Good morning and welcome. This is Keith Meister. I am the Chairman of CM Life Sciences, and I'm thrilled to be here with you today. I am joined by Eli Casdin, the CEO of CM Life, and Eric Schadt, the CEO of Sema4. We are very excited today to announce a very exciting transaction, the combination of CM Life Sciences and Sema4. As you guys know, my background, I'm a generalist investor who has sort of an expertise in helping invest in public companies and helping serve as a director and managing them through change. I've been friends with Eli since childhood. We grew up together, been friends for life. I've been fortunate enough to be the first investor in his fund, Casdin Capital, in 2012. Over the last decade, he's compounded money at exceptionally high rates of returns with a real focus on the life sciences space. Eli and I were talking about opportunities to provide capital to help grow businesses in his space back in June, and we came together and had this vision that together we could be partners where one plus one was equal to more than two, leveraging my expertise in capital markets and Eli's expertise in life sciences to form a SPAC, to help a business upscale, a $2 billion type business, enter the public markets and use the public markets as a partner to grow from a $2 billion business to a $5 billion business to a $10 billion business to a $20 billion business. Our hope was to find a great entrepreneur who wanted to grow in the public markets rather than to sell, who had a vision, who was early in his vision, and with sponsorship, with capital, and with intellectual capital, could help execute that plan. We were fortunate enough to find Eric and the Sema4 team. Eli and Eric have had a relationship for a long time. I'm going to turn it over to Eli. Simply put, we launched our SPAC in September with a view of finding a wonderful entrepreneur with a wonderful business, with a big dream and a big vision that could be accelerated by our capital and our team's know-how, and we think we found the perfect partner with Eric and the Sema4 team, and we're thrilled to share that with you today. Before I turn it over to Eric to walk through the business, I thought it might be helpful for Eli from an industry perspective to articulate why Sema4 is the perfect partner for CM Life Sciences. Eli? Thanks, Keith. I share Keith's excitement in being able to do this with Eric and Sema4 team. I think in the vision of doing a SPAC, as Keith said, the idea was to bring together great investors in the SPAC, a large capital base, and board members on the SPAC that really understood the space. You'll see that we have Sean George, CEO of Invitae, Nat Turner, co-founder and CEO of Flatiron, Emily LeProust, CEO of Twist, bringing together industry expertise, a lot of capital, and a vision to go and find a life science business, whether in the diagnostic space, in the data space, or in the tool space, or maybe beyond, and sort of come in with this expertise and capital and help them accelerate growth. We're at an exciting time in history where the integration of genomic and clinical data can be leveraged to really change health outcomes. To do so, you need a purpose-built company like Sema4, and particularly, you need expertise on how to understand that data, generate that data, and integrate that data. I think before you hear the story, what you should appreciate is that Eric Schadt, the CEO and founder of Sema4, is the world's expert in this endeavor. He has probably the most genomic publications by a factor. Those publications are of the most frequently cited and impactful. He has built a career that really tracks to all the stakeholders and necessary technologies in the space, beginning with Roche and Merck, and then moving to PacBio, one of the leading sequencing platforms, and then going to Mount Sinai and really learning and understanding how clinical data, that is the data generated from the medical health records and your medical history and medication selection, and then within an integrated health system. All those professional experiences with this deep expertise and sort of brilliance, if you will, on stringing it together, he then went out and hired hundreds of data scientists, but not just sort of people out of the tech world, but data scientists that understand biology and understand clinical data so that they can know how to pull it in and then weave it together to drive true, impactful, insightful outcomes. This company not only is driving towards a white space, an important and valuable white space in the field, but with the greatest sort of team, the heavyweights, the dream team of people behind it. With the capital and the expertise from the board, and obviously Eric's vision and team he's built out, this is just a really unique opportunity, and we're super excited to be a part of it. Eric will take you through it. You'll see the vision very quickly, I imagine. Thank you for taking the time. Hand it over to you, Eric. Thanks, Eli, and thanks, Keith. I'm Eric Schadt, the CEO of Sema4, and super excited to be here and to be able to present Sema4 to you in this partnership with CM Life Sciences. Our whole vision is centered around how do we generate, aggregate, and compute on very large scale, high dimensional, longitudinal patient health data, doing that in collaboration, partnership with patients and providers, all to deliver next-generation informed insights to better diagnose and treat patients. Hopefully you see from that vision that this really is just perfectly aligned with this CM Life Sciences team and what they envision for this SPAC and where they wanted to target it. This effort spun out of Mount Sinai about three and a half years ago, back in June of 2017, where I had started an effort at Mount Sinai as a multiscale compute guy to come in, charter was to come in and help Mount Sinai transform into a next-generation information-driven health system. How could we enable such a health system to deliver better guidance, better outcome to patients by better engaging complex information models that better inform on patient health? When I first landed at Mount Sinai, I was excited to drop into a big health system and gain access to millions of patients' worth of data, and to start analyzing those data to understand how can we better characterize longitudinal patient journeys to provide better guidance, clinically actionable guidance, around