Patents by Inventor Alexander Bagaev
Alexander Bagaev has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Publication number: 20240161284Abstract: Techniques for processing multiplexed immunofluorescence (MxIF) images. The techniques include obtaining at least one MxIF image of a same tissue sample, obtaining information indicative of locations of cells in the at least one MxIF image, identifying multiple groups of cells in the at least one MxIF image at least in part by determining feature values for at least some of the cells using the at least one MxIF image and the information indicative of locations of the at least some cells in the at least one MxIF image and grouping the at least some of the cells into the multiple groups using the determined feature values, and determining at least one characteristic of the tissue sample using the multiple cell groups.Type: ApplicationFiled: January 18, 2024Publication date: May 16, 2024Applicant: BostonGene CorporationInventors: Viktor Svekolkin, Ilia Galkin, Ekaterina Postovalova, Ravshan Ataullakhanov, Alexander Bagaev, Arina Varlamova, Pavel Ovcharov
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Patent number: 11984200Abstract: Various methods, systems, computer readable media, and graphical user interfaces (GUIs) are presented and described that enable a subject, doctor, or user to characterize or classify various types of cancer precisely. Additionally, described herein are methods, systems, computer readable media, and GUIs that enable more effective specification of treatment and improved outcomes for patients with identified types of cancer. Some embodiments of the methods, systems, computer readable media, and GUIs described herein comprise obtaining RNA expression data and/or whole exome sequencing (WES) data for a biological sample from a plurality of subjects, determining a respective plurality of molecular-functional (MF) profiles for the plurality of subjects, and storing the plurality of MF profiles in association with information identifying the particular cancer type.Type: GrantFiled: June 12, 2018Date of Patent: May 14, 2024Assignee: BostonGene CorporationInventors: Alexander Bagaev, Feliks Frenkel, Nikita Kotlov, Ravshan Ataullakhanov, Olga Isaeva
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Patent number: 11915422Abstract: Techniques for processing multiplexed immunofluorescence (MxIF) images. The techniques include obtaining at least one MxIF image of a same tissue sample, obtaining information indicative of locations of cells in the at least one MxIF image, identifying multiple groups of cells in the at least one MxIF image at least in part by determining feature values for at least some of the cells using the at least one MxIF image and the information indicative of locations of the at least some cells in the at least one MxIF image and grouping the at least some of the cells into the multiple groups using the determined feature values, and determining at least one characteristic of the tissue sample using the multiple cell groups.Type: GrantFiled: December 27, 2021Date of Patent: February 27, 2024Assignee: BostonGene CorporationInventors: Viktor Svekolkin, Ilia Galkin, Ekaterina Postovalova, Ravshan Ataullakhanov, Alexander Bagaev, Arina Varlamova, Pavel Ovcharov
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Publication number: 20240029884Abstract: Techniques for determining whether a sample obtained from a subject includes cells having homologous recombination deficiency (HRD). The techniques include: obtaining data about segments of the subject's genome; identifying a first subset of the segments, the first subset including segments associated with at least one chromosome arm of the genome and having a common copy number; identifying a second subset of the segments, each of the segments of the second subset having (i) a respective copy number different from the common copy number and (ii) a respective length that satisfies a predetermined length criterion; determining a proportion of a number of segments in the second subset to a number of chromosome arms of the at least one chromosome arm; and determining, based on the determined proportion, whether the biological sample includes cells having HRD.Type: ApplicationFiled: July 14, 2023Publication date: January 25, 2024Inventors: Nikita Kotlov, Aleksei Shevkoplias, Alexandra Melnikova, Alexander Bagaev, Mariia Guryleva
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Publication number: 20240006029Abstract: Techniques for determining therapy scores for at least two of an anti-PD1 therapy, an anti-CTLA4 therapy, an IL-2 therapy, an IFN alpha therapy, an anti-cancer vaccine therapy, an anti-angiogenic therapy, and an anti-CD20 therapy. The techniques include determining, using sequencing data for the subject and information indicating distribution of biomarker values across one or more reference populations, a first set of normalized biomarker scores for a first set of biomarkers associated with a first therapy; and a second set of normalized biomarker scores for a second set of biomarkers associated with a second therapy; providing the first set of normalized biomarker scores as input to a statistical model to obtain a first therapy score for the first therapy; and providing the second set of normalized biomarker scores as input to the statistical model to obtain a second therapy score for the second therapy.Type: ApplicationFiled: September 1, 2023Publication date: January 4, 2024Applicant: BostonGene CorporationInventors: Alexander Bagaev, Feliks Frenkel, Ravshan Ataullakhanov
