# US 10,504,615 B2 · Using cancer or pre-cancer subject sequencing data and a database of therapy biomarker distributions to determine normalized biomarker scores and generate a graphical user interface > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,504,615 B2 - Document ID: US10504615B2 - Status: Granted - Kind: B2 - Application number: 16/456,370 - Filed: 2019-06-28 - Published: 2019-10-24 - Granted: 2019-12-10 - Earliest claimed: 2017-06-13 - Assignees: BostonGene Corporation - Applicants: BostonGene Corporation - Inventors: Alexander Bagaev; Feliks Frenkel; Ravshan Ataullakhanov - Web page: https://patentgrep.com/patent/US10504615B2 ## CPC - G16B 45/00: ICT specially adapted for bioinformatics-related data visualisation, e.g. displaying of maps or networks - C12Q 1/6886: for cancer (immunoassay for cancer G01N33/575) - G06F 16/285: {Clustering or classification} - G06F 17/18: for evaluating statistical data {, e.g. average values, frequency distributions, probability functions, regression analysis (forecasting specially adapted for a specific administrative, business or logistic context G06Q10/04)} - G16B 5/00: ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks - G16B 5/20: Probabilistic models - G16B 20/00: ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations - G16B 25/10: Gene or protein expression profiling; Expression-ratio estimation or normalisation - G16B 30/00: ICT specially adapted for sequence analysis involving nucleotides or amino acids - G16B 40/00: ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding - G16B 40/20: Supervised data analysis - G16B 40/30: Unsupervised data analysis - G16B 50/00: ICT programming tools or database systems specially adapted for bioinformatics - G16B 50/30: Data warehousing; Computing architectures - G16H 10/20: for electronic clinical trials or questionnaires - G16H 20/00: ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance - G16H 20/10: relating to drugs or medications, e.g. for ensuring correct administration to patients - G16H 20/40: relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture - G16H 50/20: for computer-aided diagnosis, e.g. based on medical expert systems - G16H 50/30: for calculating health indices; for individual health risk assessment - G16H 50/50: for simulation or modelling of medical disorders - G16H 50/70: for mining of medical data, e.g. analysing previous cases of other patients - G16H 70/20: relating to practices or guidelines - C12Q 2600/156: Polymorphic or mutational markers - C12Q 2600/158: Expression markers - G16B: BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY - C12Q: MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS (immunoassay G01N33/53); COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA ## Abstract 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. ## Claims ### Claim 1 A system, comprising: at least one computer hardware processor; at least one database that stores biomarker information; and at least one non-transitory computer-readable storage medium storing processor-executable instructions that, when executed by the at least one computer hardware processor, cause the at least one computer hardware processor to perform: obtaining sequencing data about at least one biological sample of a subject known to have or suspected of having cancerous cells or pre-cancerous cells; accessing, in the at least one database, biomarker information indicating a distribution of values for each biomarker in at least a reference subset of a plurality of biomarkers across a respective group of people, each of the plurality of biomarkers being associated with at least one therapy in a plurality of therapies, the plurality of biomarkers including a first biomarker and the biomarker information including a first distribution of values for the first biomarker; determining, using both the sequencing data and the biomarker information: a first set of normalized scores for a first set of biomarkers associated with a first therapy in the plurality of therapies, and a second set of normalized scores for a second set of biomarkers associated with a second therapy in the plurality of therapies, wherein determining the first set of normalized scores comprises determining a first normalized score for the first biomarker at least in part by determining a statistical score for the first biomarker based on the first distribution of values for the first biomarker; determining, using the first set of normalized scores and second set of normalized scores, respective first and second therapy scores for the first and second therapies; generating a graphical user interface (GUI) that comprises: a first portion associated with the first therapy in the plurality of therapies, the first portion including a first plurality of GUI elements, each of the first plurality of GUI elements being associated with a respective biomarker in the first set of biomarkers and having at least one visual characteristic determined based on a normalized score of the respective biomarker in the first set of normalized scores; a second portion associated with the second therapy in the plurality of therapies, the second portion including a second plurality of GUI elements different from the first plurality of GUI elements, each of the second plurality of GUI elements being associated with a respective biomarker in the second set of biomarkers 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. ### Claim 2 (depends on 1) The system of claim 1, wherein the processor-executable instructions further cause the at least one processor to perform: determining, using both the sequencing data and the biomarker information, a third set of normalized scores for a third set of biomarkers associated with a third therapy in the plurality of therapies. ### Claim 