those patients. When I started examining the data, and how were patients being diagnosed with certain diseases. What you're looking at here is just a plot of all the diabetes patients in the Mount Sinai health system, so tens of thousands given along the rows, and along the columns is time. You're looking at when were patients in system diagnosed with diabetes. What was interesting to me is it was as if the patients were okay over a certain period of time, and then the next day they had diabetes, as if there was a switch that got flipped, and they went from being okay to having a disease. We know what I didn't see was a lot of the data that gets generated around patients being used to inform on that decision, and not just a binary choice, but in a more probabilistic way to assess risk of a patient sliding into a disease type state and resolving that. I was looking at the increasing amounts of data we can generate on patients from the molecular side, which includes DNA sequencing, RNA sequencing, the kind of genomic data that we're involved in generating around patients. All the clinical information that, again, thousands of features collected on patients over time, informing on their health in deep ways. Of course, the increasing amounts of data that can be collected around patients outside of the health system through wearable devices or through health-related apps. When I started to integrate and model those data to better assess patient risk in diagnosing disease states and resolution of disease states, especially as the density of the data got higher, what you could clearly see is you went from this, what appeared to be a binary switch, to a clear indication of patients sliding into disease states. It was loud and clear that they were going to develop the disease long before they clinically manifested the disease. Not only could you see them cascade into the disease state, but you could see their ability to resolve the disease given different treatments or participating in different therapy arms. All came into focus for me about how do we leverage that kind of information and coming up with better risk models and better diagnostic models and better therapy matching models to help physicians assess the patient journey long before they clinically manifest the disease. The whole mission became how can we span this chasm between the practice of medicine, the standard of care, and the ability to enable that standard of care to engage high-dimensional, large-scale data and decision-making tools to provide more clinically actionable guidance. How can we enable physicians to engage that information in a more meaningful, real-time way, given the very rapid rate of growth of the information and the modeling around it. How could we make that more real-time? That's the platform that we built out at Mount Sinai and ultimately spun into Sema4. It's a next-generation information platform that's currently married to a genomics platform. The platform itself, again, is about aggregating high-dimensional data around patients, both generating data, but also leveraging what exists around the patient in the medical record, reflecting those data off sophisticated models to interpret a patient's conditions and risks, and then being able to communicate those kinds of model-driven insights to physicians in an easy, digestible way. Of course, given the scale of data and the rate of information and knowledge growth, this platform, we had to architect to be very dynamic and adaptable to learn as we learn from the insights, how accurate the models were, refining the models, and so on. It's an adaptive learning type system that has the ability to deliver insights in a variety of different applications. For example, of the genome's worth of information we now obtain on patients, we can employ machine learning-based models on this platform that integrates that genome's worth of information and can provide risk assessments across an entire spectrum of disease, not just in a targeted area like cancer, but across the disease spectrum, whether it's cardiovascular disease, Alzheimer's disease, inflammatory bowel disease, the whole range of disease and wellness. In addition, the platform can deliver insights by integrating high-dimensional data generated around cancer patients. Whether it's clinical data, imaging data, the DNA sequencing data that's generated on cancer patients, both from their tumor and their germline, whole transcriptome data, integrating all of those data together to better assess molecular subtypes of the patient's tumor, and then provide for better matching to the most appropriate therapy or to the most appropriate clinical trial. Even with the molecular data aside, we don't need molecular data to provide those most meaningful insights. We have deep expertise. The platform has the capability to integrate all the high-dimensional data that's in the EMR systems to abstract from physician notes, structure those data, integrate them with the rest of the structured data, harmonize those data across health systems to provide a more meaningful scale data set. Then we build longitudinal patient journeys off of that information. To provide, for example, better risk assessments. For example, in our women's health programs, we have the ability to model all of the complications of pregnancies longitudinally as a patient progresses through the pregnancy journey. Think of complications like preeclampsia, preterm birth, and perinatal depression and hemorrhage, all of them impacting a woman's ability to have a safe pregnancy. For some of the models that we construct, like the preeclampsia models, it delivers positive predictive value, ability to predict preeclampsia in pregnant women, that's five times the standard of care. Just examples of when you're able to embrace all of the information, apply the most appropriate modeling to that data, you can truly transform standard of care. I love that example because in many of these instances, you hear about these stories that really have huge potential, but the reality of that potential is still way off in the distance. This is an example of using this data, genomic and clinical, with fivefold accuracy, diagnose the likelihood of a patient developing preeclampsia, and being able to prepare and intervene ahead of the event. That's basically the future of medicine, is medicine to date has been very reactionary, and using this