Seer, Inc. (Nasdaq: SEER) today announced the publication of a study demonstrating the performance of the technology platform underlying the Proteograph Product Suite™ for deep, unbiased, precise, scalable proteomics.
The paper, entitled “Engineered Nanoparticles Enable Deep Proteomics Studies at Scale by Leveraging Tunable Nano-Bio Interactions,” was published in The Proceedings of the National Academy of Sciences (PNAS) by an interdisciplinary team of scientists from Seer, Oregon Health Sciences University, Massachusetts Institute of Technology, and Harvard Medical School.
The study examines in detail the relationship between the unique physicochemical properties of a panel of proprietary engineered nanoparticles (NPs) and the diverse pattern of protein sampling that is enabled by a unique nano-bio interface that is created between a given NP surface and a given biological sample.
The Seer machine learning model developed in this paper enhances understanding of the molecular interactions that occur at the nano-bio interface and shows how future NPs may be rationally designed using machine learning to differentially interrogate specific protein families.
The proprietary nanoparticle technology described in the PNAS paper forms the foundation for Seer’s Proteograph Product Suite, which is the only at scale solution available to deliver peptide and amino acid level resolution that enables identification of proteins and protein variants in an unbiased manner for deep, precise, and scalable proteomics studies. Understanding the proteome in health and disease, which is comprised of millions of protein variants, is believed to be key to unlocking biological insight to enable precision medicine.
“We are excited about the publication of this seminal paper in PNAS that further highlights the technological and scientific underpinning of the Proteograph Product Suite, opening our aperture to see the vast molecular information embedded in our proteome,” said Omid Farokhzad, Chief Executive Officer and Chair of Seer. “We believe that a deeper understanding of the proteome, which can only be achieved in an unbiased way since the vast majority of the information is unknown, is key to the next wave of biological discoveries. These are exciting times for the field, and we’re at a watershed moment where our access to deep, unbiased proteomics information at scale is no longer constrained.”