MENLO PARK, Calif.–(BUSINESS WIRE)–Personalis, Inc. (Nasdaq: PSNL), a leader in advanced genomics for cancer, today announced the launch of its Systematic HLA Epitope Ranking Pan Algorithm (SHERPA), the company’s proprietary, machine learning-based tool for the comprehensive identification and characterization of cancer neoantigens. Integrated into the Personalis® NeXT Platform™, SHERPA enables the development of new neoantigen-based diagnostic biomarkers, such as the company’s proprietary Neoantigen Presentation Score (NEOPS™), and novel personalized therapies.
Personalis Announces the Launch of SHERPA™ for High-Accuracy Neoantigen Prediction and Cancer Diagnostic Biomarker Development
Data presented at the SITC Annual Meeting in November 2020 showed SHERPA outperforming commonly used neoantigen binding prediction tools in clinical tumor samples. “With more accurate neoantigen presentation prediction, we are looking to enable a new generation of precision oncology applications,” said Richard Chen, MD, Personalis CSO. “Trained on a proprietary immunopeptidomics dataset derived from engineered cell lines, SHERPA improves neoantigen presentation prediction compared to other in silico methods. With this advancement, SHERPA can enable more predictive biomarkers for cancer therapy as well as facilitate the development of neoantigen-targeting, personalized cancer therapies. Our recently-launched NEOPS is one example of a SHERPA-derived composite biomarker that has shown promise in predicting immunotherapy response in cancer patients.”
While most conventional in silico methods generally only assess the potential MHC-binding affinity and stability of identified peptides, SHERPA goes a step further by incorporating features relating to the antigen processing machinery and RNA abundance to generate a presentation rank for each detected peptide. This serves to determine the relative likelihood of a given neoantigen being presented and undergoing immunosurveillance.
This launch represents the broader commercial release of SHERPA, which is currently being leveraged by Personalis’ preferred partner, Sarepta Therapeutics, to characterize immune response to precision genetic therapeutics in patients with rare diseases, demonstrating the applicability of this machine learning tool in disease areas beyond cancer.
About Personalis, Inc.
Personalis, Inc. is a leader in cancer genomics, with a focus on data, scale, efficiency and quality. Personalis operates one of the largest sequencing operations globally. In oncology, Personalis is transforming the development of next-generation therapies by providing more comprehensive molecular data about each patient’s cancer and immune response. The Personalis NeXT Platform is designed to adapt to the complex and evolving understanding of cancer, providing its biopharmaceutical customers with information on all of the approximately 20,000 human genes, together with the immune system, from a single tissue sample. The Personalis Clinical Laboratory is GxP aligned as well as CLIA’88-certified and CAP-accredited. For more information, please visit www.personalis.com and follow Personalis on Twitter (@PersonalisInc).
All statements in this press release that are not historical are “forward-looking statements” within the meaning of U.S. securities laws, including statements relating to attributes or advantages of SHERPA, NEOPS or the Personalis NeXT Platform, the company’s business opportunities, leadership or growth, or other future events. Such forward-looking statements involve risks and uncertainties, including those related to the COVID-19 pandemic, that could cause actual results to differ materially from any anticipated results or expectations expressed or implied by such statements. Factors that could materially affect actual results can be found in Personalis’ filings with the U.S. Securities and Exchange Commission, including the company’s most recent reports on Forms 8-K, 10-K and 10-Q, and include those listed under the caption “Risk Factors.” Personalis disclaims any obligation to update such forward-looking statements.