data and approach like Sema4's, we're going to get into preemptive medicine. Preemptive medicine not only delivers better outcomes but lowers cost to the entire system. This is the future of medicine, and Eric is delivering it here today. Today, the application of that platform is spanning three different areas. We started in women's health, the first application of this platform, where we have the most comprehensive expanded carrier screening genomic test solution on the market, in addition to non-invasive prenatal testing. Also have, again, that longitudinal individualized health course trajectory modeling that we do on the pregnancy journeys as well to deliver differentiated insights through the course of care of a pregnant woman. Of the Women's Health Program today, we're at a run rate of just over 200,000 next-generation sequencing tests a year. That business is on a run rate of over $200 million in revenue a year and growing at about a 30% clip. Because there's nothing specific to the platform we developed with respect to health condition or disease condition, we last year spun up our oncology solutions as well as another application of the platform, which includes a comprehensive exome-based heritable cancer testing genomic solution, in addition to a whole exome and transcriptome somatic profiling test for cancer patients. That's also combined with a variety of informatics tools that, again, enables physician and patient, in addition to researchers, to engage that information and insights in a more meaningful way to help guide standard of care and decision-making along the patient's cancer journey. In addition to these two areas, we, again, the platform being very general, it can characterize disease with the integration of this information across the broad spectrum of disease. Because we're generating a genome's worth of information on patients, as I said a few slides ago, on the insights that can come from the platform, we can assess risk across the range of diseases by integrating the genomic and clinical data to better inform across the broad range of disease and wellness. This population health focus that we're partnering with health systems on to provide a more systematic characterization of all patients is, again, one of the first examples of the broad utility of our platform versus the specific focus in women's health and in oncology. The business we built is sound, originally targeting on the women's health side. You can see we did just over $190 million in revenue last year, the bulk of that on the women's health side. As we spun up our comprehensive oncology solutions, we're seeing really good growth on the oncology side and in addition, pharma partnership side, as a lot of the pharma partnerships are enabled by the cancer data that we generate. Roughly 8% of our revenue in 2020 was non-women's health and non-COVID-based revenue, really attributed to the oncology and pharma partnerships. We see over the next three years, the biggest revenue growth drivers will be in the oncology pharma partnerships and what we call secondary insights sides of the business, which are getting paid to interpret data that's already existing, where we have some relationships with health systems, where we're providing clinically actionable insights off genomic data that's already existing. We're not generating the data, but we're the interpreters of that data and providing clinically actionable guidance that goes into the medical record. Also we'll say, you can see this distinction between the. Yeah, go ahead, Keith. Eric, let me just interject and make one point here that as a public markets investor, I find the most powerful. You said the business is sound. I think you're being very, very humble. Eric and team have created an amazing scale business that's doing in excess of $200 million of run-rate revenue from majority 90% women's health genomic testing. On top of that revenue, there's a business that's an amazing platform. As this graph shows, between 2020 and 2023, we leverage the platform to scale growth, and we get growth on growth on growth. We get revenue growth of 38%. We get margin growth as we grow in oncology and secondary multiple insights and biopharma partnerships and health system partnerships, all things that line of sight exist on. As Eric walks through the deck, he'll talk about the biopharma partnerships and the health system partnerships, all of which are leveraging the existing platform that's been built. Our margins are lower today at 22% because we're investing for the future. As time passes, we have line of sight on growth at higher margin. As we have more growth with more margin, what we think will happen is this will go from being priced at a 7x multiple of 2021 revenue as a heavily women's health genomic testing business, to being valued as an information and data platform as Eric and Eli have walked through. That seven times multiple can expand and has the opportunity to be a double-digit revenue multiple. To me, that's the exciting story. The public markets will probably bring that multiple expansion forward very quickly, especially as we use the capital that's been raised to help leverage the platform and accelerate the growth. At the end of the deck, Eli and Eric will go through some of the organic and inorganic opportunities. I just think of the setup as, the platform's been built. There's a lot of scale revenue. As Eric now leverages partnerships and grow, there's real opportunity for multiple expansion and margin enhancement, and that's the piece that gets me most excited as a public markets expert. There's precedent for that kind of multiple expansion in the space through transactions, through these kinds of growth maneuvers. Keith's right to see it, because it's happened before. Oh, perfect. I think it brings to light that the real play here, again, is about the platform and the expansion of the platform across a variety of use cases. Keith already summarized on what we expect in having invested in this platform, which initially leads to a lower gross margin, but that's just because we're generating, again, genomes worth of information on the patients, integrating that with their clinical information. Over time, that's going to start paying off for us as we increasingly partner around that information with pharma and patients to learn more about disease and how to better target and new therapies and so