GeneDx Holdings Corp DEFA14A, filed Jun 11, 2021

GeneDx Holdings Corp. (WGS)

DEFA14A 2021-06-11

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Added on October 23, 2026

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Matt Sykes:	Great. Well welcome everybody. I have the pleasure of welcoming Sema4 to our conference. And I want to introduce Eric Schadt, the chief executive officer and founder, and Isaac Ro, the chief financial officer. Thank you both for joining, we’re lucky to have you here. I thought maybe I’d start out with about as big picture question as I can think of, which is, what does the future look like for Sema4, and maybe kind of use that as sort of an intro into the company and explain some of the key drivers that people should be aware of. I think you’re on mute, Eric.

Eric Schadt:	Sorry about that. Like everybody with that. Cliche. So we.. Yeah. So perfect. So we, the future of Sema4, five to 10 years down the road is about managing very large scale data harmonized across populations of individuals, algorithms sitting on that, that have the potential to advise, and clinical workflows, clinically actionable results and health systems, patients, providers are querying that platform, those algorithms to get the most differentiated insights on their patients, through whatever health course journey that patient is on in the intermediate leading up to that, it’s about, how do we standardize the genomic information to inform across the disease and condition space? How do we integrate data around patients within the context of a health system and standard of care to deliver precision medicine at scale to those health systems.

Matt Sykes:	Got it. That’s very helpful overview and maybe you can discuss how patient engagement plays a role in Sema4’s current base of business. And how do you envision that to change as you develop?

Eric Schadt:	So the patient engagement is central to Sema4’s DNA. The way to think about it, again, think of platform of algorithms and large-scale data as how do you engage patients and health systems and position as a partner to help aggregate data longitudinally across that patient’s journey? In many cases, we’re generating very high dimensional large-scale data around that patient and integrating harmonizing all of that information to deliver the most differentiated insights in a personalized fast fashion to that patient. So it’s really the partnership with the patient to help them manage the large-scale information around them and to bring it to bear in clinical decision-making through their standard of care episodes with the systems.

Matt Sykes:	Got it. And you know, a lot of companies are using genomics and AI. And what do you think makes you different and why is your database and approach more valuable perhaps versus others?

Eric Schadt:	It’s more about us? So the big data and the AI applied to that too, to derive insights is an important component, but it’s not the only component. So if you think of what do we need to do to deliver precision medicine into a system? It’s generating the large-scale data around the patient. It’s engaging with the physician around the actionability of that information. It’s providing it in an easy to digest way to the patient and the provider.

Eric Schadt:	So it’s wiring together a bunch of different components to actually deliver that solution for the patient and provider into the system. A lot of the information companies today, they’re just focused on just give us access to your data. We’re going to build models and algorithms, but they don’t really have that direct connectivity to the patient, to the system and the standard of care workflows. We just think there’s a lot of learning going on. There’s, nobody that has it figured out. So the partnership you need to have with patient, provider. and system is one of a learning based partnership. Not of just give me your data, we’ll come up with some models and we’ll kick that back to you. And hopefully they’ll be useful. It’s a very different play.

Matt Sykes:	Got it. Maybe that kind of a question I often ask myself when I look into companies is why hasn’t anyone done this before?

Eric Schadt:	Yeah. So, that’s a great question. So again, I think, first of all, let’s say what have others done before? So again, there are a lot of components you need to wire together, whether it’s the generation of genomic information to provide clinical reporting across a range of conditions. So there are a number of companies doing that. It’s the information, the management of the data, the derivation of insights from that. There are information companies doing that. They’re streamlining physician workflows, enabling them to engage complex information. So there’s a lot of software tool interfaces. And so on to kind of enable them to take advantage of the data being generated. So there are lots of expertise, lots of companies in each of those different components, but what differentiates Sema4 is we’re focused on how do you wire those components together? So we’re experts in some of those areas, we’ll partner in others, but it’s the commitment is one of wiring those together to provide a more holistic solution into the system, both for the patient and the physician.

