Bionano Genomics, Inc. (BNGO) Earnings Call Transcript

I want to thank my team, which has invested a ton of their time. It's not like they're not busy. They've invested a ton of their time and pulling together this story for you guys to experience today. And everyone around us in the company, I want to say that we're so proud of everything that has happened recently, and we couldn't be more excited about talking to everyone here. We have a number of key opinion leaders, luminaries in their field, who have been enthusiastic about optical genome mapping and Bionano, and they've dedicated days of their lives to come up here and participate and tell their stories. They're going to be amazing. And so the other thing that really gets me excited is seeing a lot of people I know and recognize, but even more so seeing people, I don't know. So we actually brought in some folks who are going to be new to the story here today. So we're a publicly traded company. I don't know if you knew that. But there are a few things that we need to say upfront, so we'll be making some statements about preliminary financial results as well as a series of forward-looking statements. And so I want to make sure that everybody is aware of our filings, which are available online, and you can review those. And with that, let's get started. [Presentation]

Great. So if you don't know me, I'm Erik Holmlin, I'm the President and CEO of Bionano. And this is going to be a story that we go through with you today to really lay out the Bionano story, but it's a story that you haven't heard before. It's really a story about where we're at today, and where we're going in the future from where we're at today. This is our agenda. You should have seen it. We can give you a print out of it, but what I want to start with and really cover are the key takeaways that we hope you get from this event today. And it's really trying to position for all of you in the financial community, analyst community where Bionano fits in the genome analysis landscape. There's so much going on, so many solutions, so many technologies, but where does Bionano fit? I think it's a critical question to answer, who's using our solutions today and why? Where are we pointing those solutions? Where are our target customers? You're going to get to meet some of them, of course. What our financial growth plan is, and what we think about the future financially? Importantly, we're going to talk about how mapping our proprietary methodology compares to sequencing, and address some of the hurdles that we face going forward to really make optical genome mapping a technique that is very widely adopted. And so when we think about where we're at today, we're incredibly thrilled about the progress that we've made. And I don't know if other management teams acknowledge their own sort of sense of all at the accomplishments of the company, but I certainly feel that about Bionano, and I feel that about our team. And I'm just so pleased with what we've been able to do to get to 240 of our Saphyr systems installed around the world, get to revenue levels that are in this range of around $28 million, which is substantial year-over-year growth. The number of clinical research subjects, so these are genomes that are being analyzed by some of our KOLs and others as part of clinical trials, all sorts of applications in clinical research. And Alex Hastie, who you're going to hear from. He was at a meeting and he presented the following statistics and he said that -- the meeting was in November of 2022, and he said that, up until November of '21, the number of clinical genomes that had been published was equal to the number in the preceding 12 months. So the pace of progress is incredible. And so what we see with Bionano is that we're focused on cytogenetic analysis. And what we're really bringing to an area of medicine that's incredibly important, I want you to understand that cytogenetics is the kind of routine clinical practice that we're all experiencing when we get sick. And it's an important area, and we're focused on transforming it. We're very impressed with the work that the pathologists and cytogeneticist do on a daily basis, but what they tell us is they want better tools that provide better solutions, that can bring better outcomes for their patients. And so that's what we're focused on. And when we look at the digital workflow that we're bringing to the cytogenetic space, a 10,000-fold increase in resolution. Alex talked about that in the video, really bringing very, very high resolution to genomic aberration analysis. And when we look at the success rate, so when you think about being sick and your sample going to a pathologist or cytogenetics lab, the really good ones deliver result half the time. It's the combination of sequencing and other tools, Karyotyping and FISH. And what we're able to do is really almost double that incremental success rate. And so really excited about the progress that we've made, and our focus is to really help you understand where we're headed. And this is an image that you'll see a lot over the course of the day, and it represents what we call the genome variation continuum. And others of our team will talk about it, but something you need to know is that anything that goes wrong on this whole spectrum can be a big problem for us, okay? And sequencing, which is an incredibly powerful tool, and we're blown away by the progress that Illumina has made and PacBio has made in advancing it. But this is the area of the variant continuum that's addressed reliably with these techniques. And that's where it's being used. Of course, long read is now emerging. It's not used very much in the clinic yet, but it seems to be a pretty useful tool, but sequencing lives in these areas, addressing single nucleotide variants and small structural variants. We're focused on the cytogenetic space. We're focused on this area of the variant continuum that looks at large chromosomal rearrangements and aberrations, and this is the standard of care that has evolved in cytogenetics. Karyotyping. It's been around almost as long as I have, 50 years. I beat karyotyping to the face of the earth, but it's been around a long time now. Certainly, imaging technology has improved, microscopes have improved, but the basic methodology is an individual looking through a microscope at chromosome spread on a slide in order to make decisions about whether you should take chemotherapy or not, whether you should have a bone marrow transplant or not, karyotyping. Arrays have helped, but looking at only things that go up and down, gains and losses. And FISH has also been a very helpful technique as long as you know what to look for, but when we look at these incremental diagnostic yields that are coming out of our analyses, we're often finding that these were areas of the genome that were hit, but we didn't know to look there. So FISH can't do it. And this is where optical genome mapping or OGM fits. It covers this whole space between traditional cytogenetics, and links up nicely with sequencing. And so not only is optical genome mapping a tool that can be thought of as an alternative to traditional cytogenetic methods, but you can see in that 100, 50 kb range down below, it covers a gap where there's nothing today. And so optical genome mapping, as we see it, is really an alternative to cytogenetics going forward, with a much more powerful and streamline workflow and a beautiful complement to sequencing. And so our vision is that optical genome mapping and sequencing is the future of genome analysis clinically. Now I've been the CEO of Bionano for a while. And Dan, we've been working with Dan and getting ready for this panel, and he remembers that, and he tells people's known me for a long time. And what we talk about is structural variation day in and day out and something that we find is that it's often a new term. I know that it's becoming more and more popular now, which I think is a great thing to focus on structural variations. But these are incredibly important events that happen in the genome. They're so important that cytogenetic analysis, karyotyping, FISH, microarray are the first-line tests that are recommended by all of these medical societies that set those guidelines, right? So when we get sick and there's a sample that goes to the lab, they're going to run traditional cytogenetics as the first line. And so this is a really important area of medicine. It's also got a lot of patients. So when we start to think about it financially in terms of the market size, it's substantial. And so this is the area that we're focused on and structural variation is just a key driver when we think of genetic disease and cancer, leukemias, lymphomas, solid tumors across the board, incredibly important. Another area where structural variation analysis in cytogenetics comes in is in quality control and QA assessments in the cell therapy process. So when we think about the overall workflow of deriving either an allogeneic cell type or cells from a patient delivering a gene-editing therapeutic payload to give us edited cells and then growing them up before infusion into the patient, clearly, there's the need to be assessing what's happening during that process. And so when we look at delivering the therapeutic payload, these gene-editing systems are becoming increasingly complex. Multiple events are needing to be transformed into cells in order to deliver the therapeutic effect, highly complex. There needs to be target effect analysis. There need to be on-target, off-target effect analysis. And what we see is that folks that are working on this are looking for solutions. They're turning to traditional cytogenetics, but it's not sufficient for what they're working on. Once you get the edited cells, it's important to verify that the transformation that you've aimed at is there. But then when you grow the batch of cells in successive rounds of culture, these genomes can go off. Anybody who's done cell culture knows that you can lose the genomic integrity. And so there needs to be a series of analyses that are conducted in this process. And what we see now is that biotech and therapeutic companies are coming to us and a lot of academic medical centers are using optical genome mapping for these applications. And so we'll hear about -- we'll hear about them today. And so when we think about the economic opportunity for us in transforming cytogenetics, we think of it as being very substantial. And so we've done work to understand the number of labs that are distributed around the world, and we estimate it's about 10,000 labs and that actually excludes some more developing countries. When we look at patient samples, we estimate that there's about 10 million patient samples through the combination of leukemias and lymphomas, not only initial diagnosis, but monitoring of patients through therapy, all of the genetic disorders that are being analyzed. And so it's an incredibly voluminous opportunity from samples on a regular basis. There's 1,400 pharmaceutical companies working in cell therapy. It says [ $1,400, ] it's just supposed to be 1,400. And when we add all of this up, we estimate that the total available market that we're focused on, which is a subsegment of -- the genomics market overall is about $10 billion. This is for this transformation of cytogenetics. And so the solutions that we're bringing into these labs are our products. And so many of you are probably familiar with the Saphyr system. That was originally released in 2017. We actually launched it at AGBT in 2017. And when we did, it had an amazing throughput mark. It was incredible when you pulled it out, you could do about 50-or-so genomes per year depending on what your depth of coverage was and it costs about $1,500 to run 1 genome. And the system, if you wanted to bring it into your lab, was about $350,000. And what we focused on over the last several years has really been improving that. So the throughput has gone way up. We've been able to bring the per cost -- genome per cost down to $450, but importantly, the system is a lot less expensive now. And so it's possible to get these systems into labs. And we've introduced economic models such as reagent rentals and so forth that will deliver these solutions. And we have a new instrument that's underway, and that's going to increase throughput another 13-fold. Now we've been focused on making the workflow of optical genome mapping as simple and as powerful as possible. And so we've brought in 2 acquisitions. One is Purigen, and that has given us the Ionic system. Now that's a very powerful solution for automated nucleic acid extraction that can be used throughout genomics now. And we're developing a cartridge within that system for optical genome mapping that's going to be available in the future. But the idea of streamlining the front end of the workflow is important. And then NxClinical, through the acquisition of BioDiscovery, is a software platform that allows for data analysis that's going to become VIA when we add optical genome mapping to it. And the beauty of VIA is that you'll be able to look at optical genome mapping data, of course, but right alongside sequencing and microarray data. And so what we hear from folks who are using these techniques and practicing it is an important area of medicine is that they're forced to look at multiple different techniques, all sorts of different reports, and we're going to consolidate that and bring it together for them. And importantly, the Ionic purification system and NxClinical, those are stand-alone products. So we can sell those to molecular pathology labs even if they don't have Bionano yet, and we can make them Bionano customers through that. So these are -- been important acquisitions that we've brought in. We also have Bionano Laboratories, which is an independently operated CLIA facility. It's based in San Diego. And we also have a CLIA-certified service in Salt Lake City. And so we use it for these 3 areas, really to provide a try before you buy solution to anybody who wants to look at optical genome mapping. But also we have a menu of LDTs. And why that's so critical is that clinical labs that might have an interest in adopting optical genome mapping want to send samples to us because they want to get clinical reports. And when we get those samples, we're able to bill payers and start that reimbursement conversation, which is so important. And then we offer an array of testing for genetic diseases as well. And so within the RUO services, we also offer access to the cell therapy QC solutions. And so this is a powerful platform that we use to develop new methods and make sure that anybody in the world who wants to use optical genome mapping can get access to it. So these are some of the results that I felt provided us some evidence for us really being on an upswing. And so this is the data that I spoke about earlier that Alex shared with me, and it's really this idea that we plugged along for many years a genome here, a genome there, and it's really started to take off. And so that, for us, is the best leading indicator of future utilization and future adoption, and we're so grateful to many of the folks in the room today for being part of those studies, and we know that there are many, many more that are coming. So you're going to hear about all the progress that we're making from our leaders today, and importantly, you're going to be able to meet some users, and we're so grateful to Dan Brennan for coming on board and helping us to drive those conversations. So a panel really focused on how optical genome mapping is used in the cytogenetics environment, and then a panel that will focus on how it's being used in different research. And so I hope you find this to be a very informative day. There will be time for Q&A at the end. And I want to turn it over to Chris Stewart, who is our Chief Financial Officer.