on, but also deriving multiple insights from data that we generate once but can be repeatedly interpreted for different conditions. As that increases over time, the margins also increase, the revenue mix changes. It's increasingly coming from these partnerships and repeated insights from the information. That's why you see the revenue growth over the next few years. You'll see in particular, these health system-directed expansions. These are offering these genomic test solutions into health systems, but as a more coherent, holistic play. This is about how can we bring this platform as a holistic precision medicine solution into a health system where we're standardizing the genomics platform, so enabling them to apply broad interpretations across genomes worth of information off a standardized, harmonized set of data as opposed to hundreds of vendors, and then leveraging that data in the context of the clinical health data to make better decisions, more accurate predictions around their patients. Increasingly, you'll see this expansion of health system-driven revenue, which again, is all about wiring this platform into health systems to provide those kinds of solutions. The strategy, again, is sure, we can go out and sell these solutions to individual practices and physicians, but by wiring as a platform into the health systems themselves, we'll accelerate our access to more and more patients and more and more data around those patients as we become information partner with those systems. The aim is to start with a smaller number of systems where we're really going to learn in partnership with the systems how to wire in this platform. What are the things we can automate and just dropping this platform that's functional today into the system, versus what has to be customized with the system? How do we need to integrate the information we generate, the insights we produce with their EMR systems? How do we facilitate them with tools that complement their EMR system, but taking into account physician workflows and not overburdening physicians, but actually lessening the workflows as we enable better insights? That's the game that we're going to be driving. Again, it's not just focused on cancer or women's health. This has utility across the life course of a patient. What we see today is a lot of focus on the oncology, episodic event in the life course of a patient, and lots of companies now able to leverage the next gen sequencing technologies, from the somatic profiling to germline characterization to liquid biopsy, and integrating that with information to provide better insights. A lot of energy, a lot of activity here. We're participating as well. That's just one episode in the life course of a patient. There are lots of other things that happen to patients and different diseases, whether it's autoimmune or diabetes, cardiovascular. The generalizability of our platform to focus in all these different areas and provide insights enables us to play in a space that very few are able to operate in today. We're excited to be one to have the potential to fill that kind of white space and complement the high degree of activity we see in oncology. I think it's worth calling out that this is an important slide because these are all diseases. What we see mostly in the space right now are people sort of in cancer oncology or in women's health, but there are huge markets, like as this shows, autoimmune, diabetes, cardiovascular. These are all disease states that molecular information and clinical data can start to resolve the way we've seen it on oncology. The TAM here, and the punchline is, the TAM is obviously enormous. It's great to hear Eli Casdin talk to have a sponsor who has such depth in this space, but it's a great call-out that diseases like autoimmune, cancer's not the only one that can benefit from a liquid biopsy or from genomic sequence data for integrating that molecular data with a clinical record. Autoimmune, all these areas. I'll call out autoimmune specifically. There are a variety of new biologics flooding into the autoimmune space. Most patients do not respond to those biologics, so there's a high non-response rate. There's a high AE, I want to say. There's lots of drugs flooding in. The majority of patients don't respond. There's a high adverse event rate. The physicians, so they don't really know how to prescribe those drugs, but what they do is they write it down in the physician notes. The ability to abstract from physician notes, just like it's been done in cancer, to identify the predictive features of what's going to identify a patient that will actually respond, to better target those drugs, better assess response rates, reduce adverse events, increase outcomes, like that same opportunity exists in all these spaces. The platform itself is structured as depicted here, is comprised of a data management layer. Again, this is all about managing increasing scales of data, computing on those data, so that's the insights engine, and delivering those insights, having an API sitting on top of that insights engine that can target those insights to a bunch of different applications. This is what I think is critical to the story, which is there are companies out there with one side of the data equation, where they have some patient data, EMR data, or maybe they have molecular data, like a testing company. No one has this purpose-built platform that brings all these data feeds into one system that can then lever. This is what I mean by that white space. Flatiron, which is something we were involved in, had one side on the clinical status side. Foundation Medicine had the genomic side. The vision always was to bring those things together, and Eric went out and inside the Mount Sinai system, basically purpose-built this. I think this is incredibly important, and I think the exciting thing is, and you'll hear more about, is how you leverage that data into multiple channels. Yeah. Thanks, Eli. Exactly. It really is about the end goal of Sema4 being this insights-driven engine, managing increasing amounts and complexity of data, deriving insights from those data, and being able to provide them in real time across a variety of applications, whether it's clinical reporting, clinical trials, clinical decision support, or population health management. All of those applications will increasingly depend to deliver the best outcomes engagement of the