Seer, Inc. 10-K

Item 1. Business Overview Our mission is to imagine and pioneer new ways to decode the secrets of the proteome to improve human health. Our initial product, the Proteograph Product Suite (Proteograph), leverages our proprietary engineered nanoparticle (NP) technology to provide unbiased, deep, rapid and large-scale access to the proteome. The Proteograph Product Suite is an integrated solution that is comprised of consumables, an automation instrument and software. 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 and its dynamic nature 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 the Proteograph Product Suite has the potential to enable researchers to perform these proteomics studies at scale. Proteins are the functional units of many biological processes and dynamic indicators of physiology that can gauge health over time, inform disease progression and monitor therapeutic response. Despite the central role proteins play in biology, rich functional content derived from proteomics studies is relatively unexplored compared to the genome, since large-scale proteomic studies have not been possible. 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 that limit their scalability to small, under-powered studies. Targeted or biased methods enable interrogation of a limited number of known proteins per sample. Although targeted approaches are scalable, they lack the breadth and depth necessary to appropriately characterize the proteome and catalog its many protein variants. Therefore, 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 the ability to advance characterization of the proteome to match the characterization of the genome. We believe deep, unbiased, large-scale proteomic analysis is needed for a more complete understanding of biology. We are initially focused on driving adoption of the Proteograph with customers in the proteomics and genomics markets, with those researchers who recognize the value of large-scale, unbiased, deep proteomics. Allied Market Research estimates the proteomics market was $32 billion in 2019. We believe that the Proteograph’s unique capabilities will enable researchers to undertake unbiased studies not possible today, particularly those of larger scale, and will complement genomics studies by adding critical missing information that can provide functional context to genomic variation. According to the dbSNP database, over 1 billion individual genetic variants have been identified to date; however, fewer than 0.2% of those variants have been cataloged in the ClinVar database with a reported relationship between variation and phenotype. We believe unbiased, deep and large-scale proteomics will help researchers map biological function of genomic variants, identify impactful disease and response-specific risk factors, and accelerate discovery of molecular mechanisms of health and disease. We believe these capabilities should broadly appeal to researchers and entities undertaking large-scale genomics studies and should attract spending from the genomics market, estimated by Technavio to be $21 billion in 2019. In addition, we believe the Proteograph is likely to enable novel content discovery that will lead to entirely new applications and market opportunities. We are initially focused on research applications for the Proteograph Product Suite and are selling and marketing the Proteograph for research use only (RUO). We commenced the third and final phase of our commercialization plan with broad release in January 2022. 1 The Importance of Proteomics Detailed and complex biological information resides at the protein level. Virtually every function within a living organism occurs by the action of a protein or a group of proteins interacting with each other and in concert. Thus, proteomics is a key area of focus for researchers. Proteins are dynamic indicators of health status and can be used to monitor disease progression and therapeutic response. By contrast, the genome is a static indicator of what a person’s physiology could be, not an indicator of current physiological state. In short, the genome represents risk, while the proteome reflects status. Despite the physiological impact, the human proteome is relatively unexplored compared to the human genome. Through large-scale data collection and widespread adoption of molecular profiling techniques, over one billion genetic variations have been identified across all genomes that have been sequenced. Although this information has significantly improved the understanding of biology, the functional context at the protein level has not been established for the vast majority of this genomics information. In other words, researchers have not been able to connect phenotypic information with the relevant genotypic information. We believe that if we enable researchers to generate large bodies of proteomic data that can be coupled with large bodies of genomic data, they will be better positioned to understand the relationship between variation and function and its impact on biology. Challenges of Accessing the Proteome The human proteome is more dynamic, diverse and complex in structure, composition and number of variants than either the genome or transcriptome. Starting from the genome, multiple biological steps take place to arrive at the proteome, each step creates increased complexity and diversity. The human genome has approximately 20,000 genes, which are estimated to give rise to more than 200,000 transcripts, which then give rise to 1,000,000 or more protein variants. As shown in Figure 2, this is 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 2 (PPIs). 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. Limitations of Targeted Approaches to Proteomics Unlike DNA, the structures, chemistries and concentrations of proteins in any given sample are widely variable. Proteins also lack a direct amplification mechanism, which creates technological challenges for identifying them at low concentration. Given the diversity of protein structures, coupled with the lack of a common amplification mechanism, researchers often use analyte-specific reagents (ASRs) to measure proteins. ASRs are ligands, such as antibodies, that have been designed to bind to specific areas of proteins, and therefore, involve a targeted or biased approach. This targeted approach is limited in that ASRs do not have the capability to interrogate the entirety of the protein structure of the molecule that they bind to and may not distinguish important protein variants. The average length of a human protein is approximately 470 amino acids, whereas the average binding site of an ASR is an epitope with a length of five to eight amino acids. ASRs may not recognize differences between proteins outside of the epitope binding site and, therefore, may not differentiate among protein variants, as demonstrated in recent publications including Pietzner, M. et al . ASRs and other biased readout technologies are not optimal for discovery given the inherent complexity of proteins. A large number of ASRs can be designed to detect a large number of different proteins, but this approach is limited in its ability to measure new protein variations. Targeted approaches, in general, are useful when the scientist or clinician knows what is being analyzed. This is analogous to the role of microarrays in genomics, where a specific DNA fragment is used in a targeted or biased manner to confirm the presence of a specific mutation, or a single nucleotide polymorphism (SNP), whereas NGS employs an unbiased approach to interrogate the breadth of content in the genome. With an unbiased approach, as one scales the number of samples in a study, one inherently assays a broader set of novel content. With targeted approaches, regardless of the number of samples in a study, one will not gain any additional novel content beyond the specific targets of the assay. Limitations of Current Unbiased Approaches to Proteomics Rather than interrogating proteins at the level of predefined epitopes, unbiased approaches can interrogate proteins at the peptide level, providing amino-acid level resolution to protein variants. However, current unbiased approaches do not scale well due to vastly different protein concentrations in plasma samples. Plasma protein concentration, for example, can span ten orders of magnitude from abundant proteins like albumin to some of the least abundant proteins, such as cytokines. The top 22 most abundant proteins account for approximately 99% of the total protein mass in the plasma, yet the many thousands of less abundant proteins comprising the other one percent of the total proteome by mass have significant impact on biology. Therefore, it is critical to be able to broadly and deeply detect proteins across the proteome, including those proteins that appear in low concentrations in plasma. Mass spectrometry (MS) is a broadly used technique for detection of proteins and their variants for unbiased discovery, basic research and clinical applications. Given the wide dynamic range of protein concentrations in 3 plasma and other biological samples, current MS methods for protein detection often require complex sample preparation workflows that involve depletion of abundant proteins and grouping remaining proteins and peptides into smaller units through fractionation. We believe current unbiased approaches in complex biosamples with a skewed dynamic range (e.g., blood plasma) are not widely adopted by researchers because the workflows are extremely complex, the process is expensive and the time required to complete such analysis is significant. As one example of these complex methods, in a paper from Keshishian, H. et al. , the researchers first depleted the most abundant proteins with immuno-affinity columns and then separated the remaining proteins by many subsequent and complex chromatographic steps and mass spectrometer injections. The study identified 4,500 different proteins across 16 samples, taking multiple months to complete. A critical unmet need in proteomic analysis remains how to collect unbiased proteomic data on thousands of proteins in a sample spanning more than ten orders of dynamic range in concentration and to repeat this across thousands of samples in a reasonable amount of time and cost. Genomics faced a similar unmet need before the advent of NGS, which allowed for massively-parallel sampling. Importance of an Unbiased Approach in the Discovery of Novel Content The ability to perform unbiased sampling of content at scale in biology has been transformational to biological analysis. 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, genomics researchers faced similar challenges that researchers currently face in proteomics. The introduction of NGS enabled unbiased analysis at scale of small fragments of DNA, allowing researchers to, in parallel, sequence tens of millions (currently tens of billions) of fragments of DNA per sample. This transformative approach to sampling enabled genomic sequencing at scale and enabled the discovery of novel content. The discovery of novel content created the path to genomic end-market opportunities across 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 the Proteograph Product Suite 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. Figure 3 illustrates the concept of increasing content discovery with an unbiased approach as sample cohorts increase in size. Importance of Peptide-Level Resolution in the Understanding of Biology We believe that peptide-level resolution will be critical to the discovery of novel content and new biological insights. As one example, using data from our Nature Communications paper, we identified several biologically-important novel cancer biomarkers at the peptide level that would have been missed if we had only focused on overall protein expression. One of those biomarkers, Bone Morphogenic Protein 1 (BMP1) has been reported to 4 have a dual role in cancer, but the biology is not well understood. Figure 4 below demonstrates how BMP1 at the protein level ignores the variants of BMP1, showing no apparent difference in the overall expression pattern of BMP1 between cancer and healthy subjects. If one has resolution at the peptide level, individual variants of BMP1 can be seen. It is possible that these findings may help to explain the dual role of BMP1 in cancer. This insight is enabled because an unbiased approach is able to identify peptide sequences at the amino acid-level. Our Proprietary Engineered Nanoparticle Technology Our proprietary engineered nanoparticle technology overcomes the limitations of existing methods and is the foundation for the 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 sampling of intact proteins across the dynamic range of the proteome, capturing a myriad of molecular information at the level of protein variants as well as PPIs. Our NPs 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 a 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 encounter the protein, the selective sampling of proteins by our NPs is robust and highly reproducible. 