Matt Sykes:	Got it. Yeah.

Isaac Ro:	I would just add, if you think about it through the lenses as an analyst, what you’re used to seeing probably are companies that define themselves as life science tools companies, maybe healthcare IT, software companies, maybe software companies altogether, or service providers, each of whom address one of the silos that Eric just talked about. What impressed me when I got here was that, Eric has built a company that’s really developing skills in all three of those disciplines at the same time. And, as he said, no one’s figured out the entire equation, but we think we have a formula. And that’s something that we’re excited about because it means it’s real.

Eric Schadt:	Yeah. If you think back, just about the scale of data that gets generated and you’re like whether it’s an oncology journey, profiling of the sematic genome for a tumor or expanded carrier screening, like it’s a mountain of data and what the physicians can’t do, the last thing they want is a 200 page PDF report kicked over to them to try to sift through and make the best decisions for the patients. That’s just one component. You have to engage that physician, let them engage those 200 pages in a way that doesn’t require deep expertise it’s streamlined and their workload doesn’t hold them up, makes for rapid decisions. So it’s just a way different play than delivering a point solution. Right? We’re trying to deliver a way more holistic streamlined solution for both the system, physician and patient.

Matt Sykes:	Got it. Just one thing I’ve been thinking about, there’s probably a lot of constituents and stakeholders that you deal with. Doctors, patients, et cetera. How do you coordinate that level of relationship and how do you make sure that each constituent is getting what they want or are happy with the experience and you’re achieving your goals?

Eric Schadt:	Great question, Matt, If you look at what do we invest heavily in? It’s the delivery and support teams, the customer service and addressing concerns teams. It’s teams that go in and work with the senior leadership of health systems all the way down to the physicians and understanding their workflows. We grew up in a health system. We didn’t come from the outside from an information driven company or from a purely diagnostic play. We came from within a health system and understand the complexity of those systems, the complexity of the workflows, how those have to be streamlined, what kind of burden a physician will or won’t tolerate, what the patient wants to hear? So there’s many factors, and that’s what we specialize in. So we, high touch service tools that help with all of that engagement and management.

Eric Schadt:	It’s working with the entire hierarchy of the system, not just going in through the back door to the physician to try to sell a test. So it’s just again, a completely different play. And that’s why we’ve said in our initial filings that our initial focus from those backup proceeds that will come to us, it’s like, we’re not wanting you to go out and do hundreds of health systems out of the gate. We want like five. We want learning based partnerships so that we can understand and learn together with the system. What are the right ways to wire this in, across the different divisions within the system? What are the idiosyncrasies of the system that require customization and so on? So that’s the.. So think of it as a deep learning partnership, where once we’ve done that with the number of health systems, then we’ll be in a position to think about scaling it to all systems.

Matt Sykes:	Got It. Yeah. That makes a lot of sense. Because one thing I thought about with data-driven enterprises is data always starts out personal, but quickly it becomes depersonalized. And particularly with AI and ML, the actual person behind that data often gets lost. And so it seems like you’re trying not to lose that connectivity and trying to re-personalize that data. Maybe talk a little bit about the patient engagement or other ways you try to personalize that data and make it more tangible and less of just a number.

Eric Schadt:	Yeah. Beautiful. So you got it exactly right. It’s how do you engage that patient as a partner to help manage their information, generate additional information, but help them benefit in a highly personalized way from that information. And there are two primary ways we’re doing that today. So think on the genomic side. So when we generate on our standardized genomics platform, what we call Traversa, we’re generating an exome low-pass whole genome worth of information. No matter if it’s a single gene test or a 500 gene panel test, whatever it is, there’s a lot of additional information we can derive from that genome’s worth of information to improve the diagnostics on whatever panel we’re running.

