# US 11,906,518 B2 · Tumor cell analysis using aptamers and microfluidic systems > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,906,518 B2 - Document ID: US11906518B2 - Status: Granted - Kind: B2 - Application number: 17/236,538 - Filed: 2021-04-21 - Published: 2022-10-27 - Granted: 2024-02-20 - Earliest claimed: 2021-04-21 - Assignees: X Development LLC - Applicants: X Development LLC - Inventors: Ivan Grubisic; Ray Nagatani - Web page: https://patentgrep.com/patent/US11906518B2 ## CPC - G01N 33/5308: {for analytes not provided for elsewhere, e.g. nucleic acids, uric acid, worms, mites} - G01N 33/575: for cancer - C12N 15/115: Aptamers, i.e. nucleic acids binding a target molecule specifically and with high affinity without hybridising therewith {; Nucleic acids binding to non-nucleic acids, e.g. aptamers} - C40B 30/04: by measuring the ability to specifically bind a target molecule, e.g. antibody-antigen binding, receptor-ligand binding - G01N 33/5759: {involving compounds localised on the membrane of tumour or cancer cells} - G16B 5/20: Probabilistic models - G16B 35/10: Design of libraries - G16C 20/20: Identification of molecular entities, parts thereof or of chemical compositions - G16C 20/50: Molecular design, e.g. of drugs - G16C 20/70: Machine learning, data mining or chemometrics - C12N 2310/16: Aptamers - C12N 2320/10: in screening processes - G01N 2500/10: involving cells - G01N 2800/52: Predicting or monitoring the response to treatment, e.g. for selection of therapy based on assay results in personalised medicine; Prognosis - G16B 40/20: Supervised data analysis - G01N: INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES (measuring or testing apparatus or processes other than immunoassay, involving enzymes or microorganisms C12M, C12Q) - C12N: MICROORGANISMS OR ENZYMES; COMPOSITIONS THEREOF; PROPAGATING, PRESERVING, OR MAINTAINING MICROORGANISMS; MUTATION OR GENETIC ENGINEERING; CULTURE MEDIA (microbiological testing media C12Q1/00) - C40B: COMBINATORIAL CHEMISTRY; LIBRARIES, e.g. CHEMICAL LIBRARIES (in silico combinatorial libraries of nucleic acids, proteins or peptides G16B35/00; in silico combinatorial chemistry G16C20/60) - G16B: BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY - G16C: COMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE ## Abstract Methods described herein include receiving data from flowing a plurality of aptamers over a sample of tumor cells randomly affixed to a surface of a microfluidic device. The tumor cells may include one or more unknown tumor subtypes of cells. The plurality of aptamers may include a plurality of aptamer families. Each aptamer family of the plurality of aptamer families may be determined to bind to at least one possible subtype of the tumor cells. The data may include a measure of binding affinity of each aptamer family to the tumor cells. The method may include analyzing the measure of the binding affinity of each aptamer family to the tumor cells. The analyzing may include classifying the binding affinity. The method may also include determining one or more aptamer families that characterize the one or more unknown tumor subtypes of cells based on the classifying. ## Claims ### Claim 1 A method comprising: assaying a sample of tumor cells using a microfluidic device, wherein the assaying comprises: randomly affixing the tumor cells to a surface of the microfluidic device; and flowing a plurality of aptamers over the tumor cells to allow the aptamers to interact and bind to the tumor cells, wherein: the tumor cells comprise one or more unknown subtypes of the tumor cells, the plurality of aptamers comprises a plurality of aptamer families, and each aptamer family of the plurality of aptamer families is determined by a prediction model to bind to at least one possible subtype of the tumor cells; obtaining data from assaying the sample of tumor cells, wherein the data comprises a measure of binding affinity of each aptamer family to the tumor cells; analyzing the measure of the binding affinity of each aptamer family to the tumor cells, wherein the analyzing comprises classifying the binding affinity of each aptamer family to the tumor cells; and determining one or more aptamer families that characterize the one or more unknown subtypes of the tumor cells based on the classifying. ### Claim 2 (depends on 1) The method of claim 1, wherein the measure of the binding affinity of each aptamer family is an elution time. ### Claim 3 (depends on 1) The method of claim 1, wherein the measure of the binding affinity each aptamer family is an amount of aptamers that bind to the tumor cells. ### Claim 4 (depends on 1) The method of claim 1, further comprising identifying the one or more unknown subtypes of the tumor cells to obtain one or more identified subtypes based on: (i) the determining of the one or more aptamer families that characterize the one or more subtypes of the tumor cells based on the classifying, and (ii) the at least one possible subtype of the tumor cells that each aptamer family is determined to bind to by the prediction model. ### Claim 5 (depends on 4) The method of claim 4, further comprising determining a treatment protocol for a subject having the tumor cells based on the one or more identified subtypes. ### Claim 6 (depends on 5) The method of claim 5, further comprising treating the subject based on the treatment protocol. ### Claim 7 (depends on 6) The method of claim 6, wherein the sample is a liquid biopsy of the tumor cells obtained from a fluid of the subject. ### Claim 8 (depends on 4) The method of claim 4, further comprising ascertaining a level of cancer based on the one or more identified subtypes. ### Claim 9 (depends on 1) The method of claim 1, further comprising treating a subject having the tumor cells using the one or more aptamer families that characterize the one or more subtypes of the tumor cells. ### Claim 10 (depends on 1) The method of claim 1, wherein the plurality of aptamer families is at least 3 aptamer families. ### Claim 11 (depends