CEO of Newly IPO'd Seer: For Biotech Investors, Proteins Are The New DNA

For many investors, genomics as a field is nothing new, albeit still exciting. But there's a new type of revolutionary science on the horizon, and a life sciences company called Seer (SEER -5.14%) that IPO'd in December thinks it holds the key to unlock this new frontier. 

In this Motley Fool Live video recorded on May 7, healthcare and cannabis bureau chief Corinne Cardina and Seer's CEO Dr. Omid Farokhzad talk about what healthcare investors need to know about the cutting-edge world of proteomics.

Corinne Cardina: Hi there everyone and welcome to Fool Live. I'm Corinne Cardina, Bureau Chief of healthcare and cannabis on Fool.com. Today, I'm excited to welcome, Dr. Omid Farokhzad, CEO and Co-Founder of Seer, a recently IPO-ed life sciences company in the proteomics sector. Fools, we're going to spend the next 30 minutes diving into this cutting-edge healthcare sector, learning about Seer's business, and thinking about investing in the future of proteomics. Hi, Dr. Omid, how are you today? Thank you for joining us.

Omid Farokhzad: Thank you so much, Corinne. Pleasure to be with you. Thank you.

Cardina: Let's learn about Seer. Your company IPO'd in December, then two months later you did a follow-on round of raising funds. Now, this wasn't the first company that you've founded. Could you give us a summary of your background and how you came to start Seer?

Farokhzad: Of course. I'm a physician-scientist, though I have to say the lion's share of my career has been in science and technology, technology development, and technology translation. Prior to Seer, I was a professor at Harvard Medical School, where I also founded and directed the Center for Nanomedicine at the Brigham and Women's Hospital. In the lab, the technologies that we developed together with our postdocs students in the lab in part form the basis to launch five companies, Seer was the fifth. These companies all share one common denominator and that is that they're basically all nanotechnology companies and specifically they have various different nanoparticle technologies. I think what they differ from each other is that all but Seer was focused on the use of nanoparticles to develop safer and more effective therapeutics. Seer was different in that Seer solved the massive technological hurdle for efficient sampling in a complex mixture, if you would, proteins. It leveraged nanoparticle technology to access the proteome in an unbiased way and to access the proteins across the entire dynamic range. Those two points we're going to cover later. It will become clear. That was it. That's how it started.

Cardina: Excellent. If I were going to define proteomics, would it be the study of proteins? Can you flesh that out a little bit more for us?

Farokhzad: Of course, yeah. If you think of your DNA as the software code of life, then I would say proteins are the machinery of life. They're that software code, but actually in action. They're moving, they're doing things, they're interacting with each other. If DNA, for example, does the planning, the proteins then do their doing. Virtually, every function in the body occurs either by a protein or a group of protein coming together as modules and working to perform a particular function. Does that help?

Cardina: It does. Let's talk some more about Seer's business. Can you tell us about the Proteograph product suite and how these products are leveraged by your customers?

Farokhzad: Of course. The Proteograph product suite essentially removes the technological barriers and really opens up a new gateway to the proteome. The technology allows the product, which is a combination of Seer's proprietary engineered nanoparticles, other consumables, an automation instrument that does the assay, and then a software that lets a scientist go from biological data, if you would, to biological insight. To do that, at really an unprecedented speed, skill, depth, and breadth of access to proteomic content. If you imagine, accessing the proteome can be done in a number of different ways. You can either do it in a targeted way. What that means is I know what I'm looking for, and so I'm going to go and interrogate that or it could be done in an untargeted or in unbiased way. That means that I'm going to look at the totality of the information, because I don't know what is important and what is not, and I'm going to gain biological insight. If you imagine, if you have insight already and the goal is to repetitively interrogate a particular protein or set of proteins, then targeted approaches are excellent. But if you're approaching your problem and you actually don't even know what you don't know, then you need to look at the totality of the information to actually gain biological insight, to learn the problem, to learn what's going on, and then to go ahead and interrogate it in ways that may be desirable for that particular application. Seer allows you to do that in ways that prior to Seer was just not possible.

Cardina: Great. Let's talk some more about the application. What kind of problems is this platform a solution for?