Thanks, Erik. Thanks, everybody, for being here at Bionano's first ever Strategy Day. We're super excited about it. So I'm Chris Stewart, CFO. I've been with the company for 2.5 years. And what I think the most exciting thing for me about Bionano is: one, we're part of this genomics revolution and riding the way of innovation in genomics, but we have something that other genomics companies don't have, a large existing market with legacy tools that have been around for decades and customers asking for a new solution, a new digital solution to the legacy cytogenetic techniques that Erik talked about. So that's really unique is this large existing market for us. Erik touched on it, but we wrapped up 2022 with right around $28 million that we pronounced in January that we were at the high end, just above the high end of our previously guided revenue range. We've got 240 systems and 165 software customers around the world. We're in almost every continent. The history of our company, we've sold 48,000 flow cells. You can see -- 3,000 or so were published research, but 48,000 flow cells sold, but we're just scratching the surface of this overall market with 10 million potential samples every year. We have 406 employees across 4 sites. So now to get into the markets that we're going after, we're squarely in the middle of $47 billion segments of the overall genomics TAM. We're focused on oncology, genetic disease, drug discovery. Of course, millions of people can benefit from genomic advances and access to the technology broadly is enhancing every year. Research continues to drive that forward and make it more accessible. But we have our unique spot, as Erik talked about, the unique and critical role in genome analysis by reliably reviewing these large structural variants. Going after that market, first by converting over the cytogenetic volume today day in and day out. And then secondly, to -- as recognition increases, the OGM plus NGS is the most practical and effective way to get a whole view of the genome that will even open up more markets. Erik showed this slide, I think, again, when we're talking about the markets we're going after, this just shows squarely where we're positioned. Erik talked about it. The most prolific tool being used today, karyotyping is looking through microscopes, right, microscopes. We've heard from customers that they're worried about the future for karyotyping for this cytogenetic analysis because no one's in school, no one's studying karyotyping. They're not going to school or learn how to look at chromosomes under a microscope, right? They're all -- everyone is focused on sequencing. And so they're really actively looking for the next technology, and I think we've proven that we're the right one. So Erik talked briefly, 10,000 labs, right, in the worldwide markets, 1,000-or-so large academic medical centers and hospitals with cytogenetic labs, 4,000 regional reference labs. There's a relatively small number, but they're very large, ultra large reference labs, LabCorps and Quests and whatnot of the world, and that's outside. That doesn't include China, India and other developed countries. In China alone, there's 3,300 large hospitals, 500 beds or more hospitals, and 2,000 independent clinical labs. And then Erik mentioned that 1,400 biotech companies focused on various aspects of cell therapy. All of these are potential customers. We've just scratched the surface. We do have a full commercial presence in China, marketing, sales, customer support, and we're expanding into new regions outside of this as soon as this year. We've been developing the market in India for a while now, and we're going to ramp that up this year. So what's driving those 10 million samples? This is -- it's kind of a dense slide, but across constitutional genetic testing, prenatal, postnatal, blood cancers and solid tumors, these are the indications that are driving those 10 million samples a year. NIPT positives or no results, infertility, pregnancy loss, development and intellectual disorders, birth defects, RUGD diseases, which -- rare is in the name, but it's not rare, right? In heme cancers, it's across the board for heme cancers, lymphomas, myelomas, leukemias. And on solid tumor, all of these indications, for the most part, are covered in our clinical trials that are ongoing that Alka Chaubey will talk about later today, but the key thing is these aren't rare, like structural variants aren't a rare thing. They're prevalent and occur across the genomic biomarkers for all of these indications. So huge market. Things you hear about every day that affect our family and friends and they're all have structural variant causes that today, the standard care around the world for all these today include some combination of FISH, karyotyping and microarray, just waiting for next digital solution. And some people aren't waiting -- some of the customers here they're already making the move. Erik talked about the cell bioprocessing lab -- cell bioprocessing market. This could be a $3 billion opportunity for us. A few years ago, there was 176 clinical assets in development for cancer alone. By 2025, there's estimates that the FDA will be clearing 10 to 20 new assets every year. And QC is required, like there absolutely have to have a way to verify the target effects in the genome, or they're never going to get into production, it will be too risky. These assets -- these large-scale assets can drive 50,000 to 120,000 samples a year for optical genome mapping through that QC process, both in development and then in production after development. Companies today, what they're currently doing in the development process, they're using karyotyping. But karyotyping, it's not scalable, and it's not accurate enough. It doesn't have the performance, and it just won't scale with this industry. So we're getting calls from these companies that are doing this type of work, and they're desperate for a QC solution that they can use to satisfy the regulators before they introduce these products. So I just wanted to give an example, for customers across these different segments, current customers today, what they're doing, what they hope to do down the road? So we're working with one of those large U.S.-based central reference labs. They're currently in the process of replacing FISH panels for chronic lymphocytic leukemia. And their goal ultimately is to replace FISH panels for all of their team samples, 40,000 a year. Memorial Sloan Kettering, again, looking at replacing FISH panels for myeloma today, and they would like to replace FISH panels for all blood cancer as well. Common theme, right, looking to replace the existing tools that have been around a long, long time. PerkinElmer has an LDT out for muscular -- for FSHD, a form of muscular dystrophy. They use that in conjunction with NGS for neuromuscular disorders, and they want to take it -- use OGM for all repeat expansion disorders. And finally, we are working with a global pharmaceutical company who is measuring target effects -- target -- did the on-target change happen? And is there any off-target effects that they need to be worried about? They want to replace karyotyping for some QC. So these are current customers today and what they're doing and what they're looking to do going forward. So what's driven this interest in optical genome mapping, and like Erik said, the huge growth in patients analyzed and published in clinical samples. Well, we've done a lot of work on the product. Erik has been the CEO for 12 years, and they did a lot of work on the product, and Mark Oldakowski, you'll hear from these people as the day goes on. They've increased the throughput by 13x. Erik said, we reduced the price of the genome from $1,500 down to $450. We've made multiple upgrades to our analysis and reporting tools. We've kicked off clinical studies. We've built a worldwide commercial team. We have teams that, like I said, China, Europe, the U.S., and we're expanding into other genomes, and we published results on over thousands of samples. So one of the things that we look at that is reflective of these improvements to the products that we made and the fact that we now have like a commercial-ready product that's usable today is if you look back to the -- at 240 Saphyr systems that are installed today, the ones that were installed before 2019 were predominantly in universities and research centers and nonhuman research labs. Since then, when we've made these improvements to the product, made it really commercial ready and robust, you see half of our installs are at AMCs and hospitals with cytogenetic labs, another quarter regional reference labs, and the number of systems going into research centers and nonhuman is much smaller than it was. So we're -- we think this is showing optical genome mapping move into the type of customers who have regular routine use for these cytogenetic techniques. So here's why this is important, particularly to me? Those routine users have higher pull-through. So you can see academic medical centers, reference labs, pharma, biotech companies, they drive anywhere from 3 to 5x the amount of consumable pull-through on an annual basis. That's today, and we're still early in this game, right? Utilization typically progresses with all of these customers. They first bring the system in. They figure out what they can do with it, very -- tinkering around a few samples a month, and then they progress. They select the first assay. They validate an assay. They move into routine use, and then they move on to menu expansion, adding more menu items to what they do with optical genome mapping. But we're still early in the phase. I mean, you saw a lot of those system installs have just been in the last year or 2. So this is indicative of where we think we're going, but still reflects really in the customer maturation process. So I love this chart. It's the last 3 years of quarterly revenue and Saphyr system installed base. Q4, $8.1 million to $8.4 million. And when Erik and I look at this chart, we looked at it when we crossed over $8 million, and we said, "Geez, Q1 2020, just over $1 million. So we're up almost 8x, 7x from Q1 of 2020 through Q4. Full year revenue is expected to be right around $28 million. Clearing out kind of the financial stuff. We ended Q3 with a cash balance of just over $180 million. And we did close the Purigen acquisition in Q4 of last year. So here's a little bit more on our current business. we've got good diversification across our revenue streams, as Erik talked about. We've got a little bit more than half of the revenue come from our OGM systems and consumables. We also have a strong software business and a services business comprising about 25% of our business. Now optical genome mapping is the core of our economic engine, right? That's going to drive the growth as we go down the road. But we do have these strategic revenue streams, software and now isotachophoresis with the Purigen acquisition, allows us to get into many more labs that maybe aren't ready for optical genome mapping yet. They're doing sequencing, they're doing other techniques. It gives us an entree into them because we've got amazing software products and amazing DNA isolation products. We also have great geographic diversity. Half our business is in North America. Virtually all of our lab businesses in North America. And then we've got a strong OGM presence in EMEA and a growing presence in APAC. So we're excited about the fact that we're starting to see adoption around the world. In fact, some of the other countries outside of the U.S. have a little bit easier time getting reimbursement because our systems are more supportive of new technologies kind of early on. So there's some things going on in Europe. In Canada, you hear about where there is a fair amount of reimbursement for optical genome mapping today. And so moving on, commercial team. We have -- over the past 2, 3 years, we've built a really strong commercial team. We have 135 commercial folks in 12 countries, 51 commissioned sales, 24 field support. And then in the areas where we don't have a direct field sales force, we have authorized distributor about -- 23 authorized distributors covering many other parts of the world. So we talked about the things that we've done over the past 3 years to drive some of the results you've seen. Here's what we're working on for the next 3 years. And fundamentally, these are the things that we believe will clear the remaining barriers to mass adoption, right? It's things like increasing throughput yet again. These are things our customers are asking for, need more throughput, we need more sample types. So Mark will talk to you about that later today. We're expecting to introduce new sample types with our new technology, ITP. We're launching a world-class, great analysis and reporting tool set with VIA. That's exciting and exciting to our customers who're asking for that. We're working on getting key regulatory approvals, including FDA. We're going to publish more of our clinical study results over the next couple of years and address the needs for reimbursement through coding and coverage. So when I look at this, why is now the time to invest in Bionano? Because we're going to be clearing these barriers over the next couple of years to really drive uptick in the market and penetration into that 10 million samples. So these are the things that we really think are critical to get over that hump. So now to talk about our financial targets, right? So great growth that we expect for the next 3 to 5 years, 30% to 50% CAGR. We're excited about that. But even that isn't reflective of the full potential after we clear those barriers. So super exciting, more to come down the road. We also show our target P&L at Scale, and this is our North Star. When we're doing our strategic planning and looking at our product road map and the markets we're going after, we're trying to drive towards this P&L in the future, like we have to get to scale to get here, but we're building a business that can support a really healthy, strong P&L. And we've got the initiatives in place to drive our cost of goods sold down, and allow us to be competitive with a highly competitive ASP, but still get a margin in the 50% to 70% range. We're introducing scale into our operations that will allow us to get to 40% to 60% operating expense. And we expect we can get to a 10% to 20% operating margin as we hit that scale business down the road. So I'm super excited about the next 3 years. I'm super excited for you guys to hear from the rest of the team and our KOLs today. My hope is that they're going to be reinforcing some of the things that I said. I talked about how we're going to penetrate this market for 10,000 samples. You're going to hear from a lot of the folks today about why they think that's going to happen as well. So super excited. I appreciate you all being here, and I'm going to give it back to Erik to introduce the next speaker.

Thanks so much, Chris. I want to hand it over to Dr. Alex Hastie, who's going to talk you through what we call the OGM difference. I think it's critically important to understand where optical genome mapping as a technology fits in comparison to things that are on your minds, sequencing, long-read sequencing, and it turns out that there's been amazing publications out there that really set that story. And so Alex, I'm going to turn it over to you.

