PathAI. has been granted a patent for a method that trains a model to predict patient survival times using annotated pathology images. The model assesses patient subsets likely to benefit from experimental treatments compared to standard or control treatments, enhancing clinical trial outcomes. GlobalData’s report on PathAI 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 PathAI, AI-assisted medical imaging was a key innovation area identified from patents. PathAI's grant share as of July 2024 was 46%. Grant share is based on the ratio of number of grants to total number of patents.
Predicting patient survival time using pathology images
The patent US12073948B1 outlines a method and system for utilizing a trained model to identify patient subsets likely to benefit from experimental treatments in clinical trials. The process involves analyzing annotated pathology images from two groups of patients: one receiving the experimental treatment and the other receiving a control treatment. By processing various features extracted from these images, the model predicts survival data for both groups. The accuracy of the model in identifying patients who may benefit from the experimental treatment is assessed through comparisons of the predicted survival data from both groups. Additionally, the method includes performing subset survival analyses and selecting specific patient subsets based on their predicted responses to the treatment.
The patent further details the features used in the analysis, which include various tumor and immune cell characteristics, and specifies that the trained model may employ techniques such as generalized linear models, random forests, support vector machines, or gradient boosted trees. The system is designed to be implemented on computer hardware, utilizing non-transitory computer-readable storage media to execute the necessary instructions. This innovation aims to enhance the precision of patient selection in clinical trials, potentially leading to improved treatment outcomes by identifying those most likely to respond favorably to new therapies.
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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
