GeneDx Holdings Corp. (WGS) Earnings Call Transcript & Summary

All right. Good afternoon, everyone. This is Julia Qin from the life science team at JPMorgan, and it's my great pleasure to introduce you to our next presentation today by Sema4. As a reminder, if you have a question, you can submit it through the website. And with that, let me turn it over to Eric.

Awesome. Thank you. Super great to be here today with you to update on Sema4. The slides I'm going to go through were posted on the IR website. So you can gain access to those through that website, and I'll try to be throwing out what slides I'm on. . Since we're a newest company new, certainly new to the public market, wanted to kind of just start with a kind of a recap on who is Sema4, and we're a patient center of health intelligence company that partners with patients and physicians to generate and aggregate large-scale high dimensional data around patients and to then analyze those data in partnership with patients and physicians to provide more clinically actionable guidance through the course of care for patients across a broad array of diseases and conditions. So Slide 4 of the deck I'm using, has its kind of the corporate snapshot that shows today, we're 1,200 persons run company, very science centered, over 160 PhD level MD-level scientists helping drive the show. We manage very large amounts of data, both generate and acquire and manage, greater than 46 petabytes of data, growing at a 2 petabyte a month rate, and that rate is also growing And included in that many petabytes of data are 12 million or so electronic patients, 12 million patients with electronic medical record data. Over 500,000 of those come with large-scale genomic information and at a pretty good run rate on the NGS testing side of over 250,000 tests a year. The problem we're solving, given on Slide 5, is really one of -- given all the advances, rapid advances in genomics, other molecular technologies and AI computing in the digital sphere with wearable devices and apps and so on, lots and lots of information able to now be generated on patients. But really has limited impact on patients because there's no kind of holistic way of all that information being integrated and brought to bear in the medical setting through the standard of care flows that the patient might experience. And so it's really not having the impact that it otherwise could. In Sema4, we focus on solving that problem by helping wire together these various components in partnership with health systems to deliver more holistic solutions. So it comes in 2 basic components. One is facilitating holistic care of the patient across different types of health journeys. I'm going to show you one example on the reproductive health but we're operating today in population health, heritable cancer screening, somatic tumor profiling, newborn screening. So there's lots of different engagement points where you can now deliver more state-of-the-art genomic information combined with other types of clinical data to provide more state-of-the-art interpretations around the patient in partnership with a physician. So on the reproductive health side, for example, we grew up in the health system, right? We grew up in the health system, knowing how to partner with physicians, understanding their workflows, understanding how to deliver more state-of-the-art information and tools without overburdening the physicians, streamlining their workflows, easing the burden on engagement with patients, easing the burden on billing and so on. So Sema4 kind of tackles all of that and handles all of that kind of engagement on the -- in this case, reproductive health side by offering a broad array of solutions that, again, are wired together in a way that streamlines the physician workflow with the patient. So it's everything from the sophisticated genomic testing solutions to the seamless workflow integration with EMRs to the dedicated patient engagement and support. So again, engaging patients, whether it's counseling, engaging them around their information, providing information back to them in ways that they can benefit, helping -- working through billing and so on. There's -- but then super importantly, what we're really focusing on is, again, on the axis of that information and technologies to provide better, more differentiated, better outcome characterization of the patients. So that's -- those holistic approach to the patient care is one component. The other component, of course, is the foundation on which that all gets built, which is the Centrellis platform is our information platform. So that's what's managing the 46 petabytes of data. That's what's driving insights from those data through various algorithms and then delivering those actionable insights through a number of different flows. So whether it's providing differentiated insights through the clinical reports that get generated for the testing genomic solutions or whether it's working in partnership with pharma and health systems to identify and recruit patients in the clinical trials, coming up with population health models, risk models for population health managers, real world evidence studies and even into rawer research and discovery with pharmaceutical partners around drug discovery. So all those insights. So the data is being generated. The lab service is an accelerant to spin this flywheel because