Patents by Inventor Vinay Varadan

Vinay Varadan has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20200395128
    Abstract: The present invention relates to effective diagnosis of patients and assisting clinicians in treatment planning. In particular, invention provides a medical analysis system that enables refinement of molecular classification. The system provides a molecular profiling solution that will allow improved diagnosis, prognosis, response prediction to provide the right chemotherapy, and follow-up to monitor for cancer recurrence.
    Type: Application
    Filed: June 2, 2020
    Publication date: December 17, 2020
    Inventors: Angel Janevski, Nevenka Dimitrova, Sitharthan Kamalakaran, Yasser Alsafadi, Nilanjana Banerjee, Anca Ioana Daniela Bucur, Jasper Johannes Adrianus van Leeuwen, Vinay Varadan
  • Patent number: 10679726
    Abstract: Relevance of a study genetic variant observed in diagnostic subject genetic data that is associated by a clinical study with a phenotype characteristic is assessed as follows. A set of polymorphisms functionally related to the study genetic variant are identified. A foreground distribution is computed of variants observed in the diagnostic subject genetic data for the set of polymorphisms. A background distribution is computed of variants observed in genetic data of subjects of the clinical study for the set of polymorphisms. A comparison metric is computed comparing the foreground distribution and the background distribution. Relevance of the study variant to the diagnostic subject is quantified based on the comparison metric, with higher similarity of the foreground and background distributions corresponding to higher relevance.
    Type: Grant
    Filed: November 15, 2013
    Date of Patent: June 9, 2020
    Assignee: Koninklijke Philips N.V.
    Inventors: Sitharthan Kalalakaran, Vinay Varadan, Nilanjana Banerjee, Angel Janevski, Nevenka Dimitrova
  • Publication number: 20200061073
    Abstract: A method of treating intestinal gastrointestinal, or bowel disorders in a subject in need thereof includes administering to the subject a therapeutically effective amount of 15-PGDH inhibitor alone or in combination with a corticosteroid and/or TNF alpha antagonist.
    Type: Application
    Filed: November 30, 2017
    Publication date: February 27, 2020
    Inventors: Sanford Markowitz, Won Jin Ho, Stephen P. Fink, Vinay Varadan
  • Patent number: 10541052
    Abstract: A catalog (34) of molecular marker tests specifies molecular marker tests annotated with clinical applicability annotations. An electronic patient medical record (22) stores genetic sequencing data (20) of a patient. A clinical decision support (CDS) system (30) is configured to track the clinical context of the patient wherein the clinical context includes at least a disease diagnosis and a current patient care stage. A catalog search module (32) is configured to search the catalog of molecular marker tests to identify a molecular marker test having clinical applicability to the patient in the clinical context tracked by the CDS system. The search is automatically triggered by occurrence of a trigger event defined by a set of triggering rules. A testing module (44) is configured to perform a molecular marker test identified by the identification module in silico using the genetic sequencing data of the patient stored in the electronic patient medical record.
    Type: Grant
    Filed: November 29, 2012
    Date of Patent: January 21, 2020
    Assignee: Koninklijke Philip N.V.
    Inventors: Vinay Varadan, Sitharthan Kamalakaran, Angel Janevski, Nilanjana Banerjee, Nevenka Dimitrova
  • Patent number: 10460831
    Abstract: In a predictive outcome assessment test for predicting whether a patient undergoing a breast cancer treatment regimen will achieve pathological complete response (pCR), differential gene expression level information are generated for an input set of genes belonging to the TGF-? signaling pathway. The differential gene expression level information compares baseline gene expression level information from a baseline sample (70) of a breast tumor of a patient acquired before initiating (71) a breast cancer therapy regimen to the patient and response gene expression level information from a response sample (72) of the breast tumor acquired after initiating the breast cancer therapy regimen by administering a first dose of bevacizumab to the patient. A pCR prediction for the patient is computed based on the differential gene expression level information for the input set of genes belonging to the TGF-? signaling pathway. Related predictive outcome assessment test development methods are also disclosed.
    Type: Grant
    Filed: November 22, 2013
    Date of Patent: October 29, 2019
    Assignee: Koninklijke Philips N.V.