Eric Schadt:	So take expanded carrier screening as an example, the residual risk from a carrier screen, so say you’re getting tested for, are you a carrier for the Tay-Sachs gene. The residual risk, if you’re not a carrier for known mutations, is not zero, right? You still have some risk. That’s a function of your population, the population you inherited that gene from. Well, we can use that genome worth of information to derive exactly what population group you’ve got that from to give you a superior residual risk calculation that’s best in the field. So that’s just one example of how leveraging the bigger data provides a better outcome, a better prediction for the patient.

Eric Schadt:	So that’s on the genomic side, on the clinical records side on that, having access in partnership with the patient to their electronic medical record data. So take pregnancy flows for an example, we can better integrate that information around the patient to improve risk predictions around complications of pregnancy like preeclampsia and gestational diabetes and preterm birth and perinatal depression. So those all can help advise physicians of what to pay better attention to, how to stratify patients into risk groups, give them better care, but it’s highly personalized for that individual patient. So they’re benefiting directly from the access they share with us.

Matt Sykes:	Great. Maybe we can put some kind of labels around it, you mentioned Traversa, but also can you talk a little bit more about that and Centrellis, and just kind of explain for the audience what those are and just a little more detail.

Eric Schadt:	Yeah, so Traversa is our genomics platform. So think of it as a way to standardize genomic testing across a wide array of diseases and conditions. So on this Traversa platform, so it’s an exome worth of data, plus low-pass whole genome, and as the cost of sequencing continues to drop down, we’ll just increase the amount of whole genome sequencing we’re doing until it’s just a whole genome sequencing test. But that product today, it can inform on well over 7,000 diseases and conditions. So you may, so a patient may encounter it first for like expanded carrier screening in a reproductive health setting, and we determined through the medical records or engagement with the physician that that patient’s at high risk for cancer. Well, the data already exists. We can issue a heritable cancer report on that patient as well. Drug safety, polygenic risk scoring for common disorders. So it’s a platform that enables that broad, longitudinal engagement a patient over time to continue informing on their conditions by integrating that information with the medical record.

Eric Schadt:	So, that’s Traversa. Centrellis is the data management and insight platform. So Centrellis is the platform where we’re today managing well in 20 to 30 petabytes of data. That’s all the data our lab generates, that exome low-pass whole genome worth of data on all the patients flowing through. It’s access in partnership with the health systems to the electronic medical record data. It’s a directly consenting and partnering with patients to gain access to a broader array of medical data around them. It’s pulling in from the digital universe of data, and that’s all getting managed on this platform. And then there’s the analytics layer, that’s deriving insights and an interface that then allows different types of users, whether it’s a physician wanting to get a clinical report for the best interpretation, or a pharma-researcher wanting the next best target for whatever disease area, or population health management. So many different utilities, but it’s managing information, providing an analytics data science layer to provide insights based on queries to the platform.

Matt Sykes:	Got it. That’s very helpful. I think we’ve talked obviously a lot about data, and the source of data is an important competitive advantage. Maybe you could talk a little bit about your experience cultivating this data at Mount Sinai, and how that gives the company a competitive advantage.

Eric Schadt:	Yeah, perfect. And again, it goes back to that we were born within the health system, and Mount Sinai in particular. And so we grew up with not just, “Give me your data, Mount Sinai, and we’ll do better things and kick you back some algorithms.” It was, “Hey, how...” Understanding those physician of workflows, understanding where the medical unmet needs were, understanding the needs of the patient, and leveraging the information that gets generated around patients to improve that quality standard of care, helping the systems to improve the quality metrics by which they’re graded and assess themselves, it’s how to improve standard of care. So it’s all centered around how do we both better enable patients to achieve better outcomes and how do we enable the system to deliver a superior standard of care? So it’s that kind of partnership thinking, and clinical actionability of the data that drives us. It’s, again, we’re not just a data shop that likes to apply machine learning algorithms to better predict or classify individuals. It’s how do you do that in this standard of care flow, where the patient first and foremost is benefiting from that information?

