Tempus Labs had seven patents in artificial intelligence during Q1 2024. Tempus Labs Inc filed patents for a system and method to analyze de-identified patient data to predict patient responses to treatments, aiding clinicians in discovering therapeutic insights efficiently. Additionally, methods, systems, and software were developed for detecting gene fusions, splice variants, and evaluating RNA-seq sequencing complexity in cancer patients through mRNA boundary analysis, providing valuable insights for personalized medicine. GlobalData’s report on Tempus Labs gives a 360-degree view of the company including its patenting strategy. Buy the report here.

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Tempus Labs grant share with artificial intelligence as a theme is 57% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.

Recent Patents

Application: Method and process for predicting and analyzing patient cohort response, progression, and survival (Patent ID: US20240087747A1)

The patent filed by Tempus Labs Inc. describes a system and method for analyzing de-identified patient data to create dynamic user interfaces that can predict responses of specific patient populations to certain treatments. By automating the analysis of patterns in clinical, molecular, phenotypic, and response data, clinicians can efficiently evaluate large datasets to potentially uncover therapeutic insights. The method involves provisioning a cloud computing environment with access to databases and pre-defined notebooks, allowing users to select features defining a dataset representing a cohort of cancer patients. The system generates a notebook interface with user interface elements to launch specific notebooks for analysis, monitors user resource usage, and modifies the environment accordingly.

The claims associated with the patent detail the method's steps, including loading datasets into the cloud environment, restricting access to certain data, applying preconfigured visualizations to analyzed datasets, and enabling direct comparisons between different cohorts of subjects. The system also allows for the use of machine learning models, optimal parameter identification, and user-defined models or analyses within the notebooks. Additionally, the patent covers the system's ability to provision separate servers or virtual machines, define workspaces with preconfigured services, manage access rights for multiple users, and limit data egress from the cloud environment. Overall, the patent outlines a comprehensive approach to leveraging patient data for predictive analysis and therapeutic insights in a secure and user-friendly manner.

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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.