Thank you, Erik. Thank you, everyone, for attending today. It's a real pleasure for me to present to you. I think this is a really exciting story. My name is Alex Hastie. I'm the Vice President of Clinical and Scientific Affairs. I've been with Bionano for 12 years. I started right after of my PhD and postdoctoral training as a scientist, and I came to Bionano because of the potential that I saw in ultra-long reads to solve problems in detecting structural variants, especially in cancer. And so that's what I'm going to talk about today. I'd like to exemplify that first with a specific gene, TP53. This is known as the guardian of the genome because if we lose a copy of TP53, we get cancer. Elephants actually have 40 copies of TP53, but we only have 2. So if we lose one, we get cancer, if we lost 2, we get a very aggressive cancer. Elephants don't get cancer because if they lose a copy, they still have 39 left. So this is a really important gene. But all genes can have variants. And those variants can affect your biology because biology is controlled by the genes that you have. And the variants that can affect these genes can occur in many different ways and many different sizes, and you really have to assess all of those variants. So the standard of care for testing, genetic testing has evolved to overcome these limitations to address these challenges. On the right side of this continuum that you've already seen, we can see the cytogenetic methods. The genome has 6 billion base pairs in it, and the variance can occur from whole chromosomes down to 1 base pair. The cytogenetic methods are meant to -- are able to address the largest variants. They're able -- the first technique, Karyotyping can find large variants -- large chromosomal abnormalities. Additional cytogenetic techniques that Erik already talked about, chromosomal microarray and FISH detect variants at higher resolution, but they have other limitations. And the other end of the spectrum is sequencing, which can detect single nucleotide variants and small variants. What you can see in the middle is a large gap of unmet need. So there is no technique that is really assessing that gap. During my presentation, I'm going to show you that OGM has the potential to overcome the limitations of all of these cytogenetic methods and close that gap. To visualize this a little bit differently, I have a picture of a karyotype here. This is chromosome 17 on the left. There's 2 copies of it. Chromosome 17,the left copy of it is the full chromosome. It's 81 million base pairs long. And the one on the right is missing about 1/3 of that chromosome. This is -- this 1/3 of the chromosome, this 30 million basis includes TP53. On the other side of the slide, you can see that NGS is assessing small variants, 1 base pair or a few base pairs. And these can also disrupt the gene TP53 or any other gene. So we have to use techniques that can assess small variants and large variants, but I think this really highlights the tremendous gap from 1 base pair, a few base pairs, up to millions of base pairs that is in the current standard. There has been a lot of hope and promise for NGS to fill this gap, but that has not materialized. Over the last 2 decades, with NGS Technologies making many improvements, we have seen a drastic reduction in cost and an increase in throughput that has enabled new applications, but there remains limitations. First of all, the price is still quite high, especially for clinical applications. But the second one is really innate to sequencing, which is that the reads are short. They're 150 base pairs long, and this has limited their applicability to small variants. And the status quo remains to use cytogenetic methods that are up to half a century old and sequencing to assess the genome as well as possible. So why is it that the short reads are limited to small variants? I'd like to use an analogy of putting a book in a paper shredder. So when you do a sample prep for next-generation sequencing, you shear the 6 billion base pair genome into 150 base pair segments. And that's analogous to putting a book in a paper shredder and coming out with just single words. When you have those words, you can see if there's spelling errors. You can -- and spelling errors are important so they can make a word meaningless or they can change the meaning of the word. For example, the word dessert thats' circled over there, that's the sweet treat that you have after a meal. But maybe it's spelled wrong. Maybe there's only supposed to be one s then it would be desert, and a desert is a hot dry climate. But DESERT also spells dessert like don't desert your team. So to know what that word really means and whether it's spelled wrong, you have to put it into context. And that's the OGM difference. OGM uses ultra-long reads to give you the context. And once you have the context, there's a sand dune in the desert, then you know what that word is supposed to say. And you know if it was spelled wrong, but you have to have the context. The context tells you the story. So let's look back over the years at some of the science to see the OGM difference more clearly. Scientists have been doing benchmarking studies over the years for detection of large structural variants, and they have found that optical genome mapping is very efficient at detecting these large structural variants. Shown in black is the performance of next-generation sequencing in these studies. In various studies of reference genomes at the top, the sensitivity for detecting structural variance by next-generation sequencing is only 10% to 30%. And so they're missing 70% to 90% of the large structural variants that can be detected by optical genome mapping. In cancer genomes on the bottom, next-generation sequencing is missing about 70% of those large variants. So how about long-read sequencing? Long-read sequencing, at 5 to 10x the cost of short-read sequencing, does find structural variance with higher sensitivity. In these studies, the detection of large structural variants by long-read sequencing is 50% to 70%, still really not good enough, still missing the 30% to 50% of the large structural variants. And when you apply it to cancer genomes, it performs even worse, probably because of the higher complexity of a cancer genome, only detecting about 25% of those large structural variants. So let's talk a little bit more about complexity. So this is a set of 3 different studies that compare optical genome mapping to Nanopore sequencing in different genomes. And these circle spots are showing the detection of interchromosomal structural variants that have been called by the different techniques. Optical genome mapping has clean single or 2 intra-chromosomal structure variants in these genomes. While the Nanopore sequencing result has many, many hundreds to thousands of intra-chromosomal structural variant cause, which the authors have concluded are false positives or noise in the system. So this is a result of the high complexity of genomic analysis. It is very difficult to have a technique that has very high specificity and very high sensitivity. So what are the KOLs saying today? There's been 2 recent papers by influential consortia that talk about the ability of short-read and long-read sequencing for detecting large structural variants. And they have concluded that short- and long-read sequencing are not sufficient for detecting large structural variants. In fact, in the GREGoR Consortium Publication, they remind us that short- and long-read sequencing only detect about 50% of the structural variance detected by optical genome mapping. So let's look at the requirements for clinical -- in a clinical setting. So in a clinical setting, we have to have high specificity. We have to find the variants that matter without false positives. We have to have high sensitivity. We have to find the variance we're looking for, even if they're rare in the sample, even if they're hard to find, we have to find all of them. We have to do that in a complex -- in the complexity of a genome that's 6 billion bases, and there may be multiple genomes in your sample like in a cancer sample -- in a cancer biopsy. We have to detect variants that are in just a few of those cells. This has to be cost effective. It needs to have a simple workflow with a fast turnaround time. Bionano is focused on providing a robust solution for clinical translational research. So you can see the OGM advantage in the OGM workflow. We start with ultra-long DNA molecules, and we convert those into ultra-long reads. And we use those ultra-long reads to directly compare -- to directly detect and visualize structural variants in the genome. And this results in very high sensitivity and very high specificity. The other important thing to take from the OGM workflow is that Bionano provides the whole workflow from sample to answer, which is really unprecedented in our industry and really critical for adoption. So the other question is, can OGM really overcome all the limitations of multiple cytogenetic techniques in the clinical environment? This slide shows a table of 7 recent studies among many others, which have assessed OGM for detection of clinically relevant structural variants that were initially called by cytogenetic methods, multiple cytogenetic methods. And in all of these studies taken together, the sensitivity for detecting these structural variants is over 99% -- over 99% concordance with the standard of care techniques. In addition, we find these studies have found about 25% additional clinically relevant structural variance compared to the standard of care. And this is really addressing that gap in coverage of the genomic continuum. So if we go back to kind of the standard of care and the genomic continuum that we talked about before and generalize different disorders. We can see that next-generation sequencing can effect, variants that explains symptoms, diagnose cases in about 40% of individuals. And the standard of care, cytogenetic methods can solve approximately 25% of cases. If you substitute optical genome mapping according to the results that I've just shown you, we expect a much higher diagnostic rate. And we will close that gap, and we will have -- we will leave fewer undiagnosed patients. So -- this is my last slide. I just wanted to conclude going back to TP53, which we need to assess, TP53 and all other variants that are important for disease, we need to assess with next-generation sequencing. Sequence variants can be important. But we also need to assess it with a high-resolution technique that can detect structural variants genome-wide and that's optical genome mapping. And this is really the reason that I have dedicated 12 years of my career working with optical genome mapping to drive this technology forward. So with that, I thank you for your attention.

Awesome job. Thank you, Alex. He joined Bionano about a week before I did, and some people who have been following the company may know that it was based in Philadelphia at the time, but I lived in San Diego. So when I was introduced to Alex and his family knew that maybe there might be a move afoot. Another fellow I've worked with for a very long time is Mark Oldakowski and he's really been the architect of all these incredible solutions. And I want him to tell you about the amazing progress that we've been making, including a series of really important product launches that have just been announced in the last couple of weeks, but then give you a sense of what's coming in the next 2 years. So Mark, I'm going to turn it over to you now.