Matt Sykes:	Got it. I mean, as we look forward, there’s obviously there seems to be a pretty significant opportunity for Sema4 to be the center of information-based health intelligence. You’re obviously working with hospital systems, with clinicians, researchers, pharma companies, and others. What’s the most interesting thing about Sema4 that you think investors should focus on as they continue to ramp up their work on the company?

Eric Schadt:	Yeah, my push, and would love Isaac, too, to weigh in, but my view would be that it really is about this, it’s the partnership. The delivery of a holistic solution, precision medicine solution, into a health system in partnership with physician and patients. That it’s not, we’re not just looking to say, “Hey, let’s sign as many systems so that we can get as much data as we can, build as many models as we can.” It’s how do we form a learning-based partnership in collaboration with the system? Yes, we’re delivering state-of-the-art genomic testing solutions to improve standard of care, but we’re also figuring out with the system, how do you wire that more effectively into the standard of care flows? And that our bet is, it’s that partnership, that deep, stickier relationship that you have, you’re not just the testing vendor that they flip on and off, you’re a deep, integrated partner with that system. That’s the kind of play that we think is going to move the needle again from actually delivering precision medicine into the system, instead of just talking about it.

Isaac Ro:	Yeah, I totally would, I totally agree with that. I mean, I think what I observed in getting acquainted here in the last five or so months that I’ve been with the company, was the go-to-market. That’s really what is, I think, novel beyond the obvious things. The obvious things being technology informatics, we’ve got all these great people, and scientists working on making the technology work, but it’s when we go out to the channel, to the marketplace, to reach patients and physicians that I think the strategy is very differentiated.

Isaac Ro:	Because I think when you look at startup companies in this space and you ask, “Who are your users?” You expect to see certain brands, right? You expect to see the major academic health systems, the ones that are world-famous, because those are the people that tend to be most excited about the cutting-edge technology. And I think what’s different here is that Eric has really thoughtfully gone to health systems that we think are going to be ideal partners for what we are doing, and they want to do it with open arms in such a way that allows us to not just learn, but really burrow our way into the long-term relationships we want to have with physicians and patients.

Isaac Ro:	And so, not every health system fits that mold, but there is a large plurality. I mean, you look at a distribution curve, there are, in the world, the Mount Sinai’s, the Cleveland Clinic’s, the MD Anderson’s that are always going to be out there doing really amazing stuff because they have great people. And there are going to be community hospitals that are out there serving their communities. And then in the middle is a very select, interesting group of health systems that are integrated, highly interested in next generation technology, but in many cases, don’t have the ability to do it themselves. And this is where we have an incredible ability to partner.

Isaac Ro:	And today, that partnership, that framework, is expressed through essentially four health systems, several of whom we’ve talked about in the last month or so as new partners, and in totality that allows us to reach somewhere in the order of 20 million patients, which now starts to become a really meaningful number. You look at a population in the U.S. of about 300 million. We touch a lot of people today, and we have the ability to gain access and relationships with those people over time. So I’m very excited about just what that... It might feel like a beachhead, that beachhead could become a pretty big waterfront in a very short period of time if we just execute on the model that Eric talked about with Traversa and Centrellis. So I’m just really excited that we have this opportunity now, when the marketplace that we’re in is in its infancy. There’s a lot of white space, and there’s room for many companies to be successful. We think we’re going to be one of them, and we think we have a very unique approach.

Matt Sykes:	Got it. Thank you, that’s yes. Yeah, sorry, go ahead, Eric.

Eric Schadt:	And if I could just add a little bit, Matt, sorry, just to Isaac’s point that it’s some of these systems that are ready today, like a NorthShore in Chicago, very progressive thinking, like their want to partner with us was, “Hey, help us make genomic medicine standard of care across the patient population, and we’re, we want to partner and learn with you on that.” So there may not be all the community systems in the country ready to do that, but we’re going to establish that kind of thing with the NorthShore, with the Avera Health, with an Advent Health, with a Mount Sinai, and that will roll into a more, a broader standard of care where ultimately everybody’s going to want that kind of solution, but you have to learn it, define it, partner around it first.

