F. Hoffmann-La Roche has patented a method for generating a module to determine analyte concentration in body fluid samples. The method involves using image data from test strips, recorded by various devices, to train a neural network model for accurate analysis. The system and method aim to improve analyte concentration determination in bodily fluids. GlobalData’s report on F. Hoffmann-La Roche 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 F. Hoffmann-La Roche, Cancer treatment biomarkers was a key innovation area identified from patents. F. Hoffmann-La Roche's grant share as of February 2024 was 54%. Grant share is based on the ratio of number of grants to total number of patents.

Method for generating module to determine analyte concentration in body fluid

Source: United States Patent and Trademark Office (USPTO). Credit: F. Hoffmann-La Roche Ltd

A recently granted patent (Publication Number: US11928814B2) discloses a method for generating a module that can determine the concentration of an analyte in a sample of body fluid. The method involves providing a set of measurement data derived from images of test strips, recording color transformations in response to applying body fluid containing the analyte. A neural network model is generated through machine learning using this data, and a software-implemented module with an analyzing algorithm is created to determine analyte concentration in subsequent samples. The module analyzes color information from images of test strips to provide concentration data for the analyte in the sample.

Furthermore, the patent describes a system for generating and utilizing the module to determine analyte concentration in body fluid samples. The system includes data processors that provide measurement data, generate a neural network model through machine learning, and create a module with an analyzing algorithm. This module can then be used to determine analyte concentration in a present sample by analyzing color information from images of test strips. The patent also includes a method for generating the module, involving obtaining images of test strips using mobile devices, constructing and training a neural network model based on the image data, and generating a module capable of determining analyte concentration in body fluid samples.

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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