digital universe of data, not just narrow slices of data. Today, this platform is managing on the order of 20 to 30 petabytes. We have 10 million patients of both clinical record data, and then for a big proportion of those, roughly 500,000 or so have comprehensive genomic information as well. Of course, this continues to grow as we fuel this platform, not just in partnership with health systems and by pulling data, increasing amounts of data in from the outside and the literature, but we do operate a high-end genomics testing solution lab that currently is at a run rate of over 200,000 next-generation sequencing tests a year and growing. Of course, the ability to engage patients in their health journeys and providing this kind of data insight increasingly fuels our data management engine. Ultimately, it's about deriving insights from that data and delivering those insights into the standard of care. Again, one of the things that differentiates Sema4 from a more, say, traditional multiple information-centered company is our ability to take that platform and use it directly in the engagement of patients through their standard of care journeys. Because we're providing these comprehensive genomic testing solutions, generating the data on the patients, interpreting those data, delivering clinical reports and other insights to physicians through a variety of software tools that we provide, and patient and physician portals, or integrating the insights directly into the EMR on behalf of the physician and patient. We're a partner. We're partnered with the patient, we're partnered with the physician to be able to deliver these kinds of services and insights. Because we're in this trusted context, operating in the standard of care in a very information-driven way, we have the ability to also consent very broadly the patients who onboard into our platform, because we're scheduling the appointments for them, we're doing the pre-test genetic counseling with them, we're doing post-test counseling with them. We're delivering the results to them, enabling them to take control of their information and to make it portable so they can share it with others. We're in this trusted context where patients consent at a very high rate. In fact, in our women's health and oncology channels, patients are consenting at about an 85% rate, and very broadly for us to enable them to take control and manage health-related information about them through any health system they've ever been part of. Also enables us to recontact them, and again, provide additional insights. What really enables this vision to be realized at Sema4 is our investment in four foundational pillars. The first is the state-of-the-art genomic infrastructure. While many think that the genomic sequencing today is commoditized, that's not quite true. It's still, next-generation sequencing is the only technology known to humankind to move at a super Moore's law speed. Super disruptive, moving very fast. The science is not yet fully worked out. New technologies continue to flood onto the scene. In order to keep pace with that science, to move at that super Moore's law pace, it pays to have deep technical and informatics expertise in this arena, so we maintain a very strong effort around the genomic infrastructure. Longer term, whether we need to maintain that down the road as this information platform becomes the way we interpret information and provide insights, I don't see us necessarily having to maintain that. We'll leverage what others are doing. For today, we maintain a strong focus on that technology. Another pillar is the access and engagement with both patients and physicians. Because we're providing these standard of care services in partnership with the physicians and the health systems, we have this ability to engage patients directly, consent them directly, provide them access with their information, act on their behalf to acquire information across health systems and to harmonize that data and provide it back to them, provide them insights. Again, they consent at a very high rate. It's a special relationship that we are able to form with patients that enables the patient along their journey. Our ability to analyze clinical data, genomic data at deep levels and annotate those data, curate those data, harmonize those data across health systems, make them interoperable, is a core expertise within Sema4. Again, I'll just call out the ability to go into identified patient data, into the physician notes, abstract knowledge and information from that unstructured data, structure those data, and then again, integrate it with the other healthcare information. That's not just in cancer. That, again, is across all disease conditions that effort's focused on. Ultimately, it's the unique insights, the ability to compute on those data, build predictive models, and apply those models in clinically actionable ways. I'll drill down a little bit in each of these areas just so you get a sense of what those pillars are really founded on. The first is the genomics platform. Again, our platform, what we refer to as Traversa, is based on a whole exome, low-pass whole genome framework that, again, enables us to adapt at the rate of learning. Think again, next-gen sequencing moving at super Moore's law speed, the amount of information being generated and insights from those data is growing exponentially. You need a system that's capable of adapting at that rate of learning. We think an exome-based and low-pass whole genome-based architecture is the right model. As the cost of sequencing continues to drop, we'll increase the amount of whole genome sequencing data generated, and ultimately, everything we generate will be whole genome. This information that we generate has the ability to inform across 6,000 or so conditions and diseases, so it's in a clinically actionable way. It's very holistic, very comprehensive, from delivering the most comprehensive carrier screening to heritable cancer to pharmacogenomics to more generalized common disease screening, what we call polygenic risk scoring, where you're integrating genomic level of data across the patient to assess a broad range of risks across many different disease areas, and so on. Again, it's a platform that we're able to clinically report in real time as information, as knowledge, as insights change. We can reinterpret that information. Again, it allows a system to adopt