Matt Sykes:	Got it. And you just mentioned a couple of the health systems. My next question was really to kind of go over some of the recently announced collaborations you have with these health systems. Maybe go through the different systems where you’ve announced collaborations and maybe give people a sense, Isaac, talking about that middle part, like how big of a market is that? How many other [inaudible] health systems are potentially within your sort of foreseeable TAM, just to help people kind of size the opportunity? I know you’re at 20 million patients, what could that potentially grow to if you had some additional health systems on there?

Isaac Ro:	Sure. Well, I’ll just briefly say that we don’t plan or expect to tap into all of them in the next couple of years because we don’t think that makes sense, right? Eric touched earlier on the fact that what’s really important is that we learn and partner with these systems in a way that benefits both sides, right? And so this is a very purposeful effort to sign on over the next few years, a handful of health systems, right? Not dozens, but a number that we feel really good about being, number one, valuable to our effort, but also number two, valuable to shareholders, right? We want to hit a critical mass, grow the business significantly. And we think the numbers that we’re talking about today already get us a very long way towards a much bigger business. And so, I don’t think it would be necessarily advisable for us to try and get everything in a short period of time. I think that’s not the mindset we have because the market is so big. It’s bigger than it needs to be.

Matt Sykes:	Got it.

Eric Schadt:	But just to maybe, if you’re willing, Matt, to talk a little bit about some, a couple of the different systems, how they compare and differ, is that useful?

Matt Sykes:	Yeah, that’d be perfect, that’d be perfect.

Eric Schadt:	Yeah, so the one that we’ve, was one of the earliest, and good momentum, I’ll say is NorthShore and what drove the NorthShore, and this is in Chicago, relationship was their want to partner around again, making, having access to a standardized genomics platform that can inform on thousands of diseases and conditions, and to help roll that into a standard of care where it’s, again, not just flipping a report to a physician, it’s like, how do you integrate that information into the medical record data for the patients and how do you routinely engage that over the life course of the patient? How do you educate and provide that information to physicians to make better decisions and so on? So it was driven by this more of a, think of it as a population health entry way, where they want broad genomic health type screen available to all patients, but then generating that more holistic information as part of that can then inform on, heritable cancer and drug safety and expanded carrier screening and so on.

Eric Schadt:	That was the real push. And again, that standardized genomics platform and integrating that with all the clinical record data that they collect on patients, again, to provide a superior way of diagnosis diagnosing, diagnosing treating, and assessing risk of patients. So another example would be Avera Health in the Midwest where that one was more driven by their want to establish somatic profiling of tumors as a standard of care across that kind of system. And liking that we, in the type of profiling we do there, where we’re not just looking at the somatic genome of the tumor and the transcriptome, but we’re doing the germline as well. And we’re not just doing that germline to better call variants on the somatic genome for better interpretation and to, for clinical trials and treatment decisions and so on that’s important, but we can also assess your heritable cancer risks, like in some cancers like breast and prostate, your heritable cancer risk now defines your standard of care.

Eric Schadt:	We can call all of that. You know, the drug safety pharmacogenomic information, all can be derived from that to provide a much more holistic view of the patient. And very importantly, just like NorthShore, helping integrate all that information into the clinical record, abstracting from the unstructured data of their medical record data, structuring those data to make them more accessible to the physician, to better understand the patient journey over time, and then integrating that with the genomic data. So those are just two, like one kind of driven by population health, make genomics, genomic medicine, standard of care. The other thing, Hey, we want to democratize access to advanced genomic testing solutions for our entire population patient population and to rural centers. And so on.

Matt Sykes:	Got it. You just kind of addressed my next question, which is, I think you’ve laid out a great case for the scalability of the platform, but given that a number of these health systems might have some of their own needs. And I’m wondering about the flexibility of that platform and how you can cater some of that data and be flexible for different health systems, different needs.