5 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. A variety of different methods and materials are used 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 believe the growing body of proteomic data coupled with advanced machine learning will allow us to continue to enhance the unique physicochemical properties of our nanoparticles. 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 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, across a broad range of sample types, to selectively, reproducibly and deeply sample the proteome in an unbiased way. The figure below illustrates the dynamic range of the proteome with high abundance proteins in the upper left of the curve and low abundance proteins in the lower right of the curve. Each of our unique nanoparticles has different physicochemical properties, which allows it to sample selectively across the breadth of the proteome. 6 Our NPs enable the unique capabilities of the Proteograph Product Suite, including the ability to: • eliminate complex 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; • 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 have validated our NP technology and the principle of protein corona formation as a robust and reproducible method to deeply and broadly profile the proteome in a high-throughput manner. In our publication in Nature Communications (Blume et al.), we demonstrated a rapid, deep and precise profiling of the plasma proteome with our proprietary engineered NP technology. The Proteograph Product Suite Our proprietary engineered NP technology forms the basis for our first product, the Proteograph Product Suite. The Proteograph is an integrated solution consisting of consumables, an automation instrument and software to perform unbiased, deep proteomic analysis at scale in a matter of hours. We designed the Proteograph workflow to be efficient and easy-to-use, and to leverage broadly used laboratory instrumentation to enable adoption in both decentralized and centralized settings, making deep, unbiased proteomics accessible to nearly any lab. The Proteograph consumables consist of our NP panel and all other consumables necessary to assay samples in an automated workflow on our SP100 automation instrument. Our automated workflow is custom configured for researchers to assay samples in approximately seven hours, which includes thirty minutes of hands-on time and six and a half hours of automated instrument time. The output from the Proteograph workflow is peptides ready to be processed on an MS instrument. The Proteograph Product Suite is detector agnostic and, we believe, will be adaptable to other protein detection instruments in the future. The MS component of the Proteograph workflow is either provided by the researcher’s laboratory or can be outsourced to a third-party provider. We estimate that there are approximately 16,000 MS instruments with configurations typically used to perform proteomic analysis installed worldwide and, therefore, we believe that MS systems are readily accessible by researchers. The Proteograph Analysis Suite, a data analytics software suite, provides quality control and allows researchers to analyze and interpret the output from the system and gain insights into their data. Consumables For our first Proteograph assay, we employ a panel of five NPs. The Proteograph consumables also include buffers and reagents for protein lysis and digestion, peptide purification, peptide quantification and the reconstitution of 7 lyophilized materials. We designed the performance specifications of the Proteograph Product Suite to meet the core needs of the market in terms of protein coverage and sample throughput required for proteomic experiments that are unbiased and at-scale. The current product allows for the interrogation and processing of up to 16 samples in parallel on a single 96-well plate in approximately seven hours. Each sample incubates separately with each of the five nanoparticles, resulting in 80 wells of peptides in a 96-well plate.The remaining 16 wells are for integrated quality control samples to ensure consistent process performance and to aid in troubleshooting. The ready availability of the non-particle reagents combined with our ability to efficiently design and fabricate different NPs with different chemical properties, greatly simplifies the development and production of future iterations or additional versions of the Proteograph assays to address potential customer needs, such as expanded coverage or specialized assays. Additionally, we can introduce new assays that include a different number of NPs and process different sample numbers. Automation Instrument We designed the Proteograph assay to be run in a robust and automated manner on our SP100 automation instrument, which is a custom-configured industry-standard liquid handling workstation. Our SP100 instrument is designed to consistently run experiments and to enable studies of hundreds to thousands of samples. Our automated workflow allows for rapid highly parallel proteomic sampling with just thirty minutes of set-up time. The flexibility of our instrument, coupled with the inherent diversity of our NP technology, provides for many potential applications and study workflows that can suit particular experimental needs The Proteograph workflow is driven by the Instrument Control Software (ICS) on the SP100 automation instrument. The workflow has been configured to process one full 96-well plate at a time, in just seven hours, processing 16 samples in parallel for each 96-well plate run. Future workflows and NP panels will be able to be run on the SP100 automation instrument, with an accompanying software update. The output of the Proteograph assay and instrument is peptides that are quantified, dried, and can be reconstituted when ready to inject into a mass spectrometer. MS provides quantitative detection, either on an instrument provided by the user, or sent out for MS analysis to a third-party provider. Software The Proteograph Analysis Suite is designed for ease-of-use and was developed to help users arrive at insights quickly and efficiently following quantitative detection of peptides on an MS instrument. To accommodate varying customer needs, we have designed the Proteograph Analysis Suite to be deployed as cloud-based and, in the future, more localized solutions to accommodate different customer types and geographies. Our deployment options will provide a predefined workflow for data management and analysis that leverages publicly available MS data analysis tools, as well as proprietary data analyses developed by us. Without the Proteograph Analysis Suite, proteomics analysis requires expert knowledge and scalable high-performance computer infrastructure to run efficiently. We believe that the Proteograph Analysis Suite could accelerate adoption among non-proteomic experts by providing an intuitive user interface that automates and simplifies data handling, processing and analysis, and provides access to a scalable infrastructure that can be used by any lab. Another potential roadblock for researchers is understanding and evaluating the quality of their results. The Proteograph assay incorporates a series of controls for monitoring assay performance, and an integrated view of the results of these control runs. Using the Proteograph Analysis Suite, the customer can evaluate trends over time and implement performance boundaries around the expected values that flag unexpected outcomes in the data. Providing a simple, consistent interface for customers to evaluate the control data and generate a quality control (QC) report will help them understand our approach to QC in the Proteograph workflow and simplify support. We expect that the Proteograph Product Suite will enable generation of large volumes of proteomic data, and we have developed the Proteograph Analysis Suite to ensure that handling, management and analysis of data does not create new bottlenecks for researchers. The Proteograph Analysis Suite offers ease of implementation and addresses key customer needs, which include integrated QC reporting, data management, data visualization, and statistical analysis tools. The Proteograph Analysis Suite is highly scalable and is designed to accommodate inputs from different MS platforms, rapidly expanding data volumes and emerging data analysis tools. Finally, as we continue to 8 improve and extend our product portfolio, we expect to expand the Proteograph Analysis Suite to include advanced data analysis tools, including PPI analysis, mapping of PTMs, genetic polymorphisms, multi-omics integration, and systems biology framework analysis. From Sample to Data Using the Proteograph Product Suite Proteomic analysis using the Proteograph Product Suite has five primary steps: 1. Protein Corona Formation . NPs can be mixed with a wide variety of soluble biological sample types (matrices), including cell or tissue homogenates, blood or blood components (such as plasma or serum), urine, saliva, cerebrospinal fluid, and synovial fluid. After combining the biosample and the NP, the mixture is incubated in a solution that mimics physiological conditions, producing protein-corona on the surface of the NPs. 2. Protein Corona Wash . NPs are then captured by a magnetic field, after which they undergo repeated cycles of wash with buffer to remove unbound, or loosely bound, proteins. 3. Peptide Preparation . Washed NPs are subject to enzymatic digestion to generate peptides, which are collected, quantified, dried and ready for subsequent MS analysis. 4. Mass Spectrometry . Digested peptides are prepared for measurement by dissolution in appropriate peptide reconstitution buffer suitable for MS injection, at a volume and concentration that meets MS instrument and liquid chromatography gradient requirements. 5. Data Analysis. After data acquisition, typical MS analysis methods are employed within the Proteograph Analysis Suite to identify and quantify the peptides and proteins in the sample. Quality control metrics are reported for the MS sample data, sample data summaries and output files are created, and initial cross-sample analyses are provided. Given the seven-hour run time per plate for our initial five-NP panel, one Proteograph Product Suite coupled with two MS instruments can process 48 samples in approximately two and a half days for unbiased and deep proteomic analysis. By comparison, the workflows developed by leading proteomics labs can take as long as several days to weeks, for sample preparation for MS measurement to reach an equivalent depth of proteomic coverage. Proteograph Product Suite Performance The Proteograph Product Suite provides four critical attributes: (i) breadth of protein sampling; (ii) depth of coverage; (iii) accuracy and precision of measurement; and (iv) the ability to scale the number of samples processed in a study. We believe that the Proteograph Product Suite is the only product to provide these technical and operational capabilities in an integrated solution to enable large-scale proteomic analysis. The performance of the Proteograph Product Suite as it relates to these technical attributes is described below: • Breadth of protein sampling. Refers to the ability to conduct unbiased, highly parallel sampling of the proteome. Each uniquely engineered NP selectively captures hundreds of distinct intact proteins from a biosample based on their abundance and affinity for the NP surface. Sampling is particularly strong in complex biofluids such as plasma. Our unique NPs capture significantly more proteins and protein variants than current methods of unbiased proteomic analysis, as shown in Figure 8a below. In a head-to-head experiment, the Proteograph Product Suite was compared with other unbiased proteomics methods using the same biological sample. Neat plasma represents the simplest form of unbiased proteomic analysis, requiring minimal processing time, and resulted in a breadth of coverage of 312 proteins. By adding processing steps such as depletion of high abundance proteins and fractionation (separation of the remaining proteins into multiple fractions), the breadth of protein sampling increased to 670 proteins. However, with the Proteograph Product Suite, we detected 1,656 proteins in plasma, representing a major expansion in breadth of protein coverage. 9 • Depth of coverage. Refers to the Proteograph’s ability to evaluate the proteome across the wide dynamic range of protein abundance. The depth of coverage using our assay is compared to other unbiased proteomic methods shown in Figure 8b below. The Proteograph assay samples proteins across the entire dynamic range of the plasma proteome, as defined in the Human Plasma Proteome Project database ( Schwenk et al .), with the 75th percentile point of depth of coverage shown with the orange bar. The depth of coverage for the Proteograph assay reaches further into the low abundant proteins than the fractionation, depletion and neat plasma methods. • Accuracy of measurement. Refers to how close the measured abundance of a protein is to the true abundance in a sample. Accuracy of protein abundance measurement can be demonstrated by MS signal intensity of the proteins sampled with the Proteograph assay, and comparing these values with measurements obtained directly by immuno-assay (ELISA). To demonstrate this, purified C-Reactive Protein (CRP) was added or “spiked” in to plasma at levels of 2x, 5x, 10x, and 100x of the baseline measured levels for CRP in the plasma. Samples with known concentrations of CRP were interrogated with the Proteograph Product Suite and ELISA. Figure 9 shows the linearity of measurement, as determined by MS signal intensity of four peptides within CRP when compared to the ELISA measurement of CRP. The Proteograph assay can distinguish changes in protein abundance with significant accuracy, as demonstrated by a slope response approximately equal to one and an r-squared value greater than 0.95. 