that lab is generating a lot of the big data in the standard of care flows for the patient, and we're partnered in that. We're layering and all the other types of data we can grab from the within partnership with health systems and the patient to acquire and integrate clinical data, providing those insights we've learned from the insights and that feeds right back. Like it feeds right back into the platform. So think of it as a dynamic, adaptive learning type platform. And the way to really make this type of modeling work and engagement work is in our view, kind of coming up with a fundamentally different way of partnering with patient and physician and we're doing this through health systems. So we're partnering -- forming deeper partnerships with health systems that we think is very differentiated compared to what a lot of our colleagues across the genomic testing and information spaces due today. And we're beginning with a smaller number of learning-based partners. We announced 3 of those new partners this past year, 2021 with AdventHealth, NorthShore and Avera in conjunction with our founding partner, Mount Sinai. In the way this -- so first of all, it's highly differentiated from the kind of the conventional genomics model, which is working as a vendor, pounding down the doors of the physicians, offering a narrow menu, so selling direct to the physicians. You don't necessarily have any -- any of the data or at least limited, especially on the integration front, you have limited or no access to the patient engagement beyond the test itself, versus this model we're forming with the health systems, which again, I think layering all these various components together to deliver precision medicine as a standard of care and not as a vendor flipping more tests. But as a partner with that provider to kind of elevate the standard of care for the system. And it's not just working in one narrow area, but it's really working in partnership across the genomic testing solutions space as well as the information space to cover all -- ultimately all diseases and conditions. And this gets to the ultimate model, progression of Sema4 where today, yes, we're centered in the genomic testing solutions revenue but increasing the expanse of our data solution, our partnership with health systems, acquiring more patients, more data in connectivity to that data in patients for use in developing better disease models that inform on clinical care and trials. So we're reducing costs and improving outcomes on the -- for population health managers and so on. So we're building that vast array of know-how and algorithms and insights that can be put into routine use, and importantly, because you're a standard of care partner with those systems, you're iterating in a way more intimate way to learn from those insights, learn what worked, what didn't and again, retain access to longitudinal data. And ultimately, what that turns into is this platform of algorithms where it's ultimately you're querying -- you're able to query this platform of algorithms to drive insights based on whatever data you have to facilitate matching patients to the most appropriate products and services. So ultimately, moving beyond the provider and life sciences space. In order to get to that kind of value, in order to have data that's a valuable that can drive that kind of ultimate platform of algorithms, you really -- we believe need to be partnered with the patient and the provider in a more intimate way because that data needs to be #1 longitudinal and it needs to be high frequency updates, dense information if you can drive over time on a patient. And it also needs to be prescriptive, right? It needs to ultimately be guiding physician in making standard of care decisions on a routine basis. And so when you think about the spectrum on both the data richness and patient impact that a lot of different companies work in today, we think Sema4 definitely stands apart in terms of both the richness of the data and that we're spanning multiple diseases and conditions, a more holistic partner getting access to entire EMRs worth of data, high-dimensional genomic and other molecular data built up around patients, and having that one of the biggest data stores around patients, but then also having the mechanism in these partnerships to actually have an impact on the patient beyond just diagnosing or providing some kind of screening tests. But on into developing the right kind of predictive models and insights and so on that ultimately, again, help guide the standard of care; help, again, is the partner with a physician on delivering precision medicine as standard of care that's -- those are the kinds of flows we work into and having that kind of data and access to patients. So again, I think a very differentiated play compared to, again, the very respected colleagues we have across the various company spaces that you see depicted here. And again, I just wanted to call out that we are operating across a wide array of diseases and conditions, not just siloed into cancer or rare disorders or some other limited number of diseases and conditions. Again, when a cancer patient comes in, they have more than cancer, right? They can have obesity, they can have diabetes, they can have heart disease. They can have autoimmune disorders and so on, like you have to have the entire picture of the patient to really