Farokhzad: Well, look. Proteins are dynamic and they change over time. The complexity of the proteome is orders of magnitude more complex than the genome. We all have 20,000 or so genes and every one of the cells in our body has the same genes. Now, proteins are different, is because as biology moves from the genome toward the proteome, additional layers of complexity is added. You go from the genome and then you make messenger RNA or mRNA, I think most people know what that is because of the COVID vaccines. That whole process called transcription produces the transcriptome and we have many more transcripts for any given gene. Some of those transcripts will then code for proteins, and so now the proteins are getting made, and then those proteins themselves can be modified after they're made in ways that's unique during a particular disease. It results in various different proteome forms or protein variants, and then those variants of proteins interact with each other in a unique way that is specific to health or disease. Virtually, every functional status that you have in your body, it is basically the result of your proteomic status at that moment in time. If you imagine a person is in the very early stages of cancer. They have no symptoms, they don't even know they have cancer, but during those times, that person's body is changing. Those changes are actually happening at the proteomic level, and so the proteomic signature of that individual is changing as that cancer is growing. Potentially long before any symptoms is even identified in that subject, if you could access that subject's proteome, you would be able to find signatures that could distinguish that cancer from health. By the way, this is not just a case in cancer, but also in diseases like Alzheimer's or other neurodegenerative diseases. Really virtually any condition of health and disease if you imagine, our proteome changes. In fact, if you just get a cold, while you're fighting that cold, your proteome will change. Studying the proteome and to be able to do it at the population scale will give us level of information that we just could not imagine. Just think of the Internet, I don't know, in the '80s. Could anyone have predicted what would happen to the Internet today back then? That's where we are in the context of our understanding of the proteome. Once you begin to have access to that totality of proteomic information, the end-markets that gets created, the treatments that become possible. Approaches to diagnosing disease will become possible in ways that we cannot even imagine today, and by the way, that's just human health. But as you imagine, every living organism, bacteria, plants, they all produce proteins, and the proteome of a plant will dictate how that plant evolves. Agriculture, microbiome, virome, all of those fields will be radically impacted once we get access to the proteome at scale, at a population level, deep, broad, and really understanding all the variance of the protein that exists. I think probably the best way to get our head around it is, remember, we've only had access to the genome in a scalable way for the last 15 years. Now, just imagine today being in the middle of the pandemic. If we didn't actually have access to the genome, how would we diagnose a disease or pick up who may be infected at a population level quick enough? How would we have even developed the vaccine? Our ability to be able to sequence quickly, efficiently, cost-effectively, really changed the world. We approach treatments of many cancers very differently today, just as the function of our understanding of the genome. Now, as important and as powerful that has been for frankly mankind to get access to the genome, the missing link to go from genotype to phenotype, to go from a software to actually function, is access to the proteome, and, I think, once access to the proteome becomes basically as common as access to genome is today, I really think the world will be a very different place, just like it changed radically in the last 15 years with our access to the genome.

Cardina: Seer's products are like a key that will unlock basically the potential of a new market that we can't even begin to describe the ceiling there. Does that follow?

Farokhzad: Yeah, I think that's an excellent way of saying good. Look, if you imagine, Seer's technology is going to allow us to begin to catalog protein variance because we begin to look at proteomic information at a large scale. Remember, we spend almost $3 billion to sequence one genome the first time around. Today, access to genome can be had for under $1,000, and $100 genome is just around the corner and not far off. The consequence of that broad access was that we've now sequenced a million genomes, over 10 million exomes. When you overlay that information together, we have identified over 690 million genetic variance at the population level, and yet, we know just a tiny sliver of what those variance mean in terms of health and disease. How does that even impact a way a person may respond to a disease? Or how is that different from one person to the other? Just take a look at our respond to their COVID vaccine. Some people do great, a minority of people don't. Why is that? The answer may actually reside in the differences in individuals in how they respond to that vaccine, and you'll get a lot of clue when you begin to look at the proteome. Seer will enable us to catalog all those variance. Those variance are going to produce biomarkers, biomarkers that can be used for disease diagnosis. Those protein variance can also become possible drug targets, approaches that we can treat diseases much more effectively because we understand which variance actually correspond to disease, and how proteins change. Those changes sometimes are as a function of that disease, and so if you can actually target the right variant that is implicated in a disease, you have a much more effective drug, and potentially, a more targeted and safer drug. I just think that the implications are enormous. As you know, just in the last few years, this whole field of liquid biopsy and early cancer detection has become quite important, and I'm so optimistic about us being able to pick up diseases far earlier when treatment can be far more effective or even potentially curative. Now, those approaches are largely enabled by access to the genome. But once you layer other annelid classes, metabolome, lipidome, proteome, the resolution of those technologies and those potential approaches to detect the disease will be substantially more, and of course, that would translate in us being more correct about who has cancer or who doesn't have cancer at an early stage, and by the way, not just cancer, but diseases like Alzheimer's and others. Again, totally transformative. I'm very excited about what lies ahead for this field of proteomic, and Seer is contributing from the front leading this area. But I think so much that is going to be possible, we just don't know today.

