Seegene. has been granted a patent for a method and device that accurately determines the presence of a target analyte in a sample. The method utilizes a sigmoid function and fitting accuracy (R2 value) to minimize false positive results during analysis. GlobalData’s report on Seegene 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 Seegene, AI-assisted drug screening was a key innovation area identified from patents. Seegene's grant share as of June 2024 was 30%. Grant share is based on the ratio of number of grants to total number of patents.
Method for accurate target analyte detection in samples
The granted patent US12018318B2 outlines a method for analyzing a target analyte in a sample, primarily focusing on the detection of nucleic acids. The process begins with obtaining a data set derived from a signal-generating reaction, which includes various data points such as cycle numbers and signal values. The method involves amending this data set and generating a sigmoid function to fit the amended data. The accuracy of this fit is quantified using the R-square value (R²), which is then compared against a predetermined threshold to determine the presence or absence of the target analyte. Additional parameters, such as the displacement of the data set and the maximum slope of the sigmoid function, may also be utilized to enhance the determination process.
The patent further details specific methodologies for amending the data set, including the generation of a normalization coefficient based on reference signal values. It allows for the analysis of multiple signal-generating reactions conducted under varying conditions, such as different devices or sample types. Notably, the method can detect multiple target nucleic acid sequences from a single reaction vessel by employing distinct signal-generating means that operate at different detection temperatures. The patent also describes the extraction of signals for different target sequences and the use of quadratic functions for data baselining. Additionally, it includes provisions for computer-readable storage mediums that can execute the described methods, emphasizing the integration of computational tools in the analysis process.
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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.
