公开(公告)号：US12094587B2

公开(公告)日：2024-09-17

申请号：US17031042

申请日：2019-03-11

Applicant: BIODESIX, INC.

Inventor： Carlos Oliveira ,  Heinrich Roder ,  Joanna Roder

IPC: G16H20/10 ,  G01N33/68 ,  G06N20/00 ,  G16B40/20 ,  G16H50/20 ,  H01J49/00 ,  H01J49/16 ,  H01J49/44

CPC classification number: G16H20/10 ,  G01N33/6848 ,  G06N20/00 ,  G16B40/20 ,  G16H50/20 ,  H01J49/0036 ,  H01J49/164 ,  H01J49/446

Abstract: Laboratory test apparatus for conducting a mass spectrometry test on a blood-based sample of a cancer patient includes a classification procedure implemented in a programmed computer that generates a class label. In one form of the test, “Test 1”, if the sample is labelled “Bad” or equivalent the patient is predicted to exhibit primary immune resistance if they are later treated with anti-PD-1 or anti-PD-L1 therapies. In “Test 2” the Bad class label predicts that the patient will have a poor prognosis in response to treatment by either anti-PD-1 or anti-PD-L1 therapies or alternative chemotherapies, such as docetaxel or pemetrexed. “Test 3” identifies patients that are likely to have a poor prognosis in response to treatment by either anti-PD-1 or anti-PD-L1 therapies but have improved outcomes on alternative chemotherapies. A Good class label by either Test 1 or 2 predicts very good outcome on anti-PD-1 or anti-PD-L1 monotherapy.

公开(公告)号：US20210098131A1

公开(公告)日：2021-04-01

申请号：US17119200

申请日：2020-12-11

Applicant: BIODESIX, INC.

Inventor： Joanna Roder ,  Krista Meyer ,  Julia Grigorieva ,  Maxim Tsypin ,  Carlos Oliveira ,  Ami Steingrimsson ,  Heinrich Roder ,  Senait Asmellash ,  Kevin Sayers ,  Caroline Maher

IPC: G16H50/20 ,  G16B40/00 ,  G01N33/574 ,  G01N33/68 ,  G16B40/10 ,  G16B40/20 ,  G16H40/63 ,  G16H20/30 ,  G16H20/10 ,  G16H10/40

Abstract: A method is disclosed of predicting cancer patient response to immune checkpoint inhibitors, e.g., an antibody drug blocking ligand activation of programmed cell death 1 (PD-1) or CTLA4. The method includes obtaining mass spectrometry data from a blood-based sample of the patient, obtaining integrated intensity values in the mass spectrometry data of a multitude of pre-determined mass-spectral features; and operating on the mass spectral data with a programmed computer implementing a classifier. The classifier compares the integrated intensity values with feature values of a training set of class-labeled mass spectral data obtained from a multitude of melanoma patients with a classification algorithm and generates a class label for the sample. A class label “early” or the equivalent predicts the patient is likely to obtain relatively less benefit from the antibody drug and the class label “late” or the equivalent indicates the patient is likely to obtain relatively greater benefit from the antibody drug.

公开(公告)号：US12230398B2

公开(公告)日：2025-02-18

申请号：US17119200

申请日：2020-12-11

Applicant: BIODESIX, INC.

Inventor： Joanna Roder ,  Krista Meyer ,  Julia Grigorieva ,  Maxim Tsypin ,  Carlos Oliveira ,  Ami Steingrimsson ,  Heinrich Roder ,  Senait Asmellash ,  Kevin Sayers ,  Caroline Maher

IPC: G16H50/20 ,  G01N33/574 ,  G01N33/68 ,  G16B40/00 ,  G16B40/10 ,  G16B40/20 ,  G16H10/40 ,  G16H20/10 ,  G16H20/30 ,  G16H40/63

Abstract: A method is disclosed of predicting cancer patient response to immune checkpoint inhibitors, e.g., an antibody drug blocking ligand activation of programmed cell death 1 (PD-1) or CTLA4. The method includes obtaining mass spectrometry data from a blood-based sample of the patient, obtaining integrated intensity values in the mass spectrometry data of a multitude of pre-determined mass-spectral features; and operating on the mass spectral data with a programmed computer implementing a classifier. The classifier compares the integrated intensity values with feature values of a training set of class-labeled mass spectral data obtained from a multitude of melanoma patients with a classification algorithm and generates a class label for the sample. A class label “early” or the equivalent predicts the patient is likely to obtain relatively less benefit from the antibody drug and the class label “late” or the equivalent indicates the patient is likely to obtain relatively greater benefit from the antibody drug.