this kind of platform and harmonizes, standardizes the data over the entire population. That has value to patients and physicians as we're able to link the information we generate off that platform with, again, the patient records from the health systems, combine it with the AI-driven insights that we can derive from the data, and providing a range of, again, insights back to physicians and patients. Whether it's this broad interpretation of the genomic information for better risk assessment in cancers like in heritable cancers like breast and prostate, where increasingly the germline information is being used to establish standard of care treatments when such patients at high risk get cancer, so very important component to be ahead of. Whether it's integrating that transcriptomic data in the context of network-based models that we build across the different types of cancer to inform on molecular subtyping and therapy matching, treatment matching, or clinical trial matching. Like again, the ability to go very deep with those data to better, in a more personalized, precise way, classify patients and assign them to the right treatment. The other value to patients is, again, this acting on their behalf, managing their information, engaging them in a way that they can make use of the information generated on them. As just one example, we have a pregnancy journey app for patients on a pregnancy journey who, again, onboard into our platforms because they're getting the expanded carrier screening testing, or they're getting the non-invasive prenatal testing or newborn screening or drug safety testing, whatever the test in that journey is, they consent, and then they're provided the information we can aggregate on them through this app, and it provides both context for the journey they're on. Since they're consented, they've consented us to go on their behalf into their medical record to pull information. We can do that in real time, so we can update them on all information being collected on them, what it means for the current place they're at in the journey, help educate them, provide them insights into those data in a way that's easy for them to digest to really understand what's going on at this stage of their journey, and also to provide guidance. Again, doing this in partnership with the physicians and health system. Just a more holistic engagement. I think two critical components are flagged in this slide that I just want to call out quickly. One is that there are others in the space attempting to do this, but no one has in the way Sema4 has integrated the patient, engaged with the patient and the physician and the health system. This is in cooperation, not in sort of isolation of these incredibly important stakeholders. We've integrated the stakeholders, they've reached out and connected with them, and they follow these stakeholders through the life of the patient. That just creates a virtuous circle of data coming in, value coming out the other side, creating more interest in participation, and it sort of just feeds itself in this virtuous cycle that just increases the value of the platform for Sema4 and for the stakeholders. Of course, once you have this platform, both the standardized genomic platform along with the information platform to better engage the physician and patients around insights, that's of high value to health systems. What they really want is, again, this platform that helps enable them to deliver precision medicine across areas like cancer, women's health, population health screening, and so on. We become a partner with a health system to deliver the standardized platform, standardized insights that integrate into their electronic medical record system, better characterization of patients. Again, we're partnered at a deep level with the system to help leverage that information and access to patients to better understand disease. Our value proposition to health systems is exactly along the lines of what we've already delivered today to Mount Sinai. Remember, Mount Sinai had brought me in as a multiscale guy to help enable them to better engage complex information, to leverage that information, and models built on that information to deliver better standard of care, better insights to patients, partnering with the system to enable them to enter the future of precision medicine. That's where the origins of this platform came from. Unlike companies that we may get comped with, move into these systems, they get not so sticky deals with access to data, and then they run off and sell that data. That's not our aim with these health systems. Our aim is to partner very intimately, deliver very holistic solutions by engaging the information these systems collect on patients, the type of information we generate on a standardized genomic platform that really spans the spectrum of a disease, from the cancer profiling to the woman's health, to the population health screening, to drug safety. That's the comprehensive solution we've been able to embed within the Mount Sinai system, and that we'll now seek with this additional capital to replicate across other systems. Just as an example of the kind of relationship with health systems, just give you one example of a system where we're providing, again, a standardized platform, this population health screen, where this system, very progressive in their use of genomic information and wanting to apply genomic health screening across the entire patient population to better assess risk of disease across a number of disease areas. Think hypercholesterolemia for cardiovascular, anxiety, depression, a lot of drug safety, pharmacogenomics. We can provide the standardized platform worth of data, and while we won't get paid enough for that type of test to recover the cost of generating the data, what it provides is now there's a base of data that exists on a patient that can then be used going forward to inform in different episodes of the patient's life course. For example, 20% of those patients who are tested for the population health screening will be at a reproductive health age and qualify for expanded carrier screening. The data already exists. That becomes a software query to provide clinically actionable guidance off the carrier screening test to the OBs. 10%-20% will be at high risk for cancer. The heritable cancer test, again, can be derived from that genome's worth of information and