Patents by Inventor Kostyantyn Volyanskyy

Kostyantyn Volyanskyy 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).

  • Patent number: 10964410
    Abstract: The present disclosure pertains to a system, a method of using such a system, and a non-transitory computer-readable medium containing instructions to such a system for generating annotated gene fusion data from processing both a patient's DNA and RNA sequence information thereby filtering out weak candidate gene fusions. Thus the annotated gene fusion data contains clinically relevant information and accurate gene fusion detections (low false-positives) for use in clinical and/or R&D settings. The system, method and computer-readable medium allows a user to generate gene fusion data by detecting breakpoints from a patient's DNA-SEQ and RNA-SEQ, creating candidate breakpoint data by combining matching breakpoints from the DNA-SEQ and RNA-SEQ breakpoint data, determining confidence levels of the candidate breakpoint, identifying corresponding gene fusions, and annotating clinically relevant information about the gene fusions.
    Type: Grant
    Filed: May 22, 2018
    Date of Patent: March 30, 2021
    Assignee: Koninklijke Philips N.V.
    Inventors: Yong Mao, Nevenka Dimitrova, Kostyantyn Volyanskyy
  • Publication number: 20200357484
    Abstract: A genomic/proteomic test synthesis method includes receiving a genomic/proteomic data set (12) comprising samples corresponding to persons with each sample including values of features of a set of features derived from genomic/proteomic data for the corresponding person. For each feature, univariate analysis (30) is performed to generate a sample density versus feature value data set for the feature, for example represented as a kernel density estimate (KDE) (52). Multivariate analysis (32, 34) is performed on the features using the KDEs to generate a set of discriminative features (36, 38). In one example, the multivariate analysis (32) uses energy spectral density (ESD) characteristics of the KDEs. In another example, the multivariate analysis (34) uses peak location characteristics of the KDEs.
    Type: Application
    Filed: October 23, 2018
    Publication date: November 12, 2020
    Inventors: Kostyantyn Volyanskyy, Nevenka Dimitrova
  • Publication number: 20200234801
    Abstract: A method (100) for recruiting a patient for a clinical trial, comprising: receiving (110) a dataset comprising information about one or more clinical trials each including patient eligibility criteria; extracting (120) the patient eligibility criteria from each of the clinical trials; converting (130) the patient eligibility criteria to a standardized patient eligibility criterion using a structured clinical trial mark-up language; storing (140) the patient eligibility criterion in a database (862), each of the criterion associated with one or more clinical trials; receiving (150) patient-specific data values about a patient; querying (160) the clinical trial eligibility criteria database using the patient-specific data values to identify eligibility criterion satisfied by the patient-specific data value; identifying (170) a clinical trial associated with the one or more standardized patient eligibility criterion satisfied by a received patient-specific data value; and providing (180) a report of the identifi
    Type: Application
    Filed: October 5, 2018
    Publication date: July 23, 2020
    Inventors: Yong Mao, Woei-Jye Yee, Alexander Ryan Mankovich, Qingxin Wu, Kostyantyn Volyanskyy, Nevenka Dimitrova
  • Publication number: 20200024658
    Abstract: A method and a system for interpreting data between two quantitative genomic datasets are described, wherein datasets are associated with the same disease or condition, for example, samples from the same patient obtained on different genomic platforms with varying data acquisition parameters. The data samples in each of the first and second datasets are rank ordered and the relative distances among the data samples are determined. The value ranks and relative distances are then used to correlate to data samples in the first and second quantitative genomic datasets, with the output provided to a user, such as a clinician or a patient.
    Type: Application
    Filed: March 28, 2018
    Publication date: January 23, 2020
    Inventors: Kostyantyn Volyanskyy, Nevenka Dimitrova, Yong Mao
  • Publication number: 20200020423
    Abstract: A system and method for providing a prioritized list of clinical trials that are relevant to a patient suffering from an illness or disease, such as cancer, are disclosed. Specifically, a method for conducting an automated, real time clinical trial search and a prioritization analysis is described. The method comprises the steps of conducting an automated full-text clinical trial search based on structuralization of clinical trial eligibility data and knowledge-based inference, initiating a query from the patient's side, and providing a prioritized list of all accessible clinical trials fulfilling a particular query. The system provides better sensitivity, precision and negative predictive value than the current most known clinical trial matching tool: clinicaltrials.gov.
