BIOLOGICAL STATUS DETERMINATION USING CELL-FREE NUCLEIC ACIDS

• Main Authors: Modiano, Jaime F, Kim, Jong Hyuk, Donnelly, Alicia, Khammanivong, Ali, Scott, Milcah C, Tomiyasu, Hirotaka, Makielski, Kelly
• Format: Patent
• Language: English
• Published: 16.04.2020
• Subjects: BEER; BIOCHEMISTRY; CHEMISTRY; COMPOSITIONS OR TEST PAPERS THEREFOR; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL ORENZYMOLOGICAL PROCESSES; ENZYMOLOGY; HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA; INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS; MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEICACIDS OR MICROORGANISMS; METALLURGY; MICROBIOLOGY; MUTATION OR GENETIC ENGINEERING; PHYSICS; PROCESSES OF PREPARING SUCH COMPOSITIONS; SPIRITS; VINEGAR; WINE

The techniques and systems described herein relate to using machine learning models to associate a known biological state of an organism with patterns of expression exhibited by the organism of genes of a gene signature associated with a disease state, such as to train the machine learning models to determine unknown biological states associated with the patterns of expression. Some techniques include determining an unknown biological status of an organism based on an expression pattern of genes of a gene signature in the organism, which the machine learning model may compare to known expression patients learned during the training technique. The expression patterns may be determined based on sequences of exosomal RNAs isolated from exosomes from a sample of bodily fluid from the organism and an approximate number of times each RNA sequence that substantially aligns with a gene of the gene signature occurs in the sample of bodily fluid.