10 • Precision of measurement. Refers to how close several measurements of protein abundance in the same sample are to each other. Less precision in the measurement adds noise to an experiment, requiring a larger number of samples in the study to observe a true difference. Precision is typically measured as the coefficient of variation (CV%), or standard deviation divided by the mean times 100. Therefore, a lower CV% represents a more precise outcome. The precision of the Proteograph Product Suite was compared with that of depletion, fracti onation, and neat, by evaluating the same sample three times and calculating the CV% for the detected peptides and proteins. On average across the peptides, the median precision was 16.9 C V%. At this level of performance, the Proteograph has 80% statistical power to detect a 50% change in a peptide levels with only ten samples per sample group. Using the Proteograph, lower CV% is achieved than fractionation and depletion methods, while concurrently sampling significantly more proteins, as shown in Figure 8c. In general, in unbiased assays, CV%s are expected to increase as the number of analytes detected increases. However, the Proteograph assay can increase the number of analytes that it detects while achieving comparatively better CV%s. Although neat plasma has a lower CV%, it is limited in the breadth of protein coverage to 312 proteins compared to 1,656 proteins sampled by the Proteograph. • Scalability . The Proteograph Product Suite enables rapid and large-scale proteomic sample processing in a seven-hour workflow, compared to other unbiased solutions that can take days to weeks. With our current five-NP assay, we can process sixteen samples in a single run of the Proteograph SP100 instrument.Given the seven-hour run time per plate for our initial five-NP panel, one Proteograph Product Suite coupled with two MS instruments can process 48 samples in approximately two and a half days for unbiased and deep proteomic analysis. By comparison, the workflows developed by leading proteomics labs can take as long as several days to weeks, for sample preparation for MS measurement to reach an equivalent depth of proteomic coverage. We believe the Proteograph will broadly appeal to researchers seeking an easy-to-use, scalable approach with a unique combination of attributes spanning breadth, depth, accuracy and precision of measurement and the speed and throughput necessary for large-scale proteomics studies. Sampling across the entire dynamic range has been one of the seminal challenges in the field of proteomics, as the range from the most abundant to the least abundant protein in biological samples can vary up to ten orders of magnitude, and the rich diversity of biology likely resides outside the most abundant proteins. Markets We believe the two primary near-term markets for the Proteograph Product Suite are the proteomics market, which was $32 billion in 2019, according to Allied Market Research, and the genomics market, which was $21 billion in 2019, according to Technavio. Within these markets, potential applications of the Proteograph solution span basic research and discovery, translational research, diagnostics and applied applications. Of the $32 billion proteomics market, $25 billion is estimated to be spent on reagents, $5 billion on instruments, and $2 billion on services. In the near-term, we believe we will compete in both the proteomics reagent and instrument markets. Furthermore, the $21 billion genomics market consists of approximately $13 billion spent on products and $7 billion spent on services. In the near-term, we believe we will be able to garner spend from both products and services as genomic customers link genotype to phenotype by supplementing existing genomic data with proteomics data. While we initially plan to sell and market the Proteograph Product Suite for RUO, we believe that the capabilities of the Proteograph Product Suite may enable other applications. While we currently do not intend to pursue clinical diagnostics applications, we may in the future seek premarket approval or clearance for the Proteograph Product Suite in order to allow our customers to use the Proteograph in other product offerings. We believe that the Proteograph Product Suite’s unique value proposition will resonate with proteomics researchers who already value deep and unbiased proteomic information, and who desire to scale experiments to far greater sample sizes at a fraction of the time and cost of current approaches. We also believe that as more genomics researchers incorporate other omics approaches to elucidate key genomic findings, the Proteograph will uniquely provide large-scale, unbiased and deep proteomic information to complement genomic information, and enable researchers to gain a clearer picture of biology and a deeper understanding of genomic risk factors. Longer-term, we believe that the 11 capabilities offered by the Proteograph Product Suite and future products may potentially lead to new end-markets, applications, and business models that complement existing proteomics and genomics markets. Proteomics Allied Market Research estimates the global proteomics market was $32 billion in 2019, and is expected to grow to $64 billion in 2024, representing a 15% compound annual growth rate. According to Allied Market Research, 60% of the proteomics market is focused on life sciences research, 35% for clinical applications and 5% other applications. Products in the proteomics market include spectrometry, microarray and chromatography instruments as well as reagents, used for both unbiased and biased proteomics. The majority of proteomic analysis to date either relies on biased or targeted methods or expensive, complex, and laborious unbiased or de novo deep methods that are applied only to tens of samples versus the thousands needed to power large-scale studies. Few methods are based on capture of intact proteins that enable analysis of proteome complexity at the level of amino acid variants, PTMs and PPIs, all of which have the potential to generate important biological insights. We believe the unique capabilities of the Proteograph Product Suite will appeal to researchers either as a complement or substitute for current approaches, or in creating an entirely novel path to survey the proteome. We estimate that there are approximately 16,000 MS instruments with configurations typically used to perform proteomic analysis installed worldwide. Since the Proteograph can leverage most MS instruments as a detector, we believe that we can take advantage of this installed base to accelerate adoption. We believe that we have an opportunity to provide a strong alternative to both unbiased and biased proteomics approaches, particularly in the discovery of new biology, and to grow the proteomics market by enabling new applications for unbiased proteomics. These applications currently span research, translational and clinical settings, and we believe that the Proteograph Product Suite can address all these applications over time. Genomics Technavio estimates the global genomics market was $21 billion in 2019 and is expected to grow to $38 billion by 2024, representing a 13% compound annual growth rate. We believe that large-scale deep, unbiased proteomics studies, such as those the Proteograph could enable, will provide important missing biological information to improve functional characterization of genomic variants, enabling large-scale proteogenomics. In genomics markets, complementing large-scale genomics analysis with large-scale proteomic analysis has the potential to enhance and accelerate our understanding of biology, human health and ultimately the treatment of disease. Therefore, we believe the Proteograph solution can appeal to an increasing number of genomics customers, especially those in translational settings, who are looking to leverage multi-omics approaches to further annotate genomic variants in terms of function and connect genotype to phenotype. New Markets We also believe that the Proteograph Product Suite will enable novel applications and insights leading to new end-markets, like the impact that broad access to genomics products have had in creating new applications, end-markets and business models. For example, non-invasive prenatal testing and precision oncology currently make up a significant part of the current $21 billion genomics market, yet we believe that it would have been difficult to anticipate these market opportunities a decade ago. We believe the same dynamic of new market creation will occur in proteomics. One such application for proteomics is early disease detection. We spun out a new entity, PrognomIQ, Inc. (PrognomIQ), which aims to develop and commercialize novel diagnostic tests that leverage the Proteograph Product Suite in combination with genomics and metabolomics information, and will be a participant in the existing ecosystem of early disease detection. More broadly, we believe the Proteograph solution has the potential to further stimulate growth of new applications and end-markets in additional ecosystems. The Advantages of The Proteograph Product Suite We believe the Proteograph Product Suite and its underlying NP technology have the following advantages: • The first commercially available solution to provide the combination of unbiased, deep, rapid and large-scale access to the proteome. While other proteomics technologies exist today, we believe that the Proteograph 12 Product Suite is the first and only product to provide the combination of these four attributes in a single integrated solution with an easy-to-use workflow. We believe these capabilities fill a gap that to date has been one of the rate-limiting steps in unlocking the complexity of biology. • A unique solution that provides insight into protein variation and PPIs at a depth and scale that we believe sets a new standard for unbiased and deep proteomics and is unattainable with existing approaches. The ability to observe the myriad of possible protein variations, which go beyond simple total protein abundance, with the accuracy and precision necessary to extract useful insights across large numbers of subjects, is a key differentiating attribute of our solution. Furthermore, capturing these variations at scale enables synergistic insights when combined with genomic variations, finally enabling the development of informative, individualized models of biology at population scale. • A solution that will enable broad adoption by a wide variety of customers in both decentralized and centralized settings. The Proteograph Product Suite is an integrated solution comprised of consumables, an automation instrument and software, and was designed to deliver ease-of-use, efficiency, robustness and reproducibility of results and to complement existing laboratory infrastructure. The Proteograph’s simple and integrated workflow enables the customer to use their own MS instrument or leverage a widely available installed base of MS instruments. We believe these characteristics will facilitate broad adoption of the Proteograph solution across a variety of laboratories and institutions in both decentralized and centralized settings. • A core technology from which we can develop a range of products, applications and platforms. From our growing and diverse NP library, we can develop new panels of NP consumables that address a variety of applications and customer needs. We plan to use machine learning techniques and apply large-scale data analyses of our NP binding properties to understand relationships between NP surfaces and protein binding and interactions in order to rationally design our NP panels. We believe these characteristics will enable development of additional differentiated products to enable our customers to utilize applications across the life sciences industry, ranging from basic research and discovery, translational research, diagnostics and applied applications. • A core technology that provides significant operational leverage in research and development, manufacturing and commercialization. NPs are efficient to design, develop and manufacture. We believe we will be able to rapidly increase and deploy our understanding of NP design to develop new products with our software and data analytics capabilities. In the NP manufacturing process, we use well-characterized inputs and methods, which require relatively modest capital equipment and space investments. This capital-efficient and labor-efficient