provide those insights to the physician. Again, we get reimbursed for performing what becomes largely a software query to provide that clinically actionable guidance. Once you have access to broader sets of patients, data around those patients, and ability to recontact, especially in the context of a health system, that's of high value to pharma partners across the entire drug life cycle spectrum, from the raw discovery side to the development side to commercialization. Just to demonstrate the utility our data and patient engagement is providing, just highlighting a few of the pharma relationships we have, one of which is based on a, think of a raw discovery research project to better understand disease conditions in patients by running larger scale clinical trials with deep molecular profiling, in addition to profiling patients with devices, integrating all of that information, building predictive models to help this pharma company identify the next generation of targets for this disease. Other pharma collaboration involves using our whole exome transcriptome test across different types of cancer to better molecularly stratify patients into subtypes, and better understand the drugs that are being tested in clinical trials for biomarkers to better match those molecular subtypes to the novel treatments coming out of the clinical trials. In addition, we can leverage the existing clinical genomic asset that continues to grow to help pharma partners both identify more accurately patients that would qualify for enrollment into their trials, as well as actively recruiting them into the trial. All of this is the kind of growth we'll see in the pharma partnership business as the scales of data increase and. I just want to [crosstalk]-- Yeah, go ahead. --call out one thing, which is the last four things you talked about. That's the power of a platform. Back to the sort of integrated platform story where you basically, through the same virtuous cycle of collecting data and marrying it and analyzing it, you then can deliver it back to multiple different stakeholders at different value economic terms, whether it's the patient or the health system or the pharma. In the way you've built this thing, you are sharing value with each of these partners, and everyone is incentivized to keep giving you more data and enriching the value of the platform. I think that that's, just to sort of tie it in, that's really the power of having a true platform technology. It's a great point, Eli, and I'll just say that it is a partnership with the health systems, the patients, and around the data that provides not just the fuel for Sema4 to keep driving forward, but also to the health system. There's some of these pharma deals we have where 60% of the revenue being generated by the program we launch with the pharma are going to the health systems to help carry out, basically to pay for carrying out the study, paying for indirect costs, and so on. The health systems are happy to be partnered with us because we're helping them drive revenue in innovative ways back into the system, be at the cutting edge of medicine and research. We become, again, this trusted partner with the health system doing what's right for the patient. It's really important, and it also brings up, you know, why we're excited to drive forward and going public through the CMLS SPAC is the kind of capital that can be raised in the public market and be brought to bear on our balance sheet will help us build out, fill some of the gaps in the platform that we have that will more efficiently drive our solutions into the health systems. We'll more efficiently drive them in and help with the uptake, make the uptake of those solutions more efficient and accelerated as well. We have a whole range of activities already underway to identify what are the key technologies or gaps that we may want to buy to pull in as opposed to develop ourselves. We're excited to have the scale of capital we need to, again, move the platform at a faster clip. This slide that we just put up shows the team. This is a mature organization. I'll let Eric walk through the team and some new additions that have been made, both at the management level and the board level, to help prepare the company for its debut as a public company. Eric? Just to quickly highlight, we do have a very strong senior team that has gotten Sema4 to where we're at today and will continue to help us launch into the future. Of course, the new board representation that will come from CM Life Sciences, we're looking forward to adding talent to the board. We're also very excited to announce that we recently brought on Isaac Ro as our Chief Financial Officer. Isaac, as you may know, was a former CFO of Thrive and has a very long history on the analyst side, covering this space, knows it very deeply, understands very well the mission of Sema4 and what's needed for us to advance in ways I just talked about today. We have guys like Jamie Coffin, our President, Chief Operating Officer, who has a long history having built out the health services IT businesses at IBM and Dell, knows how to build and operate at scale. Tony Prentice, our Chief Product Officer, having a deep consumer base expertise. It was very purposeful to bring somebody in who was more consumer facing versus health focused because we want to more seamlessly engage with patients, not just as part of a health system, but in a more general way. The thinking is more tuned in there and so on. Just a really solid team. Recently brought on William Oh, world renowned medical oncologist, physician scientist type, who, again, will help us continue to scale our oncology efforts. We have Mike Pellini, former CEO of Foundation and now an investor in Sema4. We're just very excited, again, to keep driving forward and now in partnership with Keith and Eli. Yeah. I would just say that we've made many investments in this space, at the end of the day, you need a strong platform, but you need amazing people. Eric has amassed, in addition to this group of operators that are seasoned, 150 data scientists, world leaders on his board. We're going to bring some leaders to his board as well from our board, you're going to have the CEO and founder behind Foundation Medicine and the one behind Flatiron now sitting at the same table aligned in a way that had never aligned before. You really just have this very unique situation of