1. Investment Snapshot
2. Thesis
3. Valuation & Price Target
4. Business & Product Moat
5. People & Governance
6. Market & Macro
7. Financial Quality
8. Risk Register
9. Prediction Market
10. 𝕏 Posts
Discussion
1. Investment Snapshot
2. Thesis
3. Valuation & Price Target
4. Business & Product Moat
5. People & Governance
6. Market & Macro
7. Financial Quality
8. Risk Register
9. Prediction Market
10. 𝕏 Posts
Discussion
1. Investment Snapshot
2. Valuation
Discussion
Symbol
SEER
Event Date
2020-12-04
IPO Date (Actual)
2020-12-02
Sector
Health Care
Subsector
Life Sciences Tools & Services
Offer Range
$19.00-$19.00
Shares Offered
9.21M
62.1M
$1.1B
14.8%
Implied Upside vs Midpoint
Description
We aim to enable exceptional scientific outcomes by commercializing transformative products for researchers to unlock deep, unbiased biological information. Our initial product, the Proteograph Product Suite (Proteograph), will leverage our proprietary engineered nanoparticle (NP) technology to provide unbiased, deep, rapid and large-scale access across the proteome. Our Proteograph Product Suite is an integrated solution that is comprised of consumables, an automation instrument and software. Our Proteograph provides an easy-to-use workflow, which has the potential to make proteomic profiling, and the analysis of the thousands of samples needed to characterize the complex, dynamic nature of the proteome, accessible for nearly any laboratory. We believe that characterizing and understanding the full complexity of the proteome is foundational for accelerating biological insights and will lead to broad potential end-markets for proteomics, encompassing basic research and discovery, translational research, diagnostics and applied applications. This full understanding of the complexity of the proteome requires large-scale, unbiased and deep interrogation of thousands of samples across time, which we believe is unavailable with the proteomic approaches available today. We believe that our Proteograph has the potential to enable researchers to perform proteomics studies at scale, similar to the manner in which next generation sequencing (NGS) technologies have transformed genomics. Proteins are the functional units of all forms of life. While deoxyribonucleic acid (DNA) may be used as a static indicator of health risk, proteins are dynamic indicators of physiology and may be used to track health over time, gauge disease progression and monitor therapeutic response. Despite the central role proteins play in biology, the proteome is relatively unexplored compared to the genome, particularly the rich functional content that could be derived from large-scale proteomics studies. We believe large-scale characterization of the proteome has not been feasible with existing proteomics approaches, which broadly fall into two categories: (i) unbiased but not scalable, or (ii) scalable but biased. Current de novo, or unbiased, approaches require complex, lengthy, and labor- and capital-intensive workflows, which limit their scalability to small, under-powered studies, and require significant processing expertise. On the other hand, targeted or biased methods only enable interrogation of a limited number of known proteins per sample. Although biased approaches are scalable, they lack the breadth and depth necessary to appropriately characterize the proteome and catalog its many protein variants. Thus, we believe that proteomics researchers are forced into an unattractive trade-off between the number of samples in a study and the depth and breadth of the analysis. These trade-offs limit researchers’ abilities to advance characterization of the proteome to match the current characterization of the genome. We believe large-scale proteomic analysis is needed for a more complete understanding of biology. --- We plan to initially focus on research applications for our Proteograph Product Suite and will sell and market our Proteograph for research use only (RUO). We plan to commercialize our Proteograph utilizing a three phase plan that has been shown to be effective and optimal for introducing disruptive products in numerous life sciences technology markets, including NGS. We are currently in the first phase, during which we will collaborate with a small number of key opinion leaders in proteomics, whose assessment and validation of products can significantly influence other researchers in their respective markets. Our first Proteograph was delivered to one of our first collaborators in October 2020, and we expect to place another Proteograph with a second collaborator before the end of 2020, pending any COVID-19-related delays. In consideration of our initial collaborators’ significant contributions to the development of