model has the potential to provide significant operating leverage to our organization. • A solution with sustainable differentiation. The Proteograph is uniquely capable of generating robust, reproducible, deep and unbiased proteomic data, and as more of this data gets created over our time and used by more customers to generate insights, we expect to create a cycle that will fuel further adoption of the Proteograph Product Suite throughout the industry. The Proteograph workflow was designed to fully integrate with customer workflows and provide a unique user experience, supported by our software packages, to create a sustainable solution within our customers’ organizations. The SP100 automation instrument, software, and NP technology are covered by numerous issued patents and pending patent applications, worldwide, covering improvements in NPs, assay methods and ways to leverage proteomic data and information for life sciences research and clinical diagnostic and drug discovery applications. Our Strategy Our mission is to imagine and pioneer new ways to decode the secrets of the proteome to improve human health. Our growth strategy is to: • Drive adoption of the Proteograph Product Suite to enable researchers to create large-scale unbiased proteomic datasets that generate transformative scientific insights. The Proteograph Product Suite uniquely enables researchers and clinicians to generate unbiased, deep proteomic information at speed and scale that was 13 not previously possible. The utility and potential applications of these capabilities are broad, spanning across basic research and discovery, translational research, diagnostics and applied applications. • Invest in market development activities to establish the importance of large-scale proteomic data and the ability to access it . To expand and accelerate demand for our products, particularly as new applications are created and adopted by customers, we plan to invest in market development activities to educate prospective customers, funding bodies, commercial entities, government-sponsored omics programs, and other stakeholders of the importance and value of large-scale unbiased and deep proteomic data. These activities will likely include collaborations with key opinion leaders, generation of peer-reviewed publications, sponsorship of targeted projects, joint publications and seminars, and industry partnerships. These activities aim to establish the value of large-scale unbiased and deep proteomic data, and demonstrate the unique capabilities offered by our products. • Continually innovate to develop and commercialize additional transformative products to access the proteome and accelerate our understanding of biology . We aim to continually innovate and develop new products, applications, workflows and analysis tools that simplify and accelerate researchers and clinicians’ ability to generate proteomic data and to connect proteomic data to genomic and transcriptomic data that drive novel biological insights. As leaders in NGS have demonstrated, our sustainable advantage will come from continual development and commercialization of new products and applications based on our technology, and we will drive innovation through both internal R&D projects and from collaborations with customers and partners. • Rapidly build our commercial infrastructure and manufacturing capabilities to enable global customer base expansion. We are building our commercial infrastructure to sell and support our products directly in the United States, the European Union and United Kingdom. We are expanding access to our products in other geographies, starting with select countries in Asia Pacific through distributors, and eventually to the rest of the world. We are also scaling our manufacturing capabilities in our facility in Redwood City, California, and will continually evaluate and optimize our manufacturing and supply chain footprint to meet our business objectives. • Foster the creation of an ecosystem of customers, partners and collaborators whose expertise and offerings complement and enhance the power and utility of our products. We intend to seed and develop a new ecosystem of applications and organizations that can take advantage of large-scale proteomic analysis. This ecosystem can include areas such as disease detection, large-scale population studies, agriculture, environmental monitoring and food safety. To help seed the growth of this ecosystem, we spun-out a new company called PrognomIQ, which plans to develop and commercialize diagnostic tests for early disease detection, leveraging the Proteograph Product Suite in combination with other omics technologies. • Expand our proprietary engineered NP technology to analyze molecules beyond proteins. Given the inherent flexibility and ability to synthesize myriad NPs, we intend to seek over the long-term to expand the scope of our proprietary engineered NP technology to analyze other biomolecules such nucleic acids, metabolites and small molecules among others. As we continue to work closely with our customers, we will better understand their needs and requirements, which will inform our product development pathway and development of our library of NPs and our software capabilities to address other omics applications. We believe our management’s knowledge and experience in both the proteomics and genomics markets will position us to take advantage of such new expansion opportunities as they arise. The Applications of the Proteograph Product Suite We believe the ability to generate unbiased, deep proteomic data at scale, with rich content at the protein variant level will have broad applications in proteomics, encompassing basic research and discovery, translational research, diagnostics and applied markets. We believe this data will be used in many of the same application areas as are used with genomics data, proteomics applications that are uniquely possible with unbiased proteomic data and in new applications that the field will develop in the future. 14 Basic Research and Discovery Applications We believe that researchers will use the Proteograph for a variety of basic research and discovery applications, including cataloging protein diversity, proteogenomics and exploring the interactome. While researchers are pursing these applications today, the studies are either limited in scale due to the complex workflows of current unbiased methods or the limited set of ASRs that are available for biased methods. The Proteograph Product Suite is designed to enable the use of unbiased proteomic data at scale, which we believe will greatly accelerate these areas of basic research and discovery. Cataloging protein diversity The Proteograph Product Suite is designed to enable researchers to broadly explore the complexity and diversity of the proteome at the peptide and amino acid levels and discover many distinct protein variants. We expect that researchers will use the Proteograph solution to catalog these protein variants much like the cataloging of genetic variants that occurred over the past fifteen years, and this will uniquely provide functional context at a scale that is not accessible today with other proteomics methods. We believe the utility of these protein variants has the potential to impact a broad spectrum of the life sciences field. In cataloging protein variants, researchers can also gain valuable insights with PTMs, such as phosphorylation. These PTMs are dynamic and the resulting protein variants can be seen with different states of health and disease. We believe that as researchers pursue large-scale proteomics studies, the literature that links disease biology to protein variants produced from alternative RNA splicing and from PTMs will exponentially increase. Proteogenomics Proteogenomics is an emerging area of research, whereby personalized protein sequence databases are generated using genomic and transcriptomic information to help identify novel peptides. In turn, the proteomic data provides functional context to genomic information and refines gene expression models for transcriptomic information. The Proteograph generates large-scale unbiased proteomic data, which will facilitate mapping protein variants to genomic variants, and therefore, the advancement of the emerging proteogenomics field. Given the current level of access to genomic and transcriptomic information, as researchers conduct the large-scale proteomics studies that the Proteograph enables, we expect proteogenomic content to rapidly increase, providing functional information to existing genomics and gene expression information. Interactome The interactome refers to the broad set of interaction networks among molecules, such as those interactions among proteins, also referred to as protein-protein interactions, or PPIs. Protein interaction networks have been used to infer the function of proteins. Different types of interaction maps can be composed by the research community for different applications. These include physical interactions or the functional pathway implications of these interactions. PPI network maps can be constructed by pegging individual proteins as nodes and linking proteins that interact to them by a drawn line. These maps naturally cluster into hubs of proteins that fall into related pathways or have related functions. Access to the deep unbiased proteomic information provided by the Proteograph may enable researchers to better understand biological implications of known PPIs. Furthermore, given our highly parallel sampling of the proteome across multiple NPs and many samples, we believe researchers using the Proteograph Product Suite may be able to leverage machine learning methods on the resulting large data sets to derive novel PPIs. Translational Research Applications Researchers can use the Proteograph to address translational research applications, which aim to shorten the cycle time from early discovery research to clinical application. The Proteograph Product Suite allows clinical and translational researchers to conduct unbiased, deep and large-scale proteomics studies in therapeutic and diagnostic research and clinical trials, which can allow for significant advances in biomarker discovery, target identification and exploration, and clinical trial applications. 15 Biomarker discovery To date, most de novo biomarker discovery research is limited by the size of studies that can be done in an unbiased way or limited to targeted studies that leverage existing knowledge. These approaches have yet to uncover the vast number of putative biomarkers that may be available as single markers or as combinations of markers for a range of clinical applications. We believe the Proteograph can greatly enable the discovery of biomarkers through large-scale, unbiased and deep proteomics studies. Target Identification and Exploration We believe that large-scale access to protein variant information that map to different states of health and disease, as enabled by the Proteograph and concurrent advances in proteogenomics, has the potential to lead to the discovery of personalized drug targets that could reach the hundred thousand range. We believe that the translational application of the Proteograph for potential biomarker development, as exemplified above in our NSCLC study, may also be applied to the identification of novel targets for therapeutic development. Components of classifiers may directly be targets themselves for drug development, or they may highlight new knowledge with respect to disease mechanism which then could help in the exploration of additional targets and/or help to elucidate the function of potential targets, particularly if these targets are discovered with genomics approaches, and lack protein functional context. Clinical Trial Applications Clinical researchers can use the Proteograph Product Suite for deep and broad proteomic profiling for subjects in therapeutic clinical trials, including to make observations on efficacy and adverse events. Applications could include the real-time monitoring of protein-related drug effects, distribution, and metabolism. Virtually all clinical trials in drug development include monitoring of this type, but currently use biased or targeted panels of proteins. It is currently impractical to do this type of monitoring with unbiased proteomic methods given the inability of these methods to scale to the hundreds or thousands of samples that are evaluated in clinical trials. The Proteograph Product Suite may also be used to select and group patients in clinical studies based on their proteomics profiles. As our understanding of the complexity of biology increases with new data accrued from the Proteograph as well as in adjacent omics spaces, our ability to refine patient selection at a higher resolution may improve the ability to confirm efficacy for novel therapies, particularly in complex diseases that involve many inter-related physiological systems. Genomic approaches are widely used to select patients in cancer and rare genetic disease clinical trials, but the use of genomics-based selection for clinical trials outside of these indications has not been as widely used, given the relative