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公开(公告)号：US11954596B2
公开(公告)日：2024-04-09
申请号：US17605224
申请日：2020-03-10
申请人： NantOmics, LLC , NantHealth, Inc.
IPC分类号： G06V10/82 , G06N3/08 , G06T7/00 , G06T7/194 , G06V10/764 , G06V10/766 , G06V10/77 , G06V10/774 , G06V20/69 , G16H10/40 , G16H30/40
CPC分类号： G06N3/08 , G06T7/0014 , G06T7/194 , G06V10/764 , G06V10/766 , G06V10/7715 , G06V10/774 , G06V10/7747 , G06V10/82 , G06V20/695 , G06V20/698 , G16H10/40 , G16H30/40 , G06T2207/10024 , G06T2207/20021 , G06T2207/20081 , G06T2207/20084 , G06T2207/30096
摘要： Techniques are provided for determining classifications based on WSIs. A varied-size feature map is generated for each training WSI by generating a grid of patches for the training WSI, segmenting the training WSI into tissue and non-tissue areas, and converting patches comprising the tissue areas into tensors. Bounding boxes are generated based on the patches comprising tissue areas and segmented into feature map patches. A fixed-size feature map is generated based on a subset of the feature map patches. A classifier model is trained to process fixed-size feature maps corresponding to the training WSIs such that, for each fixed-size feature map, the classifier model is operable to assign a WSI-level tissue or cell morphology classification or regression based on the tensors. A classification engine is configured to use the trained classifier model to determine a WSI-level tissue or cell morphology classification or regression for a test WSI.
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公开(公告)号：US20230420137A1
公开(公告)日：2023-12-28
申请号：US18465868
申请日：2023-09-12
申请人： Nantomics, LLC
IPC分类号： G16H50/20 , G16H20/40 , G16H70/60 , G16H10/40 , G16H10/60 , G16H50/30 , G16H50/70 , G16H20/10 , G16B20/20 , G16B20/10
CPC分类号： G16H50/20 , G16H20/40 , G16H70/60 , G16H10/40 , G16H10/60 , G16B25/10 , G16H50/70 , G16H20/10 , G16B20/20 , G16B20/10 , G16H50/30
摘要： Methods for analyzing omics data and using the omics data to determine prognosis of a cancer, to predict an outcome of a treatment, and/or to determine an effectiveness of a treatment are presented. In preferred methods, blood from a patient having a cancer or suspected to have a cancer is obtained and blood omics data for a plurality of cancer-related, inflammation-related, or DNA repair-related genes are obtained. A cancer score can be calculated based on the omics data, which then can be used to provide a cancer prognosis, a therapeutic recommendation, an effectiveness of a treatment.
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公开(公告)号：US20230377686A1
公开(公告)日：2023-11-23
申请号：US18359437
申请日：2023-07-26
发明人： Kevin B. Givechian , Kamil A. Wnuk , Chad Garner , Stephen Charles .Benz , Hermes J. Garban , Shahrooz Rabizadeh , Kayvan Niazi , Patrick Soon-Shiong
IPC分类号： G16B25/10 , C12Q1/6886
CPC分类号： G16B25/10 , C12Q1/6886 , C12Q2600/106 , C12Q2600/118 , C12Q2600/158
摘要： An immune gene expression signature is associated with favorable clinical features in Treg-enriched tumor samples and can be used to predict immunogenicity of a tumor, overall survival, and/or chemosensitivity.
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公开(公告)号：US11810672B2
公开(公告)日：2023-11-07
申请号：US16754088
申请日：2018-10-11
申请人： Nantomics
IPC分类号： G16H50/20 , G16H50/30 , G16H50/70 , G16H20/40 , G16H70/60 , G16H10/40 , G16H10/60 , G16H20/10 , G16B20/20 , G16B20/10 , G16B25/10
CPC分类号： G16H50/20 , G16B20/10 , G16B20/20 , G16H10/40 , G16H10/60 , G16H20/10 , G16H20/40 , G16H50/30 , G16H50/70 , G16H70/60 , G16B25/10
摘要： Methods for analyzing omics data and using the omics data to determine prognosis of a cancer, to predict an outcome of a treatment, and/or to determine an effectiveness of a treatment are presented. In preferred methods, blood from a patient having a cancer or suspected to have a cancer is obtained and blood omics data for a plurality of cancer-related, inflammation-related, or DNA repair-related genes are obtained. A cancer score can be calculated based on the omics data, which then can be used to provide a cancer prognosis, a therapeutic recommendation, an effectiveness of a treatment.
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公开(公告)号：US20230293651A1
公开(公告)日：2023-09-21
申请号：US18321635
申请日：2023-05-22
申请人： Nantomics LLC
CPC分类号： A61K39/0011 , G01N33/57484 , G16H20/00 , G16H20/40 , G16H70/60 , G16B20/20 , G16B30/10 , G16B20/00
摘要： Contemplated cancer treatments comprise recursive analysis of patient-, cancer-, and location-specific neoepitopes from various biopsy sites of a patient after treatment or between successive rounds of immunotherapy and/or chemotherapy to inform further immunotherapy. Recursive analysis preferably includes various neoepitope attributes to so identify treatment relevant neoepitopes.