our Proteograph Product Suite, including providing us with helpful data and feedback on our Proteograph, we have offered our early collaborators a special discount program for consumables that is not reflective of our expected commercial pricing. Additionally, we have provided these early collaborators with the ability to purchase our Proteograph automation instrument at a discount following the completion of the the first phase of our commercialization plan. During the second phase, early access limited release, which we expect to commence in 2021, we plan to sell our Proteograph to select sites performing large-scale proteomics or genomics research. We will work closely with these sites, which we expect will serve as models for the rest of the market, to exemplify applications that demonstrate the unique value proposition of our Proteograph. We expect this phase to continue through 2021 and lead into the third phase of commercialization, broad commercial availability, in early 2022. During the second and third phases, we expect to sell our Proteograph at list prices though we may offer volume-based discounts on consumables, consistent with industry practice. We believe by following this approach we can appropriately scale our operations, deliver exceptional customer experiences, foster publications and develop a robust pipeline of customers to drive our revenue growth. Challenges of Accessing the Proteome The human proteome is dynamic and far more complex and diverse in structure, composition and number of variants than either the genome or transcriptome. Starting from the genome, there are multiple biological steps that take place to arrive at the proteome, each step driving increasing complexity and diversity. The human genome of approximately 20,000 genes is estimated to give rise to 1,000,000 or more protein variants, in part because a single gene produces distinct ribonucleic acid (RNA) isoforms through the process of transcription and a myriad of structurally distinct proteins through the process of translation. Biological processes can further chemically modify these proteins in unique ways, resulting in a large number of protein variants through post-translational modifications. Overall, these processes result in many levels of protein diversity, from amino acid sequence and structural variations, to post-translational modifications (PTMs), to functional changes due to interactions between the proteins themselves, known as protein-protein interactions (PPIs). In addition, all of these forms of diversity can differ between states of health and disease. We believe the fundamental challenge with existing proteomics methods is their inability to measure the breadth and depth of the proteome’s complexity, rapidly and at scale. Background of Massively Parallel Sampling The ability to perform massively parallel sampling in biology has been transformational to researchers’ ability to perform large-scale and unbiased biological analysis. For example, before NGS, genomic approaches were not scalable to either read the entire genome or process very large numbers of samples. Researchers could only sequence hundreds of fragments of DNA or RNA at a time, and not easily in parallel. Genetic analysis was limited to biased, shallow genetic studies that were time-consuming and not scalable. As a result, researchers in genomics faced similar challenges that researchers currently face in proteomics. The introduction of NGS enabled massively parallel sampling of small fragments of DNA, allowing researchers to, in parallel, sequence tens of millions, and, through subsequent innovations, currently tens of billions, of fragments of DNA per sample. This transformative approach to sampling enabled genomic sequencing technologies to scale and created the path to genomic end-market opportunities, including basic research and discovery, translational research and clinical applications, including early cancer detection, recurrence monitoring and non-invasive prenatal testing. While there are no assurances that our Proteograph will have the same effect on the proteomics market as NGS technologies have had on the genomics market, given the utility of proteins for measuring function, health and disease, we believe the same, if not a greater, market opportunity exists for providing unbiased, deep, rapid and scalable access to the proteome. Our Proprietary Engineered Nanoparticle Technology Our proprietary engineered NP technology overcomes the limitations of existing methods and is the foundation for our Proteograph Product Suite’s easy-to-use workflow for unbiased, deep, rapid and scalable proteomic analysis. Our approach is based on proprietary engineered NPs that enable unbiased and massively parallel