US 12,334,190 B2
Multi-omic assessment using proteins and nucleic acids
Philip Ma, San Jose, CA (US); Bruce Wilcox, Keezletown, CA (US); Francois Collin, Berkeley, CA (US); Chinmay Belthangady, San Jose, CA (US); Mi Yang, Belmont, CA (US); Manoj Khadka, Belmont, CA (US); Manway Liu, Burlingame, CA (US); John Blume, Bellingham, WA (US); Robert S. Langer, Jr., Newton, MA (US); and Ehdieh Khaledian, Belmont, CA (US)
Assigned to PROGNOMIQ, INC., San Mateo, CA (US)
Filed by PrognomIQ, Inc., San Mateo, CA (US)
Filed on Mar. 30, 2022, as Appl. No. 17/709,185.
Claims priority of provisional application 63/322,149, filed on Mar. 21, 2022.
Claims priority of provisional application 63/312,455, filed on Feb. 22, 2022.
Claims priority of provisional application 63/288,825, filed on Dec. 13, 2021.
Claims priority of provisional application 63/288,827, filed on Dec. 13, 2021.
Claims priority of provisional application 63/278,637, filed on Nov. 12, 2021.
Claims priority of provisional application 63/256,482, filed on Oct. 15, 2021.
Claims priority of provisional application 63/229,232, filed on Aug. 4, 2021.
Claims priority of provisional application 63/229,242, filed on Aug. 4, 2021.
Claims priority of provisional application 63/228,533, filed on Aug. 2, 2021.
Claims priority of provisional application 63/228,543, filed on Aug. 2, 2021.
Claims priority of provisional application 63/184,498, filed on May 5, 2021.
Claims priority of provisional application 63/183,816, filed on May 4, 2021.
Claims priority of provisional application 63/183,852, filed on May 4, 2021.
Claims priority of provisional application 63/183,844, filed on May 4, 2021.
Claims priority of provisional application 63/183,829, filed on May 4, 2021.
Claims priority of provisional application 63/168,594, filed on Mar. 31, 2021.
Claims priority of provisional application 63/168,634, filed on Mar. 31, 2021.
Prior Publication US 2022/0328129 A1, Oct. 13, 2022
This patent is subject to a terminal disclaimer.
Int. Cl. G16B 20/00 (2019.01); G01N 33/574 (2006.01); G01N 33/58 (2006.01); G01N 33/68 (2006.01); G01N 33/92 (2006.01); G16B 25/10 (2019.01); G16B 30/00 (2019.01); G16B 40/20 (2019.01); G16B 40/30 (2019.01); G16H 20/40 (2018.01); G16H 50/20 (2018.01)
CPC G16B 20/00 (2019.02) [G01N 33/57484 (2013.01); G01N 33/587 (2013.01); G01N 33/6848 (2013.01); G01N 33/92 (2013.01); G16B 25/10 (2019.02); G16B 30/00 (2019.02); G16B 40/20 (2019.02); G16B 40/30 (2019.02); G16H 20/40 (2018.01); G16H 50/20 (2018.01); G01N 2570/00 (2013.01)] 31 Claims
 
1. A multi-omic method, comprising:
sequencing nucleic acids obtained from a biofluid sample from a subject to obtain nucleic acid sequence information;
quantifying the nucleic acids to obtain nucleic acid quantification information;
processing proteins from the biofluid sample from the subject to obtain proteomic data;
generating a combined dataset comprising at least a portion of the proteomic data, at least a portion of the nucleic acid quantification information, and at least a portion of the nucleic acid sequence information; and
determining a presence or an absence of cancer at least in part by inputting the combined dataset into a trained machine learning classifier, wherein the trained machine learning classifier has
a performance characteristic comprising an area under the curve (AUC) of a receiver operating characteristic (ROC) curve of at least 0.83, and wherein the trained machine learning classifier is trained on cancer samples and non-cancer samples.