Cardina: What is the commercialization strategy, and when are you targeting the broad release? I'd love to hear about what clients so far are benefiting from Seer's products.

Farokhzad: We began our commercialization or the Proteograph product suite in late 2020. Our commercialization strategy basically comprises three stages, starting with the collaboration phase, followed by a limited release phase, and then ultimately culminating with broad commercial release. We're currently in the second phase or the limited release phase of our commercialization plan and in that period, we have basically lighthouse customers, and some of which will become centers of excellence. These customers will quickly demonstrate, if you would, the power and the utility of our platform and pave the way for the broad commercial release, which I expect will be the end of the year or the beginning of 2022.

Cardina: You already touched on a handful of markets that could benefit from Seer's technology. There's the obvious drug development, diagnostics, you even said agriculture. But I'd love to hear a little bit more about what other markets maybe outside of the more predictable healthcare ones might be able to benefit in the long term from this proteomics technology.

Farokhzad: Look, there is an enormous unmet need for unbiased deep proteomic at scale across a broad range of customer types. You named some, academia, pharma, translational, diagnostic, applications ranging from cataloging proteins for discovery, biomarker discovery, target identification. Really enabling even multiomics or folks that take proteomics together with other and look at complex diseases, mapping the genome to the proteome, began to look at proteogenomics, which is really tying our genomic signature to the proteomic at the functional level. Then to begin to apply these not just in human health but in ag-bio, in microbiome, in virome. Begin to for example, look at the way cells begin to communicate with each other through proteins that they may secrete. I mean, I just think that the vastness of the biological insights that will come when we begin to understand the proteome, at the depth and scale that exist in that class of analytic, if you would, I think the end markets that are going to open up and expand will just be massive. In fact, when we started Seer, we looked at it as if you would a three-pronged stool that we could build the company around. One was that we could actually create massive amount of proteomic data and so you would become a data company and there's examples of that in the genomic world. Second was that we could use proteomic content to develop, for example, medical tests. Again, many, many examples of genomic companies that went down a testing path. Then the third leg was that we could actually develop the instrumentation and enable many other scientists and clinicians to access the proteome for their own studies. In that context, we would become a tools provider and enable others to do it. Now, as we were sorting out our strategy, we actually generated a tremendous amount of data, and a part of that ended up being published in a highly respected peer-reviewed journal-to-journal Nature Communications that showed that proteomic content can be used for early detection of cancer, in this case, was lung cancer. We actually spun off a company called PrognomiQ, and we did that last fall prior to our IPO. PrognomiQ is focused on early detection using a multiomic approach of which obviously proteomic is central and core to that strategy. I actually think many other end-markets, PrognomiQ was an example in early detection, but there are many other end-markets that could leverage proteomic content. Now, we're going to enable a lot of that. In some cases, our involvement would be support, but in some other cases, if we think that an end-market needs the boost to get started, we might actually spin off other companies exactly the way we spun off PrognomiQ, and PrognomiQ is actually backed by top-tier healthcare investors. I expect that company is going to do great, just like other liquid biopsy companies have that leveraged the genomic content. I just think that according to that, the magnitude of the opportunity in the proteomics rate is huge. I would say just take a look at genomics today, anything that genomics has touched, proteomics will touch and therefore perhaps the areas that proteomics will touch, that genomic just couldn't touch, by virtue of that, just that the differences in those two analytic classes.

Cardina: Could you discuss the competitive landscape in this field?

