Patents Assigned to Biodesix, Inc.
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Patent number: 11913957Abstract: Methods are provided for identifying biomarker proteins that exhibit differential expression in subjects with a first lung condition versus healthy subjects or subjects with a second lung condition. Also provided are compositions comprising these biomarker proteins and methods of using these biomarker proteins or panels thereof to diagnose, classify, and monitor various lung conditions. The methods and compositions provided herein may be used to diagnose or classify a subject as having lung cancer or a non-cancerous condition, and to distinguish between different types of cancer (e.g., malignant versus benign, SCLC versus NSCLC).Type: GrantFiled: October 18, 2017Date of Patent: February 27, 2024Assignee: Biodesix, Inc.Inventors: Paul E. Kearney, Kenneth C. Fang, Xiao-Jun Li, Clive Hayward, Douglas Spicer
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Patent number: 11894147Abstract: A method for predicting an unfavorable outcome for a patient admitted to a hospital, e.g., with a COVID-19 infection is described. Attributes from an electronic health record for the patient are obtained including at least findings obtained at admission, basic patient characteristics, and laboratory data. The attributes are supplied to a classifier implemented in a programmed computer which is trained to predict a risk of the unfavorable outcome. The classifier is arranged as a hierarchical combination of (a) an initial binary classifier stratifying the patient into either a high risk group or a low risk group, and (b) child classifiers further classifying the patient in a lowest risk group or a highest risk group depending how the initial binary classifier stratified the patient as either a member of the high risk or low risk group.Type: GrantFiled: September 2, 2022Date of Patent: February 6, 2024Assignee: BIODESIX, INC.Inventors: Thomas Campbell, Robert W. Georgantas, III, Heinrich Röder, Joanna Röder, Laura Maguire
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Patent number: 11710539Abstract: A method is disclosed for predicting in advance whether a melanoma patient is likely to benefit from high dose IL2 therapy in treatment of the cancer. The method makes use of mass spectrometry data obtained from a blood-based sample of the patient and a computer configured as a classifier and making use of a reference set of mass spectral data obtained from a development set of blood-based samples from other melanoma patients. A variety of classifiers for making this prediction are disclosed, including a classifier developed from a set of blood-based samples obtained from melanoma patients treated with high dose IL2 as well as melanoma patients treated with an anti-PD-1 immunotherapy drug. The classifiers developed from anti-PD-1 and IL2 patient sample cohorts can also be used in combination to guide treatment of a melanoma patient.Type: GrantFiled: January 18, 2017Date of Patent: July 25, 2023Assignee: BIODESIX, INC.Inventors: Arni Steingrimsson, Carlos Oliveira, Krista Meyer, Joanna Röder, Heinrich Röder
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Publication number: 20230197426Abstract: A method of predicting whether an MDS patient has a good or poor prognosis uses a general purpose computer configured as a classifier and mass-spectrometry data obtained from a blood-based sample. The classifier assigns a classification label of either Early or Late (or the equivalent) to the patient's sample. Patients classified as Early are predicted to have a poor prognosis or worse survival whereas those patients classified as Late are predicted to have a relatively better prognosis and longer survival time. The groupings demonstrated a large effect size between groups in Kaplan-Meier analysis of survival. Most importantly, while the classifications generated were correlated with other prognostic factors, such as IPSS score and genetic category, multivariate and subgroup analysis showed that they had significant independent prognostic power complementary to the existing prognostic factors.Type: ApplicationFiled: February 21, 2023Publication date: June 22, 2023Applicant: BIODESIX, INC.Inventors: Arni STEINGRIMSSON, Heinrich RODER, Joanna RODER
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Patent number: 11621057Abstract: A method of generating a classifier includes a step of classifying each member of a development set of samples with a class label in a binary classification scheme with a first classifier; and generating a second classifier using a classifier development process with an input classifier development set being the members of the development set assigned one of the two class labels in the binary classification scheme by the first classifier. The second classifier stratifies the members of the set with an early label into two further sub-groups. We also describe identifying a plurality of different clinical sub-groups within the development set based on the clinical data and for each of the different clinical sub-groups, conducting a classifier generation process for each of the clinical sub-groups thereby generating clinical subgroup classifiers.Type: GrantFiled: March 10, 2017Date of Patent: April 4, 2023Assignee: BIODESIX, INC.Inventors: Arni Steingrimsson, Joanna Röder, Julia Grigorieva, Heinrich Röder, Krista Meyer
