IP Library › Granted Patent US 9,791,446
Granted Patent B2
US 9,791,446 · App. 15/015,309 · Granted Oct 17, 2017

Signatures and determinants for distinguishing between a bacterial and viral infection and methods of use thereof

Inventors: Eran Eden (Haifa, IL); Kfir Oved (Hof HaCarmel, IL)
Assignee: MeMed Diagnostics Ltd.
G01N33/56983A61K45/06G01N33/569G01N33/56911G01N2333/4737G01N2333/914
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Quick Facts
Patent No.
US 9,791,446
App. No.
15/015,309
Granted
Oct 17, 2017
Kind
B2
Abstract

The present invention provides methods of detecting infection using biomarkers. The methods disclosed herein include measuring the expression level of one or more polypeptide determinants in which the alteration of the expression level indicates infection of the patient. The methods provided herein are for distinguishing between bacterial infection, mixed infection, and/or viral infection. The methods disclosed herein may also further comprise measuring one or more non-polypeptide determinants. The present disclosure also provides methods for selection of a treatment regimen for the subject based on whether the subject is identified as having a bacterial or mixed infection, or a viral infection.

Claims (14)

1. A method of treating a subject in need thereof, the method comprising:

(a) measuring the level of MX dynamin-like GTPase 1 (MX1) and the level of C-reactive protein (CRP) in a sample of the subject;

(b) classifying whether the subject has a bacterial infection using a hyperplane having been calculated by combining the measurements of said CRP and said MX1 of a training population; and

(c) treating the subject classified as having said bacterial infection with an antibiotic agent, thereby treating the subject.

2. The method of claim 1 , wherein said hyperplane is calculated using a statistical classification algorithm.

3. The method of claim 2 , wherein said statistical classification algorithm is selected from the group consisting of a Support Vector Machine (SVM), Logistic Regression (LogReg), Neural Network, Bayesian Network, and a Hidden Markov Model.

4. The method of claim 2 , wherein said statistical classification algorithm is a Support Vector Machine (SVM) or a Logistic Regression (LogReg).

5. The method of claim 1 , further comprising measuring the level of white blood cells of the subject.

6. The method of claim 1 , further comprising measuring the level of neutrophils of the subject.

7. The method of claim 1 , further comprising measuring the level of RSAD2 in the sample of the subject.

8. The method of claim 1 , wherein the sample is whole blood or a fraction thereof.

9. The method of claim 8 , wherein said blood fraction sample comprises cells selected from the group consisting of lymphocytes, monocytes and granulocytes.

10. The method of claim 1 , wherein said measuring is effected by electrophoretic detection or immunochemical detection.

11. The method of claim 10 , wherein said immunochemical detection is selected from the group consisting of flow cytometry, radioimmunoassay, immunofluorescence assay and enzyme-linked immunosorbent assay.

Assignments (2)
SECURITY INTEREST Recorded Mar 11, 2026
From: MEMED DIAGNOSTICS LTD.
To: WTI FUND X, INC.; WTI FUND XI, INC.
Reel/Frame 074048/0278 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 9, 2016
From: EDEN, ERAN; OVED, KFIR
To: MEMED DIAGNOSTICS LTD.
Reel/Frame 037741/0404 →
Continuity (3)
Division 13090893 · Apr 20, 2011
Provisional Application 61326244 · Apr 21, 2010
Related Publication 20160153993A1 · Jun 2, 2016