Farokhzad: Yes, of course. If I look at the proteomics space, there are perhaps three different groups of companies out there. There are those who approach proteomics in a targeted way, and so that means that they have usually a ligand, something that binds to a protein. They could do that with a small panel, let's say one or a few or large panel in the neighborhood of 1,000 or 2,000 or 3,000 or 4,000 or 5,000. But invariably, there's a ligand that binds to a protein in a targeted way, that's one group of companies. Imagine, an average human protein is 470 amino acid long. If my fist, for example, was an average human protein, and I had a ligand, and that ligand would bind to one part of this protein. A typical ligand binds to an epitope that is about maybe 5-8 amino acid long. If this ligand binds to a protein that is 470 amino acid long, I can identify the protein. But if that protein is different anywhere else other than the binding site because of all the variance that I mentioned to you in terms of complexity of the proteome versus the genome, this ligand won't be able to differentiate them. In fact, all the variance of the same protein, if this ligand binds to it, will look exactly the same to this ligand. Now, those targeted approaches are excellent if in fact you have a ligand against the right protein and your interest and desire is to go ahead and interrogate that. If you want to gain new biological insights, then you have to look at the totality of the proteomic information. Meaning you have to study this protein at the amino acid level, at the peptide level, exactly the way we study genome at the nucleotide level. Now, when the access to large-scale genomics came through next-generation sequencing and we could add, in a very scalable way, sequence genomes or transcriptomes or exomes, the rule of targeted genomic approaches did not go away. In fact, if anything, the access to untargeted genomic approaches increased demand for targeted genomic approaches because with new biological insight, you had more things to go and interrogate. One group of companies that are the targeted proteomic companies. They are excellent if you know what you're looking for. The next group of companies in the proteomics space are detector companies, and so they will have a platform for detection of a protein. Today you can use a mass spec for protein detection of which there is about 16,000 of them installed that do proteomic work globally. But there's other detectors that are also being developed by companies at various stages of development that will look at protein and identify those protein in terms of detection in different ways. Then there is a third group of companies. That group of companies is those that look as proteomic information in an unbiased way, at speed, and at scale. That group, frankly, there is a sample size of one and that is Seer. I don't actually consider the targeted approaches to be competitive to Seer because they fundamentally answer a different question. If anything, I think our roles in the space is complementary in that if you would this enormously large addressable market, the term of the proteomic, which is in the neighborhood of 40 or 50 billion lion share of that term resides around deciphering these contents and its utility. In that regard, Seer is going to have a lion's share of what is possible in terms of proteomics. Then targeted approaches can specifically look at unique problems exactly in a targeted way as that technology allows. Now, we're also detector agnostic, meaning, today, Seer's Proteograph solution sits upstream to a large installed base of mass specs. If in the future, other detectors actually develop and commercialize and half commercial traction, meaning there's enough of them in the market, then we will then tweak the back end, if you would, of our assay of the proteograph to then sit upstream to the new detector that is yet to become available, but if that happens, then the Seer solution will sit upstream to that. Again, I don't actually consider the detector companies to be our competitor. In fact, if anything, I will consider them to be our collaborator or partners. We've already formed partnerships with three of the mass spec companies, with Bruker, with Thermo Fisher, and Sciex, because our solution works well with the detector, and as detectors become available in the marketplace, we would partner with those companies in order to broaden the reach and utility of the proteogaph product suite for our customers.

Cardina: Thank you. My last question is to bundle this all together and bringing it back for investors because, of course, at The Motley Fool, that's who we are. Over the years, healthcare investors have gotten up to speed on genomics. We've made a lot of parallels here today with genomics and proteomics. Of course, there's the B2B genomics companies like Illumina, then there's the direct-to-consumer like 23andMe. You can do your genetic testing at home. Investors who have bought these kinds of stocks in the genomics industry, a lot of them have seen tremendous returns. What should investors know about the world of proteomics, and where might you point them to learn more?

Farokhzad: Look, proteomics, and I said this earlier, today is like Internet in the '80s. There is much that it will enable as the field expands, and we can only scratch the surface in our minds today if you would. There's going to be applications and discovery. We covered that enabling pharma researchers, new biomarkers, new diagnostics, new treatments, other industries. Certainly, there's publications out there that folks can look at. You can also learn more about our own technology on our own website, seer.bio. We have a great library section on our website that offers papers, posters, videos that can take you deeper and do a deep dive in basically everything that I've mentioned, not only our technology, but really just the broader field. Also, look at some data around early detection of cancer and other applications that are possible. I think the investor community is waking up really to the potential of the proteomic space. There has been a lot of activities since our IPO late last year. In other companies that have also entered the public markets. Certainly, the investors are paying very close attention to the proteomic space and are increasingly understanding the differences between targeted approaches that some other companies are taking, detector approaches that some other companies are taking, and then the deep unbiased proteomic approaches that Seer is taking. If you think of the complexity of the proteome as we know it today, we have 20,000 genes in our body, but we're going to have millions of protein variance and proteoform in our body. If you approach this in a targeted way, you are looking at tens, hundreds, maybe a thousand or two or more proteins. But the scale that we need to be operating on is really the hundreds of thousands, the million-plus, and Seer is the one that uniquely allows that, and I think the investors are recognizing that. But ultimately, the combination of these various companies and technologies together is going to enable the broad field to hopefully have frankly a much larger impact than the others have had to date.

Cardina: Excellent. Well, Dr. Omid, thank you so much for all your time and your insights here today. I learned a lot. I know the Fools listening have learned a lot. Please keep in touch, and I hope you have a great day. Fool-on everybody.

Farokhzad: Really appreciate it. Thank you so much. Bye-bye.