Illumina has patented a method to determine cancer class by analyzing cell-free DNA molecules from a subject’s biological sample. By sequencing and identifying relative copy numbers at genomic locations, a machine learning model predicts the cancer class based on training data. GlobalData’s report on Illumina 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 Illumina, Microfluidics automation was a key innovation area identified from patents. Illumina's grant share as of February 2024 was 40%. Grant share is based on the ratio of number of grants to total number of patents.
Determining cancer class using cell-free dna sequencing
A recently granted patent (Publication Number: US11929148B2) outlines a method for determining the cancer class of a subject by analyzing cell-free DNA molecules in a biological sample. The process involves extracting these molecules, removing those longer than a specified threshold length, sequencing the sample, identifying relative copy numbers at various genomic locations, and applying this data to a machine learning model trained to determine the cancer class based on genomic information.
The method detailed in the patent covers a range of cancer-related classifications, including the presence of cancer, cancer stage, type, and prognosis. By utilizing a machine learning model trained with labeled data, the approach aims to provide accurate cancer classification based on genomic information obtained from the biological sample. The patent also specifies the use of a specific threshold length for DNA molecules, the number of sequence reads required, and the application of methylation state data in the analysis process. Additionally, the method emphasizes the importance of confidence levels in determining the cancer class, comparing the results obtained through this approach with those from traditional genetic information analysis methods.
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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.
