NashBio, a pioneer in genomics and real-world data, is transforming life sciences research by making complex healthcare data more accessible. Co-founded by Leeland Ekstrom, NashBio leverages de-identified electronic health records and multi-omic data from Vanderbilt Medical Center to support pharmaceutical R&D, diagnostics, and personalized medicine.
Since its inception in 2018, NashBio has provided a unique combination of curated, longitudinal data and deep domain expertise. The company is now pivoting to a technology-first approach by launching TOTUM, a trusted research environment (TRE) that will empower users to interact directly with these robust datasets for self-service analytics.
What sets NashBio apart is its curated, multimodal, and diverse dataset, coupled with expert teams that guide clients through the complexities of genomic research. A major milestone came in 2023 with the launch of the Alliance for Genomic Discovery (AGD), a groundbreaking collaboration with Illumina and eight pharmaceutical partners to sequence 250,000 genomes—unlocking unprecedented insights.
NashBio continues to empower life sciences innovators, accelerating the development of new treatments and diagnostics. With its unique blend of data and expertise, NashBio is redefining the future of genomic research.
Listen to the interview now.
Chris Hayden:
Welcome, everyone. And thank you for tuning in for today's interview with Fierce. My name is Chris Hayden. I'm a producer here. And I'm joined today by Leeland Ekstrom, Chief Executive Officer and Co-Founder of NashBio. Leeland, I'd love it if you would take a minute and just introduce yourself and NashBio to our audience.
Leeland Ekstrom:
Sure. Thanks, Chris. I grew up in Canada and originally came down to the US to do my PhD in biomedical engineering. And that was the original track I was on. A deep love of science and technology. When I finished grad school, I joined one of the large management consulting firms and spent a lengthy period of time working in the pharmaceutical practice. That was really my exposure to the broader life sciences industry and particularly the commercial R&D side of it. And it was through that experience I really first got connected into the space of genomics and precision medicine or personalized medicine.
Towards the end of my consulting career, I was recruited to Vanderbilt Medical Center, VUMC in Nashville, Tennessee. And that was where they invited me to come and help write a business plan to deploy some of the large real-world data genomics assets that they had been building at the medical center for a number of years. And that's ultimately where NashBio came from. We're affiliated with Vanderbilt Medical Center. And the goal was to take those data sets out to the broader life sciences ecosystem to support R&D activities.
Chris Hayden:
Well, that's great. I'd love to hear a little bit more about NashBio. And what is NashBio's mission?
Leeland Ekstrom:
We like to say our mission is to help make complex healthcare data easy to use, particularly in that space of genomics and real-world data. Vanderbilt started this journey probably about 20-plus years ago now, when they first started de-identifying their electronic health record and then collecting genomic information from patients under consent. They were collecting leftover blood samples after clinical care, linking those two things together and de-identifying them for research. And so, NashBio was created to be the portal to help take those data assets out to the broader life sciences ecosystem.
We support a wide range of use cases, in terms of supporting pharmaceutical R&D, diagnostics R&D, things like drug target discovery, trying to help characterize new drug targets. Patient disease population or stratification, sorry. Looking at patient journeys and how patients move through a health system like Vanderbilt. And then some more classic HEOR types of activities, health economics, analyses, understanding how drugs respond in the real-world setting, what treatments work and what treatments don't.
Ultimately, the goal was to make it easier for those types of data to flow into the kind of practitioners and the commercial ecosystem that can make use of it. And ultimately, to make impact on human health to try and bring new drugs, new treatments, new diagnostics to market more quickly, more efficiently and more effectively.
Chris Hayden:
That's great. I'd be curious to hear what are some of the company's core products and features, including what's coming down the pike for us here for NashBio.
Leeland Ekstrom:
So, as I said, we work with de-identified real-world healthcare data derived from an electronic health record. We also work with multi-omic data derived from those residual blood specimens. Really bringing those two data assets together to use in as many different creative ways as we can to advance life science R&D. Historically, we've operated in what I'll call a services model. A company would come to us and ask us a question. We'd put together a multi or a cross-functional, or multidisciplinary team to help them answer that question. We'd work through the process of what are you trying to solve, what are the resources we have available, and how can we help you building a data set, and then analyzing that data set in custom fashion. So, that was the basis of NashBio for probably our first four or five years working in that model.
At the moment, we're in the process of pivoting to what I'll call more of a technology first organization. So, instead of having everything run through one of our services teams, we're in the process of standing up our own trusted research environment or TRE. We're going to call it TOTUM, which is Latin for whole. In this case, the whole picture or bringing about the whole information or providing whole information about the patients. And what that model will do is provide more flexibility to our customers. Those who are able and interested in interacting directly with the data sets will be able to do so. They'll be able to perform analyses, select patient populations, and really work in a self-sufficient fashion.
And then those who need a little bit more help will still be able to recruit our expert services team. So, we'll be able to layer that on top. And we think that's just going to provide more flexibility in terms of our go-to-market strategy. We'll have more channels to interact with NashBio and the resources we've got. And we think, ultimately, be a better way to service the market we operate in.
Chris Hayden:
Beyond the idea of flexibility, can you tell me a little bit more about maybe what differentiates NashBio from its competition?