come up with the best treatment plan and the best guidance to the physicians that optimize or maximize standard of care and outcomes for the patient. And just to give you an idea of how that works and again, the partnership with the health systems to get the right kind of traction and engagement and be coming into that partner, I'll talk about what we've done with an NorthShore system over the first 6 months of announcing this program we're doing with them on the genomic wellness side. And first of all, we're super excited to be partnered with the NorthShore University health care system in the Greater Chicago land area like super progressive thinking a bunch out there that's wanting to democratize access to genomic medicine throughout their broad system to help better characterize patients, better manage their care, their risks and so on in a proactive way. And so we partnered with them around this genomic wellness assessment program that involves screening of patients, delivering a genomic health test through various survey instruments and that genomic health screen. We may identify patients who are at high risk for certain diseases and conditions that indicate a deeper kind of profiling. And here just showing you an example flow over the 6 months of going through 42,000 patients who were targeted for this genomic wellness program. Think of these as being identified and enriched for heritable cancer at possible high risk for heritable cancer. 6,400 have the genomic health screen get ordered through the primary care physicians at NorthShore. And of those, 950, so about 15 -- total 15% were identified as meeting NCCN guidelines for being at high risk for heritable cancer. And then those then reflects into a more complex, comprehensive heritable cancer test that we again offer. And that flow over 6 months represents a 54% increase from the previous 6 months and what they have been doing to target on those individuals. And we started that program in one hospital system, one hospital for NorthShore, Swedish, which is it serves one of the most diverse communities in Chicago in the success of that program, that one hospital was so rapid that it quickly was put out to all the entire system. And today, over 90% of the primary care physicians are ordering from Sema4 for that program. So it's like a super. And then that -- this resulted in rolling out into mammography clinics to do the same kind of thing. And the identification of patients through the mammography clinic who may be at high risk for heritable cancer and then reflects into a heritable cancer test, 90% compliance for those women so identified who then have the test prescribed and then follow through by delivering a sample and engaging with us like super exciting to see that level of both penetration and compliance and really making an impact in NorthShore. And of course, this is now spreading beyond just that program into other programs and engagements around the data, but this is just an example of the kind of stuff we're able to do and doing other systems, there is precision oncology and so on. Once you have this kind of engagement, you have the data, you have access to the patients, you have ability to give insights and also to generate -- keep generating data through the genomic medicine front, you have a lot to offer on the biopharma partner side. And so we have offerings that kind of span the entire spectrum of development for the pharmaceutical industry and have programs today from the clinical trial type matching to Software-as-a-Service base licensing to enable those systems so think of the clinical trial design and what are the right regions for trials and so on, to the deeper partnerships, leveraging the data science capability of some for in conjunction with the data. So I think drug discovery programs, lead identification, prioritization and so on. So we have a growing number of those kinds of relationships based on, again, leveraging this flywheel and all the different components that you get in partnership with a health system, in partnership with our labs that are generating all of that information, having the right kind of platform Centrellis to manage that information and compute on it. So we have so many of these pieces that we can stitch together based on this data, again, with this good data ramp, we have an increasing number of a pipeline of collaborations with pharma that span from molecular profiling of patients in oncology and real-world evidence studies to drug discovery collaborations to clinical trial matching recruitment based on data built up around patients and different health systems or sometimes combined with genomic information and so on. So again, having and exciting. We think this is the year 2022 where we're really going to start showing a more substantial ramp on that just given the maturing of the data that we have coming from the health systems were, again, under BAAs. We're working with the identified data, helping them extract from unstructured data, structuring those data, making a better deidentified set that we have rights to use pretty broadly and doing that across all diseases and conditions, not just focused on one area. So it's a super valuable resource. With that, I'm going to maybe let Isaac, our CFO of Sema4 maybe say a few words on where we're at in Q4. We put out a release today on that. But Isaac, do you want to jump in and...