3 (depends on 2) The system of claim 2, wherein the GUI further comprises: a third portion associated with the third therapy in the plurality of therapies, the third portion including a third plurality of GUI elements, each of the third plurality of GUI elements being associated with a respective biomarker in the third set of biomarkers and having at least one visual characteristic determined based on a normalized score of the respective biomarker in the third set of normalized scores. ### Claim 4 (depends on 1) The system of claim 1, wherein determining the first and second therapy scores for the first and second therapies is performed using a statistical model. ### Claim 5 (depends on 4) The system of claim 4, wherein the statistical model comprises a linear model, a generalized linear model, a neural network model, a Bayesian regression model, an adaptive non-linear regression model, a mixture model, and/or a random forest regression model. ### Claim 6 (depends on 1) The system of claim 1, wherein determining the statistical score for the first biomarker comprises determining a Z-score based on the first distribution of values for the first biomarker. ### Claim 7 (depends on 6) The system of claim 6, wherein determining the first normalized score for the first biomarker comprises: determining an un-normalized score for the first biomarker using the sequencing data, and determining a normalized score for the first biomarker based on the un-normalized score and the Z-score. ### Claim 8 (depends on 1) The system of claim 1, wherein determining the first therapy score comprises: determining weights for two or more scores in the first set of normalized scores; and determining the first therapy score as a weighted sum of the two or more scores with summands of the sum being weighted by the determined weights. ### Claim 9 (depends on 1) The system of claim 1, wherein the plurality of therapies comprise at least two therapies selected from the group consisting 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. ### Claim 10 (depends on 1) The system of claim 1, wherein the at least one visual characteristic comprises color of a GUI element and/or size of the GUI element. ### Claim 11 (depends on 1) The system of claim 1, wherein the first portion and the second portion are positioned, relative to one another in the GUI, based on relative magnitude of the first therapy score and the second therapy score. ### Claim 12 The system of 1, wherein each of the plurality of biomarkers is selected from the group consisting of: a genetic biomarker, a cellular biomarker, a saccharide biomarker, a lipid biomarker, a heterocyclic biomarker, an elementary compound biomarker, an imaging biomarker, an anthropological biomarker, a personal habit biomarker, a disease-state biomarker, and an expression biomarker. ### Claim 13 (depends on 1) The system of claim 1, wherein each of the plurality of biomarkers is selected from the group consisting of biomarkers listed in Table 2. ### Claim 14 At least one non-transitory computer-readable storage medium storing processor-executable instructions that, when executed by the at least one computer hardware processor, cause the at least one computer hardware processor to perform: obtaining sequencing data about at least one biological sample of a subject known to have or suspected of having cancerous cells or pre-cancerous cells; accessing, in at least one database, biomarker information indicating a distribution of values for each biomarker in at least a reference subset of a plurality of biomarkers across a respective group of people, each of the plurality of biomarkers being associated with at least one therapy in a plurality of therapies, the plurality of biomarkers including a first biomarker and the biomarker information including a distribution of values for the first biomarker; determining, using both the sequencing data and the biomarker information: a first set of normalized scores for a first set of biomarkers associated with a first therapy in the plurality of therapies, and a second set of normalized scores for a second set of biomarkers associated with a second therapy in the plurality of therapies, wherein determining the first set of normalized scores comprises determining a first normalized score for the first biomarker at least in part by determining a statistical score for the first biomarker based on the first distribution of values for the first biomarker; determining, using the first set of normalized scores and second set of normalized scores, respective first and second therapy scores for the first and second therapies; generating a graphical user interface (GUI) that comprises: a first portion associated with the first therapy in the plurality of therapies, the first portion including a first plurality of GUI elements, each of the first plurality of GUI elements being associated with a respective biomarker in the first set of biomarkers and having at least one visual characteristic determined based on a normalized score of the respective biomarker in the first set of normalized scores; a second portion associated with the second therapy in the plurality of therapies, the second portion including a second plurality of GUI elements different from the first plurality of GUI elements, each of the second plurality of GUI elements being associated with a respective biomarker in the second set of biomarkers 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. ### Claim 15 (depends on 14) The at least one non-transitory computer-readable storage medium of claim 14, wherein determining the first and second therapy scores for the first and second therapies is performed using a statistical model. ### Claim 16 (depends on 14) The at least one non-transitory computer-readable storage