    Type: Application
    Filed: September 26, 2017
    Publication date: January 16, 2020
    Inventors: Qingxin Wu, Alexander Ryan Mankovich, Abhishek Talluli, Kostyantyn Volyanskyy, Nevenka Dimitrova, Yong Mao, Charles Yee
  • Publication number: 20200020421
    Abstract: A clinical genomic data processing device includes at least one microprocessor (10) and a non-transitory storage medium (12) storing instructions to implement functions of the device. A user interface (26, 28) receives requests for execution of genomic workflows and to display output generated by the execution of the genomic workflows. A genomic workflow manager manages an asynchronous messaging queue (24) and manages the execution of the genomic workflows. Service providers (20) performs jobs associated with the genomic workflows. The genomic workflow manager communicates with the service providers by messages exchanged via the asynchronous messaging queue to manage the execution of the genomic workflows via jobs performed by the service providers.
    Type: Application
    Filed: September 29, 2017
    Publication date: January 16, 2020
    Inventors: Nevenka Dimitrova, Ronen Solomon, Keswarpu Payal, Mine Danisman-Tasar, Moran Bentzur, Nadav Sharabi, Sergey Yussim, Alexander Ryan Mankovich, Vartika Agrawal, Julie Gu, Iliya Fridman, Kostyantyn Volyanskyy
  • Publication number: 20180341746
    Abstract: The present disclosure pertains to a system, a method of using such a system, and a non-transitory computer-readable medium containing instructions to such a system for generating annotated gene fusion data from processing both a patient's DNA and RNA sequence information thereby filtering out weak candidate gene fusions. Thus the annotated gene fusion data contains clinically relevant information and accurate gene fusion detections (low false-positives) for use in clinical and/or R&D settings. The system, method and computer-readable medium allows a user to generate gene fusion data by detecting breakpoints from a patient's DNA-SEQ and RNA-SEQ, creating candidate breakpoint data by combining matching breakpoints from the DNA-SEQ and RNA-SEQ breakpoint data, determining confidence levels of the candidate breakpoint, identifying corresponding gene fusions, and annotating clinically relevant information about the gene fusions.
    Type: Application
    Filed: May 22, 2018
    Publication date: November 29, 2018
    Inventors: Yong Mao, Nevenka Dimitrova, Kostyantyn Volyanskyy
  • Publication number: 20180330805
    Abstract: A data-driven integrative visualization system and a method for visualization and exploration of the multi-modal features of a cohort of samples, is disclosed Specifically, a method for providing an interactive computation and visualization front-end of a genomics platform for presenting the complex multiparametric and high dimensional, multi-omic data of a patient with respect to a cohort of samples, that assists the user in understanding the similarities and differences across individual or groups of samples, identify correlation among different features and improve treatment planning and long term patient care, is described. The method may include obtaining and inputting multi-omic data of a patient and/or cohorts, identifying multi-modal feature variations and their relationships, and displaying this information in an interactive circular format on a GUI, from which the user can access further information.
    Type: Application
    Filed: May 8, 2018
    Publication date: November 15, 2018
    Inventors: Yee Him Cheung, Yong Mao, Nevenka Dimitrova, Nilanjana Banerjee, Johanna Maria de Bont, Jozef Hieronymus Maria Raijmakers, Kostyantyn Volyanskyy
  • Publication number: 20180082042
    Abstract: In a risk level assessment method for a plurality of clinical conditions as follows, a set of laboratory test results (32) are stored with time stamps for a patient, including at least one hematology test result and at least one arterial blood gas (ABG) test result. For each clinical condition, a risk level is determined for the clinical condition based on a clinical condition-specific sub-set of the stored set of laboratory test results. This determination is made conditional on the stored clinical condition-specific sub-set of laboratory test results being sufficient to determine the risk level. A time stamp is assigned to each determined risk level based on the time stamps for the laboratory test results of the clinical condition-specific sub-set of laboratory test results. A display device (44, 46) displays the determined risk level and the assigned time stamp for each clinical condition whose determined risk level satisfies a display criterion.
    Type: Application
    Filed: March 17, 2016
    Publication date: March 22, 2018
    Inventors: Kostyantyn Volyanskyy, Minnan Xu, Larry James Eshelman