lack of genetic understanding of these diseases. We believe that the Proteograph has the potential to generate useful proteomic signatures that can complement genomic and other patient selection criteria to improve how clinical researchers select and segment patients for these trials, particularly for indications outside of cancer and rare genetic diseases. Diagnostic Applications We see significant opportunities for researchers to use the Proteograph Product Suite for diagnostic development. Similar to the way in which NGS enabled the development of ecosystems that included genomics-based diagnostics in disease areas such as cancer and rare genetic diseases, we see the unbiased, deep and scalable proteomic information provided by the Proteograph solution potentially creating ecosystems, including proteomics and multi-omics based diagnostics in cancer and other complex disease areas. We expect that the Proteograph solution will be used by companies in the healthcare testing space, including PrognomIQ, and we will support all of these customers as the ecosystem grows. We plan to enable our customers by providing the Proteograph Product Suite for their basic research and translational research applications, as they develop their own diagnostic applications. Applied Applications in Agriculture, Environmental and Food Safety Outside of the areas related to human health, we believe there are opportunities for the Proteograph solution to be applied in other applied applications, including those applications where broad scale genomics is being widely applied today, and other applications where proteomics can uniquely enable the creation of end-markets. We believe that unbiased, deep and large-scale proteomic information as enabled by the Proteograph can complement and 16 extend the value of genomics, transcriptomics, and metabolomics information in fields such as agriculture, environmental monitoring and food safety. This is exemplified in a recent plant proteomics study that identified PPIs and multi-protein complexes that likely play a role in important agronomic traits. Pathogen monitoring is a core research area in environmental sciences. Genomics-based approaches have been applied for environmental monitoring, and we believe that unbiased proteomic data can be used to complement genomic information in monitoring environmental pathogens. The food industry has complex supply chains where food can be subject to contamination and spoilage in the food product itself as one moves from raw material to processing to distribution, storage and consumption of the food product. We believe that unbiased proteomic data from the Proteograph Product Suite could complement existing biochemical approaches for tracking signals of contamination and food spoilage. PrognomIQ In August 2020, we transferred certain assets related to disease testing to PrognomIQ, a wholly-owned subsidiary of the Company, in exchange for all of its outstanding equity interests. Following the transfer, we completed a pro-rata distribution to our stockholders of most of the shares of capital stock of PrognomIQ. Following the distribution and a subsequent $55.0 million financing of PrognomIQ, we hold approximately 19% of the outstanding equity in PrognomIQ. The rationale for this transaction was to enable the growth of ecosystems around new applications that leverage unbiased, deep and large-scale proteomic information. The transaction allows us to remain focused on our core strategy, which is to be a provider, rather than a consumer, of proteomics solutions to all customers across these ecosystems. By focusing on our role as a provider of proteomics solutions, we are no longer potentially competing with, or creating the perception that we are competing with, our customers. Our relationship with PrognomIQ does not preclude us from selling the Proteograph Product Suite to any customer in any geography, nor does it preclude our customers from using the Proteograph in any way. PrognomIQ has indicated that it plans to combine the protein data from the Proteograph with genomics and other omics data, to create a multi-omics approach to health and disease testing, which we believe will help us drive the adoption of the Proteograph Product Suite in these applications. Omid Farokhzad, Chief Executive Officer and Chair of our board of directors, serves as the Chair of PrognomIQ’s board of directors. Philip Ma, Ph.D. our former Chief Business Officer serves as the Chief Executive Officer of PrognomIQ. While Dr. Ma has fully transitioned to PrognomIQ, he will remain our consultant until April 2022. We granted PrognomIQ a non-exclusive license to certain patents and patent applications that we own and a non-exclusive sublicense to certain patent applications we exclusively licensed from The Brigham and Women’s Hospital, Inc. (BWH), in each case relating to our core technology, to develop, manufacture and commercialize licensed products for the field of human diagnostics on a worldwide basis. In consideration of the non-exclusive sublicense to certain patent applications licensed from BWH, PrognomIQ paid us a low-five digit figure, and would pay a low single digit royalty, in an amount equivalent to what we would have to pay under our license with BWH, on net sales of sublicensed products beginning with the first commercial sale of a sublicensed product during the term of the agreement. For further discussion of our license and sublicense arrangement with PrognomIQ, see the section titled “Business — Collaboration and License Agreements — PrognomIQ .” We do not view these amounts to be material to our financial condition and results of operations nor do we expect these amounts to ever be material to us in the future. Commercial Commercial Strategy The Proteograph Product Suite is an integrated solution comprising consumables, an automation instrument and software. We have developed the Proteograph solution to simplify and accelerate proteomics workflow, reduce labor and capital requirements, and deliver robust and reproducible performance. We will focus on growing the installed 17 base of the Proteograph across a wide variety of customer types and driving applications, scale of experimentation and discoveries that lead to increasing utilization of the Proteograph Product Suite by our customers. We intend to initially target potential customers who value unbiased and deep proteomic information and are performing proteomic or genomic analysis at academic institutions, translational research groups and biopharmaceutical companies. Our direct sales and marketing efforts will be focused on the principal investigators, researchers, department heads, research laboratory directors and core facility directors who control the buying decision. We expect these customers to purchase the Proteograph Product Suite and associated consumables in line with typical purchases of other life science instrumentation and consumables. We believe that we have priced the Proteograph Product Suite to be affordable to most researchers who can directly make the buying decision, without the need for additional levels of approval, simplifying our sales process. For example, we price the SP100 automation instrument on a comparable basis to other similar automated fluid handling systems currently available. We price the Proteograph consumables, on a per sample basis, in a range similar to that of other life sciences consumables that provide deep and unbiased omic information. The generation of publications and scientific presentations is a core pillar of our market awareness strategy and is important for establishing validity and utility of new products in the life sciences community. We plan to work closely with our customers, including key opinion leaders, to generate clear use-cases, as well as peer-reviewed publications that illustrate our product performance claims and value proposition. In addition, we plan to drive awareness by developing and deploying online and in-person training and educational tools that explain our technology and key applications in easy-to-access, easy-to-understand, and scientifically rigorous and credible ways. We have partnered with select service facilities and core labs globally to be Centers of Excellence for the Proteograph solution. These sites have become our customers and provide fee-for service capabilities that allow interested parties to access and evaluate the Proteograph Product Suite using their own samples. We expect that these Centers of Excellence will actively promote the Proteograph solution and its capabilities and help us further raise awareness. To service our potential Proteograph customers, we will provide multiple levels of technical service for the Proteograph Product Suite, depending upon customer need. We recognize that excellent customer support can be a critical part of a customer experience, and we will invest accordingly in our technical and application support to achieve the desired levels of service. Commercial Organization We are building out our commercial organization across marketing, sales, customer success, and technical support functions to support demand and with the intent to deliver exceptional customer experience. We believe that coupling exceptional customer experience with a transformative product will allow us to deliver substantial value to our customers, build long-term customer loyalty, enhance our competitive differentiation, and, importantly, use our customer relationships to gain insights that inform our product development to grow our offerings in ways that will benefit our customers. We expect to expand our customers in North America, the European Union and United Kingdom through direct sales and customer support organizations. We expect to grow into other geographies over time, initially through distributors, starting with key countries in Asia Pacific. We expect a highly efficient sales model since the Proteograph Product Suite does not have a large capital expenditure component, can leverage the existing installed base of MS instruments and complements large-scale genomics data ecosystems. Suppliers and Manufacturing Our overall manufacturing strategy is to continuously develop and refine our processes to achieve our objectives of continuity of supply, quality of supply and margin enhancement. Over time, this may lead to in-sourcing or outsourcing certain functions, including manufacturing, in various geographic locations in order to achieve our objectives. 18 Consumables We leverage well-established unit operations to formulate and manufacture our NPs at our facilities in Redwood City, California. We procure certain components of our consumables from third-party manufacturers, which includes the commonly-available raw materials needed for manufacturing our proprietary engineered NPs. We are currently manufacturing using our pilot line and building out our manufacturing capabilities as we enter broad commercial availability. We obtain some of the reagents and components used in the Proteograph workflow from third-party suppliers. While some of these reagents and components are sourced from a single supplier, these products are readily available from numerous suppliers. While we perform some filling and packaging of the Proteograph assay and the related consumables, in the future, we may have our filling and packaging outsourced to a third-party. We conduct vendor and component qualification for components provided by third-party suppliers and quality control tests on our NPs. Automation Instrument We designed the SP100 automation instrument and have outsourced the manufacturing of the SP100 automation instrument to Hamilton Company, a leading manufacturer of automated liquid handling workstations. We have entered into a non-exclusive agreement with Hamilton that covers the manufacturing of the SP100 automation instrument and its continued supply on a purchase order basis. The agreement has an initial term that runs three years following our commercial launch. We have the option to extend the term of the agreement with Hamilton upon written notice at the end of the initial term; provided that prices are only fixed during the initial term of the agreement. Hamilton has represented to us that it maintains ISO 9001 and ISO 13485 certification. Competition The life sciences technology industry is characterized by rapidly advancing technologies, intense competition and a strong emphasis on intellectual property. The proteomics market is served by companies that offer a variety of analytical instruments, such as chromatography and MS instruments, and associated reagents. We believe that competitors in the proteomics market are differentiated by their proprietary technologies, rapid product development capabilities, applications and intellectual property. We believe that there are currently no commercially available products that offer the capability to conduct unbiased, deep proteomics studies at the same scale and throughput as the Proteograph Product Suite. Given the potential market opportunity and scientific promise of proteomics, we expect the intensity of the competition to increase and, as a result, one or more competing