Sure. Thanks, Eric. So I'm really pleased to report that we had a very strong finish to the year in 2021. Q4 results, both in terms of volume and revenue came in ahead of our forecast, ahead of the guidance that we set with investors on the Q3 earnings call. If you refer back to that point in time, we did provide guidance for the year that implied volume would be in the range of 73,000 to 79,000 tests, excluding COVID. And we exceeded 80,000 in the quarter. And then for total revenue, our guidance implied $46.6 million to $49.6 million as a range for total revenue in Q4. We expect to land somewhere between $50 million to $52 million. So we do really feel good about the end of the year on all the metrics that matter. And we finished the year as well and most importantly, with a strong cash position, $400 million in cash and equivalents as of 12/31. So we expect to provide greater detail when our quarter is closed and audited in the Q4 call, but we do want to provide this update today and feel really good about the momentum we have entering 2022.

Awesome. Thanks Isaac. And that was Slide 14, by the way. I thought Joel is here. He's going to hold up numbers for what slides I'm on. I guess I kind of got going and forgot about that. People aren't seeing the slides in real time, so I apologize for that. But hopefully, you're tracking on the narrative here is super exciting. So what's coming for one of our main primary focuses for 2022 is really on operational improvements. We started that push in last year in building out new teams to operate as a public company. We brought in guys like Isaac and Joel rebuilt finance, brought in a new Head of Ops for the lab. And so really building a lot of financial and operational muscle that wasn't apparent coming out of our Q3 earnings call, but you'll see increasingly through subsequent calls the momentum we're building on that, on the lab operations side. Like I said, we hired a very seasoned Senior VP of Lab Ops to continue to morph that lab into more state-of-the-art high throughput, scale, robust operation, key investments in lab automation also made. The focus in 2022 is going to be continuing to build out on the automation front, improving robustness of the labs, to improve our turnaround times and then the portfolio optimization from the types of tests we're offering across the broad array of diseases and conditions. On the commercial reach, we had kind of scaled up. You would have seen if you tracked our Q3 earnings call, where we were hiring new sales, ramping the sales force, coming out of this back and that really kicked in as you could see. Coming out of Q3 into Q4, we showed that in our Q3 earnings call, the headcount on the sales force side increased by 84% and some of that growth continues to hit. The aggressive volume numbers will shoot for next year. The areas of focus for 2022 will again be on new products. To open additional -- the new products we have coming, open additional channel opportunities. And again, the health system entry points to drive the oncology growth, having systems like [ ANNOVERA ] where we're running a variety of protocols and really helping deliver whole exome somatic germline and transcript on integrated with all the clinical information as the standard of care there in building the right kind of programs to end and support systems to achieve that through that system. And of course, other systems will be doing the same kind of thing. And then on the pharma and data side, we've made a number of new hires to help work with me to help drive on the pharma and data business side. We hired a Chief Data and Chief Science Officer, Gustavo Stolovitzky; and the Chief Science Officer side who think platform of algorithms is the guy who innovated on the [ dream ] competition, how do you facilitate competition-driven problem solving on the big compute algorithm side to get at best-of-breed algorithms to deliver the most differentiated insight through whether it's a health course journey or a research pharma collaboration, he's somebody who's built that kind of engine and now working with Sema4 to build that out. We hired a Chief Medical Science Officer, William Oh, one of the top medical oncologists in the country and again, working with us on a lot of the oncology and beyond programs, partnerships with pharma and the health systems to kind of get at that flywheel I showed you a couple of slides ago. Also, given the scales of data we're operating on the trust that the health systems put in us around those data. We submitted for final approval or HITRUST certification, CSF certification in 2021, expect that to be a final -- to final approval in the next few weeks here in 2022, a really big milestone for us. And again, kind of shifting a degree of focus on the C-suite to focus really on this pharma development and data monetization, where we think given where we're at today, getting to a re-transformative pharma deal that demonstrates our ability to monetize what we've built sort of as a core objective. So we'll just conclude with our capital allocation. Isaac spoke kind of a little bit to that, but the significant capital resources we have to drive long-term strategy, $400 million of cash and equivalents on the balance sheet. We have $125 million revolver that's undrawn. And our acquisition criteria include -- we want to enhance our reach into the health systems. Again, it's about how well can we penetrate the entire health care system with respect to genomic testing solutions, partnership around the data, partnership around the patient. So it's expanding that capability, enhancing our data capabilities, again, in driving these pharma relationships and then commercial revenue. So with that, I'll thank you for your attention, and I think we will move now to your questions.

Thanks, Eric. That was a great overview. So maybe looking at the path forward, I know you previously mentioned that you have 3 selection criteria for providers, integrated payer provider, early adopter of genetic testing and willingness to share data, right? So how many provider systems actually meet those criteria? And how should we think about the runway of addressable systems in the medium to long term, beyond your assumption of I know 5 systems by 2023?

Yes. I think for today, it's -- there aren't a lot of -- to get to those 4, the 3 we signed were announced last year, that's talking at 50 to 100. It was -- and it's sort of evaluating -- if a lot of them have an appetite, a lot of them have a want, but they're not quite at -- they don't have enough of the pieces to make the engagement effective. But the heavy lift on the health system side, it's a real commitment, that's money, its resources, its time spending with Sema4. And so I would say the 4 we have today are special and that they met all those criteria in already, but what I'll say is that the rest of that distribution is catching up. So we view this -- the play is we view these early ones as learning-based partners because nobody has a solution to wire all this stuff together to deliver precision medicine into the systems. That's what we're going to -- we have a lot of those pieces. Others have those pieces. We're going to work in collaboration, deep collaboration with those partners to figure out how best to wire those together in a way that we can then scale to others and make it far easier on those others. So they don't have to be quite as far along as these others are today, but they have that appetite. So we see it kind of trickling down. And by the time we're ready to scale, we'll have an easier set of solutions platform to scale into the system. We really see it ramping to a large number of systems, say, in the next -- after the next 1 to 2 years. I don't know, Isaac, if you have a...