Erik -- it's a real pleasure to be here with you all. Like Erik said, I will share with you our current product portfolio, and how we're emerging that evolving that for our customer needs. But first, I want to share with you a different dimension to the slide that you've already seen. As you've heard from Alex, OGM by itself is very capable as a stand-alone technology for many applications. and that's -- its primary use today. But we also feel that there is a strong complementarity between OGM and next-generation sequencing particularly short-read NGS to really show the most comprehensive view of structural variation in the genome. And in fact, we and Bionano are creating an ecosystem where you can bring your favorite NGS data, and there's plenty of them now, into the OGM workflow, and we will support that with -- in the upfront with our Ionic system for DNA and RNA isolation and purification, and I'll talk about that a bit more, but that will feed both your NGS system and soon your OGM system. And then on the back end, if you want great results from all that investment that you put into your NGS data, we have a solution with our NxClinical software that provides deep interpretation support for that data. And so I'll be talking about that throughout my presentation. But first, let's look at some of the key metrics that we evaluate within the OGM workflow itself. As it has been mentioned since 2017, since the Saphyr launch, we've increased our throughput by 13-fold. We're going to do that 13-fold improvement again over the next couple of years, starting this year. Along with the platform improvements, we have made tremendous advancements in our labeling and DNA isolation chemistries. And with all those changes put together, we have been able to reduce the per sample price tremendously from $1,500 to $450. And it's going to drop again. Now when you think about high throughput, low price per sample, low platform costs, fast turnaround times and an unparalleled ability to detect structural variants, these are key drivers to adoption. These are the reasons that our customers love this data type. And these are the things that we are going to be amplifying, as I'll show you in the next few slides, and making them better. So first, let's go into a little bit of detail of our current product. So Saphyr is in the center of our OGM workflow. By any standard in our industry, it's got impressive metrics. On a single Saphyr chip, you can get a maximum output of data of 15 terabase pairs across 3 samples, 3 independent samples, okay? Now you can use that bandwidth for rare disease research where you require lower levels of coverage, or you can choose to run it a bit longer to get more data for higher coverage applications like in cancer or even more data for cell bioprocessing applications. Now each of those sample runs is going to cost you the same amount. The only thing that changes is the amount of time that it takes to run the system. So that's quite unique. Now if you decide to maximize your data output from the system, the price per gigabase pair is going to be as low as $0.09 per gigabase pair, which is orders of magnitude than the cheapest sequencers on market today, which is extraordinary. And that's our current product. Now let's go back to talking about getting your NGS data from whatever sequencer you want to use into the OGM workflow to combine with the OGM data type to show you more structural variation. On the front end is the Ionic system. It's technology of isotachophoresis, is able to extract, concentrate and purify DNA and RNA from many sample types, including some of the most difficult, an FFPE used for solid tumors. That DNA is then available to run on your sequencer. We also -- on the back end, if you really care about the results that you want to get from your NGS data, we have a solution for you with NxClinical. It is able to use its powerful auto classification algorithms to help you interpret the results that you're getting, and allow you to create a report to summarize the critical findings. And so this is a software that's been used in cytogenetic and molecular labs for many years. And so it's been proven. These algorithms have been tested through many publications and tens of thousands of samples. Now let's get into a little bit of the weeds, and you'll find out why this is important. So how are we able to achieve such amazing throughput at such a low cost and get this phenomenal structural variant data? A big part of it is, with our consumable, what we call our Saphyr chip. This consumable is, what I call, a passive consumable. There is no active electronics in it. It's a passive consumable. It's manufactured in the semiconductor foundry. By being a passive consumable allows us to more easily optimize for cost and performance. And with our deep understanding of the design, how to manufacture it and our understanding of how DNA behaves in these confined structures, we're able to push a massive amount of super long DNA through these nano channels. In fact, through 120,000 nano channels in parallel at once. Now you can see that DNA in this video where it gets -- the DNA is concentrated and it's natural from cells. It gets moved through by the instrument through various structures. Those structures help to unwind and linearize that DNA and make it available for imaging. And then that imaging provides the information that our analysis tools require to then assess whether certain events are occurring, mutations are occurring, de novo. We don't need to know anything that we're looking for. It's whole genome, always de novo. These are not panels. It's always a whole genome. One other aspect that allows us to really think about how we can expand this consumable in the future is -- and we have work going on, and we filed some patents on imagining what we can do inside these nanochannels. For example, putting an in-channel detector or a nanonozzle to create a different detection modality. And we're investing a lot of effort into pushing those forward through our advanced research. Now our patent portfolio is quite broad. It covers our entire workflow, both for OGM and isotachophoresis. And we believe that it secures our on-market products really well and expands our ability to push the new applications there. But we also invest quite a bit in these advanced research applications as well, so we have a very robust pipeline of new innovations that could be coming to market in the future. We invest in those both internally and through acquiring both IP and entities like we have done recently. Now we have customers that are sharing with us at the [ Lima. ] When they run OGM data, they get results that they have not seen before that really impact their research and they want to run more OGM data. And so how do we scale with that need? And so some things that we've done recently, as Erik alluded to, we just in January, have released major improvements to many parts of our workflow on the front end to our labeling and DNA isolation chemistries, what we are referring to as our Generation 2 reagents to our chip and to various elements of our software, all in concert to be able to provide faster turnaround times and process more samples to help our customers scale robustly. Now in fact, we believe that with all these improvements, it is possible to get a sample to answer for a complex, high depth cancer whole genome within 2 days. The other aspect of what we've done with the G2, Generation 2 reagents is that they are now being manufactured in a GMP FDA registered facility, which sets us up to our future filings for regulatory approval. We have also taken the Generation 2 DLS labeling, chemistry and worked with our partner, Hamilton to automate that with their VANTAGE liquid handling system, making the world's first and only automated extraction platform for ultra-high molecular weight DNA. And so for our customers that are really looking to scale, this system is capable of doing 24 samples in a regular workday. So we're very excited about the partnership there, and we're going to be further amping that up. Now so what's next So beyond the things that we've released to help our customers scale, we're really focused on elevating all 4 of these pillars that underpin our workflow. Now when you think about our current Saphyr, it is able to process up to 1,100 high-depth cancer whole genomes per year. Many of our customers are now ready to do much more, and they're asking for much more. That's where our high throughput Saphyr comes in. So being developed as a benchtop system, this will be the world's fastest whole genome, genome analyzer. It will be able to process 5,000 high-sensitivity, clinical-grade cancer whole genomes per year in a single unit configuration and 20,000 in the 4-unit workcell. Now each of these samples that get run in the system are completely independent, no batching, no multiplexing, 1 sample per flowcell. Now why is that important? It's important for a number of aspects. One is it provides application menu flexibility. So on this system, you can run 1 sample for a rare disease, low coverage acquisition. You can have another sample that's running a high coverage cancer sample. And then another 1 that's running the highest coverage cell bioprocessing specimen. And you can have a mix of all those. Whenever they're done, they come off the instrument. And so -- so that's hugely important. But the other important aspect is that each of these samples could be run at the same negotiated price. So if you negotiated, for example, with Bionano $400 per sample because of your yearly volume commitments, then it will be $400 per sample, whether you run 1 sample that day or 10 samples that day, okay? Now sequencing can't say that because in order to leverage the lowest cost, you need to fill up your flowcell, right, with the full multiplex set. Now some labs can do that, but most labs have irregular flow of samples, right? And so we believe that this matches the -- our target customers much better than most technologies in our space. The -- this also allows us to create features that many folks in the clinical community are used to hearing about like a STAT processing, which means that -- if you identify a sample as a STAT sample, it will be treated with the highest priority throughout our workflow through this system, through our analysis pipeline, it will come -- the data will come out as fast as possible because that was the most important thing that you needed to have run for whatever reason. So we're excited to be able to provide all that flexibility. Now those Gen 2 reagents I talked about fully supported out of the box. This system is also being designed under FDA design controls. It's going to be manufactured in an FDA-registered facility. And it will be part of a filing with the FDA that I'll talk a bit about. We have entered external data late last year and are looking for commercial release this year. Now to keep pace with the amount of data that's coming out of this new high-throughput system, we need to drastically accelerate our analysis time. And we're doing that with a collaboration with NVIDIA to create a benchtop system that could keep pace. That system will comprise of novel algorithms that Bionano is developing tied with NVIDIA's most recently released Ada generation GPU cards. Just to give you a perspective, this high complexity, deep cancer whole genome will be able to be analyzed fully in less than 2 hours in that system. Now in its first incarnation, it will be a benchtop system that sits right next to every high-throughput Saphyr. And there will be other incarnations of a data center and a cloud version for more collaborative analysis. Super excited about this collaboration. Now to feed this high throughput system, we're going to be -- we are putting on to the Ionic support for OGM. What does that mean? That means that Ionic will be able to extract and purify ultra-long molecules of DNA that are suitable to be used with OGM. And back in January of 2022, we started a proof-of-concept to show us the path how to get there, and we are on that path and things are going quite nicely there. The other thing that we discovered during that proof-of-concept was that the concentrating ability of the Ionic device has certain advantages over current on-market DNA-binding technologies, especially in the areas of being able to extract DNA from samples that have a minute amount of DNA, minute small samples, minute samples, for example, needle biopsies. And then other samples that would be more diluted in liquid like DNA from buccal swabs or saliva. We believe that we'll be able to address those and use those for OGM. And once we do, that will unlock additional application, additional markets for us, which we are super excited about. Now finally, our VIA software, as was mentioned, is going to be incorporating OGM data. We started a preview of that software of showing our customers how that OGM data is incorporated in VIA. And so that brings the powerful interpretation capabilities that have been proven in labs onto OGM data. And it streamlines the creation of a report of findings and provides a workflow for labs to adapt to use this in routine analysis. And so this finishes out the workflow from sample to an assisted interpreted result. All right. Finally, what do we anticipate our milestones to be coming up here? So the high throughput Saphyr and its compute will come out into commercial release. This is the first half of 2023, followed in 2024 by the multiunit workcell. We are going to be continuing to expand our sample menu, focusing a lot of our work on the Ionic system this year and next year. So there's going to be quite a bit of product announcements for that coming out. Our VIA, full support of OGM data is going to come out this year as well. And finally, we are very excited about the progress that we've been making in the regulatory landscape. We have -- our kits have received Class I registration in China with the NMPA for indications with blood cancers. And we are going to be taking our kits and the next generation Saphyr in front of the FDA in 2024 with our first assay. So we're very excited about that, and we believe that we're ready for that. Thank you for your attention.

Wow! he got an applause. He deserves more applause for that but the customers are excited. So that's a good sign. Now I don't know who's going to replace Alka. All of us have been up here talking, and you guys have your [ faces ] and you are focused on taking notes and everything, but she has this incredible big smile. It's like so good [indiscernible], I'm going to have to sit there and smile. It's going to be easy, though, because Alka's our Chief Medical Officer, and she joined the company right around the same time Chris did towards the end of 2020, but she's been a fan of optical genome mapping and a friend of the company for many years. And I really think that -- we talked about all these innovations and product improvements, and I think all of those mattered. But without Alka, I don't think we would have had the force to drive it forward. And so she's been an incredibly impactful person. And what we're trying to describe for you today is the process of bringing a novel methodology into a space that we're focused on. We developed an initial product, and it's starting to perform well. We have identified all sorts of things that we need to do in the future to advance that product to make it penetrate as deeply as possible. But the product alone can't achieve those things. There are things that we need to do to get the medical community as a whole on board here in the United States. Adam doesn't have to deal with this in Canada. Here in the United States, we need payers on board and so Alka has really been driving these initiatives. And so Alka [indiscernible] and smile at you encouragingly and thank you very much.

