Patents by Inventor Louise Kenny

Louise Kenny 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).

  • METHODS OF PREDICTING PRE TERM BIRTH FROM PREECLAMPSIA USING METABOLIC AND PROTEIN BIOMARKERS
    Publication number: 20210033619
    Abstract: A computer implemented method of early prediction of risk of a pregnancy outcome in a pregnant woman, comprising the steps of: inputting into a computational model values for a panel of a plurality of preeclampsia specific biomarkers comprising at least one metabolite, and optionally at least one protein or clinical risk factor, selected from Table 1, in which the values are obtained from the pregnant woman early in pregnancy; selecting a subset of inputted values comprising a value for at least one metabolite and optionally at least one protein or clinical risk factor value, based on a selected pregnancy outcome selected from pre-term preeclampsia, term preeclampsia and all preeclampsia; calculating a predicted risk of the selected pregnancy outcome based on the subset of inputted values; and outputting the predicted risk of the pregnancy outcome for the pregnant woman.
    Type: Application
    Filed: February 11, 2019
    Publication date: February 4, 2021
    Applicant: METABOLOMIC DIAGNOSTICS LIMITED
    Inventors: Robin TUYTTEN, Gregoire THOMAS, Louise KENNY, Leslie BROWN
  • Detection of risk of pre-eclampsia
    Patent number: 10564146
    Abstract: A method for the early prediction of risk of hypertensive disorders in pregnant women, including for example eclampsia, mild pre-eclampsia, chronic hypertension, EPH gestosis, gestational hypertension, superimposed pre-eclampsia, HELLP syndrome, or nephropathy.
    Type: Grant
    Filed: May 16, 2018
    Date of Patent: February 18, 2020
    Assignee: University College Cork, National University of Ireland, Cork
    Inventors: Louise Kenny, Philip Newton Baker, David Broadhurst
  • DETECTION OF RISK OF PRE-ECLAMPSIA
    Publication number: 20190056380
    Abstract: A method for the early prediction of risk of hypertensive disorders in pregnant women, including for example eclampsia, mild pre-eclampsia, chronic hypertension, EPH gestosis, gestational hypertension, superimposed pre-eclampsia, HELLP syndrome, or nephropathy.
    Type: Application
    Filed: May 16, 2018
    Publication date: February 21, 2019
    Applicant: UNIVERSITY COLLEGE CORK, NATIONAL UNIVERSITY OF IRELAND, CORK
    Inventors: Louise Kenny, Philip Newton Baker, David Broadhurst
  • DETECTION OF RISK OF PRE-ECLAMPSIA
    Publication number: 20160223517
    Abstract: A method for the early prediction of risk of hypertensive disorders in pregnant women, including for example eclampsia, mild pre-eclampsia, chronic hypertension, EPH gestosis, gestational hypertension, superimposed pre-eclampsia, HELLP syndrome, or nephropathy.
    Type: Application
    Filed: January 7, 2016
    Publication date: August 4, 2016
    Applicant: UNIVERSITY COLLEGE CORK, NATIONAL UNIVERSITY OF IRELAND, CORK
    Inventors: Louise Kenny, Philip Newton Baker, David Broadhurst
  • Detection of risk of pre-eclampsia
    Patent number: 9262582
    Abstract: A method for the early prediction of risk of hypertensive disorders in pregnant women, including for example eclampsia, mild pre-eclampsia, chronic hypertension, EPH gestosis, gestational hypertension, superimposed pre-eclampsia, HELLP syndrome, or nephropathy.
    Type: Grant
    Filed: December 21, 2010
    Date of Patent: February 16, 2016
    Assignee: University College Cork, National University of Ireland, Cork
    Inventors: Louise Kenny, Philip Newton Baker, David Broadhurst
  • PREDICTION OF A SMALL-FOR-GESTATIONAL AGE (SGA) INFANT
    Publication number: 20150168419
    Abstract: A method of predicting a SGA infant in a patient at a pre-symptomatic gestational stage is described. The method comprises a step of assaying a biological sample from the patient for an abundance of a plurality of metabolite biomarkers selected from the 19 metabolite biomarkers of Table IV, correlating the abundance of the plurality of metabolite biomarkers with a metabolite fingerprint of SGA shown in Table IV, and predicting SGA based on the level of correlation between the abundance of the plurality of metabolite biomarkers and the metabolite fingerprint of Table IV.
    Type: Application
    Filed: November 21, 2014
    Publication date: June 18, 2015
    Applicant: UNIVERSITY COLLEGE CORK - NATIONAL UNIVERSITY OF IRELAND, CORK
    Inventors: Louise Kenny, Philip Baker
  • PREDICTION OF A SMALL-FOR-GESTATIONAL AGE (SGA) INFANT
    Publication number: 20130295679
    Abstract: A method of predicting a SGA infant in a patient at a pre-symptomatic gestational stage is described. The method comprises a step of assaying a biological sample from the patient for an abundance of a plurality of metabolite biomarkers selected from the 19 metabolite biomarkers of Table IV, correlating the abundance of the plurality of metabolite biomarkers with a metabolite fingerprint of SGA shown in Table IV, and predicting SGA based on the level of correlation between the abundance of the plurality of metabolite biomarkers and the metabolite fingerprint of Table IV.
    Type: Application
    Filed: November 16, 2011
    Publication date: November 7, 2013
    Applicant: UNIVERSITY COLLEGE CORK - NATIONAL UNIVERSITY OF IRELAND, CORK
    Inventors: Louise Kenny, Philip Baker
  • DETECTION OF RISK OF PRE-ECLAMPSIA
    Publication number: 20130073212
    Abstract: A method for the early prediction of risk of hypertensive disorders in pregnant women, including for example eclampsia, mild pre-eclampsia, chronic hypertension, EPH gestosis, gestational hypertension, superimposed pre-eclampsia, HELLP syndrome, or nephropathy.
    Type: Application
    Filed: December 21, 2010
    Publication date: March 21, 2013
    Applicant: UNIVERSITY COLLEGE CORK, NATIONAL UNIVERSITY OF IRELAND, CORK
    Inventors: Louise Kenny, Philip Newton Baker, David Broadhurst