sampling of intact proteins across the proteome, capturing a myriad of molecular information at the level of protein variants as well as PPIs. Our NPs are designed to eliminate the need for complex workflows required by other unbiased approaches, which we believe will make proteomics more accessible to the broader scientific community. The diameter of a nanoparticle is typically in the tens to hundreds of nanometers. As a reference, the diameter of the human hair is 80,000 nanometers. When nanoparticles are placed in contact with a biological sample, a thin layer of intact proteins rapidly, selectively and reproducibly adsorbs onto the surface of a nanoparticle upon contact, forming what is called a protein “corona.” Additional intact proteins can also join the corona layer by binding directly to a protein that has already attached to the nanoparticle through PPIs and intact protein complexes may also attach to the nanoparticle directly. Our NPs’ ability to capture whole and intact proteins and their many diverse variants provides access to protein structural information, including information on PPIs. At binding equilibrium, which occurs within minutes after our NPs come into contact with the protein, the selective sampling of proteins by our NPs is robust and highly reproducible. The protein sampling and binding of proteins to the nanoparticle surface are driven by three primary factors: (i) affinity of a given protein for a given nanoparticle’s physicochemical surface; (ii) concentration of a given protein in a biological sample; and (iii) affinity of the proteins for other proteins on the surface of the nanoparticle, forming PPIs. We can use a variety of different methods and materials to design and create different nanoparticles. Each nanoparticle can have distinct physicochemical properties that generate a unique protein corona pattern and a unique proteomic fingerprint. We can combine nanoparticles into panels to provide a representative and thorough sampling across the dynamic range of the proteome, from high to low abundance proteins. In effect, the properties of protein binding to a panel of nanoparticles are functionally equivalent to, and can replace, complex, biochemical laboratory workflows for the preparation of samples for deep, unbiased mass spectrometry (MS), and which enable the capture of thousands of proteins from biofluids for large-scale proteomics studies. Virtually any solubilized biological sample can be interrogated with nanoparticles, including cell or tissue homogenates, blood or blood components (such as plasma or serum, urine), saliva, cerebrospinal fluid and synovial fluid. The versatility of nanoparticles provides the opportunity to use a vast universe of different nanoparticles with different physicochemical properties to selectively, reproducibly and deeply sample the proteome in an unbiased way. --- Our NPs enable the unique capabilities of our Proteograph Product Suite, including the ability to: • eliminate complex biofluid processing workflows required by other unbiased proteomic approaches; • sample in an unbiased manner across the dynamic range of the proteome in a variety of biological samples, including cell or tissue homogenates, blood or blood components (such as plasma or serum), urine, saliva, cerebrospinal fluid, and synovial fluid; • identify and distinguish protein variants at the peptide level; • identify and quantify protein variants and PPIs; • use machine learning to design, synthesize and select different NPs and NP panels to create multiple products and applications; and • be compatible across a wide range of laboratory workflows, automation equipment and sample processing and detection methods, lowering the hurdle for product adoption. --- We were incorporated in Delaware on March 16, 2017, under the name Seer Biosciences, Inc., and changed our name to Seer, Inc. on July 16, 2018. Our principal executive offices are located at 3800 Bridge Parkway, Suite 102, Redwood City, California 94065. Our telephone number is 650-543-0000. Our website address is www.seer.bio.
Seer, Inc. annual income statement and balance sheet, FY 2020 to FY 2025, as reported in SEC filings.
| Metric | FY 2020 | FY 2021 | FY 2024 | FY 2025 |
|---|---|---|---|---|
| Revenue | $656K | $6.6M | $14.2M | $16.6M |
| Gross profit | $656K | $3.4M | $7.1M | $8.5M |
| Operating income | ($33.6M) | ($71.5M) | ($100M) | ($78.0M) |
| Net income | ($32.8M) | ($71.2M) | ($86.6M) | ($73.6M) |
| Metric | FY 2020 | FY 2021 | FY 2024 | FY 2025 |
|---|---|---|---|---|
| Total assets | $442M | $539M | $367M | $296M |
| Total liabilities | $10.7M | $36.2M | $39.0M | $36.8M |
| Total equity | $432M | $503M | $328M | $259M |
| Cash & equivalents | $334M | $233M | $40.8M | $47.3M |