F. Hoffmann-La Roche had 72 patents in artificial intelligence during Q1 2024. The patents filed by F. Hoffmann-La Roche Ltd in Q1 2024 cover a range of innovative technologies in the field of healthcare and biotechnology. These include systems and methods for processing digital pathology images to generate tumor immunophenotypes, predicting optimal treatment metrics based on patient characteristics, forecasting cell viability in bioreactors during biomolecule manufacturing processes using machine learning, designing proteins through sequence modification and function prediction, and evaluating geographic atrophy progression using retinal images and predictive models. These patents showcase the company’s commitment to advancing medical research and technology. GlobalData’s report on F. Hoffmann-La Roche gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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F. Hoffmann-La Roche grant share with artificial intelligence as a theme is 15% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Tumor immunophenotyping based on spatial distribution analysis (Patent ID: US20240104948A1)
The patent filed by F. Hoffmann-La Roche Ltd. describes systems and methods for processing digital pathology images to determine tumor immunophenotypes. The techniques involve accessing digital pathology images depicting biological samples with reactive regions, subdividing the images into tiles, calculating local-density measurements for different biological object types in each tile, generating spatial-distribution metrics based on these measurements, and determining the tumor immunophenotype based on the metrics. The method aims to provide insights into the spatial relationships between tumor cells and immune cells within the images, which can help in characterizing the tumor microenvironment.
Furthermore, the patent outlines the use of various spatial-distribution metrics such as Jaccard index, Sørensen index, and Moran's index to quantify the spatial relationships between different biological object types in the digital pathology images. By analyzing these metrics, the system can classify the tumor immunophenotype as "desert," "excluded," or "inflamed" based on the density of immune cells and tumor cells in the images. The method also includes generating results that can assist in assessing the medical condition of a subject, predicting treatment outcomes, and determining eligibility for clinical trials based on the spatial distribution of biological objects in the images. Overall, the patent introduces a comprehensive approach to analyzing digital pathology images for tumor immunophenotyping, which can have significant implications for cancer diagnosis and treatment planning.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
