Freenome had two patents in artificial intelligence during Q2 2024. Freenome Inc’s patents filed in Q2 2024 describe systems and methods for analyzing blood-based cancer diagnostic tests using multiple classes of molecules. The system utilizes machine learning to analyze cell-free DNA, cell-free microRNA, and circulating proteins from a biological sample, increasing sensitivity and specificity by leveraging independent information between signals. The system separates molecule classes, identifies feature sets for machine learning models, performs assays on each class, and obtains output classifications for detecting specified properties in the sample. GlobalData’s report on Freenome gives a 360-degree view of the company including its patenting strategy. Buy the report here.
Smarter leaders trust GlobalData
Freenome had no grants in artificial intelligence as a theme in Q2 2024.
Recent Patents
Application: Machine learning implementation for multi-analyte assay development and testing (Patent ID: US20240202603A1)
Freenome Inc. has developed systems and methods for blood-based cancer diagnostics that utilize machine learning to analyze multiple classes of molecules, such as cell-free DNA, microRNA, and circulating proteins, from biological samples. By employing various assays like whole-genome sequencing and quantitative immunoassay, the system can enhance the sensitivity and specificity of diagnostics by leveraging independent information between signals. The system receives a biological sample, separates different classes of molecules, identifies feature sets for machine learning input, performs assays on each molecule class, creates a feature vector from measured values, and uses a machine learning model to classify whether the sample exhibits a specified property, such as lung cancer.
The patent claims detail a method and system for screening individuals for lung cancer by assaying different classes of molecules in biological samples using various assays, including whole-genome sequencing and enzymatic methyl sequencing. The system involves identifying feature sets, preparing feature vectors, training a machine learning model with training samples, and inputting feature vectors to classify individuals based on the presence of lung cancer. The system can analyze classes of molecules like cell-free DNA and polyamino acids, including peptides, proteins, and autoantibodies, to provide accurate and reliable cancer screening. Additionally, the system can utilize different machine learning models like linear discriminant analysis and support vector machines to enhance the accuracy of lung cancer classification based on measured values from plasma samples.
To know more about GlobalData’s detailed insights on Freenome, buy the report here.
Data Insights
From
The gold standard of business intelligence.
Blending expert knowledge with cutting-edge technology, GlobalData’s unrivalled proprietary data will enable you to decode what’s happening in your market. You can make better informed decisions and gain a future-proof advantage over your competitors.
GlobalData, the leading provider of industry intelligence, provided the underlying data, research, and analysis used to produce this article.
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.