Yes, I would just add that like the number of systems, it's really important that the number -- it's quality, not quantity, is our mindset, right? The right partners doing the implementation the right way. And then if you look at sort of the number of patients that we can impact. I mean that's already in the tens of millions, right? So I think that as we look at the economic opportunity, it's already really significant with the 4 that we've announced, and we think the pipeline that we have will get us even further down that road. So we don't need for there to be 50 partners for this to be a much, much bigger business. And that's why we feel like, again, focusing on quality not quantity is the best model.

Got it. Makes sense. And I know you're setting the maximum number of health systems to have by 2023 at about 10. So beyond the 3 criteria I mentioned about like how would you further narrow down the funnel? I mean, obviously, oncology is going to be the main focus, but what other factors would you consider when choosing say, an oncology program to partner with?

Well, I mean, oncology is one area that we could engage. I'll say, for example, NorthShore I said is -- the initial engagement was around population health, like a very different kind of a play that then spreads into lots of different diseases that we're excited about because once you're into the genomic health arena and screening in target populations, you're now able to leverage the genomic and clinical information across thousands of diseases and conditions to help guide decision-making and characterization. So I would say the ones that are coming, again, are just increasingly able to the kinds of data they have, the accessibility of the electronic medical record data, how mature their IT infrastructure like one of the things that slowed us down a bit is in terms of getting more rapid penetration on these health systems as they're kind of the data side, the big lift. Like these IT infrastructures that exist at these systems are just intended transactional to [ log ] what's going on with the patients and what they need to build for. They're not being -- they don't have the teams there to say, well, how do you restructure that data to be able to compute on it and drive insight. So it's looking increasingly at maturity of the IT infrastructure. But I think more than anything, it's the commitment of the leadership to want to transform their care into a precision medicine framework and kind of commit the resources that it takes to uptake. And what I'll say on the 10 is these are a big lift for now, and it will depend on how fast we learn. If it takes us through 2023 to learn how are we going to scale this [ to 100 ]. That's what we think it could take that long. But what we're seeing from these early partners as there may be components pretty holistic solutions that are hitting like, for example, oncology or population health that may be able to go out more rapidly to more systems.

Got it. Got it. I know you start each partnership with a master service agreement. So how much does that kind of pave the way for multi-indication expansion down the road? Or is indication-specific usage still up to the individual hospital departments? And we know, I mean, what are your latest thoughts on having a land expand strategy for each health system so you maximize the value of these partnerships and also have more shots on goal with pharma versus focusing on a more homogenous indication across all systems for better scalability?

Yes, I like the question -- the latter part of that question is a good one. I would say that as we had laid out on Slide 15 and 16, that a lot of focus on the commercial REIT side is around the existing health systems that we have signed. And we -- the kind of metrics we think about in terms of are we being successful with those systems that we have? Think about like what's the -- to what extent have you displaced other vendors in offering genomic testing solutions. If we have a standardized genomic backbone that you generate the data once, can analyze it for a lifetime around the patient across a broad array of diseases and conditions. Does that obviate the need for other vendors to come in and offer those solutions? What's the -- how many -- what's the number of patients that we've been able to engage or touch through the various programs? So what's the amount of data -- what percentage of the data are we able to engage in partnership with the health systems and so on. So there are all those kinds of metrics that we think will help highlight the extent to which we're being successful, and there's going to be a very concerted effort to drive that penetration through the year. And I think -- and just to be clear, like our strategy is one of that holistic nature as opposed to let's pick one program like precision oncology. Let's just figure that one out and then let's expand that to hundreds of systems. The problem with that gets back to, again, the platform of algorithms play and that increasingly to be competitive even in oncology, in the kinds of treatments that are coming are here, the drug interactions, the drug safety, the complications from comorbid conditions with cancer, other conditions like obesity, diabetes, autoimmune disorder, but you need to have this more holistic understanding of the patient and data around it. And in the end, it's an arms race. In the arms races, who's going to have the largest, densest longitudinal data on the most patients that can derive then those insights to make the best decisions on clinical care, and that's what will drive diagnostics in the future, and that's kind of where we're at. We think once we figure that out, that kind of holistic play for 5 to 10 systems, we'll be in a position to scale that to 1,000 -- to whatever number. And in that way, the penetration is just going to be -- there'll be nobody who's going to catch up at that point.

That's great. I know you're expecting the pharma business to see meaningful acceleration this year. So tell us about the pipeline across your offerings from drug discovery to trial master real-world evidence what does the mix look like today? How about the mix between germline versus somatic right? And then looking beyond the increased commercial focus this year, like are there any limiting factors that you think you can overcome in the near term to further accelerate that pharma business?