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Patent number: 11842797Abstract: Techniques for determining therapy scores for at least two of an anti-PD1 therapy, an anti-CTLA4 therapy, an IL-2 therapy, an IFN alpha therapy, an anti-cancer vaccine therapy, an anti-angiogenic therapy, and an anti-CD20 therapy. The techniques include determining, using sequencing data for the subject and information indicating distribution of biomarker values across one or more reference populations, a first set of normalized biomarker scores for a first set of biomarkers associated with a first therapy; and a second set of normalized biomarker scores for a second set of biomarkers associated with a second therapy; providing the first set of normalized biomarker scores as input to a statistical model to obtain a first therapy score for the first therapy; and providing the second set of normalized biomarker scores as input to the statistical model to obtain a second therapy score for the second therapy.Type: GrantFiled: June 28, 2019Date of Patent: December 12, 2023Assignee: BostonGene CorporationInventors: Alexander Bagaev, Feliks Frenkel, Ravshan Ataullakhanov
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Patent number: 11705220Abstract: Techniques for generating therapy biomarker scores and visualizing same. The techniques include determining, using a patient's sequence data and distributions of biomarker values across one or more reference populations, a first set of normalized scores for a first set of biomarkers associated with a first therapy, and a second set of normalized scores for a second set of biomarkers associated with a second therapy, generating a graphical user interface (GUI) including a first portion associated with the first therapy and having at least one visual characteristic determined based on a normalized score of the respective biomarker in the first set of normalized scores; and a second portion associated with a second therapy and having at least one visual characteristic determined based on a normalized score of the respective biomarker in the second set of normalized scores; and displaying the generated GUI.Type: GrantFiled: April 22, 2021Date of Patent: July 18, 2023Assignee: BostonGene CorporationInventors: Alexander Bagaev, Feliks Frenkel, Ravshan Ataullakhanov
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Publication number: 20230178178Abstract: Techniques for determining one or more cell composition percentages from expression data. The techniques include obtaining expression data for a biological sample, the biological sample previously obtained from a subject, the expression data including first expression data associated with a first set of genes associated with a first cell type; determining a first cell composition percentage for the first cell type using the expression data and one or more non-linear regression models including a first non-linear regression model, wherein the first cell composition percentage indicates an estimated percentage of cells of the first cell type in the biological sample, wherein determining the first cell composition percentage for the first cell type comprises: processing the first expression data with the first non-linear regression model to determine the first cell composition percentage for the first cell type; and outputting the first cell composition percentage.Type: ApplicationFiled: December 15, 2022Publication date: June 8, 2023Applicant: BostonGene CorporationInventors: Aleksandr Zaitsev, Maksim Chelushkin, Ilya Cheremushkin, Ekaterina Nuzhdina, Vladimir Zyrin, Daniiar Dyikanov, Alexander Bagaev, Ravshan Ataullakhanov, Boris Shpak
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Publication number: 20230132030Abstract: Aspects of the disclosure relate to methods for determining whether or a subject is likely to respond to certain adoptive cell therapies (e.g., chimeric antigen receptor (CAR) T-cell therapy, etc.). In some embodiments, the methods comprise the steps of identifying a subject as having a tumor microenvironment (TME) type based upon a molecular-functional (MF) expression signature of the subject, and determining whether or not the subject is likely to respond to a chimeric antigen receptor (CAR) T-cell therapy based upon the TME type. In some embodiments, the methods comprise determining the lymphoma microenvironment (LME) type of a lymphoma (e.g., Diffuse Large B cell lymphoma (DLBCL)) subject and identifying the subjects prognosis based upon the LME type determination.Type: ApplicationFiled: December 23, 2022Publication date: April 27, 2023Applicant: BostonGene CorporationInventors: Nikita Kotlov, Georgy Sagaradze, Alexander Bagaev, Grigorii Nos, Lev Begniagin, Dmitry Kravchenko, Anna Gribkova
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Patent number: 11587642Abstract: Techniques for determining one or more cell composition percentages from expression data. The techniques include obtaining expression data for a biological sample, the biological sample previously obtained from a subject, the expression data including first expression data associated with a first set of genes associated with a first cell type; determining a first cell composition percentage for the first cell type using the expression data and one or more non-linear regression models including a first non-linear regression model, wherein the first cell composition percentage indicates an estimated percentage of cells of the first cell type in the biological sample, wherein determining the first cell composition percentage for the first cell type comprises: processing the first expression data with the first non-linear regression model to determine the first cell composition percentage for the first cell type; and outputting the first cell composition percentage.Type: GrantFiled: March 29, 2022Date of Patent: February 21, 2023Assignee: BostonGene CorporationInventors: Aleksandr Zaitsev, Maksim Chelushkin, Ilya Cheremushkin, Ekaterina Nuzhdina, Vladimir Zyrin, Daniiar Dyikanov, Alexander Bagaev, Ravshan Ataullakhanov, Boris Shpak