Eric Schadt:	So perfect. So you’ve got it exactly because and that again, defines why only five or so systems to begin with, because it’s exactly to your point, it’s a learning where, what’s the commonalities across these systems where you can kind of standardize the platform and plug it in. And it applies to all systems. What are the idiosyncrasies of the system that are going to require more specialized customization and so on? And what are the right kinds of delivery and development teams that you need to understand that what’s, spending the time in mapping out the different workflows across a bunch of different care pathways, not just reproductive health, not just cancer, but into a broader array of applications and understanding, again, the best ways to model that in terms of helping physicians manage the patient journeys through those kinds of flows.

Eric Schadt:	So, we don’t have the magic answer for you today on how is that all going to work. That’s part of the learning partnership. Like that’s what we’re going to learn, and we’re going to then be in a position after the first year or two. And that deep knowledge we’ll say, five systems to now be able to scale that to all systems or a much larger number of systems and understanding what it’s going to take to actually scale that and deliver something high enough quality that you become the sticky forever partner with a system.

Isaac Ro:	I think it’s also important to add that in almost all of these cases, there has been a very consistent dialogue with the health systems that we are going to be coming in and providing more than you’re currently getting with an alternative options. And so there’s a little bit of a replacement effects that we can’t quantify for you right now, but I think it’s important to know that we’re not just going into these greenfields, there are situations where these companies, these health systems are using genomic testing platforms from other vendors, and we are winning because of the approach that we take, where there’s a lot more in it for the health system, and certainly for the patients and providers to work with a partner like us, where it’s a holistic experience. So we didn’t ask to be a big competitive advantage as we scale it. But again, how that manifests over time, I think they’ll take the passage of time to see exactly.

Matt Sykes:	Got it.

Eric Schadt:	Yeah. Great, great point. I think as day one with a system, we are delivering advanced genomic testing solutions. Yeah. That kind of moves the needle for them right away. We get reimbursed for that. So we’re able to generate revenue and make it possible to apply that to entire system patient populations. And that’s been out of the gate, but it’s more like, think of it as you’re vectoring over time to an increased resolution picture of health of individual in the population. And that’s kind of the trajectory we want to ride.

Matt Sykes:	Got it. Maybe taking a question from the audience, are there big external data sets available to be bought or partner with? And is that something we could expect to happen over the course of the year?

Eric Schadt:	Yeah. So we certainly, if you think of the HIE’s, systems like CancerLinQ, claims databases, there’s a lot of accessible data out there that can be acquired either directly through subscription or partnerships. So we definitely have an eye on that, but again, the true, real push is one of, if you’re intimately tied to the patient. So if you just think about, if you buy access to something, do you have access to the patient? Do you have access to high frequency updates as the day to day condition of the patient changes through whether it’s a pregnancy or cancer journey?

Eric Schadt:	You don’t have access to any of that. You have information that may be population-wide, is useful, but it’s not as useful for individual patients. So again, the idea in differentiating thing for Sema4 is one of engaging patient and physicians through those flows and getting more real time longitudinal access to that data while we generate, genome wide scale of data to better inform. So the digital universe like acquiring those databases is important, it does help. It does help increase accuracy of the models to some degree, but not as well as if you’re getting high frequency acquisitions of patient data through their life course in partnership with a system. Again, our bet is that that quality scale density of data is going to be superior to what you’re buying from other sources.

Matt Sykes:	Got it. And maybe Isaac turning to you, I’ve got a couple of questions, just maybe help us a little bit with the economic model in, it strikes me as the potential for be sort of like more of a software license subscription type model, but it just maybe explained to the audience how the economic model works and how you expect it to evolve over time?

