Freenome‘s patented method screens for colorectal advanced adenoma by analyzing multiple classes of molecules in a biological sample using various assays. Utilizing machine learning, the system identifies features, prepares feature vectors, and inputs them into the model to classify the presence of the condition accurately. GlobalData’s report on Freenome gives a 360-degree view of the company including its patenting strategy. Buy the report here.

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According to GlobalData’s company profile on Freenome, AI-assisted genome sequencing was a key innovation area identified from patents. Freenome's grant share as of January 2024 was 6%. Grant share is based on the ratio of number of grants to total number of patents.

Blood-based cancer diagnostic test using multiple molecule classes

Source: United States Patent and Trademark Office (USPTO). Credit: Freenome Inc

A recently granted patent (Publication Number: US11847532B2) outlines a method for screening individuals for colorectal advanced adenoma. The method involves assaying a variety of molecules in a biological sample, such as whole blood, plasma, or serum, using different assays to obtain sets of measured values. These molecules include nucleic acids and polyamino acids, with specific assays like methylation sequencing applied to cell-free DNA (cfDNA) and polyamino acids. Features corresponding to the properties of these molecules are identified and used to create a feature vector for input into a machine learning model. The model, trained using samples with and without colorectal advanced adenoma, classifies whether an individual has the condition based on the input feature vector.

Furthermore, the method includes various classes of molecules like peptides, proteins, autoantibodies, and circulating proteins, with assays ranging from whole-genome sequencing to mass spectrometry. The machine learning model can be constructed using different techniques such as linear discriminant analysis, random forest, support vector machine, decision trees, and more. The biological sample, which can be plasma, provides measured values including methylation patterns of cell-free DNA. This comprehensive method aims to accurately screen individuals for colorectal advanced adenoma by analyzing a wide range of molecules and utilizing advanced machine learning models for classification.

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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.