Khosla Ventures Acquisition (KVSA)

Filed: 8 Nov 21, 4:43pm

Filed by Khosla Ventures Acquisition Co.

Pursuant to Rule 425 under the Securities Act of 1933

and deemed filed pursuant to Rule 14a-12

of the Securities Exchange Act of 1934

Subject Company: Khosla Ventures Acquisition Co.

Commission File No. 001-40131

Chris Katje: Joining us on SPACs Attack we have David Berry, the founder and CEO of Valo Health company merging with Khosla Ventures Acquisition ticker KVSA. David, welcome to SPACs Attack.

David Berry: Chris, thank you. It’s a great pleasure to be here.

Chris Katje: Awesome! Well, David, we’re so excited to have you on the show. One of the first questions we always like to start with here on SPACs Attack is why the decision to go public via SPAC for Valo Health? Was a traditional IPO also considered by your company?

David Berry: Chris a great question. We did think about the opportunities of going public by a standard IPO as well as that with a SPAC and in the framework that we’re in, going public through a normal course IPO is of course the normal course thing that we would do. But what we saw in the context of KVSA was an opportunity to create a true partnership and one that would bring forth more durable value for the company. And I say that because of course, Khosla as a firm is incredibly well known, incredibly well respected in the context of the tech world, in the investments that they make, in the opportunities to transform industries and that’s exactly what we’re trying to do. But more so, we’ve had deep relationships historically, I’ve known Samir and Vinod for 15-20 years. That I think creates for a great working relationship and a deep trust and relationship which I think is very important. But the other piece of this is that I think anytime one wants to consider a SPAC transaction, there has to be fundamental alignment. And that is the case here because what’s in this bag is first an absence of warrants. Second, a tiered promote structure such that the economics really come into play for Khosla when we’re getting above $30 a share and that is 3x times the merger value. So that creates a much more intrinsic alignment here and speaks to the speaks to the framework of delivering long term value on behalf of shareholders, which is what we’re all really aligned around and of course on top of that, they have a longer than market a longer than market lockup. So again, they’re indicating to their mark to the market, their real commitment to the value we’re all looking to create together.

Chris Katje: Perfect, yeah. We always like to talk about yeah, the lack of expiration, so nice validation there by Khosla, you know, to have that longer lockup, definitely great of you to highlight that, David. So for viewers out there who aren’t familiar with Valo Health, the company is building a fully integrated end to end human centric artificial intelligence driven drug discovery platform. Tell us what does this mean? Those are some great words there. But tell us you know, what, what is the company? What do they do for anyone not familiar with Valo out there?

David Berry: Sure. So let me touch on a couple pieces of this. First and foremost, when we think about how drugs get created, outside of rare exceptional cases, they these this is a process that takes 12 to 15 years, but more importantly, it takes 10, 15 odd steps that involve various clinical trials, a set of things that are done preclinically and the problem with it is it’s actually been created into this disintegrated framework. That is, each of these steps is done by a different set of people with a different set of data. There isn’t a connection between the metrics of success are not aligned and they’re not all aligned towards delivering a drug that ultimately that ultimately benefits a patient. They’re focused on how do I advance through this step? And what we saw as the opportunity in around 2018, 2019 was, for the first time, the scale of human data was just becoming available. When I say human data, what I mean is clinical data how peak patients have responded to drugs, what happens in the course of disease, the sort of stuff that a doctor would collect in normal course, the scale and density of that data was just emerging to the point that we can say, you know what, it’s now time to build a new model of how drugs are discovered, and how drugs are developed. And that’s what we set out to do. And what we the way we’re looking to do this. And what we’ve been working on is using human data at each and every step of

the drug discovery and development lifecycle but doing it in a framework where we’ve created an integrated model, a vertically integrated model. That is, it’s aligned, we use the same sort of computational tools. But again, we’re bringing this to bear because ultimately, we’re trying to develop drugs for people, and we’re trying to do it in a way we can do it at lower cost, and we can do it faster. And that’s really important because ultimately, when I went through medical school we were told there are about 13,000 or so diseases. The number of drugs that the FDA has approved thus far, is only about 1,500. And many of them are being developed for the same disease several times over. So when you think about the number of untreated maladies that are out there, it’s enormous. The only way that we can start changing our interface with disease is to fundamentally change the way that drugs are developed. And the reason I get into this is because right now, mice cells, extracted from people put on plastic, that’s what you what’s used in the standard to develop drugs. And one could argue, it’s no wonder that there’s a 95% failure rate in clinical trials. Arguably, it’s one in 4000 through the lifecycle of a drug by using human data and using computation across we think that there’s an opportunity to fundamentally transform that probability of success by bringing forth confidence in that drug earlier on making sure we’re developing it for the patient in the first instance, and doing that in a way where ultimately the benefit that we think we can deliver can ideally have a transformative benefit to those patients.