Isaac Ro:	Sure. Good question. So today, I would say the business portfolio is principally driven by reimbursement for genetic testing, as you would expect from a lot of other companies in our peer group. And the economics there are favorable in so far as market adoption is still very low. Reimbursement is still very high and the costs, the fundamental inputs continue to drop because NGS is our primary input, right? So that equation allows us to have a very compelling top line story that we intend to augment with the expansion of some of the other assets that Eric had touched upon. Right? So I think there’s an opportunity to build a couple of streams of revenue that are going to be very different than a traditional diagnostics company. You’ve got access to the data in a de-identified way. I should mention that. One of the things that I asked as a question when I was thinking about joining was how we think about the sanctity of patient data.

Isaac Ro:	And I can tell you that if Eric and the team were really thoughtful in respecting that this data is patient data. And so while they generate a lot of the insights and we use that in our algorithms, you have to protect it. And that’s something that’s important. And so anytime we use the data for the purposes of monetization, we’re very respectful of the privacy and all these things. That’s very important, but you can imagine in a population scale, when you have the ability to synthesize all these learnings, you can monetize them in the form of secondary insights. You can monetize them to help drive drug development. And so those are things that I think over the next several years will become much bigger parts of our portfolio and will carry with them very different unit economics and margin profiles. Right?

Isaac Ro:	All of which we think will be very favorable. That is sort of the trajectory of our book of business. And I would say that underneath all of that, which is less glamorous, but equally important to, I think investors is that the origin of this company coming out of Sinai was one of being, I think creative and bootstrapped and thoughtful about getting up to scale, getting to the revenue base that we now have. I think as we move forward as a public company, there’s going to be a tremendous opportunity to drive better efficiency. Right. And especially when you think about what happened last year in the world with COVID, there’s a whole world of opportunity for us to, as we grow out of that experience, get more efficient. So there’s a whole series of work streams tied to that that are, again, things that you might associate with a mature company ,but I think with a high growth opportunity like this, we’re finding really interesting ways to balance growth initiatives with efficiency-based initiatives. And I think both of those are going to have an effect on our margin profile over time.

Matt Sykes:	Got it.

Eric Schadt:	Probably, just to add a few though for the longer-term feedback, cause it’d be interesting to hear your thoughts too is... So today it is about leveraging the data in partnership with a patient. So think, drug discovery, collaborations, real-world evidence studies, a patient ID, and aiding and recruitment into clinical trials. So there’s those kinds of uses of data. But what Isaac quickly mentioned was the secondary insight type idea that we’re doing. And that’s once you already have the data and it’s generated and so on, you can repeatedly derive insights from it and deliver those into standard of care. And you can get paid for that. And so think of what I started with a 5-10 year view of this platform of algorithms that people are querying and they’re paying a small amount of money say for each query and we’re running a billion of those queries a year. That’s the long-term goal.

Matt Sykes:	Got it. Yeah, I mean, I think it’s with a number of companies with very large data sets. I think the drug discovery element has come up a lot. And I think it’s just always that striking that balance between the sanctity of the data, Isaac, that you mentioned the monetization of that data and making sure you’re doing it all in the right way for the patient.

	In terms of... Isaac, the proxy was filed in early May. Maybe you could provide an update on some of the key milestones that we should be watching for over the coming months.

Isaac Ro:	Sure. Yeah. Thanks for asking. So in beginning of May, we filed our proxy in partnership with CM Life Sciences with the SEC. And the next step in that process is to respond to SEC comments, which we’re doing right now and expect as a result to refile the SEC, the proxy filing, very, very soon along with Q1 numbers. And so that sort of new information will be available in a public context very soon. And that will set in motion. We think the final steps towards having a definitive proxy statement after which the SPAC shareholders can vote. And I think at that point in time, we’ll close the deal and be in a position to be a public company. And we expect that process to conclude by the end of July.

Matt Sykes:	Okay.

Isaac Ro:	And that’s consistent with what we said in May when we filed the proxy.

Matt Sykes:	Got it. And, Isaac, as Eric mentioned, you were spun out of Mount Sinai, which is obviously a non-profit hospital system, and I’d just be kind of curious to know if you’ve identified any kind of low hanging fruit, so to speak, as you kind of prepare to take the company public in the coming months, and is there costs that you can take out, ways you can make things more efficient that you’ve identified?