    Inventors: Vinay Varadan, Sitharthan Kamalakaran, Angel Janevski, Nilanjana Banerjee, Nevenka Dimitrova, Lyndsay Harris
  • Patent number: 10340027
    Abstract: The present invention relates to a method for identifying multi-modal associations between biomedical markers which allows for the determination of network nodes and/or high ranking network members or combinations thereof, indicative of having a diagnostic, prognostic or predictive value for a medical condition, in particular ovarian cancer. The present invention further relates to a biomedical marker or group of biomedical markers associated with a high likelihood of responsiveness of a subject to a cancer therapy, preferably a platinum based cancer therapy, wherein said biomedical marker or group of biomedical markers comprises at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 8, 19, 20 or all markers selected from PKMYT1, SKIL, RAB8A, HIRIP3, CTNNB1, NGFR, ZCCHC11, LSP1, CD200, PAX8, CYBRD1, HOXC11, TCEAL1, FZD10, FZD1, BBS4, IRS2, TLX3, TSPAN2, TXN, and CFLAR.
    Type: Grant
    Filed: October 4, 2011
    Date of Patent: July 2, 2019
    Assignee: Koninklijke Philips N.V.
    Inventors: Nilanjana Banerjee, Angel Janevski, Sitharthan Kamalakaran, Vinay Varadan, Nevenka Dimitrova, Robert Lucito
  • Publication number: 20180247010
    Abstract: A system and method for determining the functional impact of somatic mutations and genomic aberrations on downstream cellular processes by integrating multi-omics measurements in cancer samples with community-curated biological pathways are disclosed.
    Type: Application
    Filed: August 26, 2016
    Publication date: August 30, 2018
    Inventors: Abolfazl Razi, Vinay Varadan, Nevenka Dimitrova, Nilanjana Banerjee
  • Patent number: 10055842
    Abstract: Methods, apparatus, and other embodiments distinguish disease phenotypes and mutational status using co-occurrence of local anisotropic gradient orientations (CoLIAGe) and Laws features. One example apparatus includes a set of circuits that acquires a radiologic image (e.g., MRI image) of a region of tissue demonstrating breast cancer, computes a gradient orientation for a pixel in the MRI image, computes a significant orientation for the pixel based on the gradient orientation, constructs a feature vector that captures a discretized entropy distribution for the image based on the significant orientation, extracts a set of texture features from the MRI image, and classifies the phenotype of the breast cancer based on the feature vector and the set of texture features. Embodiments of example apparatus may generate and display a heatmap of entropy values for the image. Example methods and apparatus may operate substantially in real-time, or may operate in two, three, or more dimensions.
    Type: Grant
    Filed: January 3, 2017
    Date of Patent: August 21, 2018
    Assignee: Case Western Reserve University
    Inventors: Prateek Prasanna, Nathaniel Braman, Anant Madabhushi, Vinay Varadan, Lyndsay Harris, Salendra Singh
  • Publication number: 20180089392
    Abstract: The present invention relates to effective diagnosis of patients and assisting clinicians in treatment planning. In particular, invention provides a medical analysis system that enables refinement of molecular classification. The system provides a molecular profiling solution that will allow improved diagnosis, prognosis, response prediction to provide the right chemotherapy, and follow-up to monitor for cancer recurrence.
    Type: Application
    Filed: November 29, 2017
    Publication date: March 29, 2018
    Inventors: Angel Janevski, Nevenka Dimitrova, Sitharthan Kamalakaran, Yasser Alsafadi, Nilanjana Banerjee, Anca Ioana Daniela Bacur, Jasper Johannes Adrianus van Leeuwen, Vinay Varadan
  • Publication number: 20180033138
    Abstract: Methods, apparatus, and other embodiments distinguish disease phenotypes and mutational status using co-occurrence of local anisotropic gradient orientations (CoLIAGe) and Laws features. One example apparatus includes a set of circuits that acquires a radiologic image (e.g., MRI image) of a region of tissue demonstrating breast cancer, computes a gradient orientation for a pixel in the MRI image, computes a significant orientation for the pixel based on the gradient orientation, constructs a feature vector that captures a discretized entropy distribution for the image based on the significant orientation, extracts a set of texture features from the MRI image, and classifies the phenotype of the breast cancer based on the feature vector and the set of texture features. Embodiments of example apparatus may generate and display a heatmap of entropy values for the image. Example methods and apparatus may operate substantially in real-time, or may operate in two, three, or more dimensions.
    Type: Application
    Filed: January 3, 2017
    Publication date: February 1, 2018
    Inventors: Prateek Prasanna, Nathaniel Braman, Anant Madabhushi, Vinay Varadan, Lyndsay Harris, Salendra Singh
  • Patent number: 9858392
    Abstract: The present invention relates to effective diagnosis of patients and assisting clinicians in treatment planning. In particular, invention provides a medical analysis system that enables refinement of molecular classification. The system provides a molecular profiling solution that will allow improved diagnosis, prognosis, response prediction to provide the right chemotherapy, and follow-up to monitor for cancer recurrence.