Chris Katje: Awesome. So Valo has the Opal platform and one of my favorite slides from the SPAC merger presentation is Slide 14, which lists four words, build, validate, scale, and democratize. So right now currently in the build and the Validate phase, can you talk to us a little bit about build and validate and also how Valo will push forward into scaling and democratizing the business model going forward?

David Berry: Sure. So, of course, the first thing we set out to do was to build our Opal computational platform. And our Opal computational platform uses large scale human data. In this case, we have data from over 8 million patients where we have a unique framework of this data, because what we have is comprehensive data for about 15 years on this these patients with which with what’s called a zero or near zero, missing rate that is, it’s complete data and includes not just say a medical record, but it includes lab tests and images, and tracings like EKGs and EEG measurements of the heart in the brain and things along those lines. And that’s really exciting because it allows us to get deep insights into what’s happening over the course of a disease in a person. Now by using that in the context of a single platform that does things like uncovering what is the way to intervene in a disease, in what patients at what time in that disease, that helps us figure out what to develop drugs against. Then we have engineering systems that allow us to develop small molecules in particular, but other things as well, where and ultimately the benefit of small molecules is these are the sorts of drugs you can take at home. You can take them as a pill as opposed to say, an injection in the eye or an infusion for 12 hours.

That makes it more likely that a patient’s actually going to be able to take their drug and benefit from their drug. But when we make these small molecules, we have we do it in a closed loop fashion. Think of it as an engineering system that brings tremendous efficiency in the speed by which we’re able to develop them. And we have tools that allow us to predict what might happen with that small molecule in the clinic. I.e. can we predict is it going to be safe or toxic? is where is it going to go in the body? How is it going to move around? And then we have tools that we’ve been developing that allow us to figure out what are the right patients for whom it should go into? what is the right time for us to give that drug? Think of these as so called biomarkers and with all of those tools the opal computational platform allows us to do all of those steps of drug discovery and development. So in the first instance, we’ve been focused on developing the capabilities. In the second instance, we have a pipeline of 17 drugs thus far, and we’re using those drugs that we’ve been developing to validate our capabilities. Of course, we’ve done all sorts of computational validations thus far and have a reasonable confidence in what we’re

bringing forward. But we have, for example, a lead drug OPL 301 that we expect to enter a phase two clinical trials later this year, another one OPl 401 will enter phase two clinical trials next year, followed by another 15 preclinical molecules. And what we’re doing in the context of validation is the advancement of that pipeline, which is a significant size pipeline. Now ultimately, the power of the computational platform that we’re building, especially because it’s driven by a flywheel where every time we do something, we get data, it flows back into our, into our computational platform. It allows us to learn, it allows us to get smarter, the scale by which will ultimately be able to execute, we think becomes tremendous. And that has the potential to progressively increase probability of success, reduce cost and reduce time. And even though drug development happens to be expensive, we think there happens to be this opportunity to make a market difference, but the bigger and the biggest impacts that we can have, are not just doing it within our four walls. And what we expect to do is to start to externalize the capabilities that we have in very targeted ways and do that systematically. But ultimately, as the efficiency of our capabilities within Opal get high enough. We think it allows us to open up an opportunity to democratize drug discovery and development. If we want to tackle 13,000 diseases, and potentially more than get discovered as tools become more plentiful. Then we need to be able to open up these in a way where people can actually start developing drugs to the various ideas that that are out there and not rest on a single company to have all of the ideas and we’re very excited to be the engine that allows for that transformation. Because ultimately, the calling that I think brings us all here is we want to transform disease. We want to transform it for the benefit of patients for the benefit of their families. And we want to create the tools that allow people to be able to do that.

Chris Katje: Perfect yeah, you hit on a couple of the drugs in the pipeline. That was going to be my next question. So let’s go right there. There is a slide in the presentation. You know, that breaks down some of those drugs in trial. So your two most advanced looking towards phase two. Can you just give us you know, an update on you know, maybe the timeline of some of these trials. When can we expect to hear more about these lead candidates and how do they all fit into the timeline once Valo completes the SPAC merger?