medium of claim 14, wherein determining the statistical score for the first biomarker comprises determining a Z-score based on the first distribution of values for the first biomarker. ### Claim 17 (depends on 16) The at least one non-transitory computer-readable storage medium of claim 16, wherein determining the first normalized score for the first biomarker comprises: determining an un-normalized score for the first biomarker using the sequencing data, and determining a normalized score for the first biomarker based on the un-normalized score and the Z-score. ### Claim 18 (depends on 14) The at least one non-transitory computer-readable storage medium of claim 14, wherein the plurality of therapies comprise at least two therapies selected from the group consisting 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. ### Claim 19 (depends on 14) The at least one non-transitory computer-readable storage medium of claim 14, wherein the at least one visual characteristic comprises color of a GUI element and/or size of the GUI element. ### Claim 20 (depends on 14) The at least one non-transitory computer-readable storage medium of claim 14, wherein the first portion and the second portion are positioned, relative to one another in the GUI, based on relative magnitude of the first therapy score and the second therapy score. ### Claim 21 (depends on 14) The at least one non-transitory computer-readable storage medium of claim 14, wherein each of the plurality of biomarkers is selected from the group consisting of biomarkers listed in Table 2. ### Claim 22 (depends on 14) The at least one non-transitory computer-readable storage medium of claim 14, wherein each of the plurality of biomarkers is selected from the group consisting of: a genetic biomarker, a cellular biomarker, a saccharide biomarker, a lipid biomarker, a heterocyclic biomarker, an elementary compound biomarker, an imaging biomarker, an anthropological biomarker, a personal habit biomarker, a disease-state biomarker, and an expression biomarker. ### Claim 23 A method, comprising: obtaining sequencing data about at least one biological sample of a subject known to have or suspected of having cancerous cells or pre-cancerous cells; accessing, in at least one database, biomarker information indicating a distribution of values for each biomarker in at least a reference subset of a plurality of biomarkers across a respective group of people, each of the plurality of biomarkers being associated with at least one therapy in a plurality of therapies, the plurality of biomarkers including a first biomarker and the biomarker information including a distribution of values for the first biomarker; determining, using both the sequencing data and the biomarker information: a first set of normalized scores for a first set of biomarkers associated with a first therapy in the plurality of therapies, and a second set of normalized scores for a second set of biomarkers associated with a second therapy in the plurality of therapies, wherein determining the first set of normalized scores comprises determining a first normalized score for the first biomarker at least in part by determining a statistical score for the first biomarker based on the first distribution of values for the first biomarker; determining, using the first set of normalized scores and second set of normalized scores, respective first and second therapy scores for the first and second therapies; generating a graphical user interface (GUI) that comprises: a first portion associated with the first therapy in the plurality of therapies, the first portion including a first plurality of GUI elements, each of the first plurality of GUI elements being associated with a respective biomarker in the first set of biomarkers and having at least one visual characteristic determined based on a normalized score of the respective biomarker in the first set of normalized scores; a second portion associated with the second therapy in the plurality of therapies, the second portion including a second plurality of GUI elements different from the first plurality of GUI elements, each of the second plurality of GUI elements being associated with a respective biomarker in the second set of biomarkers 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. ### Claim 24 (depends on 23) The method of claim 23, wherein determining the first and second therapy scores for the first and second therapies is performed using a statistical model. ### Claim 25 (depends on 23) The method of claim 23, wherein determining the statistical score for the first biomarker comprises determining a Z-score based on the first distribution of values for the first biomarker. ### Claim 26 (depends on 25) The method of claim 25, wherein determining the first normalized score for the first biomarker comprises: determining an un-normalized score for the first biomarker using the sequencing data, and determining a normalized score for the first biomarker based on the un-normalized score and the Z-score. ### Claim 27 (depends on 23) The method of claim 23, wherein the plurality of therapies comprise at least two therapies selected from the group consisting 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. ### Claim 28 (depends on 23) The method of claim 23, wherein the at least one visual characteristic comprises color of a GUI element and/or size of the GUI element. ### Claim 29 (depends on 23) The method of claim 23, wherein the first portion and the second portion are positioned, relative to one another in the GUI, based on relative magnitude of the first therapy score and the second therapy score. ### Claim 30 (depends on 23) The method of claim 23, wherein each of the plurality of biomarkers is selected from the group consisting of biomarkers listed in Table 2.