon Hill [00:22:46]:
Right.

Steve Swan [00:22:46]:
To tune out the noise.

Jonathon Hill [00:22:47]:
To tune it out. Right. We often see when you have too small of a training set, you over fit every time. And so we gotta make sure that we have that. And I think that's something that as a society, we're more aware of today, too, that this needs to include different genders and races and age groups and all of these different factors that we may not think, have an effect, but in some way they may have effect on, say, an epigenetic signal.

Steve Swan [00:23:13]:
Sure. For example. Well, same thing as creating a team. Right. You get different shapes and size of people, so you get different opinions and different thought processes going into it, you know?

Jonathon Hill [00:23:22]:
Exactly.

Steve Swan [00:23:22]:
Yeah. Now, let's say I'm a student. Let's say I'm a scientist. Let's say I'm looking right now and I want to go somewhere. I'm a kid. Why would I want to come? And I'm just putting you right on the spot, Jonathan. And if you don't want to answer, don't answer. Why do I want to work with you, for you, around you, in your group at.

Steve Swan [00:23:40]:
Do I call it west side? Should I call it BYU? I don't really know. It sounds like it's kind of one in the same. But why would I want to be there versus.

Jonathon Hill [00:23:47]:
Yeah, I mean, BYU is going to appreciate if I emphasize they're not the same. Okay, good. Monsanto is a company. It is separate. It has licensed technology from BYU. It is also funding research at BYU. Right. So there's a partnership, but they are separate entities.

Steve Swan [00:24:01]:
Fair enough.

Jonathon Hill [00:24:02]:
And so you have to give two kinds of sides to that answer. First, on the company side, I think if someone in the biotechnology world, in the pharmaceutical world, et cetera, is looking at ways to get a unique view on their data. Right. We are here to partner with you. You can go to wasatchbiolabs.com dot. Most of our hits come through the website. There's a form you can fill out there, reach out. I often get on these calls directly.

Jonathon Hill [00:24:29]:
We found to get the scientists talking to each other is the best thing, and we really work out the best experiment, the best way forward, and design something together. We want to partner with you. It's not just a service, it's a partnership. And especially because I think something we don't think about, as I mentioned earlier, epigenetics is something that changes with disease state, with age, with environment, et cetera. And so this is a powerful way to look at the effectiveness of drugs as a co diagnostic. This is an effective way to diagnose disease. And by partnering, and even if it's on the research side initially, this is going to be set up in a way that is scalable, et cetera, and may evolve into that codiagnostic down the road once the clinical trials are finished, et cetera. And we're going to be there the whole way with you, working with you.

Jonathon Hill [00:25:22]:
We even have CLIA professionals that can help with the CLIA certification of these tests and things like that. So we're there with you. That's why I would say someone would want to come work with us. Right. Because they're going to get that partner on the research side at BYU. I think what's really cool is that we have set it up in a way where we can launch students on their own careers. Right. Like I said, we are allowing students to spin out their own companies and take them with that.

Jonathon Hill [00:25:46]:
And I think that's very unique, the university space. And so for these students, they are getting a direct look at what it is like on the biotechnology, on the business side, not just in the academic research, and they're able to take their own ideas. We actually have a little pitch that they do to us if they have an idea and we vet it and the business people vet it, and, you know, they have to go through the whole real process. But if it's approved, then they get to take that research and they get to run with it. Really? Yeah. And so it creates a really cool experience, I think, that really will make stars in our field.

Steve Swan [00:26:22]:
Yeah.

Jonathon Hill [00:26:22]:
Your own little incubator as these students are coming up. Yes, exactly. Yep.

Steve Swan [00:26:27]:
Wow.

Jonathon Hill [00:26:28]:
So it's a cool partnership we've created.

Steve Swan [00:26:30]:
Don't get that every day either. Nice. Very.

Jonathon Hill [00:26:33]:
No, you don't. Very cool.

Steve Swan [00:26:35]:
Very cool. So, anything more you think we should touch on before I ask my last final question, which I usually ask of every guest?

Jonathon Hill [00:26:41]:
Uh oh. What is that question?

Steve Swan [00:26:44]:
You're focused on the wrong thing. So is it nothing. Nothing more we should touch on? We're good.

Jonathon Hill [00:26:51]:
I can't think of anything. I'm. You're my second podcast, so it's all right. You know, it's not like I have. Oh, I say this every time kind of thing, yet.

Steve Swan [00:27:00]:
Yeah.

Jonathon Hill [00:27:00]:
No, so I think it's good.

