InVitae. has filed a patent for a system, method, and computer program product to optimize determining the phenotypic impact of molecular variants in subjects by incorporating, updating, and auditing evidence models. The method involves recording evidence data, evaluating performance metrics, generating hash values, and ranking evidence models for accurate predictions. GlobalData’s report on InVitae 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 InVitae, AI-assisted genome sequencing was a key innovation area identified from patents. InVitae's grant share as of January 2024 was 38%. Grant share is based on the ratio of number of grants to total number of patents.
Predicting phenotypic impact of molecular variants using evidence models
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The patent application (Publication Number: US20240006021A1) describes a computer-implemented method for predicting the phenotypic impact of a molecular variant of interest. The method involves recording an evidence model comprising evidence data, evaluating validation performance data based on production data, generating a hash value of supporting data, evaluating test performance data, ranking the evidence model, and providing the predicted phenotypic impact using the best-performing evidence model. The validation and test performance data are computed using a uniform set of performance metrics, ensuring an unbiased estimate of the predictive performance of the evidence model at different times. The method aims to provide accurate predictions of phenotypic impacts for molecular variants, particularly those with unknown or unavailable phenotypic impacts at the time of model generation.
Furthermore, the patent application includes additional claims related to the performance metrics used, the recording and importing of evidence models, the use of distributed databases, and the generation of evidence models based on production data using various techniques such as machine learning, functional assays, or biophysical simulations. The method also involves providing auditing records to the variant interpretation terminal, enabling the audit of supporting data and the time of creation. Additionally, the application covers the storage of evidence models on non-transitory computer-readable storage mediums and the use of systems comprising computer hardware processors to implement the predictive method. Overall, the patent application outlines a comprehensive approach to predicting phenotypic impacts of molecular variants, emphasizing the importance of unbiased performance evaluation and accurate ranking of evidence models for optimal predictions.
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