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Patent number: 11568959Abstract: Aspects of the disclosure relate to methods for determining whether or a subject is likely to respond to certain adoptive cell therapies (e.g., chimeric antigen receptor (CAR) T-cell therapy, etc.). In some embodiments, the methods comprise the steps of identifying a subject as having a tumor microenvironment (TME) type based upon a molecular-functional (MF) expression signature of the subject, and determining whether or not the subject is likely to respond to a chimeric antigen receptor (CAR) T-cell therapy based upon the TME type. In some embodiments, the methods comprise determining the lymphoma microenvironment (LME) type of a lymphoma (e.g., Diffuse Large B cell lymphoma (DLBCL)) subject and identifying the subject's prognosis based upon the LME type determination.Type: GrantFiled: July 6, 2021Date of Patent: January 31, 2023Assignee: BostonGene CorporationInventors: Nikita Kotlov, Georgy Sagaradze, Alexander Bagaev, Grigorii Nos, Lev Bedniagin, Dmitry Kravchenko, Anna Gribkova
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Publication number: 20220389512Abstract: Various methods, systems, computer readable media, and graphical user interfaces (GUIs) are presented and described that enable a subject, doctor, or user to characterize or classify various types of cancer precisely. Additionally, described herein are methods, systems, computer readable media, and GUIs that enable more effective specification of treatment and improved outcomes for patients with identified types of cancer. Some embodiments of the methods, systems, computer readable media, and GUIs described herein comprise obtaining RNA expression data and/or whole exome sequencing (WES) data for a biological sample; determining a molecular-functional (MF) profile for a subject using the data; determining visual characteristics GUI elements using the data; generating a GUI personalized to the subject using the determined visual characteristics; and presenting the generated personalized GUI to a user.Type: ApplicationFiled: March 18, 2022Publication date: December 8, 2022Applicant: BostonGene CorporationInventors: Alexander Bagaev, Feliks Frenkel, Nikita Kotlov, Ravshan Ataullakhanov, Olga Isaeva
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Publication number: 20220375543Abstract: Aspects of the disclosure relate to methods for improving compatibility of nucleic acid sequencing data obtained using different techniques. The disclosure is based, in part, on methods for mapping expression levels for genes expressed in a biological sample and obtained from a subject using a first protocol to expression levels as would have been determined through a second protocol if the second protocol were used to process the biological sample instead of the first protocol.Type: ApplicationFiled: May 18, 2022Publication date: November 24, 2022Inventors: Nikita Kotlov, Kirill Shaposhnikov, Maksim Chelushkin, Ilya Cheremushkin, Artur Baisangurov, Svetlana Podsvirova, Svetlana Khorkova, Dmitry Kravchenko, Cagdas Tazearslan, Alexander Bagaev, Ekaterina Postovalova
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Publication number: 20220372580Abstract: Techniques for using machine learning to estimate tumor expression levels of genes in tumor cells. The techniques include obtaining expression data for a set of genes comprising a first plurality of genes associated with the tumor cells and a second plurality of genes associated with tumor microenvironment cells; determining the tumor expression levels of the first plurality of genes in the tumor cells using a plurality of machine learning models, the determining comprising: generating a first set of features for the first gene; providing the first set of features as input to the first machine learning model to obtain an output comprising a tumor microenvironment expression level estimate of the first gene in the tumor microenvironment cells; and determining a first tumor expression level for the first gene in the tumor cells using the output of the first machine learning model and a total expression level for the first gene.Type: ApplicationFiled: April 29, 2022Publication date: November 24, 2022Applicant: BostonGene CorporationInventors: Aleksandr Zaitsev, Alexander Bagaev, Maksim Chelushkin, Valentina Beliaeva, Boris Shpak, Daniiar Dyikanov, Anastasia Zotova, Michael F. Goldberg, Cagdas Tazearslan
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Publication number: 20220319638Abstract: Aspects of the disclosure relate to methods, systems, computer-readable storage media, and graphical user interfaces (GUIs) that are useful for characterizing subjects having certain cancers, for example renal cell carcinomas such as clear cell renal carcinoma (ccRCC). The disclosure is based, in part, on methods for determining the renal cancer (RC) tumor microenvironment (TME) type (RC TME type) of a renal cancer subject and the subject's prognosis and/or likelihood of responding to certain therapies (e.g., immunotherapy or tyrosine kinase inhibitors) based upon the renal cancer type determination.Type: ApplicationFiled: March 9, 2022Publication date: October 6, 2022Inventors: James Hsieh, Alexander Bagaev, Natalia Miheecheva, Ekaterina Postovalova, Danil Stupichev, Kristina Perevoshchikova