products emerging in the future. Competing products may emerge from various sources, including life sciences tools, diagnostics, pharmaceutical and biotechnology companies, third-party service providers, academic research institutions, governmental agencies and public and private research institutions. Current companies that provide proteomics products include Agilent Technologies, Bruker, Danaher, DiaSorin and Thermo Fisher Scientific. There are also a number of companies that provide proteomic analysis services. In addition, a number of emerging growth companies have developed, or are developing, proteomics products, services and solutions, such as Nautilus Biotechnology, Olink Proteomics, Quanterix, Quantum-Si and SomaLogic. Government Regulation The development, testing, manufacturing, marketing, post-market surveillance, distribution, advertising and labeling of certain of medical devices are subject to regulation in the United States by the Center for Devices and Radiological Health of the U.S. Food and Drug Administration (FDA) under the Federal Food, Drug, and Cosmetic Act (FDC Act) and comparable state and international agencies. FDA defines a medical device as an instrument, apparatus, implement, machine, contrivance, implant, in vitro reagent or other similar or related article, including any component part or accessory, which is (i) intended for use in the diagnosis of disease or other conditions, or in the cure, mitigation, treatment, or prevention of disease, in man or other animals, or (ii) intended to affect the structure or any function of the body of man or other animals and which does not achieve any of its primary intended purposes through chemical action within or on the body of man or other animals and which is not dependent upon being metabolized for the achievement of any of its primary intended purposes. Medical devices to be commercially distributed in the United States must receive from the FDA either clearance of a premarket 19 notification, known as 510(k), or premarket approval pursuant to the FDC Act prior to marketing, unless subject to an exemption. We label and sell our products for research use only (RUO) and expect to sell them to academic institutions, life sciences and research laboratories that conduct research, and biopharmaceutical and biotechnology companies for non-diagnostic and non-clinical purposes. Our products are not intended or promoted for use in clinical practice in the diagnosis of disease or other conditions, and they are labeled for research use only, not for use in diagnostic procedures. Accordingly, we believe our products, as we intend to market them, are not subject to regulation by FDA. Rather, while FDA regulations require that research use only products be labeled with – “For Research Use Only. Not for use in diagnostic procedures.” – the regulations do not subject such products to the FDA’s jurisdiction or the broader pre- and post-market controls for medical devices. In November 2013, the FDA issued a final guidance on products labeled RUO, which, among other things, reaffirmed that a company may not make any clinical or diagnostic claims about an RUO product, stating that merely including a labeling statement that the product is for research purposes only will not necessarily render the device exempt from the FDA’s clearance, approval, or other regulatory requirements if the totality of circumstances surrounding the distribution of the product indicates that the manufacturer knows its product is being used by customers for diagnostic uses or the manufacturer intends such a use. These circumstances may include, among other things, written or verbal marketing claims regarding a product’s performance in clinical diagnostic applications and a manufacturer’s provision of technical support for such activities. If FDA were to determine, based on the totality of circumstances, that our products labeled and marketed for RUO are intended for diagnostic purposes, they would be considered medical devices that will require clearance or approval prior to commercialization. Further, sales of devices for diagnostic purposes may subject us to additional healthcare regulation. We continue to monitor the changing legal and regulatory landscape to ensure our compliance with any applicable rules, laws and regulations. In the future, certain of our products or related applications could become subject to regulation as medical devices by the FDA. If we wish to label and expand product lines to address the diagnosis of disease, regulation by governmental authorities in the United States and other countries will become an increasingly significant factor in development, testing, production, and marketing. Products that we may develop in the molecular diagnostic markets, depending on their intended use, may be regulated as medical devices or in vitro diagnostic products (IVDs) by the FDA and comparable agencies in other countries. In the U.S., if we market our products for use in performing clinical diagnostics, such products would be subject to regulation by the FDA under pre-market and post-market control as medical devices, unless an exemption applies, we would be required to obtain either prior 510(k) clearance or prior premarket approval from the FDA before commercializing the product. The FDA classifies medical devices into one of three classes. Devices deemed to pose lower risk to the patient are placed in either class I or II, which, unless an exemption applies, requires the manufacturer to submit a pre-market notification requesting FDA clearance for commercial distribution pursuant to Section 510(k) of the FDC Act. This process, known as 510(k) clearance, requires that the manufacturer demonstrate that the device is substantially equivalent to a previously cleared and legally marketed 510(k) device or a “pre-amendment” class III device for which pre-market approval applications (PMAs) have not been required by the FDA. This FDA review process typically takes from four to twelve months, although it can take longer. Most class I devices are exempted from this 510(k) premarket submission requirement. If no legally marketed predicate can be identified for a new device to enable the use of the 510(k) pathway, the device is automatically classified under the FDC Act as class III, which generally requires PMA approval. However, FDA can reclassify or use “de novo classification” for a device that meets the FDC Act standards for a class II device, permitting the device to be marketed without PMA approval. To grant such a reclassification, FDA must determine that the FDC Act’s general controls alone, or general controls and special controls together, are sufficient to provide a reasonable assurance of the device’s safety and effectiveness. The de novo classification route is generally less burdensome than the PMA approval process. Devices deemed by the FDA to pose the greatest risk, such as life-sustaining, life-supporting, or implantable devices, or those deemed not substantially equivalent to a legally marketed predicate device, are placed in class III. Class III devices typically require PMA approval. To obtain PMA approval, an applicant must demonstrate the reasonable safety and effectiveness of the device based, in part, on data obtained in clinical studies. All clinical 20 studies of investigational medical devices to determine safety and effectiveness must be conducted in accordance with FDA’s investigational device exemption (IDE) regulations, including the requirement for the study sponsor to submit an IDE application to FDA, unless exempt, which must become effective prior to commencing human clinical studies. PMA reviews generally last between one and two years, although they can take longer. Both the 510(k) and the PMA processes can be expensive and lengthy and may not result in clearance or approval. If we are required to submit our products for pre-market review by the FDA, we may be required to delay marketing and commercialization while we obtain premarket clearance or approval from the FDA. There would be no assurance that we could ever obtain such clearance or approval. All medical devices, including IVDs, that are regulated by the FDA are also subject to the quality system regulation. Obtaining the requisite regulatory approvals, including the FDA quality system inspections that are required for PMA approval, can be expensive and may involve considerable delay. The regulatory approval process for such products may be significantly delayed, may be significantly more expensive than anticipated, and may conclude without such products being approved by the FDA. Without timely regulatory approval, we will not be able to launch or successfully commercialize such diagnostic products. Changes to the current regulatory framework, including the imposition of additional or new regulations, could arise at any time during the development or marketing of our products. This may negatively affect our ability to obtain or maintain FDA or comparable regulatory clearance or approval of our products in the future. In addition, regulatory agencies may introduce new requirements that may change the regulatory requirements for us or our customers, or both. As noted above, although our products are currently labeled and sold for research purposes only, the regulatory requirements related to marketing, selling, and supporting such products could be uncertain and depend on the totality of circumstances. This uncertainty exists even if such use by our customers occurs without our consent. If the FDA or other regulatory authorities assert that any of our RUO products are subject to regulatory clearance or approval, our business, financial condition, or results of operations could be adversely affected. For example, in some cases, our customers may use our RUO products in their own laboratory-developed tests (LDTs) or in other FDA-regulated products for clinical diagnostic use. The FDA has historically exercised enforcement discretion in not enforcing the medical device regulations against LDTs and LDT manufacturers. However, on October 3, 2014, the FDA issued two draft guidance documents that set forth the FDA’s proposed risk-based framework for regulating LDTs, which are designed, manufactured, and used within a single laboratory. In January 2017, the FDA announced that it would not issue final guidance on the oversight of LDTs and LDT manufacturers, but would seek further public discussion on an appropriate oversight approach and give Congress an opportunity to develop a legislative solution. More recently, the FDA has issued warning letters to genomics labs for illegally marketing genetic tests that claim to predict patients’ responses to specific medications, noting that the FDA has not created a legal “carve-out” for LDTs and retains discretion to take action when appropriate, such as when certain genomic tests raise significant public health concerns. As laboratories and manufacturers develop more complex genetic tests and diagnostic software, FDA may increase its regulation of LDTs. Any future legislative or administrative rule making or oversight of LDTs and LDT manufacturers, if and when finalized, may impact the sales of our products and how customers use our products, and may require us to change our business model in order to maintain compliance with these laws. We would become subject to additional FDA requirements if our products are determined to be medical devices or if we elect to seek 510(k) clearance or premarket approval. If our products become subject to FDA regulation as medical devices, we would need to invest significant time and resources to ensure ongoing compliance with FDA quality system regulations and other post-market regulatory requirements. International sales of medical devices are subject to foreign government regulations, which vary substantially from country to country. In the future, if we decide to distribute or market our diagnostic products as IVDs in Europe, such products will be subject to regulation under the European Union (EU) IVD Directive and/or the IVD Medical Device Regulation (IVDR) European Union (EU) 2017/746. The IVDR was published in 2017, will replace the IVD Directive, is significantly more extensive than the IVD Directive, including requirements on performance data and quality system, and will become fully enforceable in 2022. Outside of the EU, regulatory approval needs to be sought on a country-by-country basis in order to market medical devices. Although there is a trend towards harmonization of quality system, standards and regulations in each country may vary substantially which can affect timelines of introduction. 