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Patent number: 11594403Abstract: A method of predicting whether an MDS patient has a good or poor prognosis uses a general purpose computer configured as a classifier and mass-spectrometry data obtained from a blood-based sample. The classifier assigns a classification label of either Early or Late (or the equivalent) to the patient's sample. Patients classified as Early are predicted to have a poor prognosis or worse survival whereas those patients classified as Late are predicted to have a relatively better prognosis and longer survival time. The groupings demonstrated a large effect size between groups in Kaplan-Meier analysis of survival. Most importantly, while the classifications generated were correlated with other prognostic factors, such as IPSS score and genetic category, multivariate and subgroup analysis showed that they had significant independent prognostic power complementary to the existing prognostic factors.Type: GrantFiled: February 20, 2018Date of Patent: February 28, 2023Assignee: BIODESIX INC.Inventors: Arni Steingrimsson, Heinrich Röder, Joanna Röder
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Publication number: 20230005621Abstract: A method for predicting an unfavorable outcome for a patient admitted to a hospital, e.g., with a COVID-19 infection is described. Attributes from an electronic health record for the patient are obtained including at least findings obtained at admission, basic patient characteristics, and laboratory data. The attributes are supplied to a classifier implemented in a programmed computer which is trained to predict a risk of the unfavorable outcome. The classifier is arranged as a hierarchical combination of (a) an initial binary classifier stratifying the patient into either a high risk group or a low risk group, and (b) child classifiers further classifying the patient in a lowest risk group or a highest risk group depending how the initial binary classifier stratified the patient as either a member of the high risk or low risk group.Type: ApplicationFiled: September 2, 2022Publication date: January 5, 2023Applicant: BIODESIX, INC.Inventors: Thomas CAMPBELL, Robert W. GEORGANTAS, III, Heinrich RÖDER, Joanna RÖDER, Laura MAGUIRE
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Patent number: 11542340Abstract: Provided are monoclonal antibodies, or antigen-binding fragments thereof, that bind to specific peptides of C163A or LG3BP, compositions comprising such antibodies and/or fragments, as well as methods of use and devices employing such antibodies and/or fragments.Type: GrantFiled: October 29, 2021Date of Patent: January 3, 2023Assignee: Biodesix, Inc.Inventors: Gary A. Pestano, Hestia Meliert
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Publication number: 20220341939Abstract: A method for predicting whether an early stage (IA, IB) non-small-cell lung cancer (NSCLC) patient is at a high risk of recurrence of the cancer following surgery involves subjecting a blood-based sample from the patient (obtained prior to, at, or after the surgery) to mass spectrometry and classification with a computer implementing a classifier. If the patients blood sample is classified as “high risk”, highest risk“or the equivalent, the patient can be guided to more aggressive treatment post-surgery. The classifier, or combination of classifiers, can be arranged in a hierarchical manner to make intermediate classifications, such as intermediate/high or intermediate/low, as well as low risk” or “lowest risk” classifications. Such additional classifications may guide clinical decisions as well.Type: ApplicationFiled: January 29, 2020Publication date: October 27, 2022Applicant: BIODESIX, INC.Inventors: Heinrich RODER, Joanna RÖDER, Lelia NET, Laura MAGUIRE
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Patent number: 11476003Abstract: A method for predicting an unfavorable outcome for a patient admitted to a hospital, e.g., with a COVID-19 infection is described. Attributes from an electronic health record for the patient are obtained including at least findings obtained at admission, basic patient characteristics, and laboratory data. The attributes are supplied to a classifier implemented in a programmed computer which is trained to predict a risk of the unfavorable outcome. The classifier is arranged as a hierarchical combination of (a) an initial binary classifier stratifying the patient into either a high risk group or a low risk group, and (b) child classifiers further classifying the patient in a lowest risk group or a highest risk group depending how the initial binary classifier stratified the patient as either a member of the high risk or low risk group.Type: GrantFiled: June 10, 2021Date of Patent: October 18, 2022Assignee: BIODESIX, INC.Inventors: Thomas Campbell, Robert W. Georgantas, III, Heinrich Röder, Joanna Röder, Laura Maguire
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Patent number: 11467167Abstract: Provided herein are methods for developing selected reaction monitoring mass spectrometry (LC-SRM-MS) assays.Type: GrantFiled: December 4, 2019Date of Patent: October 11, 2022Assignee: Biodesix, Inc.Inventors: Paul E. Kearney, Xiao-Jun Li, Clive Hayward
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Publication number: 20220188701Abstract: Shapley values (SVs) have become an important tool to further the goal of explainability of machine learning (ML) models. However, the computational load of exact SV calculations increases exponentially with the number of attributes. Hence, the calculation of SVs for models incorporating large numbers of interpretable attributes is problematic. Molecular diagnostic tests typically seek to leverage information from hundreds or thousands of attributes, often using training sets with fewer instances. Methods are described for evaluate SVs using Monte Carlo sampling or exact calculation in polynomial time (i.e., reasonably quickly and efficiently) using the architecture of a ML model designed for robust molecular test generation, and without requiring classifier retraining.Type: ApplicationFiled: June 28, 2021Publication date: June 16, 2022Applicant: BIODESIX, INC.Inventors: Heinrich RÖDER, Joanna Röder, Laura Maguire, Robert W. Georgantas, III, Thomas Campbell, Lelia Net