David Berry: Sure. So first, our most advanced on this are the first to enter the phase two trial is OPL 301. This is a therapeutic candidate that we’re developing for what what’s called left ventricular dysfunction, post myocardial infarction, which is a very fancy way to say we’re trying to treat what happens after a heart attack. And I mentioned that because what’s important to us is to go after diseases that matter, diseases that affect patients, diseases that frankly, without change, kill people, rip apart families, and we want to be able to impact that kind of change and do it in a meaningful way. And it’s in this spirit we’re making, we’re trying to make impactful drugs. Now this drug, this drug candidate is on track to enter phase two clinical trials this year. We expect to have interim data come out sometime, most likely by the by the end of next year. But that but the clinical trial is, will continue to be in progress along those lines thereafter. OPL 401 is going after diabetic retinopathy in the first instance and diabetic complications as the following. Diabetic retinopathy is the loss of vision that occurs as a side effect or complication associated with diabetes, but there’s other such complications as well, which include neuropathy, which is where diabetics lose feeling. It’s, there’s a cardiac apathy or cardiomyopathy, where the heart starts to have problems functioning and of course, nephropathy, which is what affects the kidney, and these cause significant morbidity challenges in diabetic patients. Now, right now, in diabetic retinopathy. There’s about an $8 billion market that exists that’s mostly met by drugs that are injected into the eye that are only really given to patients who have severe disease. And what we’re doing here is we’re developing a small molecule that we believe will be capable of being consumed orally, i.e. a pill, being able to get into the eye and have a significant benefit for diabetic retinopathy. And in that context, we think that opens up the opportunity to not just treat patients with

severe disease, but catch them earlier. Catch them when it’s still mild to moderate catch them while they’re still keeping certain amounts of their vision. And we think that can be something that’s very powerful, but also by not requiring an injection into the eye. Patients are likely to be where we believe we’re more likely to be willing to take these kinds of therapeutics and that one, we expect to enter a phase two clinical trial next year. And behind that, of course, we’re going after a whole series of different therapeutic candidates across cardiovascular disease across oncology across neurodegeneration, and really excited about the potential of what these drugs might be able to do for patients across a whole spectrum of very important diseases.

Chris Katje: To clarify on the pipeline here, so these are all wholly owned drugs for the company any chance of you know partnerships down the road to bring these to market or is the plan to you know, go 100% of Valo right now?

David Berry: Sure. So we are developing these right now. Our view is we have capabilities that are vertically integrated. We can do target discovery, we can make the drugs and we do our own clinical trials. We’re not dependent on the on partners to do clinical trials. And in that context, we’re really bringing together tech and life sciences and we see ourselves as having that opportunity to use technology to transform the way we discover and develop drugs. But it’s really important to own that value chain internally. Because unless you actually do clinical trials, you may not actually appreciate the nuance of what it takes to do it well, you may not get the right data and in this way, we think we have better control over our destiny, and have a better chance of delivering a better impact for patients, but also in delivering drugs that can be more valuable over time, drugs that can help us learn better and help us to drive the flywheel at the core of the Opel computational platform.

Chris Katje: Perfect. We talk a lot here on the show about TAM, total addressable market. I want to get into you know, Valo’s opportunity going forward. Obviously, we know that biotech space is a trillion dollar plus market. Can you just break down a little bit of maybe the targeted tam for Valo, you know, over the next 5 to 10 years and you know, broadly in the future.

David Berry: So first, of course the healthcare market and even the subset that is just drug discovery and development is an enormous market and and there’s many, many drivers for this. But a big part of this is that the drug discovery system, the model that exists has set itself up, I believe to be ripe for disruption. And that’s really because we’ve seen R&D productivity decrease across the board we’ve seen pricing pressures, we hear about this in Washington, probably on a daily if not weekly basis. And a lot of that stems from the model that is behind drug discovery and development. And I just want to flag this because when we look at the history of how drugs have been developed, right the beginning of biotechnology was this notion where you might find one protein that’s associated with one disease. And if you go and make that protein, you can make a new drug and companies like Amgen, and Genentech. were delivered out of that. Now, more recently, we’ve seen what I like to call integration and that’s where engineering systems have been used in local parts of the drug discovery and development value chain. And we’ve already seen the benefit of that because in the context of the development of the COVID vaccine, technologies that build off this digital integration, were deployed and we’ve seen in a very short period of time, multiple vaccines developed from a standing start to in billions of patients in two odd years. And I think that really comes down to digital integration. What we’re doing is creating a digitally native, vertically integrated capability, which is bringing this technology core with a data driven flywheel across the way we think about drug discovery and development, at large. And we’re deploying it in the first instance, in cardiovascular disease, oncology, and neurodegeneration, which are probably three, the three if not three of the biggest therapeutic areas from a value perspective. We see this as an