21 In August 2020, the Department of Health and Human Services (HHS) announced rescission of guidance and other informal issuances of the FDA regarding premarket review of LDT absent notice-and-comment rulemaking, stating that, absent notice-and-comment rulemaking, those seeking approval or clearance of, or an emergency use authorization, for an LDT may nonetheless voluntarily submit a premarket approval application, premarket notification or an Emergency Use Authorization request, respectively, but are not required to do so. The impact of this HHS rescission policy, including whether or how this policy will be implemented under the current administration, as well as other legislative, executive, and agency actions of the current administration remains unclear. The Biden administration has also issued a “regulatory freeze” memorandum that directs department and agency heads to review any new or pending rules of the prior administration. Any restrictions or heightened regulatory requirements on LDTs, IVDs, or RUO products by the FDA, HHS, Congress, or state regulatory authorities may decrease the demand for our products, increase our compliance costs, and negatively impact our business and profitability. We will continue to monitor and assess the impact of changing regulatory landscape on our business. In the future, to the extent we develop any clinical diagnostic assays, we may pursue payment for such products through a diverse and broad range of channels and seek coverage and reimbursement by government health insurance programs and commercial third-party payors for such products. In the United States, there is no uniform coverage for clinical laboratory tests. The extent of coverage and rate of payment for covered services or items vary from payor to payor. Obtaining coverage and reimbursement for such products can be uncertain, time-consuming, and expensive, and, even if favorable coverage and reimbursement status were attained for our tests, to the extent applicable, less favorable coverage policies and reimbursement rates may be implemented in the future. Changes in healthcare regulatory policies could also increase our costs and subject us to additional regulatory requirements that may interrupt commercialization of our products, decrease our revenue and adversely impact sales of, and pricing of and reimbursement for, our products. For further discussion of the risks we face relating to regulation, see the section titled “Risk factors—Risks related to our business and industry— Our products could become subject to government regulation as medical devices by the FDA and other regulatory agencies even if we do not elect to seek regulatory clearance or approval to market our products for diagnostic purposes, which would adversely impact our ability to market and sell our products and harm our business. If our products become subject to FDA regulation, the regulatory clearance or approval and the maintenance of continued and post-market regulatory compliance for such products will be expensive, time-consuming, and uncertain both in timing and in outcome .” The federal Health Insurance Portability and Accountability Act of 1996 (HIPAA), as amended by the Health Information Technology for Economic and Clinical Health Act of 2009 (HITECH), and their implementing regulations, which impose obligations, including mandatory contractual terms, with respect to safeguarding the transmission, security and privacy of protected health information by covered entities subject to HIPAA, such as health plans, health care clearinghouses and healthcare providers, and their respective business associates that access protected health information. HITECH also created new tiers of civil monetary penalties, amended HIPAA to make civil and criminal penalties directly applicable to business associates in some cases, and gave state attorneys general new authority to file civil actions for damages or injunctions in federal courts to enforce the federal HIPAA laws and seek attorneys’ fees and costs associated with pursuing federal civil actions. In addition, in the U.S., numerous federal and state laws and regulations, including state data breach notification laws, state health information privacy laws, and federal and state consumer protection laws, govern the collection, use, disclosure, and protection of health-related and other personal information. For example, in June 2018, the State of California enacted the CCPA, which came into effect on January 1, 2020 and provides new data privacy rights for consumers and new operational requirements for companies. While we are not currently subject to the CCPA, we may in the future be required to comply with the CCPA, which may increase our compliance costs and potential liability. Furthermore, the CCPA could mark the beginning of a trend toward more stringent state privacy legislation in the U.S., which could increase our potential liability and adversely affect our business. Furthermore, the collection, use, storage, disclosure, transfer, or other processing of personal data regarding individuals in the European Economic Area (EEA), including personal health data, is subject to the GDPR, which became effective on May 25, 2018. The GDPR is wide-ranging in scope and imposes numerous requirements on 22 companies that process personal data, including requirements relating to processing health and other sensitive data, obtaining consent of the individuals to whom the personal data relates, providing information to individuals regarding data processing activities, implementing safeguards to protect the security and confidentiality of personal data, providing notification of data breaches, and taking certain measures when engaging third-party processors. The GDPR also imposes strict rules on the transfer of personal data to countries outside the EEA, including the United States, and permits data protection authorities to impose large penalties for violations of the GDPR, including potential fines of up to €20 million or 4% of annual global revenues, whichever is greater. The GDPR also confers a private right of action on data subjects and consumer associations to lodge complaints with supervisory authorities, seek judicial remedies, and obtain compensation for damages resulting from violations of the GDPR. In addition, the GDPR includes restrictions on cross-border data transfers. The GDPR may increase our responsibility and liability in relation to personal data that we process where such processing is subject to the GDPR, and we may be required to put in place additional mechanisms to ensure compliance with the GDPR, including as implemented by individual countries. Compliance with the GDPR will be a rigorous and time-intensive process that may increase our cost of doing business or require us to change our business practices, and despite those efforts, there is a risk that we may be subject to fines and penalties, litigation, and reputational harm in connection with our European activities. Further, the United Kingdom’s decision to leave the EU, often referred to as Brexit, has created uncertainty with regard to data protection regulation in the United Kingdom. As of January 1, 2021, and the expiry of transitional arrangements agreed to between the United Kingdom and EU, data processing in the United Kingdom is governed by a United Kingdom version of the GDPR (combining the GDPR and the Data Protection Act 2018), exposing us to two parallel regimes, each of which potentially authorizes similar fines and other potentially divergent enforcement actions for certain violations. Pursuant to the Trade and Cooperation Agreement, which went into effect on January 1, 2021, the United Kingdom and EU agreed to a specified period during which the United Kingdom will be treated like an EU member state in relation to processing and transfers of personal data for four months from January 1, 2021. This period may be extended by two further months. Furthermore, following the expiration of the specified period, there will be increasing scope for divergence in application, interpretation and enforcement of the data protection law as between the United Kingdom and EEA. For further discussion of the risks we face relating to regulation, see the section titled “Risk factors—Risks related to our business and industry— We are currently subject to, and may in the future become subject to additional, U.S., state and foreign laws and regulations imposing obligations on how we collect, store and process personal information. Our actual or perceived failure to comply with such obligations could harm our business. Ensuring compliance with such laws could also impair our efforts to maintain and expand our future customer base, and thereby decrease our revenue compliance with such laws could also impair our efforts to maintain and expand our future customer base, and thereby decrease our revenue. ” Intellectual Property Our success depends in part on our ability to obtain and maintain intellectual property protection for our products and technology. We use a variety of intellectual property protection strategies, including patents, trademarks, trade secrets and other methods of protecting proprietary information. As of December 31, 2021, our owned patents and patent applications, if issued, are expected to expire between 2023 and 2043, in each case without taking into account any possible patent term adjustments or extensions and assuming payment of all appropriate maintenance, renewal, annuity, or other governmental fees. Such patent portfolio owned by us includes: • pending U.S. and PCT patent applications that are directed to methods for sampling a proteome at specific levels of protein coverage, methods for sampling a proteome under particular assay conditions, and biosensor compositions for the same; • a pending PCT patent application that is directed to methods for interrogating protein pathways and PPIs with the biosensors; • a pending PCT application that is directed to methods for analyzing protein and nucleic acid molecules in a biological sample; 23 • an issued U.S. patent and a pending U.S. patent application directed to the identification and classification of biological states; and • an issued U.S. patent and a pending PCT patent application directed to methods for biomarker discovery, including an algorithm-based method that uses data sampled by the biosensor platform. We exclusively license U.S. patents and patent applications, as well as ex-U.S. patents and pending patent applications from BWH, as of December 31, 2021. These patents and patent applications are directed to methods for identifying a biological state, including classification and early detection of cancers and other diseases, using nanoparticle and biosensor compositions, as well as other nanoparticle compositions. Our in-licensed patents and patent applications, if issued, are expected to expire between 2027 and 2037, in each case without taking into account any possible patent term adjustments or extensions and assuming payment of all appropriate maintenance, renewal, annuity, or other governmental fees. In addition to licensing patents and patent applications from BWH, we have also non-exclusively licensed certain of our patents and patent applications to PrognomIQ for use in the field of human diagnostics. Pursuant to our agreement with PrognomIQ, we also assigned a patent application related to lung cancer biomarkers to PrognomIQ. In connection with our agreement with PrognomIQ, we have granted PrognomIQ a non-exclusive sublicense to certain patents and patent applications that we license from BWH under our license agreement with BWH for use in the field of human diagnostics. For further information on the intellectual property transfer and license agreement with PrognomIQ and the license agreement with BWH, see the section titled “Business —Collaboration and License Agreements.” We intend to pursue additional intellectual property protection to the extent we believe it would be beneficial and cost-effective. Our ability to stop third parties from making, using, selling, offering to sell, importing or otherwise commercializing any of our patented inventions, either directly or indirectly, will depend in part on our success in obtaining, defending and enforcing patent claims that cover our technology, inventions, and improvements. With respect to both our owned and in-licensed intellectual property, we cannot provide any assurance that any of our current or future patent applications will result in the issuance of patents in any particular jurisdiction, or that any of our current or future issued patents will effectively protect any of our products or technology from infringement or prevent others from commercializing infringing products or technology. Even if our pending patent applications are granted as issued patents, those patents may be challenged, circumvented or invalidated by third parties. Consequently, we may not obtain or maintain adequate patent protection for any of our products or technologies. In addition to our reliance on patent protection for our inventions, products and technologies, we also rely on trade secrets, know-how, confidentiality agreements and continuing technological innovation to develop and maintain our competitive position. For example, some elements of manufacturing processes, analytics techniques and processes, as well as computational-biological algorithms, and related processes and software, are based on unpatented trade secrets and know-how that are not publicly disclosed. Although we take steps to protect our proprietary information and trade secrets, including through contractual means with our employees, advisors and consultants, these