Leeland Ekstrom:
There's a few different areas we think about when we get asked that question. The first area of differentiation is really the data sets that we leverage from our partners at Vanderbilt. There's a number of different characteristics that we think set this resource apart. First of all, it's a curated and normalized real-world data set. So, what that means is we've done a fair bit of refinement and processing to make it ready for rapid research use, so we brought it into a common data model. We've normalized it so all the different pieces are connected together, and then standardized the vocabulary so that you can start to do analysis more quickly without having to do a lot of data jockeying underneath it.
The second aspect of the data set is its, what we'll call multimodality and multi-omic nature. Multimodality means that we have a lot of different types of data available, so thinking about structured data, things like coding and medications and laboratory measurements, but also then unstructured data. Things like clinical text, radiologic imaging, waveforms. A lot of other color commentary is the way I like to describe it, that happen or that really fills in the picture of what happens when a patient interacts with the healthcare system. So, that multimodality really provides a depth of information that is not available in many other data sources.
In addition to multimodality, multi-omics is the other piece of it. And it's admittedly a bit of a buzzword, but what that means is a number of different layers of molecular information to help understand really what's happening in patients with a particular disease or receiving a particular treatment. So, most of our data is in the genomics space. That's measuring the DNA or analyzing the DNA to produce whole genome sequencing as an example, and then being able to analyze that genetic data. But we're in the process of opening up other multi-omics layers at this moment as well. We're seeing a lot of demand from the broader industry in terms of things like proteomics, and transcriptomics, and metabolomics. And so, we're actively exploring how we could provide some of those different different dimensions.
Third area of the data set that really stands out is the longitudinality. And so, what that means is the data set moves forward in time. It's not a static snapshot from one episode of care with the patients. It really tracks over time what has happened to the patients, how are they evolving, how are they changing. And particularly, what's useful or what's interesting about that is we're able to see things like patient progression, patient response to underlying therapeutics, seeing how people's diseases change over time. All of us are dynamic individuals in that regard. Likewise, our diseases are dynamic. And so, just having that longitudinality really enables studying much more complex and frankly, real-world applications than static data sets.
The last differentiator within the data is the demographic diversity. And what I mean by that is we span all different disease areas. We span all different age populations that interact with the health system. And then ancestral diversity is another component of that as well. And really what that means is that we have a real breadth of disease areas and really breadth of problems that we can help study. We're not limited to any one therapeutic area. We can see how conditions interact across different therapeutic areas and really be a broad service partner to a number of different clients. So, that's all within the data space.
The other area of differentiation that we think about is the teams that we bring to bear in support of our clients. And so, we're really domain experts in terms of practitioning or practicing with real-world data and genomic data assets. We have across our scientific teams, our clinical teams and our technical teams, deep domain knowledge in these areas. We're really able to help our clients navigate these complex data sets and more quickly get to the answers that they are ultimately getting or ultimately looking to get out of these resources. So, it's really the fusion of those two things, the underlying data set and then the expertise that our teams bring on top of that to really unlock it.
Chris Hayden:
So, let me ask you this: You've been at it for a number of years. What have been some of the company's most significant milestones along that time?
Leeland Ekstrom:
Yeah. I really couldn't have predicted how this journey would play out over time, as when we first started. We launched the company in 2018, and so that was obviously one of the first big milestones, just getting things up and running. Obviously, we benefited from a lot of the foundational work that I highlighted earlier. Vanderbilt started this journey back in 2004, 2005 timeframe, so we're a later chapter in that regard. But that launch date is still a milestone that stands out in my mind. Some of the commercial milestones that really stand out for me, our first commercial contract of any kind, and then what I'll call our first large contract. And I still remember both of those milestones, where exactly I was sitting when we found out about them. The first commercial contract, I was on an airplane at the Nashville Airport, when we got word that the client wanted to go through and that's a moment I won't forget.
And then the first large contract was in June 2020, which seems like distant memory at this point, but that was kind of the depths of the pandemic. And we were trying to figure out what it would mean for all of us. And so, it was really rewarding to see that validation come through. With both of those milestones, I mean, we've been revenue generating right from the start, in terms of the business model we've deployed. With some of those milestones, we were able to be profitable from our early years. I think year two or year three we're profitable, and so that's another important milestone that stood out.
The last one that's I think probably our biggest accomplishment to date was the 2023 launch of what we ultimately called the Alliance for Genomic Discovery or AGD. This was an initiative with Illumina and eight large pharmaceutical partners. And the mission was to hold genome sequence 250,000 individuals from the biobanks, which generate a very large scale data set and really take advantage of some of those other characteristics I mentioned. And happy to report that we've just recently completed the sequencing and we'll be releasing the final data set shortly to our members. And rewarding for a whole number or a whole host of reasons.
It was a complex transaction. It took us a number of years to put it together. But really, it benefited from a lot of the groundwork we had laid in the early years, in terms of our customer orientation and familiarity with what companies in this space would want. And just being able to bring it together. And then over the past couple of years, deliver it to the members. That's certainly been the thing I'm most proud of through our journey so far.
Chris Hayden:
That's great. Well, Leeland, thank you so much for taking the time today. It's been great to get to know you, and NashBio and to hear what you guys are doing down there. That's fascinating.
Leeland Ekstrom:
Great. Thank you for having me, Chris. I appreciate it.
Chris Hayden:
Of course. And just wanted to thank our audience as well. Thank you for joining us today. Once again, my name is Chris Hayden. And really appreciate Leeland stopping by today, and lending his knowledge and expertise to us. So, thank you very much, everybody.