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公开(公告)号：US11682195B2
公开(公告)日：2023-06-20
申请号：US16733192
申请日：2020-01-02
申请人： NantOmics, LLC
发明人： Bing Song , Gregory Chu
IPC分类号： G06T7/00 , G06K9/62 , G06T7/11 , G06N7/00 , G06V10/50 , G06V10/44 , G06N3/04 , G06T7/187 , G06V20/69 , G06V10/82 , G06F18/21 , G06F18/20 , G06F18/2411 , G06F18/23213 , G06F18/2413 , G06F18/2415 , G06N3/045 , G06N7/01 , G06V10/764 , G06V10/778 , G06N20/00
CPC分类号： G06V10/82 , G06F18/21 , G06F18/2193 , G06F18/23213 , G06F18/2411 , G06F18/24137 , G06F18/24147 , G06F18/24155 , G06F18/285 , G06F18/29 , G06N3/04 , G06N3/045 , G06N7/01 , G06T7/0012 , G06T7/11 , G06T7/187 , G06V10/454 , G06V10/50 , G06V10/764 , G06V10/7796 , G06V20/695 , G06N20/00 , G06T2207/10056 , G06T2207/20021 , G06T2207/20084 , G06T2207/20156 , G06T2207/30024
摘要： A computer implemented method of generating at least one shape of a region of interest in a digital image is provided. The method includes obtaining, by an image processing engine, access to a digital tissue image of a biological sample; tiling, by the image processing engine, the digital tissue image into a collection of image patches; identifying, by the image processing engine, a set of target tissue patches from the collection of image patches as a function of pixel content within the collection of image patches; assigning, by the image processing engine, each target tissue patch of the set of target tissue patches an initial class probability score indicating a probability that the target tissue patch falls within a class of interest, the initial class probability score generated by a trained classifier executed on each target tissue patch; generating, by the image processing engine, a first set of tissue region seed patches by identifying target tissue patches having initial class probability scores that satisfy a first seed region criteria, the first set of tissue region seed patches comprising a subset of the set of target tissue patches; generating, by the image processing engine, a second set of tissue region seed patches by identifying target tissue patches having initial class probability scores that satisfy a second seed region criteria, the second set of tissue region seed patches comprising a subset of the set of target tissue patches; calculating, by the image processing engine, a region of interest score for each patch in the second set of tissue region seed patches as a function of initial class probability scores of neighboring patches of the second set of tissue region seed patches and a distance to patches within the first set of issue region seed patches; and generating, by the image processing engine, one or more region of interest shapes by grouping neighboring patches based on their region of interest scores.
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公开(公告)号：US11623001B2
公开(公告)日：2023-04-11
申请号：US15292095
申请日：2016-10-12
申请人： NantOmics, LLC
发明人： Patrick Soon-Shiong , Stephen Charles Benz , Andrew Nguyen , Shahrooz Rabizadeh , Kayvan Niazi , Oleksandr Buzko , Jay Gardner Nelson
摘要： Methods and compositions for preparation and use of recombinant viruses or other recombinant expression systems are presented in which neoepitopes are first identified in a patient- and cancer-specific manner and then further filtered by HLA-match to the patient. Selected neoepitopes are then expression using sequence elements that direct the expressed neoepitope to the HLA-type (MHC-I and/or MHC-II subtype) that has desirable affinity to the filtered neoepitope.
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公开(公告)号：US11557375B2
公开(公告)日：2023-01-17
申请号：US17059157
申请日：2019-08-14
申请人： NantOmics, LLC
发明人： Jeremi Sudol , Kamil Wnuk
摘要： Techniques are provided for predicting MHC-peptide binding affinity. A plurality of training peptide sequences is obtained, and a neural network model is trained to predict MHC-peptide binding affinity using the training peptide sequences. An encoder of the neural network model comprising an RNN is configured to process an input training peptide sequence to generate a fixed-dimension encoding output by applying a final hidden state of the RNN at intermediate state outputs of the RNN to generate attention weighted outputs, and linearly combining the attention weighted outputs. A fully connected layer following the encoder is configured to process the fixed-dimension encoding output to generate an MHC-peptide binding affinity prediction output. A computing device is configured to use the trained neural network to predict MHC-peptide binding affinity for a test peptide sequence.
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公开(公告)号：US20220375602A1
公开(公告)日：2022-11-24
申请号：US17381675
申请日：2021-07-21
申请人： NantOmics, LLC , NantHealth, Inc. , NantCell, Inc.
发明人： Mustafa I. JABER , Liudmila A. BEZIAEVA , Bing SONG , Christopher W. SZETO , Stephen Charles BENZ , Shahrooz RABIZADEH
摘要： A method of determining a region of interest in an image of tissue of an individual by an apparatus including processing circuitry may include executing, by the processing circuitry, instructions that cause the apparatus to partition an image of tissue of an individual into a set of areas, identify a tissue type of each area of the image, and apply a classifier to the image to determine a region of interest, the classifier being configured to determine regions of interest based on the tissue types of the set of areas of the image.
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公开(公告)号：US11504420B2
公开(公告)日：2022-11-22
申请号：US16571008
申请日：2019-09-13
申请人： NANTOMICS, LLC
IPC分类号： A61K39/00 , C12N5/09 , C07K16/30 , G01N33/574 , C07K16/22 , C07K14/47 , A61K47/68 , C12N5/0783
摘要： Certain universal neoepitopes and cancer specific neoepitopes and methods therefore are presented that may be used in immunotherapy and cancer diagnosis. Preferred therapeutic and diagnostic compositions include antibodies or fragments thereof that bind to neoepitopes on cancer cells.
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