Steve Swan [00:27:01]:
I think it's phenomenal. I mean, I love everything I heard. I mean, the whole incubator idea, you know, really pulling those scientists along, then being the partner. Once you. Once you get in partnership or in business, if you will, with a company, I think that's all great stuff. And I think an organization, depending on their scale and size and what their needs are, absolutely would benefit from getting involved with you folks, is there? So maybe I should ask this question, too. If I'm looking at this podcast and if I'm company x but I'm involved with a particular therapeutic area, should I say that Jonathan's group is better at one therapeutic area than another, or is it agnostic as far as that's concerned.

Jonathon Hill [00:27:40]:
It's very agnostic as far as the therapeutic area, the specific application. In fact, our platform for targeting specific regions of the genome we found can identify many different features. It can look at methylation states, it can look at copy number variants, it can look at single nucleotide variant, it can look at larger deletions. And we have partners who are working with us on tests that look at multiple things at once. Right? So they might be looking for particular genetic predispositions for a disease and at the same time looking for epigenetic signatures that are indicative of disease, all in a single test that we're developing with them. And so whatever the area, we're able to.

Steve Swan [00:28:20]:
No issues. Okay. I just thought I'd ask that because we didn't.

Jonathon Hill [00:28:22]:
No issue.

Steve Swan [00:28:23]:
We didn't really cover that. So, final question here. Live music concerts have. Do you have a favorite one or even one that you've ever seen that year? Maybe you've never gone to a concert. I don't know. But any live music, any concert that you would say, boy, that was my favorite concert. That was my favorite. I'm a live music guy, so that's why I always ask everybody this.

Jonathon Hill [00:28:44]:
Yeah, I'm going to disappoint you, because I am not a live music guy.

Steve Swan [00:28:47]:
Okay. Some people don't like crowds. Right. You know, I was going to say.

Jonathon Hill [00:28:50]:
Too crowded, too loud.

Steve Swan [00:28:54]:
So, never been to a concert. Nothing. Nothing you'd point to that you like, but. Okay.

Jonathon Hill [00:28:58]:
You know, I've gone to the orchestra and the symphony.

Steve Swan [00:29:01]:
Fair enough.

Jonathon Hill [00:29:02]:
Couple operas, but not what you would consider a live concert. Actually, there was one that I went to. It was kind of fun. So I did my PhD in New York City.

Steve Swan [00:29:11]:
Okay.

Jonathon Hill [00:29:12]:
Right. And we found that a lot of the youth in my church there lived in the city their whole lives, but they never saw anything. They'd never been to the Statue of Liberty. They had never been to the Brooklyn Bridge. Right. So we created an amazing race style day where we got donors and we got them to pay for things. So they went to the Today show street concert, and I think it was coldplay that was.

Steve Swan [00:29:38]:
Oh, really? Okay. Yeah.

Jonathon Hill [00:29:39]:
And we got to watch that concert, so that's the only one I've been to. And then, you know, they had to run over to the Brooklyn Bridge, and they had to go to the seat of the Statue of Liberty, and they had tasks to do at each one. It was a really fun day for.

Steve Swan [00:29:49]:
These kids, almost like a scavenger hunt kind of thing. Right. You know?

Jonathon Hill [00:29:52]:
Yes, exactly. And so they. So they got to see their own city and gain an appreciation for a city they lived in but had never been able to afford to actually take advantage.

Steve Swan [00:30:02]:
Well, it's also when you're. Because I'm not even an hour from the city. I mean, I went to Statue of Liberty in third grade. You know, we're talking about going to Ellis island in a couple weeks. I've never been. And my wife's father and uncles all came into Ellis island from Italy. It's like, never been there, you know, so.

Jonathon Hill [00:30:19]:
Right. It's so easy to do when it's close. Right, right. You're like, oh, I can always go. And then you never get.

Steve Swan [00:30:24]:
Right. Yeah. Yeah, exactly.

Jonathon Hill [00:30:26]:
So that was a fun experience and probably my own only concert experience.

Steve Swan [00:30:30]:
Hey, that's a good one. Cold played. Never seen him. Chris?

Jonathon Hill [00:30:33]:
Yes.

Steve Swan [00:30:34]:
Martin. I forget his name. I think it's Chris. Martin. I forget. Anyway, well, thank you very much for joining me. That was great. That was informative, and I appreciate it.

Jonathon Hill [00:30:41]:
No problem. I appreciate being on. Thanks for chatting with me.

Steve Swan [00:30:43]:
Thanks.

Jonathon Hill [00:30:44]:
Take care.