opportunity to elicit this kind of transformation, as we think about pharmaceutical discovery, broadly. So our interest is not just developing a pipeline internally. And that goes back to one of the slides that you referenced, which is we’re developing a pipeline in the first instance because it allows us to validate our capabilities. But we want to scale well beyond that. We want a scale where we can have impact in the way that the industry develops the drug and become the technology underpinning of the future of the industry, ultimately with a goal of democratizing so we’re very excited about how we might be able to reach well beyond our four walls, and think about something that can transform the market at large. Think about how we can transform drug discovery and development at large and reach even beyond over time. The three therapeutic areas that we’re focused on.

Chris Katje: Perfect and along that same lines, you know, is this something where Valo would license out its technology and be able to monetize that with other companies using it down the road?

David Berry: So that’s exactly the way we’re thinking about this, which is in the first instance we focused on our own drug discovery and development internally. But we’ve been developing approaches and tools such that we can externalize it through licensing and other such models and enable others. But in this way, it’s important from our standpoint to maintain a closeness in with our customer in the way that we ultimately use our models because ultimately, our models are learning models. And the more we’re working together, the deeper value we can collectively create, the better impact we can have for patients. And this is where it gets interesting from my perspective, because again, each and every experiment that we do, we’re taking the data, we’re putting it right back into our capability set in the way drugs are developed today. Data is captured, whether it’s on a clinical trial or something in a lab, and it’s put in a notebook, and it stays there. That ability to learn collectively does not exist. Let me just put that into a different perspective. When we do experiments, we can get data that in certain cases can be orders of magnitude larger than are captured by others who might think about a traditional approach. And so when we think about the way we can work with partners, embracing that learning approach, delivers a real benefit to us and our partners. And it’s really important to make sure we have that alignment.

Chris Katje: Along with going public via SPAC you will get some additional capital, which it looks like you know what continue to fund that pipeline of existing drugs that you have. My question is, you know, any opportunities for M&A down the road, whether it’s acquiring, you know, drug targets, or maybe getting into new verticals, or is the plan to just keep building on what Valo has built over the years?

David Berry: So first, we our heads down, focused on building Valo to become in the first instance, the first digitally native, vertically integrated pharmaceutical company and then in the second instance, the technology underpinning of the industry. And we’re really focused on that we’re not focused on M&A. We don’t believe in the historical biotech model that is, build this to a certain point and then just turn it over. Because this is really a technology company that happens to be in the drug discovery and development industry. And it’s with that spirit that we want to make sure that we’re living up to that ethos. So from that perspective, could we get approached by a pharma company who wants to acquire one of our drugs? Sure, could we get approached by someone over time who’s interested in M&A? Sure, but our focus is we want to deliver we want to build we want to create a company that has this lasting and durable impact.

Chris Katje: Perfect. Well, David, this has been great, great insight into the company. The questions in the chat are mostly about partnerships and it seems like you’ve answered that you know, a lot of people out there want to know, you know, will Valo partners with Palantir will they partner with you know, leading drug companies, what’s to come? So my guess is that you’re not able to dive into any of that today, but maybe we will hear more about you know, some potential partnerships down the road it would that be correct.


David Berry: We’d absolutely love to talk about talk about where we’re going on the partnership fronts. Down the down the road. Of course, the substrate that we build drugs is exactly what pharma companies want. The technology structure that we’re building, the technology stack that underpins the open computational platform is unique, dealing with health data, dealing with human data requires a different form of computation. And that’s something that I have to imagine the technology companies broadly are very interested in, because it’s not just applying your standard form of compute, and hoping that you can get into yet a new industry. This is something that requires a dedicated focus and we think we’ve put that in and we’re very excited about that. The framework that we’ve built thus far.

Chris Katje: Awesome. Well for everyone out there in the chat again joining us on this back to pack David Berry, the founder and CEO of Valo Health company merging with Khosla Ventures acquisition current ticker KVSA. David, thanks so much for taking time out of your busy schedule, and we look forward to hearing more about your company in the future.

David Berry: Well, thank you, Chris. Really appreciate and looking forward to continuing the conversation.