on 1) The method of claim 1, wherein the plurality of aptamer families comprises more aptamer families than a number of subtypes of the one or more unknown subtypes of the tumor cells. ### Claim 12 (depends on 1) The method of claim 1, wherein: the data comprises results from flowing a first aptamer family and a second aptamer family concurrently over the tumor cells, the first aptamer family is determined by the prediction model to bind to a first possible subtype, the second aptamer family is determined by the prediction model to bind to a second possible subtype, the data comprises results from flowing the first aptamer family and a third aptamer family concurrently over the tumor cells, the third aptamer family is determined by the prediction model to bind to a third possible subtype, the second aptamer family and the third aptamer family are not flowed concurrently over the tumor cells, the method further comprising: determining that the measure of the binding affinity for the first aptamer family is greater than the measure of the binding affinity for the second aptamer family, determining that the measure of the binding affinity for the third aptamer family is greater than the measure of the binding affinity for the first aptamer family, determining that the third possible subtype has a higher population in the tumor cells than the first subtype, and that the first possible subtype has a higher population than the second possible subtype. ### Claim 13 A system comprising: a microfluidic device configured to perform an assay on a sample of tumor cells, wherein the microfluidic device comprises: a surface comprising randomly affixed tumor cells comprising one or more unknown subtypes of the tumor cells, a channel configured to deliver the sample to the surface and flow a plurality of aptamers over the tumor cells to allow the aptamers to interact and bind to the tumor cells, wherein the plurality of aptamers comprises a plurality of aptamer families, and each aptamer family of the plurality of aptamer families is determined by a prediction model to bind to at least one possible subtype of the tumor cells, and a detector configured to obtain data points that make up a data signal associated with a measure of binding affinity of each of the plurality of aptamer families to the tumor cells; one or more data processors; and a non-transitory computer readable storage medium containing instructions that, when executed on the one or more data processors, cause the one or more data processors to perform actions including: obtaining the data signal from the microfluidic device; analyzing the measure of the binding affinity of each aptamer family to the tumor cells, wherein the analyzing comprises classifying the binding affinity of each aptamer family to the tumor cells; and determining one or more aptamer families that characterize the one or more unknown subtypes of the tumor cells based on the classifying. ### Claim 14 (depends on 13) The system of claim 13, wherein the actions further include identifying the one or more unknown subtypes of the tumor cells to obtain one or more identified subtypes based on: (i) the determining of the one or more aptamer families that characterize the one or more subtypes of the tumor cells based on the classifying, and (ii) the at least one possible subtype of the tumor cells that each aptamer family is determined to bind to by the prediction model. ### Claim 15 (depends on 14) The system of claim 14, wherein the actions further include determining a treatment protocol for a subject having the tumor cells based on the identity of the one or more unknown subtypes of the tumor cells. ### Claim 16 (depends on 14) The system of claim 14, wherein the actions further include ascertaining a level of cancer based on the identity of the one or more unknown subtypes of the tumor cells. ### Claim 17 A computer-program product tangibly embodied in a non-transitory machine-readable storage medium, including instructions configured to cause one or more data processors to perform actions including: obtaining a data signal from a microfluidic device configured to perform an assay on a sample of tumor cells, wherein the data signal is obtained by: flowing a plurality of aptamers over the tumor cells randomly affixed to a surface of the microfluid device, which allows the aptamers to interact and bind to the tumor cells, and obtaining data points that make up the data signal associated with a measure of binding affinity of each aptamer family of a plurality of aptamer families to the tumor cells, wherein the plurality of aptamers comprises the plurality of aptamer families, and each aptamer family of the plurality of aptamer families is determined by a prediction model to bind to at least one possible subtype of the tumor cells; analyzing the measure of the binding affinity of each aptamer family to the tumor cells, wherein the analyzing comprises classifying the binding affinity of each aptamer family to the tumor cells; and determining one or more aptamer families that characterize the one or more unknown subtypes of the tumor cells based on the classifying. ### Claim 18 (depends on 17) The computer-program product of claim 17, wherein the actions further include identifying the one or more unknown subtypes of the tumor cells to obtain one or more identified subtypes based on: (i) the determining of the one or more aptamer families that characterize the one or more subtypes of the tumor cells based on the classifying, and (ii) the at least one possible subtype of the tumor cells that each aptamer family is determined to bind to by the prediction model. ### Claim 19 (depends on 18) The computer-program product of claim 18, wherein the actions further include determining a treatment protocol for a subject having the tumor cells based on the one or more identified subtypes. ### Claim 20 (depends on 18) The computer-program product of claim 18, wherein the actions further include ascertaining a level of cancer based on the one or more identified subtypes.