    Type: Grant
    Filed: May 6, 2009
    Date of Patent: January 2, 2018
    Assignee: Koninklijke Philips N.V.
    Inventors: Angel J. Janevski, Nevenka Dimitrova, Sitharthan Kamalakaran, Yasser Alsafadi, Nilanjana Banerjee, Anca Ioana Daniela Bacur, Jasper Van Leeuwen, Vinay Varadan
  • Patent number: 9798856
    Abstract: An imaging visualization workstation (30) includes a graphical display device (32) and an electronic data processor, and is configured to perform a method including: spatially registering a biopsy sample extracted from a medical subject with a medical image (12) of the medical subject; combining the medical image with a graphical representation of information (20, 22) generated from the biopsy sample to generate a combined image in which the graphical representation is spatially delineated based on the spatial registration of the biopsy sample; and displaying the combined image on the graphical display device of the imaging visualization workstation. A method comprises extracting a biopsy sample spatial sample from a medical subject, processing the biopsy sample to generate biopsy information, acquiring a medical image of the subject, spatially registering the biopsy sample with the medical image, and displaying the medical image modified to include an annotation generated from the biopsy information.
    Type: Grant
    Filed: March 20, 2013
    Date of Patent: October 24, 2017
    Assignee: Koninklijke Philips N.V.
    Inventors: Nilanjana Banerjee, Sitharthan Kamalakaran, Vinay Varadan, Angel Janevski, Nevenka Dimitrova
  • Patent number: 9552649
    Abstract: Image texture feature values are computed for a set of image texture features from an image of an anatomical feature of interest in a subject, and the subject is classified respective to a molecular feature of interest based on the computed image texture feature values. The image texture feature values may be computed from one or more gray level co-occurrence matrices (GLCMs), and the image texture features may include Haralick and/or Tamura image texture features. To train the classifier, reference image texture feature values are computed for at least the set of image texture features from images of the anatomical feature of interest in reference subjects. The reference image texture feature values are divided into different population groups representing different values of the molecular feature of interest, and the classifier is trained to distinguish between the different population groups based on the reference image texture feature values.
    Type: Grant
    Filed: October 25, 2013
    Date of Patent: January 24, 2017
    Assignee: Koninklijke Philips N.V.
    Inventors: Nilanjana Banerjee, Nevenka Dimitrova, Vinay Varadan, Sitharthan Kamalakaran, Angel Janevski, Sayan Maity
  • Publication number: 20160132637
    Abstract: This disclosure relates to systems and methods that employ a noise model generated from control samples to detect copy number alterations (CNA) in one or more test samples. The noise model can be generated to represent an indication of noise associated with chromosomes of control biological samples obtained via a common protocol. The indication can be determined by comparing chromosomes of the control biological samples. The noise model can be used to detect CNAs within the test sample by analyzing variability thereof with respect to the noise model.
    Type: Application
    Filed: November 12, 2015
    Publication date: May 12, 2016
    Inventors: Vinay Varadan, Kishore Guda
  • Publication number: 20150347679
    Abstract: In a predictive outcome assessment test for predicting whether a patient undergoing a breast cancer treatment regimen will achieve pathological complete response (pCR), differential gene expression level information are generated for an input set of genes belonging to the TGF-? signaling pathway. The differential gene expression level information compares baseline gene expression level information from a baseline sample (70) of a breast tumor of a patient acquired before initiating (71) a breast cancer therapy regimen to the patient and response gene expression level information from a response sample (72) of the breast tumor acquired after initiating the breast cancer therapy regimen by administering a first dose of bevacizumab to the patient. A pCR prediction for the patient is computed based on the differential gene expression level information for the input set of genes belonging to the TGF-? signaling pathway. Related predictive outcome assessment test development methods are also disclosed.
    Type: Application
    Filed: November 22, 2013
    Publication date: December 3, 2015
    Inventors: VINAY VARADAN, SITHARTHAN KAMALAKARAN, ANGEL JANEVSKI, NILANJANA BANERJEE, NEVENKA DIMITROVA, LYNDSAY HARRIS
  • Publication number: 20150310632
    Abstract: Image texture feature values are computed for a set of image texture features from an image of an anatomical feature of interest in a subject, and the subject is classified respective to a molecular feature of interest based on the computed image texture feature values. The image texture feature values may be computed from one or more gray level co-occurrence matrices (GLCMs), and the image texture features may include Haralick and/or Tamura image texture features. To train the classifier, reference image texture feature values are computed for at least the set of image texture features from images of the anatomical feature of interest in reference subjects. The reference image texture feature values are divided into different population groups representing different values of the molecular feature of interest, and the classifier is trained to distinguish between the different population groups based on the reference image texture feature values.