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Publication number: 20220189638Abstract: A method for predicting an unfavorable outcome for a patient admitted to a hospital, e.g., with a COVID-19 infection is described. Attributes from an electronic health record for the patient are obtained including at least findings obtained at admission, basic patient characteristics, and laboratory data. The attributes are supplied to a classifier implemented in a programmed computer which is trained to predict a risk of the unfavorable outcome. The classifier is arranged as a hierarchical combination of (a) an initial binary classifier stratifying the patient into either a high risk group or a low risk group, and (b) child classifiers further classifying the patient in a lowest risk group or a highest risk group depending how the initial binary classifier stratified the patient as either a member of the high risk or low risk group.Type: ApplicationFiled: June 10, 2021Publication date: June 16, 2022Applicant: BIODESIX, INC.Inventors: Thomas CAMPBELL, Robert W. GEORGANTAS, III, Heinrich RÖDER, Joanna RÖDER, Laura MAGUIRE
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Publication number: 20220026416Abstract: A blood-based sample from a cancer patient is subject to mass spectrometry and the resulting mass spectral data is classified with the aid of a computer to see if the patient is a member of a class of patients having a poor prognosis. If so, the mass spectral data is further classified with the aid of the computer by a second classifier which identifies whether the patient is nevertheless likely to obtain durable benefit from immunotherapy drugs, e.g., immune checkpoint inhibitors, anti-CTLA4 drugs, and high dose interleukin-2.Type: ApplicationFiled: October 6, 2021Publication date: January 27, 2022Applicant: BIODESIX, INC.Inventors: Carlos OLIVEIRA, Heinrich RODER, Julia GRIGORIEVA, Joanna RODER
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Patent number: 11193935Abstract: The present invention provides methods for identifying biomarker proteins that exhibit differential expression in subjects with a first lung condition versus healthy subjects or subjects with a second lung condition. The present invention also provides compositions comprising these biomarker proteins and methods of using these biomarker proteins or panels thereof to diagnose, classify, and monitor various lung conditions. The methods and compositions provided herein may be used to diagnose or classify a subject as having lung cancer or a non-cancerous condition, and to distinguish between different types of cancer (e.g., malignant versus benign, SCLC versus NSCLC).Type: GrantFiled: August 18, 2017Date of Patent: December 7, 2021Assignee: Biodesix, Inc.Inventors: Paul Edward Kearney, Kenneth Charles Fang, Xiao-Jun Li, Clive Hayward
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Patent number: 11150238Abstract: A blood-based sample from a cancer patient is subject to mass spectrometry and the resulting mass spectral data is classified with the aid of a computer to see if the patient is a member of a class of patients having a poor prognosis. If so, the mass spectral data is further classified with the aid of the computer by a second classifier which identifies whether the patient is nevertheless likely to obtain durable benefit from immunotherapy drugs, e.g., immune checkpoint inhibitors, anti-CTLA4 drugs, and high dose interleukin-2.Type: GrantFiled: January 5, 2018Date of Patent: October 19, 2021Assignee: BIODESIX, INC.Inventors: Carlos Oliveira, Heinrich Röder, Julia Grigorieva, Joanna Röder
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Publication number: 20210118538Abstract: A 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 for the sample. In one form of the test, “Test 1” herein, 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 treatment of the cancer. In another configuration of the test, “Test 2” herein, 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.Type: ApplicationFiled: March 11, 2019Publication date: April 22, 2021Applicant: BIODESIX, INC.Inventors: Carlos OLIVEIRA, Heinrich RODER, Joanna RODER
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Publication number: 20210098131Abstract: 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.Type: ApplicationFiled: December 11, 2020Publication date: April 1, 2021Applicant: BIODESIX, INC.Inventors: Joanna Roder, Krista Meyer, Julia Grigorieva, Maxim Tsypin, Carlos Oliveira, Ami Steingrimsson, Heinrich Roder, Senait Asmellash, Kevin Sayers, Caroline Maher
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Patent number: 10950348Abstract: 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.Type: GrantFiled: May 29, 2018Date of Patent: March 16, 2021Assignee: BIODESIX, INC.Inventors: Joanna Röder, Krista Meyer, Julia Grigorieva, Maxim Tsypin, Carlos Oliveira, Arni Steingrimsson, Heinrich Röder, Senait Asmellash, Kevin Sayers, Caroline Maher
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Patent number: 10870891Abstract: The present disclosure relates to a rapid diagnostic test system that includes the prospective collection of whole blood, preservation of circulating nucleic acids at ambient temperature, and the reproducible detection of nucleic acids including DNA and mRNA (including fusion transcripts and differentially expressed transcripts) by different genomic methodologies.Type: GrantFiled: January 5, 2018Date of Patent: December 22, 2020Assignee: BIODESIX, INC.Inventors: Hestia Mellert, Leisa Jackson, Gary A. Pestano