agreements may be breached or may be unenforceable and we may not have adequate remedies. In addition, third parties may independently develop substantially equivalent proprietary information and techniques or otherwise gain access to our trade secrets or disclose our technology. As a result, we may not be able to meaningfully protect our trade secrets. For further discussion of the risks relating to intellectual property, see the section titled “Risk factors—Risks Related to our Intellectual Property.” Collaboration and License Agreements The Brigham and Women’s Hospital In December 2017, we entered into an exclusive patent license agreement with BWH, pursuant to which we obtained an exclusive, royalty-bearing, sub-licensable (with approval from BWH) license to certain U.S. and foreign patents and patent applications in one patent family related to methods for identifying a biological state using nanoparticle and biosensor compositions and other nanoparticle compositions to develop, manufacture, use and commercialize products and processes in all fields, including but not limited to therapeutic, diagnostic, or other uses, on a worldwide basis. In addition, we were also granted an exclusive, royalty-bearing, sub-licensable (with approval 24 from BWH) license to certain U.S. pending patent applications in another patent family to develop, manufacture, use and commercialize products and processes in all fields, including but not limited to therapeutic, diagnostic, or other uses, other than for the treatment of cancer through antigen-specific immune stimulation or the treatment of disease through immune tolerance or immune switching of lymphocyte subclasses. We may sublicense the patent rights licensed under the agreement subject to certain conditions, including obtaining the review and approval by BWH of such sublicense and any such sublicense must be consistent with and subject to the terms of the agreement. In consideration for the licenses granted under the agreement, we must pay BWH annual license fees prior to the first commercial sale of a licensed product that range in the low- to mid-five digit figures, and a low single digit royalty on net sales of licensed products beginning with the first commercial sale of a licensed product in any country during the term of the agreement. In the event we commercialize a product in the therapeutic space, we are also required to make certain drug-approval regulatory and commercialization milestone payments to BWH of up to a mid-seven digit figure in the aggregate for licensed products. In the event we sublicense any of the licensed intellectual property, we must pay BWH a percentage of any sublicense income received by us, which on a going-forward basis will be in the high single digits. Under the terms of the agreement, we are required to use commercially reasonable efforts to develop and commercialize the licensed products, including in accordance to certain developmental, funding, regulatory and commercialization milestones. BWH controls the prosecution, maintenance and enforcement of all licensed patents and patent applications under the agreement. Unless earlier terminated, the agreement continues until the expiration of the last to expire patent right licensed under the agreement. Subject to an applicable cure period, BWH may terminate the agreement if we fail to comply with applicable payments or diligence obligations or upon a breach of our obligation under the agreement, or for certain insolvency-related events. PrognomIQ In August 2020, we entered into an intellectual property transfer and license agreement and, in October 2020, we entered into an intellectual property sublicense agreement, in each case with PrognomIQ in connection with the spin-out of PrognomIQ. Under the intellectual property transfer and license agreement, we granted PrognomIQ a non-exclusive, perpetual, irrevocable (subject to termination for breach) license to certain patents and patent applications that we own and, under the intellectual property sublicense agreement, we granted a non-exclusive sublicense to certain patent applications exclusively licensed from BWH, in each case, relating to our core technology to develop, manufacture and commercialize licensed products for the field of human diagnostics on a worldwide basis. In addition, we assigned a patent application relating to lung cancer biomarkers, and transferred certain clinical samples, contracts and other related assets to PrognomIQ. PrognomIQ may extend such licensed and sublicensed rights to customers of licensed products. PrognomIQ is not required to pay us any royalties or fees pursuant to the intellectual property transfer and license agreement. In consideration of the non-exclusive sublicense to certain patent applications licensed from BWH, PrognomIQ paid us a low-five digit figure, and would pay a low single digit royalty, in an amount equivalent to what we would have to pay under our license with BWH, on net sales of sublicensed products beginning with the first commercial sale of a sublicensed product during the term of the intellectual property sublicense agreement. In the event we elect to grant an exclusive license to a third party in the field of human diagnostics for any of the patents and patent applications licensed or sublicensed, as applicable, to PrognomIQ under the respective agreements, we are required to first negotiate with PrognomIQ for a period of sixty days for a license or sublicense, as applicable, to such rights on reasonable terms. Furthermore, for a period of two years after the effective date, we are required to negotiate in good faith with PrognomIQ for a license or sublicense, as applicable, to any improvements to the patents and patent applications assigned or licensed or sublicensed, as applicable, under the intellectual property transfer and license agreement and the intellectual property sublicense agreement. Neither party may assign the intellectual property transfer and license agreement nor any rights or obligations under the agreement without the other party’s prior written consent, other than to an affiliate or pursuant to an acquisition. PrognomIQ may not assign the intellectual property sublicense agreement or any rights or obligations under the 25 agreement without our prior written consent, other than to an affiliate or pursuant to an acquisition, and in any event only with BWH’s prior written consent. Our right to assign the intellectual property sublicense agreement and any rights or obligations under the agreement is subject to the terms and conditions of our license with BWH. Unless terminated earlier, the terms of the both agreements continue until the expiration of the last to expire intellectual property right granted under such agreement. Either party may terminate either agreement for an uncured breach of the other party, upon which all licenses granted under such agreement to the breaching party will terminate. Collaborators Oregon Health & Science University (OHSU), an academic health center, and The Broad Institute of MIT and Harvard (Broad Institute), a biomedical and genomic research center, are our collaborators. Researchers at OHSU are using our product to facilitate various research efforts focused on proteomic profiling of various oncology versus control samples to determine protein signatures common between various cancer samples versus signatures found in control samples. Researchers at the Broad Institute use our product to analyze protein signatures in diseased vs. non-diseased samples undergoing drug perturbations in various clinical applications including cardiovascular disease. In January 2021, Discovery Life Sciences, a biomedical and genomic research center, became one of our collaborators. In March 2021, the Salk Institute for Biological Studies, a multi-disciplinary research institute, focused on addressing challenging health issues, including cancer, Alzheimer’s, diabetes, became one of our collaborators. In January 2022, we entered into an agreement to form the Proteogenomics Consortium with Discovery Life Sciences and SCIEX. Through this multi-year effort, Discovery will expand and offer unbiased proteomics capabilities to their existing genomics customers using the Proteograph Product Suite and the SCIEX ZenoTOF 7600 platform. Scientific Advisory Board We have assembled a highly qualified scientific advisory board composed of advisors who have deep expertise in the fields of nanotechnology, proteomics, genomics, medicine, regulatory compliance and data science. Our scientific advisory board is composed of Robert Langer, Sc.D., Mostafa Ronaghi, Ph.D., Steve Carr, Ph.D., Vivek Farias, Ph.D., Philip Kantoff, M.D., Erwin Böttinger, M.D., Charles Cantor, Ph.D., Bradley Hyman, M.D., Wolfgang Parak, Ph.D., Ralph Weissleder, M.D. and Luis Diaz, M.D. Employees Our employees are guided by our mission to imagine and pioneer news ways to decode the secrets of the proteome to improve human health. Our core values Better Together, Customer Centric, Difference Makers, People First and Trailblazers guide us on our path toward achieving our mission. Our core values set the foundation for how we conduct business, interact with each other and our customers and evaluate employee performance. As of December 31, 2021, we had 118 employees, all based in the United States, many of whom hold masters and doctorate degrees. Of these employees, 62 were engaged in in research and development activities, 13 were engaged in manufacturing and operations, and 43 were engaged in selling, general and administrative activities. We consider our relationship with our employees to be good. None of our employees are represented by a labor union or covered under a collective bargaining agreement. Our human capital resources objectives include, as applicable, identifying, recruiting, retaining, incentivizing and integrating our existing and new employees, advisors and consultants. The principal purposes of our equity and cash incentive plans are to attract, retain and reward personnel through the granting of stock-based and cash-based compensation awards, in order to increase stockholder value and the success of our company by motivating such individuals to perform to the best of their abilities and achieve our objectives. Corporate Information and History 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 http://seer.bio. 26 Information contained on, or that can be accessed through, our website should not be considered to be part of this Annual Report. We use Seer and Proteograph as trademarks in the United States and other countries. This Annual Report contains references to our trademarks and service marks and to those belonging to other entities. Solely for convenience, trademarks and trade names referred to in this Annual Report, including logos, artwork and other visual displays, may appear without the ® or TM symbols, but such references are not intended to indicate in any way that we will not assert, to the fullest extent under applicable law, our rights or the rights of the applicable licensor to these trademarks and trade names. We do not intend our use or display of other entities’ trade names, trademarks or service marks to imply a relationship with, or endorsement or sponsorship of us by, any other entity. References There are published studies referenced throughout this Annual Report and the citations for those studies are listed below. The studies listed below are not a part of this prospectus and are not incorporated by reference in this Annual Report. Bludau, I. et al. Proteomic and interactomic insights into the molecular basis of cell functional diversity. Nat Rev Molec Cell Biol 21, 327–340 (2020). Blume, J.E. et al. Rapid, deep and precise profiling of the plasma proteome with multi-nanoparticle protein corona. Nat. Commun. 11 (2020). Keshishian, H. et al. Quantitative, multiplexed workflow for deep analysis of human blood plasma and biomarker discovery by mass spectrometry. Nat. Proc. 12 1683-1701 (2017). Keshishian, H. et al. Multiplexed, quantitative workflow for sensitive biomarker discovery in plasma yields novel candidates for early myocardial injury . Molec & Cellular Proteomics 14(9) 2375-2393 (2015). Pietzner, M. et al. Synergistic insights into human health from aptamer- and antibody-based proteomic profiling. Nat Commun. 12, 6822 (2021). Schwenk, J.M. et al. The Human Plasma Proteome Draft of 2017: Building on the Human Plasma Peptide Atlas from Mass Spectrometry and Complementary Assays. J. Proteome Res. 16, 4299-4310 (2017). Szklarczyk, D., et al. STRING v11: Protein-protein association networks with increased coverage supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res . 47, D607-D613 (2019). Available Information We make our Annual Reports on Form 10-K, Quarterly Reports on Form 10-Q, Current Reports on Form 8-K, and amendments to those reports, available free of charge at our website as soon as reasonably practicable after they have been filed with the SEC. Our website address is http://seer.bio. Information on our website is not part of this report. The SEC maintains a website that contains the materials we file with the SEC at www.sec.gov. 27