Integrated Biosensor and Simulation System for Diagnosis and Therapy

• US 20090204379A1
• Filed: 04/14/2009
• Published: 08/13/2009
• Est. Priority Date: 08/22/2003
• Status: Active Grant

• Current Assignee: Dennis Fernandez
• Original Assignee: Dennis Fernandez
• Inventors: Fernandez, Dennis S.
• Granted Patent: US 8,374,796 B2
• Time in Patent Office: Days
• US Class Current: 703/11
• CPC Class Codes: A61B 2562/028 Microscale sensors, e.g. electromechanical sensors [MEMS]
• CPC Class Codes: A61B 5/0002 Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network A61B5/07 takes precedence; transmission systems for measured values G08C; transmission H04B; transmission of digital information H04L; wireless communication networks H04W
• CPC Class Codes: A61B 5/02028 Determining haemodynamic parameters not otherwise provided for, e.g. cardiac contractility or left ventricular ejection fraction
• CPC Class Codes: A61B 5/0215 by means inserted into the body catheters A61M25/00
• CPC Class Codes: A61B 5/024 Detecting, measuring or recording pulse rate or heart rate A61B5/0205, A61B5/021 take precedence
• CPC Class Codes: A61B 5/026 Measuring blood flow A61B3/1233, A61B3/1241 take precedence
• CPC Class Codes: A61B 5/076 Permanent implantations telemetry using implanted circuitry A61B5/0031; implanted stimulators for therapy A61N1/3605, A61N1/362, A61N1/372
• CPC Class Codes: A61B 5/145 Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissuemeasuring of blood pressure or blood flow A61B5/02; non-radiation detecting or locating of foreign bodies in blood A61B5/06
• CPC Class Codes: A61B 5/14539 for measuring pH
• CPC Class Codes: A61B 5/14542 for measuring blood gases A61B5/14551 takes precedence
• CPC Class Codes: A61B 5/14546 for measuring analytes not otherwise provided for, e.g. ions, cytochromes
• CPC Class Codes: A61B 5/411 Detecting or monitoring allergy or intolerance reactions to an allergenic agent or substance
• CPC Class Codes: A61B 5/413 Monitoring transplanted tissue or organ, e.g. for possible rejection reactions after a transplant
• CPC Class Codes: A61B 5/415 the glands, e.g. tonsils, adenoids or thymus
• CPC Class Codes: A61B 5/418 lymph vessels, ducts or nodes
• CPC Class Codes: A61B 5/4839 combined with drug delivery
• CPC Class Codes: A61B 5/486 Bio-feedback A61B5/375 takes precedence
• CPC Class Codes: A61B 5/686 Permanently implanted devices, e.g. pacemakers, other stimulators, biochips A61B5/6861 takes precedence
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61P 9/00 Drugs for disorders of the cardiovascular system
• CPC Class Codes: C12Q 1/04 : Determining presence or kind of microorganism; Use of selective media for testing antibiotics or bacteriocides; Compositions containing a chemical indicator therefor C12Q1/6897 takes precedence
• CPC Class Codes: C12Q 1/68 : involving nucleic acids
• CPC Class Codes: C12Q 1/6886 : for cancer immunoassay for cancer G01N33/574
• CPC Class Codes: C12Q 1/70 : involving virus or bacteriophage immunoassay for viruses G01N33/56983
• CPC Class Codes: C12Q 2600/156 : Polymorphic or mutational markers
• CPC Class Codes: G01N 33/53 : Immunoassay; Biospecific binding assay; Materials therefor
• CPC Class Codes: G06Q 40/08 : Insurance
• CPC Class Codes: G06Q 50/22 : Social work or social welfare, e.g. community support activities or counselling services
• CPC Class Codes: G16B 5/00 : ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
• CPC Class Codes: G16B 5/20 : Probabilistic models
• CPC Class Codes: G16B 5/30 : Dynamic-time models
• CPC Class Codes: G16H 10/60 : for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 40/63 : for local operation
• CPC Class Codes: G16H 50/50 : for simulation or modelling of medical disorders
• CPC Class Codes: G16H 70/60 : relating to pathologies
• CPC Class Codes: Y02A 90/10 : Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Abstract

BioMEMS/NEMS appliance biologically monitors an individual, using biosensors to detect cellular components. Data is simulated or analyzed using systems-biology software, which provides diagnostic or therapeutic guidance.

Claims

1. A method for treating a patient with HIV comprising the steps of:

using a Celera Diagnostic Viroseq™

HIV system to diagnose a patient as HIV positive;

storing the HIV positive diagnosis in a database such that patient records comprising reports indicating gene expression, a history of diagnoses, patient age, height, weight, symptoms, allergies, diet, previous or present medications, medical or family history of disease, sickness or infection, results of previous blood or urine tests, or environmental or immunological factors is accessible using an on-screen search of a patient record; and

using mathematical methods comprising neural networks, artificial intelligence, fuzzy systems, or probabilities on the patient records to simulate one or more conditions of a patient; and

reporting one or more therapy recommendations based on the conditions of the patient to a medical professional on a user interface.

2. An apparatus for treating a patient with HIV comprising:

a Celera Diagnostic Viroseq™

HIV system to diagnose a patient as HIV positive;

a database for storing the HIV positive diagnosis such that patient records comprising reports indicating gene expression, a history of diagnoses, patient age, height, weight, symptoms, allergies, diet, previous or present medications, medical or family history of disease, sickness or infection, results of previous blood or urine tests, or environmental or immunological factors is accessible using an on-screen search of a patient record;

a data analyzer using mathematical methods comprising neural networks, artificial intelligence, fuzzy systems, or probabilities on the patient records to simulate one or more conditions of a patient; and

a user interface for reporting one or more therapy recommendations based on the conditions of the patient to a medical professional on a user interface.