Thank you, Erik. So as all of you heard, I joined 2 years ago -- over 2 years ago. And one of the things was, what is going to be the role. You've heard from I think every speaker today, what has been going on in the clinical genomic space, which I was also a part of. And you are going to hear from most of the panelists that are now optical genome mapping adopters and users and the impact that it has made on the global genomics community. So my talk is going to focus on all the efforts that we have put in place as part of our clinical development programs to transform medical practice. So you've heard some of that along the way. Now this slide, I think, all of you will walk out of here absolutely captivated in your eyes. The point that I want to make here is, as you heard and as you hear from multiple other people, karyotyping is almost 5 decades old. It's still the global standard of care. And we've all been part of this in one form or the other. Now the question is, as -- as over the decades, every new technique that came in became standard of care. But did they all become standard of care at the same time, no. They all evolved over a process, went through this entire path of getting implemented as standard of care. And this is what I intend to show you all today. Now you saw this initially when Erik was mentioning in his introduction that you look at any genetic disorder, whether it is constitutional genetic disorders in a prenatal or postnatal setting or in your hematological malignancies. You go from any professional medical society, the World Health Organization, NCCN, American Academy of Pediatrics, American Academy of Neurology. All of them recommend these tests that you see, the conventional cytogenetic tests along with sequencing panels and sequencing tests that came in almost a decade ago as the first-line test (you see the reflex test). I think as you can see, is that some of these end up being reflex after the first-line test doesn't provide an answer. If you remember what Alex showed you all of these tests together only provide an answer in 25% of cases. And I think you also saw, and I will also show you where optical genome mapping has the potential, and we promise to replace 1 or multiple of these standard of care tests. Now we are talking about transforming medical practice. There are 2 key elements. The 2 key elements are: get the medical community on board, and we have 6 clinicians and researchers and pathologists in the audience today and get the payers on board. Now to get both of these communities on board is dependent on a number of drivers. What you see in the middle are all the things that any technique or technology has had to follow and evolve through to become the standard of care. What we are trying to do and what these drivers are, there needs to be abundant data on optical genome mapping, number one. The clinical validity and utility needs to be established. You heard a little bit about specificity, sensitivity, and so I think that we are really leaps and bounds ahead of any other technology. We also have to demonstrate what is the health economics of any technology for it to become standard of care. And then we need numerous publications, peer-reviewed publications, citing the advantages of any technique. And of course, the publications are tied with adoption and utilization, which you heard Chris show you that we have seen a tremendous increase in adoption and utilization. When we put all of this together is when key opinion leaders who are the influencers of these medical societies come together to basically recommend any technique to be included in medical guidelines. And that is when it has a global impact as standard of care. And of course, we'll focus a little bit on the coding and reimbursement because that is a critical criteria for any clinical adoption. So what have we done, as I mentioned, in terms of the drivers. Let's go to the first one, right? Basically having abundant optical genome mapping data being generated. What we did was we launched large clinical trial programs that you all are aware of. And I think that you get updates periodically from Erik. And these are underway to address multiple key drivers. I'm not going to go into the details of this slide but the one thing that should come out is, not only have publications coming out of these clinical trials show that there is 100% site-to-site reproducibility, now this is really important because we have multiple Saphyrs at multiple institutions placed, and they're all performing optimally. Not only that, all of these clinical trials have shown that there is 100% concordance with standard of care data, no matter which technique from the list that you have been seeing across the day-to-day. And it has also these publications are showing that optical genome mapping not only replaces 1 but maybe 2, 3 or 4 standard of care tests. So this is also demonstrating how fast and accurate you're going to get your results on any specific clinical sample. But the magic is that, okay, you are as good as standard of care, so what? The so what is there is that filling the gap is giving relevant answers back to these physicians, oncologists for their clinical and translational research that is really powerful and really important for any therapeutic or clinical management. So I think you'll see a lot of these trends today. Now as part of this program, here are listed all of our clinical trial sites. And we have all of these principal investigators, some of whom are sitting in the audience today that are part of these professional medical societies that influence guidelines and reimbursement. So I think you'll have the opportunity to ask some of those questions with them today. But wait, we're also making huge international progress. One of our panelists today, Dr. Adam Smith, he chairs the International Heme Working Group, which is a global effort that he and others have embarked upon to demonstrate how optical genome mapping should be implemented in a standardized format across the globe for optical genome mapping adoption. I think this is really critical and powerful. But we've also seen, as published by this multisite paper that we have an AML consortium on optical genome mapping. And 2 of the co-authors, Dr. Ravi Kolhe and Dr. Rashmi Kanagal-Shamanna are also sitting here today. This paper also demonstrated a significant increase in diagnostic yield and the potential that optical genome mapping has for hematological malignancies. Now one of the other key drivers is actually publications. Now you've been seeing across the day-to-day, especially from Alex's talk is that not only does optical genome mapping perform as equivocal with standard of care but also gives this really valuable information by increasing the diagnostic yield. What we have seen across the past several years, whether it is cancer or whether it is genetic diseases, what you can see is that the cohort size over here, which is I'm going to point -- take you back to one of the slides that Erik showed that hockey stick curve where the number of human clinical genomes has increased exponentially using optical genome mapping. Now, Erik mentioned Bionano labs. And so I'm going to expand on it a little bit. So adoption of optical genome mapping is another key driver. Now we already had our services lab at Bionano but we now have this CLIA-certified, and we have applied for CAP-accreditation. And we have launched these LDTs. These LDTs that we have launched are to do 2 most important things: one, to support the global community. By sharing under this clear umbrella, we can accelerate and support different laboratories across the globe if they want to adopt optical genome map. The second thing is this allows us to engage with payers for coding, pricing and reimbursement. So this is really critical. What you see in the graph below is the progress that we have made in terms of global LDTs that have really come to the front in the past 2 years. And I think that this is really incredible in terms of demonstrating optical genome mapping adoption. Now one of the key questions with adoption comes out what is the reimbursement. So we have parallel paths in place that are driving optical genome mapping adoption and reimbursement. You can probably ask a few questions from a few of our panelists today. But there are multiple PLA codes, which are proprietary laboratory analyte codes. As you can see, the first one on the list is Augusta University, driven and led by Dr. Ravi Kolhe. So there are multiple PLA codes that are approved and priced. And there are some that are pending pricing determination. They are going through that process. But also, we are in the process of applying for a category 1 CPT code for optical genome mapping for both constitutional disorders or genetic diseases and cancer. And we have initiatives in place where we will be engaging with payers and different Medicare administrative contractors for local coverage determination for optical genome mapping and also with private payers, as Erik alluded to in his introduction. So we have all of these parallel paths going on in order to demonstrate optical genome mapping adoption by the genomic community. What I want to highlight with this slide is really something very simple. Around the same time last year, we had these 2 key publications with human clinical genomes that were published. And you can see the total number of patients published, roughly 400. Around the same time as of today, what you see now is over 1,000 human genomes published using optical genome mapping across constitutional, genetic disorders, and across hematological malignancies. And this is really critical -- this is really critical for the genomics community to be aware to adopt and to be able to hold to that promise that they can provide more answers to the samples that come for testing in the laboratories. So these are 4 important metrics that over the past 2 years, if we just convert them into percentages, these are really staggering. In terms of the human samples that have been run using optical genome mapping, we've seen a 600% increase. And for publications involving human genomes, you've seen a 275% increase. This is really, really significant in terms of where we are intending to go in the future. With respect to clinical utility and validity, this is really important to demonstrate that any tool or technique has the highest amount of precision and performance in any setting. And as I've shown you, whether it is a prenatal setting or a postnatal setting or a hematological malignancy setting, there are efforts that have already demonstrated or are underway to keep basically solidifying this stance with respect to clinical utility. We have global efforts ongoing with respect to investigating the health economics involving optical genome mapping. And with respect to adoption and utilization, I think you heard from Chris, the number of flowcell increase and the number of Saphyrs being placed, but in terms of LDTs, we've seen a 1,500% increase in LDTs developed using optical genome mapping. So where do we go from here? This is all the incredible amount of work that the team and the community did together to be able to come to this point. So I'm going to take you all back to the drivers that I mentioned initially. If you look at all of the drivers that are really needed and important for transforming any medical practice to include any new tool as standard of care, all of these things need to be done. What all we did in 2022 is all mentioned here. I think the critical thing for all of you to note is how does anything get included into medical guidelines. What we saw last year, and you'll probably hear from some of our panelists today is that for any technique to be recommended as first-line test in peer-reviewed publications has already started to come out. And by virtue of that, these key opinion leaders are going to play a very important role in writing consensus statements to make that global impact. We anticipate a minimum of doubling the human genomes in the next 2 years. And we also anticipate over 100 publications coming out, demonstrating the utility of optical genome mapping in genetic disorders, be it constitutional or hematological malignancies. We will establish the health economic benefits of optical genome mapping over standard of care. And the reason is very simple. If you compare everything that I have shown you, and if you go back and read any of the abstracts of these publications, it's actually a no-brainer because what you will see is 1, 2, 3, 4 first-line test or reflex test in combination, this is already going to demonstrate that. And some of the panelists today have used this model to implement optical genome mapping in their laboratories. We will also focus on meeting the key evidence requirements for payer coverage, and we are going to monitor and drive by virtue of Bionano laboratories to support and expand our LDTs globally. As I mentioned, we will be applying for a category 1 CPT code for both constitutional and heme disorders. So in the next 2 years, we anticipate and believe that there will be a code for optical genome mapping, and we will continue our conversations with payers for appropriate pricing and coverage. So I think there was a theme that we were focused on last year that Erik started the future is bright. So I hope that I've been able to show you that the future is really bright with optical genome mapping. And there is a promise to not only the cytogenetics community but the molecular community that is going to really bridge these gaps and bring the community together. So with that, thank you. Stay tuned.

Thank you so much, Alka, amazing progress. This is for any of my Board members who might be following on the webcast, we're actually ahead of schedule, which rarely happens for us. So -- at this point, we're going to take a little break, maybe about 10 minutes or so, and you can get some refreshments and then we will transition into a discussion with some of our KOLs who have come. So it's break time. [Presentation]

I want to welcome to the stage now, Dan Brennan, who many of you know [Audio Gap] and leading these discussions. He's going to talk with Dr. Ravi Kohle, who you saw as the subject of that amazing video, really delving into the detective work that people in this field do, Dr. Gordana Raca and Dr. Adam Smith, who are themselves luminaries in the field. Gordana is at Children's Hospital, Los Angeles and Adam leads one of the biggest, if not the biggest, cancer testing laboratory in Canada. And so they've been optical genome mapping users, pioneers with us, early adopters, certainly, but you're going to hear about the progress they're making, and I'm going to turn it over to you, Dan. Thank you very much.

Thanks for having me up here. Just to give you a sense of the format, so we have 25 minutes here for Q&A. And then I believe we have about another 10 or 15 minutes afterwards for audience questions, if you have any. So listen, I'm pleased to be up here. It's been a great experience getting to know the company better, although Erik, I've been doing [ HBT for years. ] So I've seen you down there, but certainly, it's been a great opportunity to go deeper for today and having spent time with the luminaries on stage with me here. So obviously, Ravi, you just heard from on the video. He's at Augusta University, and he's at the Medical College of Georgia. To his left, we have Dr. Adam Smith, who's Associate Professor at the University of Toronto. He's the Director of the Cancer Cytogenetics lab at the University Health Network [ and cheers as ] you heard during the presentation, Global Heme Group regarding OGM. And then finally, to Adam's left is Dr. Gordana Raca. She's an MD PhD. She is Director of the Clinical Cytogenomics lab, Center for Personalized Medicine at the Children's Hospital of L.A., Los Angeles. And then more extensive bios are obviously available, I believe, in the deck that the company put out. So maybe with that long introduction, I thought it would be great just even though Ravi, you had the presentation up there. Maybe just starting each of you spend a minute or 2 and just give a little background of what you're doing in your labs and facilities and maybe how -- just as an intro how OGM is fitting in.

Thanks, Dan. It was a little bit awkward watching yourself on the big screen, but it was -- this was very well done, and this was my first time seeing that. So that was also really good. I'm Ravi Kolhe. I'm a pathologist by training. I've specialized in molecular pathology and cytogenetics and also do some surgical pathology when I get time. I've been doing this for the last 10, 15 years, very early adopter for next-generation sequencing. And when OGM was introduced to me, the first thought came in is we really need to look at heme malignancies. And that's what at my journey have been. I'm a professor of Pathology. I do a lot of things, both on the research as well as the clinical side. And I am in Augusta, Georgia, the home of masters, if you are in golf.

Thanks, Ravi. Just as a brief disclaimer. My name is Adam Smith, no relation to The Wealth of Nations' Adam Smith. So that's like only finance joke. I'm the Director of Cancer Cytogenetics at the University Health Network in Toronto. I am also the system professor at the University of Toronto. And our lab came to optical genome mapping. A few years ago, we saw a presentation, I think, at AMP, and we're very excited by the technology, especially because around that time as well, we've been looking at hematological malignancies of complex karyotype and using techniques like whole genome sequencing and RNA-Seq in order to be able to characterize them more completely. So we knew that we were missing a lot of things by looking -- using these other genome-based techniques. But when we looked at the informatics pathway that was required to do that kind of work in a clinical scale, it really just wasn't practical. And when I saw the OGM presentation, I immediately went to my -- the head of our department, and I said, we need to do this now and a very supportive group at UHN, which helped us to bring it in as a pilot project and take us to the position that we're in right now. Great.

I am Gordana Raca from Children's Hospital, Los Angeles and my original training was in Medicine but then I got PhD in Genetics and further training in clinical cytogenetics and molecular testing. I worked for 17 years now in different clinical testing laboratories, last 7 years at Children's Hospital, Los Angeles. We have Center for Personalized medicine where we do integrated genetic testing for constitutional genetic disorders and oncology, all pediatric tumors. And I'm mostly involved with our Cytogenomics section, which incorporates cytogenetics FISH and chromosomal microarrays, but I also participate in case review and [sign out ] for all other tests in the laboratory. And my interest is particularly in pediatric hematologic malignancies when it comes to clinical [ signouts ] and [indiscernible] I shall research I'm involved in. I can also tell about our path to optical genome mapping maybe from my own angle. So I've just mentioned that I'm interested in hematologic malignancies in pediatric population. Those are mostly leukemias, the lymphoblastic leukemia and acute myeloid leukemia. Those are the key disorders that you have in children. And in pediatric leukemias, in particular, it's really all about structural variants, about chromosomal translocations that create fusions and then copy number aberrations. So we were really in a need for very robust technologies for structural variation detection. And to illustrate that, we were for decades doing karyotype and FISH, and we were able to maybe resolve what is the key genetic driver in about 50%, at the most 70% of the cases. So our laboratory then started adding new assays on top of karyotype and FISH just to address that gap. So we were doing Arrays on every case and NGS panels, and that got us maybe in [indiscernible] to 80%, 85% of the cases. But at least 15% of the cases that you still don't have an answer after all those 4 techniques, which was very frustrating because you are already wasting so many resources, adding turnaround time. So we were really looking for better solutions for pediatric leukemia in particular, and I first decided to do a little test and send some of our unknown cases as well as some of our knowns to a research laboratory at Bionano. And sure enough, all of our known cases, we were getting concordant results and then a subset of our known cases, unknowns were also resolved and found that critical driver. And so the stuff that I was reading about in other people's publications that you can really get the same results as karyotype, FISH and Array combined and increase your diagnostic yield on top of it. When I saw that in our own cases, it's a completely different feeling when you read about something in other people's publications and when you see it in your own cases. And when I saw that in our own cases, seeing that we can do it more efficiently with just one assay and get more answers for more high proportion of cases. That's where I [indiscernible] then started advocating within our institution for optical mapping. So that was our path to using optical mapping.

Great. Maybe just discussing sequencing for a moment. It's been presented throughout today so far in terms of kind of where sequencing fits and where OGM fits. Maybe just within your own respective labs and kind of locations, if you will. Do you see optical genome mapping today and going forward, both with short-read and long-read sequencing, like how will they fit together the -- are they mutually exclusive? Are they complementary? Could they be competitive? Maybe not as much today, in the future? Just would love to hear your thoughts on that. So maybe we can just go down the line, Ravi?

Sure. I mean as of the beginning of this year, we are clinically live for combining optical genome mapping with short-read sequencing for heme malignancies. And whatever the short-read sequencing have issues with we're able to complement with the optical genome mapping. And I think this question about with or without or on top of it, I think it's very difficult, and it goes group by group -- disease group by disease group. For heme malignancies, I think all these things which we have missed with the sequencing, optical genome is finding it. But for us, I think it's the karyotype FISH and Array is the most important aspect, which we use optical genome mapping for rather than the sequencing.

