US 12,439,892 B2
Systems and methods for identifying disease causing agents and interventions based on sample metadata and molecular signatures
Julius Barsi, Stateline, NV (US); Arnulf Graf, Stateline, NV (US); and Joe Schroeter, Stateline, NV (US)
Assigned to Symphony Diagnositcs, Inc., Stateline, NV (US)
Filed by Symphony Diagnostics, Inc., Stateline, NV (US)
Filed on Jul. 10, 2024, as Appl. No. 18/768,731.
Claims priority of provisional application 63/512,733, filed on Jul. 10, 2023.
Prior Publication US 2025/0017174 A1, Jan. 16, 2025
Int. Cl. A01K 29/00 (2006.01); G01N 33/00 (2006.01); G06N 20/00 (2019.01); G16H 15/00 (2018.01); G16H 50/30 (2018.01)
CPC A01K 29/005 (2013.01) [G01N 33/00 (2013.01); G06N 20/00 (2019.01); G16H 15/00 (2018.01); G16H 50/30 (2018.01)] 33 Claims
 
1. A method comprising:
a) obtaining a non-human animal sample and sample metadata associated with said non-human animal sample, said sample metadata including demographic information, health information, and environmental information, wherein said environmental information includes presence of same-species animals, density of same-species animals, and/or presence of different-species animals;
b) conducting a multiplex assay on nucleic acid molecules obtained from said sample to identify nucleic acid sequence information from a plurality of microorganisms and viruses and generate a molecule signature; and
c) generating a health report based on said molecular signature and said sample metadata with using an artificial intelligence and machine learning (AI/ML) system, wherein said health report includes identities of one or more disease-causative microorganisms and viruses and provides a preventative or interventional approach.