    Type: Application
    Filed: October 25, 2013
    Publication date: October 29, 2015
    Inventors: NILANJANA BANERJEE, NEVENKA DIMITROVA, VINAY VARADAN, SITHARTHAN KAMALAKARAN, ANGEL JANEVSKI, SAYAN MAITY
  • Publication number: 20150294063
    Abstract: Relevance of a study genetic variant observed in diagnostic subject genetic data that is associated by a clinical study with a phenotype characteristic is assessed as follows. A set of polymorphisms functionally related to the study genetic variant are identified. A foreground distribution is computed of variants observed in the diagnostic subject genetic data for the set of polymorphisms. A background distribution is computed of variants observed in genetic data of subjects of the clinical study for the set of polymorphisms. A comparison metric is computed comparing the foreground distribution and the background distribution. Relevance of the study variant to the diagnostic subject is quantified based on the comparison metric, with higher similarity of the foreground and background distributions corresponding to higher relevance.
    Type: Application
    Filed: November 15, 2013
    Publication date: October 15, 2015
    Applicant: KONINKLIJKE PHILIPS N.V.
    Inventors: Sitharthan Kalalakaran, Vinay Varadan, Nilanjana Banerjee, Angel Janevski, Nevenka Dimitrova
  • Patent number: 9074206
    Abstract: The present invention relates compositions and methods for microRNA (miRNA) expression profiling of colorectal cancer. In particular, the invention relates to a diagnostic kit of molecular markers for identifying one or more mammalian target cells exhibiting or having a predisposition to develop colorectal cancer, the kit comprising a plurality of nucleic acid molecules, each nucleic acid molecule encoding a miRNA sequence, wherein one or more of the plurality of nucleic acid molecules are differentially expressed in the target cells and in one or more control cells, and wherein the one or more differentially expressed nucleic acid molecules together represent a nucleic acid expression signature that is indicative for the presence of or the predisposition to develop colorectal cancer.
    Type: Grant
    Filed: November 13, 2009
    Date of Patent: July 7, 2015
    Assignee: Fudan University
    Inventors: Ying Wu, Hongguang Zhu, Jian Li, Liang Xu, Wilhelmus F. J. Verhaegh, Yiping Ren, Angel Janevski, Vinay Varadan, Zhaoyong Li, Nevenka Dimitrova
  • Publication number: 20150097868
    Abstract: An imaging visualization workstation (30) includes a graphical display device (32) and an electronic data processor, and is configured to perform a method including: spatially registering a biopsy sample extracted from a medical subject with a medical image (12) of the medical subject; combining the medical image with a graphical representation of information (20, 22) generated from the biopsy sample to generate a combined image in which the graphical representation is spatially delineated based on the spatial registration of the biopsy sample; and displaying the combined image on the graphical display device of the imaging visualization workstation. A method comprises extracting a biopsy sample spatial sample from a medical subject, processing the biopsy sample to generate biopsy information, acquiring a medical image of the subject, spatially registering the biopsy sample with the medical image, and displaying the medical image modified to include an annotation generated from the biopsy information.
    Type: Application
    Filed: March 20, 2013
    Publication date: April 9, 2015
    Inventors: Nilanjana Banerjee, Sitharthan Kamalakaran, Vinay Varadan, Angel Janevski, Nevenka Dimitrova
  • Publication number: 20150058322
    Abstract: When generating visual representations of gene activity pathways for clinical decision support, a validated pathway database that stores a plurality of validated pathways is accessed, wherein each pathway describes at least one interaction between a plurality of genes. A processor (18) is configured to execute computer-executable instructions stored in a memory (16), the instructions comprising visually representing gene activity level (28) for at least one gene across a plurality of populations, retrieving a pathway (32) from the validated pathway database, wherein the pathway includes the at least one gene, and visually representing gene activity levels for all genes in the pathway.
    Type: Application
    Filed: March 27, 2013
    Publication date: February 26, 2015
    Applicant: KONINKLIJKE PHILIPS N.V.
    Inventors: Nevenka Dimitrova, Angel Janevski, Nilanjana Banerjee, Vinay Varadan, Sitharthan Kamalakaran