Ozette Announces New Suite of Machine Learning-Powered Computational Analytics Solutions Combined with High-Dimensional Full-Spectrum Cytometry Data Generation to Accelerate Decision-Making for Clinical Biomarker Teams

Machine Learning


Ozette Technologies, Inc., a technology-driven life sciences company, announces the launch of its Assay-to-Insights product, a streamlined, state-of-the-art process for investigating the immune system in fresh and frozen samples. The Ozette Assay-to-Insights combines three of his technologies developed by the company. One is world-class data generation at the Ozette Laboratory based on Good Clinical Laboratory Practices (GCLP) guidelines. Rapid computational monitoring of predefined biomarker endpoints using Ozette Endpoints™. Unbiased discovery and annotation of single-cell cytometry data with Ozette Discovery™. Insights generated from Ozette Endpoints™ and Ozette Discovery™ are available through the Ozette Platform™, a cloud-based system that enables clinical teams to interact and explore cytometry data in a central dashboard.

Alongside these, Ozette is announcing the Assay-to-Insights Partner Grant Program. Researchers who meet Ozette’s eligibility requirements are encouraged to apply and inquire through Ozette’s website.

Ozette Endpoints™ provide clinical biomarker teams with rapid access to decision-enabling data. This advance in speed and quality surpasses conventional solutions that can take orders of magnitude longer to identify target or novel cell phenotypes. Working with Ozette’s in-house data science and immunology experts, Ozette Endpoints™ ensure the robustness, reproducibility, transparency, and rapid results clinical trial teams need to make informed decisions quickly. allow it to be received.

“Ozette Endpoints™ provide clinical researchers with a robust tool for measuring key biomarker endpoints with unmatched speed and resolution in an integrated platform,” said Vice President of Translational Sciences at Ozette. said Cherie Green of “Ozette’s in-house clinical biomarker experts, combined with our purpose-built computational analytics platform, ensure transparency and visibility of the process while increasing efficiency and robustness. We look forward to introducing Ozette Endpoints™ in 2023 and sharing this game-changing technology that will redefine the future of clinical trials and, ultimately, patient outcomes.

Ozette Discovery™ provides best-in-class, unbiased, robust, and transparent automated cell population detection and annotation from single-cell cytometry data. This technology will change the way lab and bioinformatics scientists spend their time. This will enable all scientists to review and explore all single-cell data in context and in real-time. When cytometric experiments are analyzed using Ozette Discovery™, results can be explored on her Ozette platform. It is an innovative computer environment that facilitates seamless collaboration, supports long-term data collection observed in clinical trials, and is rapid, uniform, standardized and transparent. Data analysis of single-cell cytometry data from diverse single-cell proteomics techniques. Scientists from immunologists to computational biologists can collaborate, share, and access all data and results from a single source of truth in one dashboard, reviewing and manipulating data on demand can.

“We have developed technology that enables Ozette to support the entire therapeutic development cycle, from preclinical studies to FDA approval. We will advance the world’s understanding of immunology and disease by deciphering the insights that make up the world,” said Ozette CEO and Co-Founder Ali Ansary. “We provide biopharmaceutical companies and academic partners with interpretable and reproducible biology so patients can receive life-saving treatments faster.”

Four Ozette scientific presentations and poster sessions at CYTO 2023 highlight the unprecedented speed, analytical depth and reproducibility of Ozette’s core technology.

  • High-dimensional cytometry: Computational Methods for Effective Exploration and Comparison of High-Dimensional Cytometry Data and 2D Embeddings (Presented by Trevor Manz)
  • Data science: A platform for comprehensive and standardized analysis of large-scale, high-dimensional cytometry experiments using interpretable machine learning (Courtesy of Greg Finak)
  • Single cell “-omics”: Robust and interpretable discovery of cell populations of antibody-tagged proteins in single-cell RNAseq (presented by Denise Allen)
  • Commercial Tutorial: Revolutionizing Single Cell Immune Profiling and Computational Analysis Using the Ozette Platform (Presented by Cherie Green and Greg Finak)
  • Poster session: Leverage AI/ML to analyze the effects of leukocyte isolation and cryopreservation on surface protein expression in peripheral blood samples using a 48-color full-spectrum cytometric pan-immune profiling panel (By Kurt Van Gunst presented)

For more information on presentations and poster sessions, please click here. Contact us for more information about Ozette’s products.

Follow Ozette on LinkedIn and twitter For the latest news and information, see the Ozette team live at CYTO (booth #539).

About Ozette

Ozette Technologies, Inc. plans a transformational leap in cell discovery and annotation of the human immune system. This Seattle-based life sciences company leverages new and differentiated ML technologies to build a breakthrough high-resolution single-cell immune monitoring platform and high-resolution data corpus. Founded in late 2020, Ozette was spun out of Fred Hutchinson Cancer Center and cultivated at the Allen AI Institute. Ozette’s multidisciplinary team is made up of a wealth of scientists, statisticians, engineers, and designers with extensive experience across Genentech, Google, Microsoft, Amazon, Airbnb, and more. Ozette’s team also includes leaders and pioneers in the field of medical research and single-cell analysis, including founder Dr. Ali Ansally, and scientists Greg Finnak, Evan Green and Rafael Gotthard. It contains.





Source link

Leave a Reply

Your email address will not be published. Required fields are marked *