Isaac Ro:	Yeah, sure. Well, first of all, I think we should start by saying we’re extremely-

Eric Schadt:	Try to control yourself on that answer Isaac.

Isaac Ro:	I actually would start saying how thankful and appreciative we are to our sponsors. Sinai, it’s going to be, I think, a landmark, experience for them as an institution. The fact that Sema4’s had this level of success and now becoming, soon a public company, we’re really grateful to them. And having said all of that right, it’s a large nonprofit health system and we are, building out a publicly traded commercial company. And those are two very different ways of living. And so I think there are lots of opportunities for us to find efficiency. But I really want to emphasize, we are in a high growth mindset with a high growth ambition and we are going to invest for growth. And so there is big primary focus is on driving growth with attention on ways to be efficient with that.

Isaac Ro:	So, it’s an interesting dichotomy to be investing aggressively for growth while also looking for ways to get tighter with efficiencies. And I’d say the low hanging fruit so far has been to really bring in a world- class finance team to help make sure that we can drive a lot of the operational results and visibility that we want. So we brought in over the last few months, a new leadership team in finance, most of those people have prior experience at larger public companies. And so, very excited about what that can mean, both operationally and culturally to the team. So I just want to give a shout out to that team, doing the hard work. I’m the face to it, but there’s a lot of great people doing things that I think will put us in a position to execute on Eric’s vision.

Matt Sykes:	Got it. Maybe as we close, you’re a leader in women’s health, genetic testing, and you’re, planning to introduce an expanded carrier screening test later this year. Maybe you could talk about the women’s health market and your approach and what does that experience allow you to do in terms of your roadmap for other markets?

Eric Schadt:	Yeah. So we’re very excited about the reproductive health, women’s health market, where, where we do play a leadership role and maintaining that. Our roadmap, or how do we grow and maintain that leadership? It’s about... We started largely... So think of higher risk pregnancies in vitro fertilization based pregnancies, maternal fetal medicine practices, like physicians who are more savvy with, or used to using big technology solutions. It was providing the most comprehensive assessments of carrier screening risk in reproductive health couples. Again, it was enabling the engagement of that information and seamless, easy to digest ways. It was partnering with the patients, leveraging things like the ancestry I mentioned. Deriving that from the genomic data to improve residual risk calculations.

Eric Schadt:	So it’s a continuing to make the test better and better, more comprehensive. Reducing the risk of problem pregnancies. It’s delivering now improved insights as we partner around the data, and can aid the physician and patient in better understanding their risk profiles, not just with respect to the genomic testing, but a broad array of conditions like I mentioned, on the pregnancy complications. It’s now starting to spread that beyond the high tech focused higher risk pregnancy physicians into more standard OBGYN practices.

Eric Schadt:	It’s again, helping the physicians and patients in those flows understand genomic medicine, the application of that beyond the pregnancy journey. So think of heritable cancer, breast, ovarian, endometrial types are reproductive health diseases. So those... Increasingly OBGYNs are advising and assessing risk of patients for that. So there’s application and those flows to heritable cancer testing in addition to the expanded carrier screening and noninvasive prenatal testing and so on.

Eric Schadt:	There’s the newborn. One of the exciting products we have with some of the donor sperm egg banks, is around the characterization of newborns, with respect to risk across a broad array of diseases as well. So think of it almost like a womb to tomb. You start, you’re capturing patients at a very special time in their life course, and now you have the kind of standardized platform engagement with a clinical data to advise for the rest of their life. So it’s that kind of evolution that we’re expecting over the next several years.

Matt Sykes:	Great. And, and with that, I think we’re unfortunately out of time, but Eric, Isaac, thank you so much for joining us. Fascinating story. And we look forward to learning more about it.

Eric Schadt:	Awesome Matt, thank you.

Matt Sykes:	All right, take care.

Isaac Ro:	Thank you.

Matt Sykes:	See you.