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Patent number: 11430545Abstract: Various methods, systems, computer readable media, and graphical user interfaces (GUIs) are presented and described that enable a subject, doctor, or user to characterize or classify various types of cancer precisely. Additionally, described herein are methods, systems, computer readable media, and GUIs that enable more effective specification of treatment and improved outcomes for patients with identified types of cancer. Some embodiments of the methods, systems, computer readable media, and GUIs described herein comprise obtaining RNA expression data and/or whole exome sequencing (WES) data for a biological sample; determining a molecular-functional (MF) profile for the subject at least in part by determining first and second visual characteristics for first and second GUI elements using the data; generating a personalized GUI personalized to the subject using the first and second visual characteristics; and presenting the generated personalized GUI to a user.Type: GrantFiled: June 12, 2018Date of Patent: August 30, 2022Assignee: BostonGene CorporationInventors: Alexander Bagaev, Feliks Frenkel, Nikita Kotlov, Ravshan Ataullakhanov, Olga Isaeva
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Publication number: 20220230707Abstract: Techniques for determining one or more cell composition percentages from expression data. The techniques include obtaining expression data for a biological sample, the biological sample previously obtained from a subject, the expression data including first expression data associated with a first set of genes associated with a first cell type; determining a first cell composition percentage for the first cell type using the expression data and one or more non-linear regression models including a first non-linear regression model, wherein the first cell composition percentage indicates an estimated percentage of cells of the first cell type in the biological sample, wherein determining the first cell composition percentage for the first cell type comprises: processing the first expression data with the first non-linear regression model to determine the first cell composition percentage for the first cell type; and outputting the first cell composition percentage.Type: ApplicationFiled: March 29, 2022Publication date: July 21, 2022Applicant: BostonGene CorporationInventors: Aleksandr Zaitsev, Maksim Chelushkin, Ilya Cheremushkin, Ekaterina Nuzhdina, Vladimir Zyrin, Daniiar Dyikanov, Alexander Bagaev, Ravshan Ataullakhanov, Boris Shpak
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Patent number: 11373733Abstract: Various methods, systems, computer readable media, and graphical user interfaces (GUIs) are presented and described that enable a subject, doctor, or user to characterize or classify various types of cancer precisely. Additionally, described herein are methods, systems, computer readable media, and GUIs that enable more effective specification of treatment and improved outcomes for patients with identified types of cancer. Some embodiments of the methods, systems, computer readable media, and GUIs described herein comprise obtaining RNA expression data and/or whole exome sequencing (WES) data for a biological sample from a subject; determining a molecular-functional (MF) profile for the subject; identifying an MF profile cluster with which to associate the MF profile for the subject; and clustering the plurality of MF profiles to obtain the MF profile clusters.Type: GrantFiled: July 2, 2020Date of Patent: June 28, 2022Assignee: BostonGene CorporationInventors: Alexander Bagaev, Feliks Frenkel, Nikita Kotlov, Ravshan Ataullakhanov, Olga Isaeva
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Patent number: 11367509Abstract: Various methods, systems, computer readable media, and graphical user interfaces (GUIs) are presented and described that enable a subject, doctor, or user to characterize or classify various types of cancer precisely. Additionally, described herein are methods, systems, computer readable media, and GUIs that enable more effective specification of treatment and improved outcomes for patients with identified types of cancer. Some embodiments of the methods, systems, computer readable media, and GUIs described herein comprise obtaining RNA expression data and/or whole exome sequencing (WES) data for a biological sample from a subject; determining a molecular-functional (MF) profile for the subject; identifying an MF profile cluster with which to associate the MF profile for the subject; and clustering the plurality of MF profiles to obtain the MF profile clusters.Type: GrantFiled: June 12, 2018Date of Patent: June 21, 2022Assignee: BostonGene CorporationInventors: Alexander Bagaev, Feliks Frenkel, Nikita Kotlov, Ravshan Ataullakhanov, Olga Isaeva
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Publication number: 20220186318Abstract: Aspects of the disclosure relate to methods, systems, computer-readable storage media, and graphical user interfaces (GUIs) that are useful for characterizing subjects having certain cancers, for example lymphomas. The disclosure is based, in part, on methods for determining the tumor microenvironment (TME) type of a lymphoma (e.g., follicular lymphoma) subject and identifying the subject's prognosis based upon the TME type determination.Type: ApplicationFiled: December 10, 2021Publication date: June 16, 2022Applicant: BostonGene CorporationInventors: Mark Meerson, Nikita Kotlov, Olga Kudryashova, Alexander Bagaev