Yes. So I'm going to think from a Canadian perspective, too, we have a little bit of a different flavor because we try to keep things as cost effective as possible. I'm not saying that in any kind of derogatory way. I'm just saying that we have a limited amount of health care dollars that we can spend. And so when we looked at optical genome mapping in relation to how it compared to the standard of care techniques, we saw that advantage. There's, of course, no way -- we also need -- if you look at the guidelines, we also need the information that we get from the sequencing panels that we use. And ultimately, what we need to do is we need to drive the selection of therapy for patients. And in some diseases, like Ravi said, there are a variety of different therapy options. And the correct selection of that therapy is really done by having all the right information. So having the structural variants, having the small nucleotide variations. And that's really important. So I think that for us, we need to put those technologies together in most cases. And even in -- I think in a lot of cases, from a logistical perspective, there's a lot of diseases that we really don't handle very well in the lab, they are rare diseases because we just don't have the capacity to have all these different FISH probes and different assay set up for all these rare diseases that we don't. But OGM gives us the capacity to look at all those diseases in high resolution irrespective of what they come in for us. So it's -- from our perspective, it's a huge advantage, and it's a tool that brings equity into the lab like we haven't seen before.

So we often hear that whole genome sequencing is the ultimate test that -- you can just do that one test and get all the answers. And I would like to argue that that's not completely true. And then even when you are running whole genome and even if you are doing additional very complex at this time analysis to get structural variation from whole genome and especially in the clinical setting, you still will not get there completely. So I mentioned that we -- I will now get away from my favorite topic, hematologic malignancies. I would look at the constitutional side of our laboratory testing, where we run a lot of exome sequencing, starting into genome sequencing and then a lot of gene panels and focus what we call focused exomes. And so partial exome analysis for constitutional cases. And it really is clear that even for those single gene and [ daily disorders ] that we are trying to [indiscernible] by sequencing a large subset are caused by deletion, duplication of that gene of interest. So it became expected that you will be also looking at those events, deletions and duplications as part of your exome and genome. So sure enough, we are doing bioinformatic very complex analysis to look for those deletions and duplications from our exome and genome. And it's still very complex and it's just not robust and reliable enough to be directly used in clinical testing without some complementary, orthogonal confirmation that we think optical mapping would fit perfectly. So for every case, if we could do optical mapping as orthogonal confirmatory test for the structure variants that are still really, supremely difficult from just short-read sequencing, that would be such a powerful combination. Not only as confirmatory test that we really feel is needed for being able to use information clinically but also for stuff that's being missed, there were some beautiful cases in recent symposium, optical mappings even at Bionomics symposium, scientific symposium, which was outstanding. And some interesting constitutional cases, highlighting what is being missed from genome sequencing and exome sequencing, even when you do structural analysis -- structural variant analysis from NGS short-read data. So they showed examples of deletions that are missed in hard-to-sequence GC-rich regions, regulatory first exon. And that's where your optical mapping had filled the gap. They showed some beautiful examples of insertions of transposons. So those [ transposons ] sequences to our genome that will not align to your reference, so your short-read sequencing will be completely blind to those and those cause a subset of these single-gene disorders. So that's where I see that is complementation to genome sequencing and exome sequencing, optical mapping as confirmatory method, is something that fills those gaps where those other techniques are having weaknesses, is powerful. So I think that there is no competition. I think there is really this complementary role between the two. Not to mention my favorite, now I am going back to hematologic malignancies in pediatrics, the lymphoblastic leukemia, where there may be only out of 24 subtypes, there are only maybe 2 or 3 that are caused by sequence mutation as the key driver. All other 22 subtypes, these are translocations reading, creating fusions in our copy numbers. So clearly, structural, strong structural assay like optical mapping is clear first line for our pediatric leukemias where you would then kind of have sequencing as a second line. So yes, it's very disease specific. And if I look from my angle, for pediatric leukemias, very strong first line for all our constitutional exomes and genomes, orthogonal confirmation will be needed for a long time to come. And then those blind spots for genome and exome are beautifully filled by optical mapping.

Great. Thank you.

I think when this thing was introduced to us, we did a pretty thorough research on this, also published it. And we pretty much came to conclusion that at this given time, the short-read sequencing are just going to look at single-gene mutations and SNVs and optical genome mapping is going to do the structural variants in the clinical lab. The amount of stuff, investment and everything you would need to run a whole genome in the clinical lab to achieve the kind of promise it gets -- it's near impossible. So I mean we have put together a beautiful proposal, a pathway where you combine these 2 technologies in heme malignancies and achieve maybe 100x kind of -- 100x more information you would get from what some of those proposals are being put together for whole genome.

Great. Maybe just we've 8 minutes up in this presentation, and then we still have sold another 15 minutes after. But just give us a sense of, if you think about top down, the extent of usage that's occurring for optical genome mapping today across, say, the addressable applications at your centers, the management team laid out this $10 million sample per year opportunity. So where are you today? How early are we in that penetration curve, if you will? And what has to happen for that penetration really to accelerate?

So in my lab, we are very early adopters of whole GM. We have 2 instruments. We are nearing around 1,000 samples in different categories. We are looking at prenatal, products of conception in IVF failures, postnatal settings. We're looking at solid tumors. We're looking at cell lines. We're looking at -- but the key bulk I'm very personally interested is heme malignancies. And I think that is an area where most of the early adaptation will happen along with postnatal setting. And this is again, the adaptation is going to be a little bit different in U.S. and outside the U.S. purely because, especially in the clinical labs because of the reimbursement and the methodology we have here. But at this moment is going to be in parallel to karyotype, FISH and Array for some time until we convince the peers that this is a true alternative to those 3 technologies. And I know Adam and then the other -- my peers in Europe has already moved on from those technologies to OGM for clinical use. But I think in U.S. it is going to take some time. And I think that's where we are. We do run karyotype, FISH and then OGM plus shorter sequencing for the complete path for our key malignancies, and that's where we are right now.

Yes. So as Ravi commented, I think we have sort of a different funding package in Canada, the way we fund testing. We have kind of 2 basic systems. We have kind of what we call a global budget. So the Ministry of Health says you get x dollars to operate per year. And we have per test funding. And so we've had a couple of really exciting announcements in Ontario in the last couple of months. One of those exciting announcements was a funding package for patients with myelodysplastic syndrome or myeloproliferative neoplasm. So this is a fairly significant number of patients, maybe 5,000 to 7,000 new patients in Ontario alone that are going to be getting testing. And this is now funded testing through the government. And the government has said, you can test using legacy techniques, so karyotype and FISH at X price point or you can use an alternative technology such as optical genome mapping and still take that funding that we're offering at that price. Now for us, that price point is basically the price of an OGM as opposed to running, say, multiple legacy tests. So that's really exciting for us. So we're actually at a place now where we've launched our first clinical test this week. So we -- January 30 was our clinical launch for testing for myeloid and lymphoid neoplasms with the eosinophilia and tyrosine kinase rearrangement. Sorry, that's a mouthful. But even I don't like the name, and I work with it every day. But it's very exciting, as we replaced a very complex FISH panel with one test that has greater resolution, higher sensitivity. So that's where we are right now today. And we are working very hard in the next 3 to 4 months to bring on and transfer probably 85% of our frontline karyotyping to OGM, that's how excited we are about this technology.

So not so much to add to what Ravi and Adam said already. Here in U.S. we are little envious to our cytogenetics colleagues in Europe and in Canada because they are marching ahead with clinical implementation. What is holding us here is reimbursement. And then just recognition also by clinical professional societies and our clinicians that this is just as good, and I want to argue better than our standards -- are definitely better than our standards, which is FISH and karyotype and Array. So I think that all our -- my professional colleagues, cytogeneticists are absolutely convinced, but what is holding us back in clinical implementation is, as I mentioned, reimbursement and recognition by oncology community. And that's why I think what Alka what talking about all those clinical trials and publications that they will prove for -- prove to the payers, there are potential savings by using optical mapping rather than combined traditional technologies, and those trials will also prove that you get just as robust and better results for clinical management, those things will get us there in the U.S. So I think that many laboratories are looking into technology and getting experienced with the technology but to move it into routine clinical testing, we will have to get over those barriers.

I'll just add super quickly that I get multiple requests per week now from our clinical group. They're like, "Oh, we haven't been able to resolve this patient. Can we do OGM? Can we do OGM? So our clinical group is very excited about it.

So maybe we'll go from Gordana back this way with this question, which is like a 2-parter, which is the first part is all the technological advancements that Bionano has made and they showcased and you're obviously aware of to date and what they're promising going forward to the future? Just how do you think about what's to come your level of kind of impact, if you will? Is it -- anything really stand out, whether the throughput or the software or some of the sample prep or the informatics, things like that? Just kind of give us a sense of how meaningful that is for adoption? And then b, just thoughts on guidelines? Like when do you think there was a lot of details about all the work that's being done to get in the guidelines and then ultimately get reimbursement in really expansion? Is that something you think happens in '24, early, '25? Like where are we on that pathway? So maybe with Bionano?

No, all those updates that we've heard about today in advancement in technology are very exciting to us. I think that optical mapping technology has already got a long away from being something that only researchers were using to now being a mature solution for clinical testing laboratories. And we were able to install it and implement it in our laboratory within weeks of time. It's robust. It's reproducible in -- it is reasonable investment in equipment, and there is no need for lot of bioinformatic support, it is a full solution ready to go. So it's already mature for clinical application. And -- but for maybe medium smaller-sized laboratories. And then, of course, every ease in workflow is always welcome regardless size of your laboratory. So the advances that they were talking about today with higher throughput and it will be very exciting for this to be a great solution for larger laboratories, commercial sized laboratories. And then you see your workflows and it will be just fantastic for everybody. Excited -- very exciting about informatics solution for automated and integrated analysis between optical mapping, sequencing data and Array data that's another thing that's very important for clinical laboratories, the fewer software you need, the more integration between different assays to compare the data, they are better, they are more efficient. So I think that, as I said, over time, technology already matured to be ready for clinical implementation, but this will just take it to the next level, the updates that we heard about today.

I think for us, one of the really important things is you're looking at a few of us up here. And there really aren't that many of us, right? Scientists' time is really precious. And the software -- the interpretation software that we've been piloting the beta with Bionano is really fantastic. It's going to allow us to look at all of the structural variation data that we get off the platform and characterize it very quickly and report it very quickly. And this is absolutely unique in the space because when we look at other kinds of large-scale genome analysis, we have multiple levels of analysis. We have frontline technologist analysis, then we have a variant interpretation specialist analysis. And then we have scientists review and reporting. And a lot of that for a lot of labs is really problematic because not only is it people, but it's also various levels of software integration. So you need to take raw data, you have to move it into a package, you have to interpret. You have to take that package, you have to move to another package to report it. So there's all these steps, labs are just paying a lot of money to actually get that integration across this space. Well, Bionano is actually offering us as a solution where we run the sample, we get the data, we analyze it, and we click a button and paste that report into our clinical reporting system. So from my perspective, like as a clinical scientist with a limited amount of time, I really -- this is a super advantage for us in terms of being able to report higher resolution data, more accurately, giving better results and not actually doing -- I mean, you know what it's like to have to I'm going to cut and paste this little piece of test and I'm going to put it over here. It drives us crazy, you know. Like we know -- you know there's a better way to do it, right? There has to be -- and this is -- I've always been really, really impressed with the software integration. The visualization, even the software that we have right now with access, the level of visualization that we have of the genome and the tools that we can use to look at variances is really fantastic. It's -- so we're super excited about what's coming in terms of the software packages that are going to be released for this.

