Integrated biosensor and simulation system for diagnosis and therapy

• US 9,110,836 B1
• Filed: 02/25/2013
• Issued: 08/18/2015
• Est. Priority Date: 08/22/2003
• Status: Active Grant

• Current Assignee: Dennis Sunga Fernandez
• Original Assignee: Dennis Sunga Fernandez
• Inventors: Fernandez, Dennis Sunga
• Primary Examiner(s): DeJong, Eric S
• Application Number:
  US13/776,169
• Time in Patent Office: 904 Days
• Field of Search: None
• US Class Current: 1/1
• 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. Integrated biosensor and simulation method to assist in medical decision-making comprising the steps of:

sensing a biological host by a biosensor platform comprising a multifunctional array coupled to a plurality of sensors that each sense automatically one or more system-level function of the biological host; and

simulating by a controller comprising a systems-biology platform comprising a genomics database, proteomics database, pharmacogenomics database, metabolomics database, pharmacokinetics database, transcriptomics database, disease database and drug database;

such that the controller uses the systems-biology platform to simulate automatically the biological host at each said one or more system-level function of such biological host by such simulation using each function sensed by the biosensor platform and also such simulation using each database of said systems-biology platform according to one or more knowledge-based techniques in the systems-biology platform to provide therapy, diagnosis or other automated feedback.

2. The method of claim 1 further comprising:

using mathematical modeling and simulation of biological processes in a systems biology platform for differential diagnosis of metabolic, immune or genetic disorder in biological system.

3. The method of claim 1 further comprising

predicting one or more kinetic interactions between a drug and biological molecules in a biological system.

4. The method of claim 3 further comprising:

analyzing the kinetic interactions between the drug and biological molecules in the biological system.

5. The method of claim 1 further comprising:

predicting adverse reaction to a drug in a biological system.

6. The method of claim 1 further comprising:

analyzing drug toxicity in a biological system.

7. Integrated biosensor and simulation system to assist in medical decision-making comprising:

a biosensor platform comprising a multifunctional array coupled to a plurality of sensors that each sense automatically one or more system-level function of a biological host; and

a controller comprising a systems-biology platform comprising a genomics simulation model, proteomics simulation model, pharmacogenomics simulation model, metabolomics simulation model, pharmacokinetics simulation model, transcriptomics simulation model, disease simulation model, or drug simulation model;

such that the controller uses the systems-biology platform to simulate automatically the biological host at each said one or more system-level function of such biological host by such simulation using each function sensed by the biosensor platform and also such simulation using each simulation model of said systems-biology platform according to one or more knowledge-based techniques in the systems-biology platform to provide therapy, diagnosis or other automated feedback.

8. Integrated biosensor and simulation system comprising:

a biosensor platform comprising a multifunctional sensor array coupled to a plurality of sensors that each sense automatically a plurality of biological systems-level functions of a biological host; and

a controller comprising a systems-biology simulation platform comprising a genomics model, proteomics model, pharmacogenomics model, metabolomics model, pharmacokinetics model, transcriptomics model, disease simulation model, or drug simulation model, such that the controller simulates the biological host at a plurality of biological systems-level functions automatically at each said systems-level function of such biological host, whereby the systems-biology simulation platform simulates the biological host using each said systems-level function sensed by the biosensor platform and each said model of said systems-biology simulation platform.