Yes. Yes, I love that question too because it is a big focus for Sema4. And what I'll say is the deals we did this year and -- or this past year and some in 2020 that we're focused on a broad array of problems pharma had and it's from drug discovery. So running collaborations that can help identify and prioritize next generation of targets for a given disease. There's the clinical side with real-world evidence-type studies to identification of patients and facilitating recruitment of patients in the clinical trial. So we have kind of a little bit of all of those. And what I believe, held us back some from those deals that can be, say, $0.5 million to $1 million or $2 million to much larger scale size deals was kind of maturity of the data and maturity of the relationships with the systems around that data. So our initial traction was on oncology for those kinds of studies that I just talked about. And we have a much more limited -- we're not -- again, we're not scaling across all of cancer, we're largely focused with a number of health systems around their cancer data, and we're going to -- so the amount of data we had is more limited compared to what others might have. But now what we have is access to the broader array of data across all diseases and conditions where we've been able to mature that by abstracting not just from cancer data from unstructured data across all the data and the over 10 million patients worth of data and abstracting from that, structuring those data, creating a much more valuable data set, way more differentiated because it gets a deeper characterization of patients. And so what we hope to see going forward is increased acceleration around those real-world evidence studies and patient ID and recruitment into clinical trials for a more kind of transformative deal because we're going to have the ability to expand such a wide broad range of the disease and condition space. And that will -- that's everything from rare disorders where we have algorithms today that we've developed in partnership, and this is one of the interests from AdventHealth that can -- with 85% precision and 80% recall identified from EMR data. Whether you harbor genetic lesion that has you having a monogenic disorder that's -- most of those are undiagnosed. So being able to characterize on a broad scale. As you know, in rare disorders, identifying patients who have those disorders and being able to recruit them or get them on the right medication is a big problem. And we think we have paths to be as effective on the rare disorder side as we are on the cancer side and autoimmune disorders. So I'd say it's just a way more wide open and attractive resource at this point. And I don't know if Isaac, you want to say anything off that a little bit.

No, I think you covered it really well, Eric. I did want to come back briefly to my comments on the quarter. I did neglect to mention the quality of the results. I think we're extremely healthy across the board. We came in above our guidance. And I wanted to emphasize that it was both in the core business as well as the COVID business. And I think that's important because it gives us a little bit of context around the momentum we have entering the new year, where a lot of things are talked about are things that we think are going to start to translate into both continued growth as well as better performance in the overall business this year. So I'm just really excited about where we are entering 2022. With the understanding that we have a lot of work to do, lots of things that we want to deliver for shareholders. And as well on the capital deployment side, remaining very disciplined on the types of things that we think are going to create value for shareholders while also making sure that we maintain an incredibly strong stage of liquidity for the business so that we can fuel our growth ambitions organically and inorganically.

That's great. In the remaining minute or so, I want to make sure I hit on the questions submitted through the website. So how should we think about ASG dynamics? I know you know, you're expecting a step-up through [ billing ] collection improvement. So how much of a step-up should we expect with that and once you get CMS coverage by midyear? And then longer term, what about ASP dynamics on the germline side because I think we've all observed the dynamics that [indiscernible] has gone through with the private payer contract renewal. So maybe just talk about that.

Sure. So first thing I'd say is that we'll get into some forward-looking statements, when we get closer to reporting Q4 results. But I think in general, the year closed out exactly the way we expected it to on the ASP front and the team, both on revenue cycle and market access continues to grow and that we think is going to give us a very strong position to improve our reimbursement in select areas, continue to stabilize it in some of the more mature parts of the business. And all those should fuel what we think will be a very strong growth platform for 2022 and beyond. I also want to mention that the commercial team in the aggregate went through a tremendous amount of growth in 2021. We ended the year with a much larger sales reach. So as we think about the combined effect on everything that we're doing on the billing side, on the revenue cycle side as well as the commercial effort, those together will still put us in a very strong position to deliver strong growth that we'll again talk more about when we report earnings. And I think having said all of that, I think we're doing this with the belief that we have a position to strength with our partners both on the health system side, a great relationship with all the payers. And so that together gives us a great runway to create the future state that Eric is talking about. The platform of algorithms and the monetization of our data, that's the end game that we're solving for, and the diagnostic business, which we want to continue to support is going to deliver, I think, on continued growth to enable that feature.

All right. Great. Thank you so much, Eric, and Isaac. That was a great overview. We'll leave it at that, and good luck with the rest of the conference.

Great. Thanks, Julia, and thanks for everyone attending.