And I think the same thing. I mean, the thing to add is you have a faster DNA isolation, increased throughput and a better reporting and accurate results. So it's very rare in clinical medicine that you get all those things from the same manufacturer. It's nearly impossible. Bionano is the only company in my lab, which has all these things coming from one manufacturer. And this is very critical in the CLIA and CAP setting. And just to you an example, when we do sequencing, we do DNA isolation kit from QIAGEN, the library prep is from Agilent, the sequencer is Alumina and the analysis is PierianDx. And in these 3 -- I mean, it's all this complex supply chain issue, let's -- if I don't get QIAGEN isolation kit, which was the problem during COVID. So all the downstream of sequencing was stopped for oncology patients. If PierianDx server goes down, then we can't do any analysis and reporting. So these are the real issues in the clinical lab and having everything by the one manufacturer makes it a pretty significant difference in implementation and adaptation in the clinical space. And the other side is if something doesn't work, then we can only blame one person or one company. So that's a pretty significant advantage in the clinical space is like right now, when something goes wrong in the sequencing, we don't know it was the QIAGEN extraction kits or Agilent's library prep kit or actually the sequencer or the PierianDx software, which is doing the analysis. So you are going to see a lot more faster adaptation and implementation of Bionano purely because you're going to get a fast, quick automated DNA extraction, increased throughput, I think this is going to be the most important part of all this -- but the most -- other important, especially when it comes to me for an analysis, reporting and resulting is the software and especially getting integrated, the Array data as well as the NGS data in one software, which is a game changer for the guy who's sitting, whose signature is at the bottom of those reports. So I mean some of this thing, I didn't even know. And I'm the one who is doing OGM a lot. So this was very exciting for me personally to see the extraction, high throughput and the software piece, what they're working on.

So we've got about 10 minutes left. And I guess now is the time that either we could see if anyone has any questions in the audience, by all means, or we can keep going. So maybe we have a spotter here. I guess there's a question in the back over here.

Question about long-read sequencing technologies. And Bionano did a great job presenting the differences, the comparisons between Nanopore based and the false-positive rates, et cetera. I was wondering if you guys have looked at PacBio technology potentially? And are there certain applications where you think they might actually have some utility? Or do you think just between OGM and short-read sequencing you can cover all the bases?

The short answer is yes. So between OGM and short-read sequencing, we can cover everything as far as clinical is considered. For research, I think it's a different story. And one of the most critical factor in lab medicine especially is turnaround time. We want -- each and every day delay is a delayed treatment for the patient. If you have a cancer, you don't want to waste 20 days, 25 days, 30 days to get the results back from these bigger technologies.

I think one of the other important considerations when you look at either ONT or PacBio and we've had a little bit of experience because we ran a project with the Ontario and [indiscernible] [ super ]cancer research versus our neighbor to the -- actually the same building. So they had an ONT platform, and we had the OGM platform. We thought it would be great to compare data -- and so they said, okay, here's 10 samples, Adam. Can you give us the OGM date on this? And I said, sure no problem. About a month later, I sent them the files. That was 2 years ago. I'm still waiting for the data back on that one. It's difficult. Long-read sequencing is difficult. I don't want to -- I don't think we should underplay this from a clinical perspective. Then the other thing that I was talking to one of my colleagues about, and this is important. So we had a talk about coverage, okay. Coverage is how many times you repeat the sequence that you're looking at to make sure that you know what's going on. So you need coverage for 2 things. You need coverage because you need to have -- you need to be sure that you're detecting that thing when it's in a low quantity, for example. So if you have something that's in 5% or 10%, you need to have 200x, 300x 400x coverage, which is what OGM gives us for fixed cost per sample. So on ONT or for PacBio, it might cost $1,000 to do a genome but that genome is 30x. So then you just have to do the math. You have to start multiplying. It's not clinically feasible. It's not financially feasible. The other problem is with ONT, and the guys were telling me this, they get 30x, I got to have a technologist that stands over the cell and he's got to pump the DNA in every like 1.5 hours in order to get up to the 30x. So there are some technical pieces that they're totally solvable, I think, but currently today in the clinical space, both cost and logistically, it's not practical.

I mean I think they explained and covered it beautifully. And then also, the question is about -- in the clinical setting of detecting abnormalities that are clinically significant and make difference in clinical care. And many of the things that we haven't covered and haven't discovered by genome -- short-read genome sequencing and things like tools like optical mapping and other structural tools in the past. They're still in research arena, and we don't know how to interpret their clinical significance. So a lot of research has to happen with long-read sequencing to understand the significance of those alterations before we will be using them clinically. So completely agree with Ravi and Adam and not feasible financially, logistically and not clinically necessary and justified at this time.

Great. Any other questions right now? Okay.

Just maybe a quick one here. We talked about the importance of the health economics, especially on the reimbursement front in the U.S. and the speed in terms of what you can do. Is this something that might be an issue if you have to use it as a complement to other methods of doing the work or if you have to use it with FISH or next-gen sequencing? And so -- and then once you ultimately can use genome on its own, maybe those things get better? Or how do we think about cost and speed, if you use it with others?

So Medicare has one same part. I mean, they're not going to get any more money. Anything we go and ask, it has to replace something. And OGM technically replaces FISH and karyotype. And if you look at how expensive FISH and karyotype is for Medicare, they will be more than happy to pay us for OGM when we say that not only are we are going to give you faster, better and more information as compared to karyotype and FISH. I think we have some initial discussion. And I think having a CPT code and other things put together, this platform definitely has a potential as alternative for FISH and karyotype not only purely based on the technical aspect, which we have proven the medical necessity. We have proven the technical assessment but payers, who understand the economics a lot better than I do, they would love to jump on something like this and which they have done in the past. And I think this is the approach collectively we will have to do along with Bionano so that the payers comes on board for that. But at this moment where we are still in initial phases, you will see some complementary testing along with them to show the payers that, hey, we ran 200 cases, and these are the true prospective 200 cases where I'm showing you, look, this was karyotype. This is FISH. We didn't find much. This is OGM, we found this thing and then get the payers on board for something like this.

So I could just actually give one quick example for that as well. Not all diseases are time -- they're really time constrained. But certainly, like Gordana and I know that, d Ravi as well. All of us know that diseases like acute myeloid leukemia are really time-tested. Most of our clinicians want to begin treatment in 5 days, which means that's our time window. So what happens now is we do a karyotype type, and we try to get the result with the karyotype. And then if we need to do something else, we do it with FISH, but that means that we're not giving that full result in 5 days because we don't know before we do the karyotype, what we need to do for FISH. So we have sort of this tiered approach to testing. So the difference with OGM is that we do the test and we get pretty much everything we need right up front. We don't need to do any -- a lot of ancillary testing in most cases, for cases that we test frontline.

Thank you. Ravi, thanks for your presentation, and I tuned into your webcast, I think, last week. One of the things I think you said was that OGM detected additional clinically relevant SVs, CNVs and novel gene fusions that will contribute towards the diagnosis, prognosis and therapy selection of cancer. So I think a lot of us in this room are quite familiar with Foundation Medicine and Guardant Health in the solid tumor space. I feel like therapy selection may not have its standard of care, perhaps in hematological cancers. So maybe -- can you add a little bit of skin to the bones on this topic because I feel like oncology is a very large market. I know constitutional genetic disorders, in some cases, can be smaller markets. But maybe, I guess, what would your recommendation be to Bionano to develop therapy selection panels across hematological malignancies?

Sure. So you know how we came to this point where we are doing all this therapy selection based on these sequencing. We had the TCGA start which sequence all the tumor, solid as well as liquid. We identified driver mutations. And that's how on the other side of that, all the trials started, especially the NCI-MATCH trial. What was missing in the TCGA structural variants? There were no technology. I would wish we could get back to all those samples and do OGM on them and then create this structural variant database. Even after all this, we will still have a huge number of patients who we don't know what's driving their tumors. I think structural variants might be a group where what we have missed in the TCGA and what we have missed on short-read sequencing will add value, not only for diagnosis, we're going to make a lot better diagnosis. We're already making a better diagnosis with adding OGM. We'll make better classification. If you look at the 2022 heme classification, there is a huge list of Aves which are purely based on fusions. And I'm not going to run a 20 fusion panel just to make that subclassification. A single OGM will give you all those positives are negative for subclassification of AML. The third and important thing is prognosis. So having a complex karyotype definitely shifts the prognosis, the risk stratification for these myeloid neoplasms. And then the final would be is therapy selection. And when I say therapy selection, going back to the MATCH trial, there are very few segments in the MATCH trials which are based on fusions. And there are very few based on structural variants purely because we just don't know them. And you can't count what you don't see. So I think this is where at the beginning, where we're going to create this knowledge base of structural variants, once you get that critical mass of a few thousand cases of heme malignancy, solid tumors, we're going to find new structural variants in these categories, which we'll be defining, driving, and once you put those things together, the pharmaceutical companies are just going to find target for those structural variants especially in the fusions or even see amplification category. And then that's where you see the true revolution for target selection will happen. But for the target selection at this point, I think we are in the phase where we are really collecting knowledge on structural variants, which I personally think we have missed out in the TCGA database.

Great. Sorry. If you want to make a final comment. I think with that, we're going to wrap up this first panel because going to move to the second one, but...

I was just going to say that in the few hundred samples, we run on OGM in the past 2 years. We've detected novel fusions like a fairly significant amount. So it doesn't happen a lot, right? But it's happening like 5%, 10% of the time and a few hundred. And if you look at my lab's history, like we run 1,200, 1,300 karyotypes a year, and I can count on my hand how many novel fusions we've actually done in 10,000 or 12,000 karyotypes. So I totally agree with Ravi. This is amazing discovery that's going to drive medical interventions.

Final comment about therapy selection. So we are pediatric institution and there are even fewer targeted therapies -- classical target therapies pediatrics because something has to be tried and true in adults before they can start running pediatric trials. However, our oncologists constantly breathe down next to give them genetic results because our prognosis is critical and therapy gets tailored based on prognosis based on risk. So it will dramatically change -- their prognostic genetic marker would dramatically change their therapy even if it's not targeted therapy specifically for one particular driver, one particular drug, but the intensity of therapy gets changed all the time with the genetics. So it's still therapy is driven by genetics.

Well fantastic. What a great panel. Obviously, Ravi, Adam and Gordana, thank you. And I think we're going to move to the next one. [Presentation]

[indiscernible] fellow San Diego residents, so we really know how good it can be. That was an amazing presentation, Ben, thank you for donating your time and putting that together. It's an amazing storytelling Catherine Brownstein, who is at Boston Children's Hospital. Thank you, Catherine. And Dr. Rashmi Kanagal-Shamanna, who is at a cancer center in Houston called MD Anderson, I'm pretty sure you've heard of it. And so these folks have been working on optical genome mapping for a long time. And they're working across a diverse spectrum of applications. Certainly, Rashmi has been very active within these heme consortia, and she can talk to you about her specialties and so forth, but also in applications of optical genome mapping in the cell therapy, quality control, CAR-T and so forth that we've been talking about. So that sort of participate talk about those research applications. Catherine, we got to know because of her interest in really explaining complex cases, but then through consortium that Ravi and Alka organized around host genome response in COVID and then Ben, as you heard, is an amazing cancer biologist doing groundbreaking research. So I'm excited for Dan to bring some further insights into the research applications of optical genome mapping.

Yes, the way I look at it as an analyst with folks like this to my left, is like my job isn't to screw this up, right? We have 3 great speakers obviously. So the goal is to get the most out of this session as we can. So obviously, I'm really pleased to be leading the charge here. So I thought, although Eric just gave a nice intro and certainly, we heard about Ben back, but maybe a little bit more from each of you about explain what your roles are and maybe just touch upon a little bit how optical genome mapping maybe is starting to be used by you in your work?

