Patents by Inventor Akshata Ramrao UDYAVAR

Akshata Ramrao UDYAVAR has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • TUMOR PHENOTYPE PREDICTION USING GENOMIC ANALYSES INDICATIVE OF DIGITAL-PATHOLOGY METRICS
    Publication number: 20240105283
    Abstract: A machine-learning model (e.g., a clustering model) may be used to predict a phenotype of a tumor based on expression levels of a set of genes. The set of genes may have been identified using a same or different machine-learning model. The phenotype may include an immune-excluded, immune-desert or an inflamed/infiltrated phenotype. A treatment strategy and/or treatment recommendation may be identified based on the predicted phenotype.
    Type: Application
    Filed: December 8, 2023
    Publication date: March 28, 2024
    Applicant: Genentech, Inc.
    Inventors: Akshata Ramrao Udyavar, Yulei Wang, Cleopatra Kozlowski
  • CD8+ t cell based immunosuppressive tumor microenvironment detection method
    Patent number: 11881286
    Abstract: A machine-learning model (e.g., a clustering model) may be used to predict a phenotype of a tumor based on expression levels of a set of genes. The set of genes may have been identified using a same or different machine-learning model. The phenotype may include an immune-excluded, immune-desert or an inflamed/infiltrated phenotype. A treatment strategy and/or treatment recommendation may be identified based on the predicted phenotype.
    Type: Grant
    Filed: September 25, 2020
    Date of Patent: January 23, 2024
    Assignee: GENENTECH, INC.
    Inventors: Akshata Ramrao Udyavar, Yulei Wang, Cleopatra Kozlowski
  • TUMOR PHENOTYPE PREDICTION USING GENOMIC ANALYSES INDICATIVE OF DIGITAL-PATHOLOGY METRICS
    Publication number: 20210098082
    Abstract: A machine-learning model (e.g., a clustering model) may be used to predict a phenotype of a tumor based on expression levels of a set of genes. The set of genes may have been identified using a same or different machine-learning model. The phenotype may include an immune-excluded, immune-desert or an inflamed/infiltrated phenotype. A treatment strategy and/or treatment recommendation may be identified based on the predicted phenotype.
    Type: Application
    Filed: September 25, 2020
    Publication date: April 1, 2021
    Inventors: Akshata Ramrao UDYAVAR, Yulei WANG, Cleopatra KOZLOWSKI