Seegene has developed a method for calibrating data sets of target analytes in samples, reducing signal variations between instruments. The technique uses normalization coefficients based on reference values and cycles, applicable to various analytical instruments like real-time PCR. This innovation enhances diagnostic data 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 February 2024 was 32%. Grant share is based on the ratio of number of grants to total number of patents.
Method for calibrating data sets to reduce signal variations
A recently granted patent (Publication Number: US11915796B2) discloses a method for reducing inter- and intra-instrument signal variations of a data set of a target analyte in a sample. The method involves providing a normalization coefficient for calibrating the data set by using a reference value, a reference cycle, and the data set obtained from a signal-generating process such as polymerase chain reaction (PCR) or real-time PCR. The normalization coefficient is defined by establishing a relationship between the reference value and a signal value at a cycle of the data set corresponding to the reference cycle. By applying this normalization coefficient, a calibrated data set with calibrated signal values is obtained, which can be used for qualitative or quantitative detection of the target analyte in the sample. The method also includes steps for removing instrument blank signals, selecting reference cycles, and determining reference values to ensure accurate calibration.
Furthermore, the patent includes claims related to using identical or different reference values for calibrating multiple data sets obtained from different signal-generating processes or instruments. It also describes the process of determining the reference value based on signal change values and provides a mathematical equation for obtaining calibrated signal values. Additionally, the patent covers the use of a non-transitory computer-readable storage medium containing instructions for configuring a processor to perform the calibration method, as well as a device comprising a computer processor and the storage medium for analyzing the data set of the target analyte in a sample. Overall, the patented method offers a systematic approach to reduce signal variations in data sets obtained from signal-generating processes, ensuring accurate and reliable detection of target analytes in samples.
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