Yes, absolutely. So I'm Rashmi Kanaga-Shamanna. I'm a hematopathologist and the molecular pathologist at MB Anderson Cancer Center. And I'm also the Director of the MicroArray section within the molecular diagnostic lab, which is the CLIA-certified lab. And in addition, I have a portion of my time funded by research. So I'm a transitional scientists as well where I am the lead of the hematopathology core for the AML MDS moonshots at MD Anderson. So when I first got introduced to optical genome mapping was at a vendor booth in one of the -- at the Cancer Genomics Consortium -- so that's where -- so at that time, I was kind of -- my research focus is actually myeloid neoplasms, primarily myelodysplastic syndromes, to identify underlying genomic abnormalities, to find -- to improve prognosis and then find targets for therapy. So through the AML MDS moonshots, we've like extensively characterize these disorders, right, using whole genome sequencing, using transcriptomic, proteomics, et cetera. But then majority of these cases, we don't have targets to treat these patients. And we don't understand how the disease progresses. Some patients do very well and then there are patients that progress really bad. And one thing we really didn't investigate was were the structure variants. And the optical genome map being turned out to be a great platform. Again, similar to one of the other speakers, we initially investigated just 10 cases with the help of Bionano and the amount of information we found was just stupendous. So that's how my interest started. And since then, in our lab, we've kind of performed mapping on close to over 100 patients now, just baseline myelodysplastic syndrome patients. And we recently published last year in the leukemia journal, how the data from optical genome mapping together with the targeted NGS kind of not only showed concordance, but it identified so many additional, in fact, twice the number of clinically significant abnormalities. But then again, there are tons more of abnormalities that at this time, we don't have enough evidence to show these are clinically significant, right? These are all for -- that need to be investigated in a research setting. There are -- we've identified several that are recurrent among this cohort that we are now working to see what implications these might have.

Great. Okay, Catherine?

I am Catherine Brownstein, I am at Boston Children's Hospital and Harvard Medical School. I'm the Assistant Director of the Molecular Genetics core facility of Boston Children's. So we've had a Saphyr since 2019 and run projects for academics and researchers at the Longwood area and also for industry. In addition to that, I am the Scientific Director of the Mountain Center for Orphan Disease Research. So we've been using Saphyr a lot in our -- as part of trying to solve and end the diagnostic odyssey for patients with unknown conditions where they come to us wanting answers. So we got the Saphyr in 2019. In 2018 or 2017, my then boss Louis Kunkel, who discovered the muscular dystrophy gene, DMD before the genome was even published, called me down to his office and said, "You need this," and I said, okay, he's like write a grant. And so I did. It got denied, wrote it again. Got it. And sure enough, we knew it was going to be a game changer. So -- but being 2019 and what it was, early 2020 came and it shut down everything in the lab unless you are working on COVID. So fortunately, Bionano stepped up and formed this consortium where looking at the host genome. And we are able to continue working at Boston Children's looking at MISC, the multisystem inflammatory syndrome of children and also just collaborating on the wider efforts.

Great. And Ben, I don't know if you want to just add a little bit to the movie.

A little intro and you saw most of it there. But I'm Ben Finlay, and I'm a research associate professor at Sanford Burnham Prebys in La Jolla. And I'm also the Director of the tumor analysis shared resource, and we started doing optical genome mapping in 2019. We gave 6 samples to [ Alex Pastis ] team, and they came through our lab meeting and showed it to us, and we were blown away. But we did it at the [ Optoway ] I ran to my boss and said, write a grant, but luckily as I'm Director of a core facility, we were able to use some institutional funds to get a machine and we've been running over an academic lab until from my close. But every sample we get that we run on it, I'm still blown away at the things that it finds, it's an amazing technology.

Great. So this is, first question we wrote here is a bit high level. So maybe I can ask them in a certain way. Basically, what potential do you see for OGM as a tool in discovering new biomarkers, excuse me, in applications around drug development, solving complex cases. So it's very kind of generalized. But maybe a better way to articulate it is if you could speak a little bit to everyone in the audience is familiar with a lot of different instruments and tools and technologies that are being used by scientists and pharma companies to do just that, right, to basically develop drugs and find new biomarkers. So maybe could you articulate a little bit like if we look at say, over the next 5 years, where do you think like how powerful will OGM be in certain indications for doing this? And are we in the first pitch of the first inning? Or do you feel like the community is becoming aware of the power of this technology?

I can go first. I think the community is certainly paying attention to OGM. At least that's what I gather from -- I sit in several of these guidelines meetings, and that's what I'm gathering, which I'm very happy about. So again, going back to the -- some of the data that we found, we found like things like MECOM rearrangement and NUP98 rearrangements that are -- that were completely cryptic, we missed it by karyotype. I mean, it's supposed to be [ crypting ]. NUM98, you will not be able to pick it up by karyotype by definition. And if you don't know, you don't order the FISH anyway. So these were actually we picked it up by doing OGM in retrospect. And now we are having clinical trials targeting these specific abnormalities. One of the oncologists at our institution is leading the Menin inhibitor trials. So if these abnormalities were actually detected, these patients would have become eligible, opened up an opportunity for therapy for such patients. And this is just an example. I can tell you several more that I've kind of described in the paper as well. So I think this certain -- this is kind of -- I mean, if you look at individual patients, who presents with say, normal karyotype, no abnormality and he is considered to have a good prognosis and then if it is NUP98, he suddenly skips the intermediate and goes to adverse. And if you can put him on a trial that targets this, that's like a game changer for that patient. I see a lot of potential. And the discovery is just beginning. And once more institutions kind of explore into this data, builds up, it's going to open up -- there's got to be updates in several of the prognostication, the therapeutic guidelines, all of these are going to evolve.

Anything to add?

I think we're just getting started with the price of NGS coming down so much, we're going to have a lot more people getting exomes and genomes which means a heck of a lot more negative exomes and genomes. And then they're going to be coming and still wanting answers. And I really believe OGM is going to replace karyotyping, which is expensive and slow and people don't want to do it anymore. And our kind of -- we got complacent, accepting a lot of this complex structural variation that we just couldn't capture. And now we don't need to be complacent anymore. We can delve right into it.

Yes, I'm going to agree with everything -- scientifically, academically, it's becoming really well known. But every time I show some data to an academics, they are again amazed. If I show them data from a sample they gave me, it's like you've changed their world. So optical genome mapping is the future of cytogenetics.

I'd like to add something. So the current diagnostic classification schemes that came out, the WHO and ICC -- I was involved in the development of the WHO side, and we have 32 abnormalities that are AML defining. So if the patient has low blasts, but in the presence of these 30 -- any of these 32 abnormalities, the diagnosis is upgraded to acute myeloid leukemia. So the whole theme is -- everything is genomic based. And -- and none of those 32 are mutations. I'm only talking about structure variance. So that's how things are moving. So I guess the clinical panel alluded to it that you cannot really test for these 32, you cannot have 32 FISH assays on every patient coming through. And as they also emphasize, this OGM would be a single platform, you can identify all of those and probably treat accordingly.

So maybe related to that, in terms of the pathway, Ben, even what you highlighted like on the video in terms of responders and nonresponders and eventually, you could see this becoming like your patient need to get an OGM in order to get -- put on a drug. Like what's the timetable? What has to happen? Like where is pharma do you think in this? Are they aware of the power of this technology today? And like if you look out 5 years, like what does the landscape look like there in terms of OGM being used with drug therapy?

So I think OGM is already being used in this respect, but I think we need academic scientists as you get to play with all these different technologies and you get to -- we like to think we set the bar for what's going to happen in a few years' time, but we need to actually prove that first in an academic setting and then in a true clinical trial setting and this can actually give the oncologist an extra leg up.

Anything to add on to that? So maybe I wanted to switch gears for a second. We'll come back. But I did want to talk a little bit about Cell QC because that came up during the presentation and Eric and the team highlighted it to be a really meaningful opportunity we highlighted several times throughout. So the company talked about OGM in utility and cell bioprocessing, cell therapy for genome QC target effects analysis, excuse me, genome integrity analysis. So maybe we could start with maybe Rashmi e. Just maybe provide some examples in your experience of how OGM is being used today or could be used in this area? And just how do you view the utility of OGM versus sequencing or other types of QC alternatives?

Right. So OGM, I think, has an important part to play at multiple levels. First of all, if you -- so I was -- I'm working on the CAR-T side of things, so I can speak about that. So when we kind of get the T cells from the patient and then we process these cells, put in the CARs and then put those cells back into the patient, right? So before putting the patient cells back, the alterations that might have happened could have damaged or compromised the integrity of genome. Right now, the only way that we look at it is by karyotype. But we already know that CAR-T is an amazing type of therapy, very expensive. Unfortunately, about 40% of the patients show these responses, 60% do not show this amazing response. And what might be the reason? Is it because we are injecting damaged cells back. Possibly, right, that we are not picking up by karyotype. I think OGM, considering it's high resolution and the fact that it can pick up several different types of structure variants would play a role in kind of policing that before damaged cells are in certain -- back into this already susceptible patient. And this could also save tons of cost for the patient. These patients are usually advanced-stage cancer. So if we put ourselves in their shoe, financially, it matters a lot. And secondly, I think a publication came out last year, which performed whole genome sequencing on the tumor and the microenvironment and demonstrated that the responses correlate with these abnormalities. Again, they only looked at mutations. And I believe that if we also evaluate the structural variance in these, we might come up with a few more predictive markers and that way to kind of identify biomarkers, so to speak, to predict CAR-T responses.

For us, we're a tertiary medical center. So patients are already coming to us a lot of times with exome or genome panels. And it's very hard to want to redo a genome, even a long-range genome. So OGM is a very logical next step to capture that dark area of the genome that we're missing through just looking at traditional NGS. And so also being in academics and researchers want the most bang for their buck. And so adding on OGM on top of an existing genome is a very cost-effective way to do a comprehensive analysis.

Okay. And similar to what Rashmi said, we are doing very similar stuff except with not CAR-T cells, with their close cousins, CAR natural killer cells, but it's exactly the same rationale, you take these cells. You need to make sure they're genetically fit at the start before you're going to do these very expensive manipulations. And you're inserting a gene into them. You don't really know where it goes, how many copies, what other genes have petered. And any time you either just grow cells in the lab, there's a potential for a loss of genomic integrity and optical genome mapping is just an extremely cheap, fast and sensitive way to analyze these cells. For $500, you can get 400x coverage in 5 days. And these therapies can cost in the order of hundreds of thousands of dollars. Why would you not just do $500 at the end to make sure the patient is going to get something that works.

So maybe just one more follow-up there. So in order for OGM to become more like a de facto standard today, I'm sort of labor on the world are using whether it be karyotyping or sequencing or like what do you think happens? Is it just other guidelines? Is it just publications? Just kind of what is the outlook for OGM in QC for cell therapy?

I think there is still no publications out there, definitely publications. And I think it's easier to kind of -- for the Q3 purpose, just because of the risk that we indicated, just to do a $500 assay before actually putting something back into the patient, that knowledge and awareness is going to catch on. And I think right now, there's no other assay that can identify all the structural variants. Some people have tried MicroArray but you cannot really pick up balanced translocations with it.

So maybe in terms of some of the road map, which I asked the last panel the question, but obviously, the improvement in the technology and the throughput and the price point and the ease of use and the company is highlighting a pretty aggressive road map today that they've outlined. Just talk a little bit about your use today across your labs, University and how the new technology advances, are they -- is it evolutionary -- does anything really stand out to you as maybe even accelerate usage [indiscernible] So maybe we can -- we'll go to this direction first. Ben?

Yes, sure. We use it on every sample we can get. Obviously, our initial focus is leukemia because it's easy to get samples from patients. We've done this with every patient sample we can get. We've done sarcomas, lots of [ tumor sarcomas alone ]. And every time we find sort of 40 to 80 structural variance on average that have just never been detected in a healthy human before. Sometimes there are events that have been detected in those cancers, sometimes there are events that have been checked in other cancers. And a lot of the time, these are structural variants that have never been seen before.

Catherine?

I'm not working with cancer and leukemia, but actually, the resolution of OGM has actually been a game changer and looking at the amount of structural variation in the general population and being able to accurately assess it in the ill population, sick population. I think we're just moving the needle forward in terms of accurate diagnostics and really figuring out the -- what's truly a disease-causing variant or structural variant, copy number variants from other things that are benign and just rare, but in the general population.

And anything with the new technology that really struck you today, whether it'd be software or the throughput or the some of the informatics capabilities?