Integrated biosensor and simulation system for diagnosis and therapy

• US 20060178841A1
• Filed: 03/20/2006
• Published: 08/10/2006
• Est. Priority Date: 08/22/2003
• Status: Active Application

• Current Assignee: Dennis Fernandez
• Original Assignee: Dennis Fernandez
• Inventors: Fernandez, Dennis S.
• Application Number:
  US11/385,054
• Publication Number:
  US 20060178841A1
• Time in Patent Office: Days
• US Class Current: 702/19
• 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

1-10. -10. (canceled)

11. Implantable network-biosensor comprising:

a sensor unit for receiving a multi-sensor signal from a biosensor platform for detecting a biological material of a host; and

a controller for processing a systems-biology platform for verifying or modifying a simulation model associated with the biological material.

12. The network biosensor of claim 11 wherein:

the sensor unit is configurable or programmable for detecting multi-sensor signaling, thereby enabling the biosensor platform to access one or more sensor signals from a DNA or RNA sensor, a peptide or protein sensor, an antibody or antigen sensor, a vector or virus-vector sensor, a lipid or fatty-acid sensor, or an inorganic-ion or electrochemical sensor.

13. The network biosensor of claim 11 wherein:

the sensor unit is configurable or programmable for detecting multi-sensor signaling, thereby enabling the biosensor platform to access one or more sensor signals from a tissue-factor sensor, a steroid sensor, a neurotransmitter sensor, a pH sensor, a free-radical sensor, a carbohydrate sensor, a neural sensor, a chemical sensor, a small-molecule sensor, an exon sensor, a metabolites sensor, an intermediate sensor, a chromosome sensor, or a cell sensor.

14. The network biosensor of claim 11 wherein:

the sensor unit comprises a positioning chip for immobilizing or positioning the biological material for sensing thereof.

15. The network biosensor of claim 11 wherein:

the sensor unit receives another multi-sensor signal from another biosensor platform for detecting another biological material of the same or another host.

16. The network biosensor of claim 11 wherein:

the controller is configurable or programmable for processing multiple simulation applications, thereby enabling the systems-biology platform to access one or more simulation models comprising a genomics model, a proteomics model, a computational chemistry model, a pharmacogenomics model, a computational biology model, a computational biophysics model, a computational cell behavior model, a pharmacokinetics model, a metabolomics model, or a transcriptomics model.

17. The network biosensor of claim 11 wherein:

the controller is configurable or programmable for processing multiple simulation data, thereby enabling the systems-biology platform to access one or more simulation data comprising a genetic-disorder or mutation data, an infectious disease or infection data, an immunity-disease data, a single-organ or cell-type autoimmune disease data, or a neoplasia data.

18. The network biosensor of claim 11 further comprising:

a therapeutic unit for releasing or dispensing a therapeutic material from a reservoir in or onto the host, whereby the sensor unit may automatically detect an effect of the therapeutic material on the host.

19. The network biosensor of claim 18 wherein:

the therapeutic unit is configurable or programmable for releasing or dispensing the therapeutic material alternatively from manufacture means, thereby enabling the systems-biology platform to instruct the therapeutic unit configurably or programmably using one or more manufacture-means components comprising pharmaceuticals, biopharmaceuticals, reconfigurable biocatalytic chips, tissue scaffolds, or micro or nano-array or electro-mechanical tools.

20. The network biosensor of claim 11 wherein:

the controller processes the systems-biology platform adaptively for generating a diagnostic or therapeutic signal or report, whereby the systems-biology platform may access one or more simulation applications comprising a neural or learning network, a statistical or probabilistic expert, fuzzy-logic or knowledge-based system, an artificial intelligence or decision-making inference-engine or program, or a supervised or unsupervised Bayesian or Markovian analysis, clustering, criterion or classification program.