capital, platform, and talent coming together to tackle a really big opportunity that there is no one positioned like this company. Keith and I and Eric, I think I couldn't be more excited to be now an investor in Sema4 and helping them grow. With this solid team and the proceeds that are going to come from this transaction, the aim is to continue to fill out our platform to accelerate uptake and adoption into health systems and beyond. Some of the more important components of this platform center around a more complete portfolio of tests. We think liquid biopsy, in particular therapy selection and MRD, are very important components to offer more comprehensive precision medicine oncology into health systems. Of course, we want to increase ASPs across all the cancer tests, operating in multiple states, running in partnerships with health systems, the clinical utility and value-based studies that will aid in adoption and increase reimbursement. That's kind of on the genomic testing platform front. On the information side, we aim to, again, continue to accelerate our ability to integrate and harmonize data across health systems, kind of scale that platform. Along the commoditized front with companies that are already at scale and want to continue developing those partnerships, of course, so we can focus more deeply on where the science still remains to be fleshed out, which is in abstracting from unstructured data. In addition, there's beefing up the software development, product design development teams to be able to customize the integration of this platform into health systems in more customizable, streamlined ways. On this slide, we have already a number of deals that we're looking at across the different domains I just talked about from, again, the liquid biopsy front, the information front, and those are all well on their way, and we hope to, in fact, have some of these in LOI stages over the coming months. Yeah, I think this is an exciting component of the strategy, which is to recognize that this is very much a platform, and in the true sense of a platform, there's inorganic actions you can take to expand the platform and increase the productivity of the engine and expand the TAM. That includes, as Eric said, investing in technologies on the front end for improved detection or disease monitoring and on the back end for better data integration or expanding into other areas of the system ramp up. All those accelerate growth, increase TAM, and in the end, expand multiple. We saw this very clearly with Invitae and ArcherDX, where Invitae was in the women's health business growing like a weed, but really trying to accelerate its push into oncology. Through the ArcherDX transaction, not only got oncology business much further along, but also at the same time, enabled the decentralized model. Those kind of one plus one equals more than two, and in that process, obviously, the company has really benefited. Those one plus one equals more than two kind of transactions, there are a variety of them in the space, orphan companies, orphan technologies, or even attractive growing companies that want to be part of the Sema4 platform. Eric has a really good network in those, and we do as well, and we think combined, we can really help stimulate this inorganic component of the strategy, which is an important piece in this space. Let me maybe spend a second on that just in terms of going through the transaction terms, because I think it highlights how this transaction is being structured to help accelerate growth. We see a lot of value as Sema4 emerges from having been incubated and built inside of a health system like Mount Sinai with a very, very high cost of capital, and then venture funding from leading sponsors into a fully distributed public company. Just the way Sema4 has been purpose-built to succeed in the industry, we've worked with Eric to try and construct this transaction to be purpose-built to accelerate the growth. As you saw in our announcement today, we raised a $350 million PIPE. The total sources of capital in the transaction are approximately $793 million, $443 million from the existing CM Life SPAC, and $350 million from new PIPE investors. As the press release highlights, those PIPE investors include some of the leading large mutual funds, some of the world's leading growth investors, and some of the world's leading dedicated long-only, long dedicated healthcare investors, several of whom are existing investors in Sema4, increasing their participation. We have $793 million of new capital, and the uses are first and foremost, to capitalize the company's balance sheet with $500 million of net cash at closing. If you spend any time with Eric and Eli, and I've spent a lot over the last several months, they're almost giddy thinking about the opportunities to invest that money in the business to grow both organically and inorganically. There'll be a $500 million net cash position at closing, and the incremental proceeds, approximately $335-ish million, will be used to buy down existing investors. That was really driven by us and how we structured the transaction with a real goal to do a win-win transaction with Mount Sinai, where they can still be a large strategic partner with two board seats in the pro forma company and a key partner, but also a 25-ish% shareholder and not a 50% shareholder, which we think helps Sema4 succeed as a public company. The transaction announced today at a $2 billion valuation approximately represents approximately 7x revenue. The transaction is expected to close in the first half of 2021. Frankly, the longest timing element in that is completing the 2020 audit. We expect to have that completed in March and immediately thereafter, file the proxy and expect to close the transaction in the first half of 2021. I hope you guys share the excitement that Eli and Eric and I have. I'll conclude today just by thanking Eric, the entire Sema4 family, all the employees, the investors, the shareholders, Mount Sinai, for letting us come together and to join you in this journey, and we're thrilled to help partner to accelerate the next leg of the journey. We welcome all of you and look forward to following up appropriately as you have questions. We hope you've been intrigued by your first exposure to Sema4, and we look forward to communicating with you frequently in the weeks, months, quarters, and years to come. Thank you very much.